Copyright is owned by the Author of the thesis. Permission is given for a copy to be downloaded by an individual for the purpose of research and private study only. The thesis may not be reproduced elsewhere without the permission of the Author. EFFECTS OF GENERAL ANAESTHESIA AND INTRAVENOUS FLUID THERAPY ON RENAL BIOMARKERS IN CATS UNDERGOING OVARIOHYSTERECTOMY A thesis presented in partial fulfilment of the requirements for the degree of Master Of Veterinary Science at Massey University, Manawatu, New Zealand. Sruthi Valsan 2022 ii I would like to dedicate this thesis to my father, Valsan Madhavan Vadakkath, my source of positivity. iii ABSTRACT Traditional screening tests used to evaluate renal function have been demonstrated to be insensitive in detecting early kidney damage, such as subclinical acute kidney injury. It is probable that general anaesthesia and routinely performed surgical procedures could cause subclinical changes in the renal structure, predisposing the animal to subsequent functional impairment. However, these active changes might go undetected while screening using traditional renal markers, such as serum creatinine (SCr) and blood urea nitrogen (BUN). Novel urinary biomarkers, that indicate renal injury earlier than conventional markers, have been extensively studied in humans during the perioperative period. A feline model of mild acute kidney injury, potentially induced through general anaesthesia during routine surgeries, may prove useful in testing novel renal biomarkers and providing insight into the effects of anaesthesia on kidneys. A randomised controlled trial was performed using 60 healthy cats presented to the Massey University Veterinary Teaching Hospital for routine ovariohysterectomy. Blood and urine samples were collected immediately before (0 h), and after (24 and 48 h) anaesthesia and spay surgery. Traditional renal marker levels (SCr, BUN) were measured from the serum samples. Commercial assays were used to detect the levels of novel markers, such as N-acetyl-β-D glucosaminidase (NAG) enzyme, Neutrophil Gelatinase-associated Lipocalin (NGAL), Retinol Binding Protein (RBP) and Kidney Injury Molecule-1 (KIM-1), in the urine samples. This study aimed to use these urinary markers to investigate the effects of general anaesthesia and intraoperative fluid therapy on feline renal structure. Statistical tests such as t-test and ANOVA were conducted to establish differences in renal marker values between the time points and between treatment groups. Upon comparing the changes in renal marker concentrations, the study found no measurable evidence of structural or functional kidney damage in the cats. This is plausible since the vital parameters, such as arterial blood pressure and oxygenation levels, of the study cats were maintained within or near the borderline physiological range throughout the surgical procedure, resulting in the apparent absence of assessable kidney damage postoperatively. It is inferred that a more severe form of renal injury would be required to test the sensitivity of these novel renal markers in cats. iv ACKNOWLEDGEMENTS First and foremost, I would like to thank my supervisors, Drs Kavitha Kongara (chief supervisor), Carolyn Gates and Paul Chambers (Co-supervisors), for allowing me to participate in this study. I am endlessly and eternally grateful for their guidance, support, extreme patience, and understanding, which made all this possible for me. They have provided invaluable input throughout the writing of this thesis. I want to extend my thanks to a whole group of people who helped complete this study. I have been fortunate to have been mentored by Dr V. S. R. Dukkipati, who was instrumental in conducting the laboratory analyses. I learned much from Sarah Fulton’s expert handling of the cats. Professor Dorothy Bienzle, of Ontario Veterinary College, provided guidance on laboratory work. In addition to all those who made the recruitment process seamless, I also thank Dr Thomas Odom, who helped with the spay procedures whenever required, and Hanan Hassan, a veterinary student who was involved in the study. And of course, the cats, who were awesome companions and always managed to amuse me with their personalities and antics. I am also grateful to the university for all the help they provided during COVID. This Master’s was made possible through the personal financial support provided by the Phyllis Irene Grey Fellowship and Massey University COVID-19 Master’s Research Bursary along with the research funding received from Winn Feline Foundation, USA and Companion Animal Health Foundation, NZ. The study had the approval of the Massey University Animal Ethics Committee (protocol no 20/34). I would further like to thank my family members, who were there for me no matter the time or distance. My father who was always my main support system. My mother, Meena Valsan, who encouraged me from the sidelines. My sister, Smrithi Valsan, and her spouse, Nitish Sadasivan, who were there for me through it all. My aunt, Latha Romikuttan, who helped proofread the entire manuscript in a short span of time when it took me ages to do the same. My cousin, Anagha Romi, who brought laughter to the longest nights. I must also mention the cheeky lights of my life: Bliss (my dog), Snowy and Rocky (my rabbits), whose innocent faces never failed to bolster my spirit. v Table of contents Page ABSTRACT ⅲ ACKNOWLEDGEMENTS ⅳ Table of contents ⅴ List of Tables ⅷ List of Figures ⅸ Abbreviations ⅹ CHAPTER 1 INTRODUCTION 1 2 REVIEW 3 2.1 OVERVIEW OF RENAL PHYSIOLOGY 3 2.1.1 Renal Architecture 3 2.1.2 Renal Vasculature 7 2.1.3 Nervous Innervation of the Kidneys 9 2.2 RENAL FUNCTION 9 2.2.1 Glomerular Filtration Rate (GFR) 11 2.2.2 Autoregulation of Renal Blood Flow (RBF) 11 2.3 FELINE RENAL DISEASE 13 2.4 ACUTE KIDNEY INJURY (AKI) 16 2.5 CHRONIC KIDNEY DISEASE (CKD) 22 2.6 RISK FACTORS 26 2.6.1 General Anaesthesia and Surgery 26 2.6.2 Intravenous Fluid Administration 32 2.7 DIAGNOSIS OF RENAL DYSFUNCTION 33 2.7.1 Conventional Indicators of Renal Dysfunction 33 2.7.1.1 Direct GFR Indicators 34 2.7.1.2 Indirect GFR Indicators 35 2.7.2 Novel Indicators 43 2.7.2.1 Urinary Tubular Proteins 44 2.7.2.2 Enzymuria 52 vi 2.8 CONCLUSION 56 2.9 RESEARCH QUESTIONS 57 3 MATERIALS AND METHODS 58 3.1 EXPERIMENTAL DESIGN 58 3.2 STUDY ANIMALS 59 3.3 PERIOPERATIVE PROCEDURE 60 3.3.1 Pre-Operative Preparations 60 3.3.2 Operative Procedure 62 3.3.3 Post-Operative Care 63 3.4 SAMPLE COLLECTION 63 3.4.1 Blood 64 3.4.2 Urine 64 3.5 ANALYTICAL METHODOLOGY 65 3.5.1 Kidney Injury Molecule-1 (KIM-1) 65 3.5.2 N-Acetyl β-D Glucosaminidase (NAG) Enzyme 66 3.5.3 Neutrophil Gelatinase-Associated Lipocalin (NGAL) 69 3.5.3.1 Trial 1 69 3.5.3.2 Trials 2 and 3 70 3.5.3.3 Trial 4 73 3.5.3.4 Final run 74 3.5.4 Retinol Binding Protein (RBP) 76 3.5.4.1 Trial 1 76 3.5.4.2 Trial 2 77 3.5.5 Dipstick Analysis 78 3.6 STATISTICAL ANALYSIS 79 3.6.1 Descriptive statistics 79 3.6.2 Inferential statistics 80 3.7 DESCRIPTIVE STATISTICS 81 3.8 INFERENTIAL STATISTICS 83 3.8.1 Intraoperative variables (Study Population) 83 3.8.2 Intraoperative variables (Treatment Groups) 85 3.8.3 Baseline (0 hr) renal marker values 99 3.8.3.1 Traditional Markers 100 3.8.3.2 Novel Renal Markers 102 vii 3.8.4 Renal marker values across time-points (Study Population) 103 3.8.5 Renal marker values (Treatment Groups) 106 3.8.5.1 Group-Wise Differences 108 3.8.6 Effect of treatment group 110 3.8.7 Other factors associated with the change in renal marker values 115 3.8.8 Summarizing the intraoperative effects of fluid and treatment protocols 141 3.9 INTRAOPERATIVE FINDINGS 146 3.10 EFFECT OF THE ANAESTHETIC PROTOCOLS ON PHYSIOLOGICAL PARAMETERS 147 3.10.1 Heart Rate and Respiratory Rate 147 3.10.2 Arterial Blood Pressure 148 3.10.3 Body Temperature 149 3.10.4 Oxygenation Saturation 149 3.10.5 End-Tidal Carbon Dioxide 150 3.10.6 Isoflurane 151 3.11 RENAL MARKERS AT BASELINE 151 3.12 RENAL MARKERS ACROSS TIMEPOINTS 152 3.13 RAAS INVOLVEMENT 155 3.14 FLUID AND ISOFLURANE ADMINISTRATION 155 3.15 PROTECTIVE FUNCTION OF ANAESTHESIA 156 3.16 LIMITATIONS OF THE STUDY 157 4 CONCLUSION 158 5 REFERENCES 160 6 APPENDIX A 177 7 APPENDIX B 191 viii List of tables Page Table 1 IRIS AKI grading criterion (Cowgill, 2016). ..................................................................................... 20 Table 2 IRIS Staging of CKD (IRIS CKD Pocket Guide; IRIS Staging of CKD, 2019). ............................... 25 Table 3 Summary of renal markers. Modified from Hokamp and Nabity (2016). .......................................... 54 Table 4 Premedication and anaesthetic induction protocols used in the study. .............................................. 61 Table 5 Baseline demographic data of the study population. .......................................................................... 81 Table 6 Baseline demographic data of the study cats across the treatment groups. ....................................... 82 Table 7 Intra-operative data of the study population. ..................................................................................... 84 Table 8 Intra-operative data of the study cats across the treatment groups. .................................................... 86 Table 9 Difference in the intraoperative variables recorded for the treatment protocols (T.P). ...................... 89 Table 10 Difference in the intraoperative variables recorded between the treatment groups. ....................... 94 Table 11 Baseline values for various renal markers. ...................................................................................... 99 Table 12 Baseline values for markers normalized to urine creatinine value. ................................................ 100 Table 13 Difference in renal marker values at 0 hr between the treatment groups. ...................................... 102 Table 14 Renal marker concentration at different time points. ..................................................................... 104 Table 15 Renal markers with statistically significant difference in values between time-points. ................. 106 Table 16 Renal marker values for the treatment groups across the different time points. ........................... 107 Table 17 Difference in the renal marker values between the treatment groups across time points. .............. 108 Table 18 Renal markers (mean difference) influenced by treatment groups. ............................................... 111 Table 19 List of factors associated with the change in mean renal marker values between time points. ...... 116 Table 20 Factors associated with the change in renal marker values between time points. .......................... 118 Table 21 Univariable analysis of factors associated with a change in the renal biomarkers between different study time points. .......................................................................................................................................... 132 ix List of figures Page Figure 1 Kidney cross-section........................................................................................................................... 4 Figure 2 A) Parts of a nephron and B) oxygen gradient across the renal cortex, outer medulla, and inner medulla (Bonventre & Yang, 2011). .............................................................................................................................. 5 Figure 3 Difference in blood pressure across the renal vasculature in the human body. .................................. 8 Figure 4 Functions of the nephron. ................................................................................................................. 10 Figure 5 Effect of arterial blood pressure (BP) on renal blood flow (RBF) and, consequentially, on GFR. . 12 Figure 6 Spectrum of AKI and CKD pathophysiology. ................................................................................. 21 Figure 7 Renal filtration performance across the stages of CKD. ................................................................... 36 Figure 8 Curvilinear relation between SCr and GFR as seen in dogs (Lefebvre et al., 2015). ...................... 37 Figure 9 Anaesthetic duration for the study groups. ....................................................................................... 83 Figure 10 Baseline values of A) m-MAP, B) m-SAP, C) m-DAP, D) m-Temp, E) m-SpO2, and F) m- Isoflurane in different treatment groups. ......................................................................................................... 87 Figure 11 Baseline values of A) l-MAP, B) l-SAP, C) l-DAP, D) l-Temp, E) l-SpO2 and F) maximum Isoflurane percentage in treatment groups. ..................................................................................................... 88 Figure 12 Effect of the treatment protocols on A) RR (bpm), B) HR (bpm). ................................................. 91 Figure 13 Effect of the treatment protocol on A) m-MAP (mmHg) and B) DAP (mmHg). ........................... 92 Figure 14 Baseline values (0 hr) for conventional renal markers A) serum creatinine (SCr), B) blood urea nitrogen (BUN), C) symmetric dimethylarginine (SDMA), D) urine total protein (UTP), and E) urine protein creatinine ratio (UP:C) across treatment groups. .......................................................................................... 101 Figure 15 NAG Index (U/g) at baseline (0 hr) across the different treatment groups. .................................. 102 Figure 16 Baseline values (0 hr) for novel renal markers A) KIM-1 OD, B) NGAL, C) NAG activity, D) RBP, E) KIM-1 ratio and F) UNCR across treatment groups. ............................................................................... 103 Figure 17 Mean difference in A) KIM-1 OD 48 -24 hrs and B) KIM-1 ratio 48-24 ..................................... 113 Figure 18 Mean difference in SDMA between A) 24 and 0 hrs; B) 48 and 24 hrs. ...................................... 113 Figure 19 Mean difference in BUN between A) 24 and 0 hrs; B) 48 and 0 hrs; C) 48 and 24 hrs. .............. 114 Figure 20 Mean difference in UTP between A) 24 and 0 hrs, B) 48 and 0 hrs. ............................................ 115 Figure 21 Association of IV fluid administration with HR (bpm). ............................................................... 141 Figure 22 Intraoperative variables (mean values) such as A) ETCO2, B) RR, C) ET isoflurane (%), D) m-MAP (mmHg), E) m-SAP (mmHg), and F) m-DAP (mmHg) with different anaesthetic protocols. ..................... 143 Figure 23 Intraoperative variables (lowest values) such as A) m-Isoflurane (%), B) l-MAP (mmHg), C) l-SAP (mmHg), D) l-DAP (mmHg), E) HR (bpm), and F) m-Temp ( °C) with different anaesthetic protocols. .... 144 x Abbreviations AA: Afferent arteriole AKI: Acute kidney injury AM: Acepromazine-Morphine-Alfaxalone ANOVA: Analysis of variance ARF: Acute renal failure ASA: American Society of anesthesiologists BP: Blood pressure BUN: Blood urea nitrogen C: Control CIM-1: Cochlear injury molecule-1 CKD: Chronic kidney disease Cl-: Chloride ion DAP: Diastolic arterial pressure DCT: Distal convoluted tubule DKT: Dexmedetomidine-Ketamine-Butorphanol EA: Efferent arteriole ECF: Extra-cellular fluid ELISA: Enzyme-linked immunoassay ET: Endotracheal tube ETCO2: End-tidal carbon dioxide FiO2: Fraction of Inspired Oxygen GFB: Glomerular filtration barrier GFR: Glomerular filtration rate HAVCR-1: Hepatitis A virus-cell receptor-1 HMW: High molecular weight HR: Heart rate IM: Intra-muscular IMW: Intermediate molecular weight IRIS: International renal interest society IV: Intravenous JGA: Juxta-glomerular apparatus JGC: Juxta-glomerular cells KD: Kidney disease KIM-1 OD: Kim-1 Optical density KIM-1: Kidney injury molecule-1 l-MAP: Lowest MAP l-DAP: Lowest DAP l-SAP: Lowest SAP l-SpO2: Lowest SpO2 l-Temp: Lowest temperature LFA: Lateral flow assay LMW: Low molecular weight m- SpO2: Mean SpO2 MAP: Mean arterial pressure m-DAP: Mean-DAP m-MAP: Mean MAP MMP-9: Matrix metalloproteinase-9 m-SAP: Mean SAP m-Temp: Mean temperature n: Number Na+: Sodium-ion NAG: N-Acetyl β- D- Glucosaminidase NGAL: Neutrophil Gelatinase-associated Lipocalin OHE: Ovariohysterectomy P.E: Physical examination PCT: Proximal convoluted tubule RBF: Renal blood flow RBP: Retinol Binding Protein RR: Respiratory rate S3: Third segment of PCT SA-HRP: Streptavidin-horse radish peroxidase SAP: Systolic arterial pressure SCr: Serum Creatinine SDMA: Symmetric dimethyl-arginine sP: Serum phosphorus SpO2: Oxygen saturation T.P: Treatment protocol T: Test Temp: Temperature TID: ter die sumendum TIM-1: T-cell immunoglobulin-1 UCr: Urine creatinine UNCR: Urine NGAL to creatinine ratio uNGAL: Urinary NGAL UP:C :- Urine protein creatinine ratio UPC: Urine protein concentration UPCR: Urine protein to creatinine ratio uRBP: Urinary RBP uRBP:Cr :- uRBP to UCr ratio USG: Urine specific gravity UTP: Urine total protein 1 1 INTRODUCTION Kidney dysfunction is a common finding in cats, especially in those aged over 12 years, with a significant number of cases being detected only when the animals have advanced stages of renal damage. Kidney disease (KD) is associated with a reduced quality of life, poor prognosis, and survivability once it becomes clinically apparent. In diagnosing renal damage, clinicians are sometimes limited by the absence of overt clinical signs delaying its detection until the damage becomes irreversible. The loss of function is masked by the compensatory action of the kidneys and nephrons (Lefebvre et al., 2015). Thus, the clinical signs of KD primarily manifest once the kidneys are incapable of compensating for the damaged renal mass. Our current tests for kidney dysfunction rely on identifying elevated levels of specific markers in serum (e.g., serum creatinine, blood urea nitrogen). However, these traditional markers are not produced by the kidney, but rather filtered from the blood by the kidneys and excreted from the body. Thus, increased levels of these markers in the serum are correlated with a loss of kidney function as they accumulate in the blood due to improper filtration (Segev, 2018a). These markers are imperfect tools for diagnosing early renal damage, where we would expect to find evidence of structural damage occurring long before the loss of renal function. Another limitation with the current panel of markers is that they are primarily produced extra-renally (Hokamp & Nabity, 2016). Therefore, their increase and decrease cannot be solely attributed to kidney damage. They can be influenced by factors not concerning the kidneys, such as diet, exercise, and pathology in other organ systems. This makes it difficult to interpret the significance of slight fluctuations in traditional renal marker values over a short period of time. The inability to determine the effect of onset factors on renal function and structure, due to the insensitivity of our current diagnostic tools, is a major concern with renal studies. The causes mentioned above, including the delayed presentation with seemingly normal biochemical findings, make it nearly impossible to identify the inciting cause of kidney damage (Syme, 2019). Furthermore, it is currently believed 2 that the cause for KD is multifactorial, with the interplay of several inciters leading to the progression of kidney damage, as evidenced by a large proportion of clinical cases having no known cause for KD (Dunn et al., 1980; Jepson, 2016). While these shortcomings are receiving critical attention, more research is needed to understand and, thereafter optimize the use of these markers in studying the causation of KD. There is a growing recognition of probable links causing the increasingly common occurrence of KD in the later years of a cat’s life (Jepson, 2016). However, it is often difficult to determine an aetiological agent because mild kidney injury is subtle in its approach, with the cat showing no apparent clinical signs of KD. Furthermore, the traditional markers of renal dysfunction are inadequate tools for detecting mild kidney injury. It is necessary to conduct more studies to improve and develop the diagnostic panel in order to identify slight changes in kidney function and structure. Identifying new biomarkers that can provide an immediate and accurate assessment (‘snapshot’) of the kidneys has become increasingly important. As humans and animals share many similarities, the novel markers used for the former are now being applied to animals to study their potential. There is a growing body of literature that recognizes the importance of developing these markers. There is evidence to suggest that these markers are proportional to renal structural damage rather than function and are, thus, more sensitive to renal damage (Vaidya, Ferguson, & Bonventre, 2008). Their rapid increase in response to injury will aid in quick diagnosis and reduce the incidence of higher grades of KD, by allowing for targeted therapy earlier in the course of the disease. We have witnessed a dramatic shift in the use of general anaesthesia and elective surgical procedures in companion animals over the past century. It is well known that both of these factors can cause transient changes in the physiological state of animals (Grauer, 1996; Senior, 2017). There is still much uncertainty about whether these factors can affect renal structure, by creating an environment unfavourable for the renal tissue, especially in cats. Studies to identify the changes wrought by potential risk factors are made more challenging, with the increasing reliance on alternative study designs to animal testing, due to ethical concerns. Clinicians must take measures to minimize the risk of renal injury, 3 for example, by using anaesthetic agents that have been shown to have limited adverse effects on the kidneys. The increased use of general anaesthesia in recent years has raised the question of whether general anaesthesia is associated with the increased prevalence of renal dysfunction in cats as anaesthetics may affect renal perfusion through their cardio-depressant effects. This study investigates the effects of general anaesthesia and intraoperative fluid administration on renal markers in cats and, thus, its effects on the kidney. We do so by determining the changes in serum and urine markers, after routine ovariohysterectomy, in those cats admitted to the teaching hospital. The use of novel and traditional markers will provide information on both structure and function of the kidneys after exposure. This will also help us compare the markers to validate the sensitivity of novel markers in cats, as reported in other studies. The following review covers the physiology and pathology of kidneys in cats, potential risk factors (specifically anaesthetic agents and fluids), and various renal markers used to detect renal dysfunction. 2 REVIEW 2.1 OVERVIEW OF RENAL PHYSIOLOGY 2.1.1 Renal Architecture The ureotelic excretory system in mammals comprises the kidneys, ureters, urinary bladder and urethra. Normal kidney function is paramount for maintaining the blood volume, blood pressure (BP) and osmolarity for physiological homeostasis. The mammalian kidneys are paired organs found in the retroperitoneal space of the abdominal cavity (Aspinall, 2004), i.e., between the parietal layer of the peritoneum and the roof of the abdomen. The bean-shaped kidneys in cats are smooth and mobile (Sjaastad et al., 2016), with large capsular veins (Alpern et al., 2013, p. 596). Macroscopically, the kidneys are divided into the highly vascular outer cortex and the well-developed inner medulla, as shown in Figure 1. The medulla 4 Figure 1 Kidney cross-section. Diagrammatic representation of internal kidney structures within the renal cortex and medulla. The placement of a nephron (light yellow) has been depicted along with the path of urine drainage. Image reprinted from Maurya et al. (2018). The nephron (nephronum) is the functional unit of the kidney. It consists of two main elements, i.e., the renal corpuscle (Malpighian corpuscle/glomerulus corpusculi renalis) and the tubular element (Aspinall, 2004), as seen in Figure 2 (A). The kidney contains around 1,90,000-2,00,000 juxtamedullary nephrons in cats (Dukes & Reece, 2004, p. 74). These nephrons are a type of mammalian nephron characterized by long tubular loops that dip into the medullary region of the kidney (Chmielewski, 2003; Dukes & Reece, 2004; Sjaastad et al., 2016). These nephrons are known for their urine concentrating role, above par due to the pressure and osmotic gradient across the cortex as well as the medulla (Chmielewski, 2003). While these nephrons are generally believed to have long tubular components, some of these nephrons in cats do not invade the deeper sections of the medulla. In fact, they resemble the cortical nephrons found in other species (Seldin & Giebisch, 1985, p. 272). consists of the renal pelvis (crest-type) and the renal sinus (Schmidt-Nielsen, 1987). The vascular, lymphatic and nervous branches enter the kidneys through the renal hilus, which opens into the renal sinus (Hall, 1983; Sjaastad et al., 2016). 5 Figure 2 A) Parts of a nephron and B) oxygen gradient across the renal cortex, outer medulla, and inner medulla (Bonventre & Yang, 2011). A) The nephron consists of the renal corpuscle (Bowman’s capsule and glomerulus) and the tubular components: proximal convoluted tubule (convoluted and straight tubule), Henle’s loop (descending, thin ascending, and thick ascending limb), distal convoluted tubule and collecting duct. The vasa recta are a network of arterioles which loop in and around Henle’s loop and act as the main source of blood supply for the medullary structures. B) The countercurrent exchange of oxygen across the vasa recta network results in an oxygen gradient which maintains a near-hypoxic environment in the deeper layers of the kidney (medulla). The glomerulus and Bowman’s capsule, together, form the renal corpuscle. This structure serves as the primary site for fluid transfer, across the capillary bed and into the Bowman’s space, a process regulated by the high-pressure environment found within the involved renal blood vessels (Dukes & Reece, 2004). The glomerulus is a mass of richly vascular, 6 interlinked capillary loop that dips into the Bowman’s capsule (Chmielewski, 2003; Dukes & Reece, 2004). This vascular loop is an extension of the afferent arteriole (AA), which continues as the efferent arteriole (EA) as it exits the capsule. The AA carries the blood containing systemic metabolites and waste materials to the glomerulus before branching into vessels that are in close apposition with the Bowman’s capsule. The vessels then continue as the EA, now carrying filtered blood. The EA divides to form an intricate network of peritubular capillaries (vasa recta) around the long tubule of the nephron. The vasa recta are a part of a low-pressure complex, essential for the re-absorptive and secretory function of the kidneys (Dukes & Reece, 2004; Finch, 2014; Sjaastad et al., 2016). The glomerular filtration barrier (GFB) is a complex trilaminar interface present between the glomerulus and Bowman’s capsule. It comprises the endothelial cells (glomerular capillaries) held together by the glycocalyx, glomerular basement membrane and podocytes (epithelial cells of Bowman’s capsule). These charged layers effectively prevent the loss of essential macromolecules, such as albumin, from the vascular lumen (Menon et al., 2012; Sjaastad et al., 2016). The pressured environment, within the vascular component of the corpuscle, ensures that the supplied blood is filtered through the GFB to produce urine. The ultrafiltrate/primary urine filters into the Bowman’s space and is carried through the tubular components of the nephron, i.e., the proximal convoluted tubule (PCT/ tubulus convolutes proximalis), the loop of Henle, distal convoluted tubule (DCT/ tubulus convolutes distalis), the collecting tube- joins those of the other nephrons to form an arcade- that finally continues as the cortical collecting duct (Seldin & Giebisch, 1985), which opens into the renal sinus. The juxtaglomerular nephrons are equipped with an additional limb (ascending) of the loop of Henle’s (Chmielewski, 2003). The ultrafiltrate comprises ~ 27-31% of the supplied venous plasma in cats. It is subjected to secretory/excretory and re- absorptive physiological processes that enables systemic homeostasis (Finch, 2014; Sjaastad et al., 2016). Almost 99% of the filtrate is reabsorbed into the surrounding Extracellular Fluid (ECF), maintaining its osmolarity, a factor essential to ensuring the urine concentrating ability of nephrons. 7 2.1.2 Renal Vasculature Each kidney has a rich source of blood supply, delivered by a direct branch of the abdominal aorta, i.e., the renal artery. The renal vascular system is a portal system, i.e., the capillary beds (glomerular and peritubular capillaries) are enveloped by arteries (Chmielewski, 2003). The renal arteries divide into smaller vessels: the segmental arteries, multiple interlobar arteries, interlobular arteries, arcuate arteries and cortical radiate arteries, until they finally continue as the AA (Glaser, 2017). The AA and EA form the distal limbs of the invaginating tuft of porous glomerular capillaries. The EA continues as the interlobular and interlobar veins and then exits the kidney as the renal vein (Aspinall, 2004) before emptying into the caudal vena cava. The vasa recta, a division of the EA and peritubular capillaries, perfuses the tubular component of the nephron in the medullary region (Dukes & Reece, 2004), as shown in Figure 2. They play a significant role in osmoregulation through the counter- current mechanism- essential for urine concentration- and are responsible for carrying the venous blood from the deeper parts of the medulla (Chmielewski, 2003; Seldin & Giebisch, 1985). The kidneys are supplied by 20% of the total cardiac output (Chmielewski, 2003); 90% of the renal blood supply is directed towards the cortex and about 7.5% to the renal medulla. This difference in blood supply across the regions, i.e., the renal cortex (high blood flow) and the outer-/inner- medulla (Eaton & Pooler, 2009, p. 13), is essential for the production and excretion of concentrated urine (Sjaastad et al., 2016, p. 558). Figure 3 illustrates the difference in renal BP across the different vessels, such as the difference between the AA and the peritubular capillaries, supplying the various structures in the human kidney, assumably like what would be seen across the renal vasculature in cats. 8 Figure 3 Difference in blood pressure across the renal vasculature in the human body. As depicted in the graph, the blood pressure across the renal vasculature drops, especially in the afferent and efferent arterioles. The higher glomerular pressure ensures proper filtration in the renal corpuscle, while the lower pressure in the peritubular capillaries maintains the osmotic gradient with the tubule system. Permission for reprinting was granted by The McGraw-Hill Companies Inc. The parts of the nephron found in the medulla are suited to function in a low-pressure environment as the tubular fluid is of a different composition than blood (containing charged, heavy molecules). The vasa recta supply the outer medulla with blood containing low oxygen reserves (Kanagasundaram, 2015), playing a role in urine concentration. Essentially, this unique environment of varied blood supply across the cortex and the medulla places regions such as the PCT and the loop of Henle (highly metabolically active) at an increased risk of injury (Kirita et al., 2020)- especially if there is a discrepancy in renal blood flow or RBF (De Loor et al., 2013), such as a decrease leading to anoxia in the medulla (Evans et al., 2020), as it is already maintained at a precariously hypoxic environment to enable the process of urine concentration (Brezis & Rosen, 1995), as seen in Figure 2 (B). 9 2.1.3 Nervous Innervation of the Kidneys The sympathetic/adrenergic efferent nervous system works in tandem with the vital systems in the body to maintain homeostasis. The postganglionic sympathetic neurons innervate the renal tissue, including specialized cells, i.e., the juxtaglomerular granular cells or JGC (Dukes & Reece, 2004; Seldin & Giebisch, 1985). Sympathetic stimulation, in stressful conditions, reduces urine production by mediating the vasoconstriction of the AA and the release of norepinephrine from the adrenal medulla. This reduction in urine production occurs due to the resulting decrease in the RBF (Glaser, 2017). The sympathetic nervous system also plays a role in the autoregulation of renal BP (Sjaastad et al., 2016). 2.2 RENAL FUNCTION The kidneys perform several vital functions in the body (Aspinall, 2004, pp. 134-144; Hall, 1983; Sjaastad et al., 2016), as shown in Figure 4. Namely, 1) excretory function, which involves the removal of non-gaseous metabolites such as nitrogenous wastes, excess water, detoxified products and inorganic ions, 2) production of proteinaceous substances such as erythropoietin (RBC production), renin (BP regulation) and calcitriol (calcium homeostasis), and 3) Ionic balance maintenance through secretory/re-absorptive processes carried out in the tubular portions of the nephron. Tubular functions include removal/absorption of salt, proteins, glucose, and electrolytes (Potassium, sodium). Other functions include: 4) osmoregulation which helps maintain the composition, and volume of ECF among other body fluids. This is carried out by a complex interplay of factors such as renin, angiotensin, aldosterone, antidiuretic hormone, baroreceptors, and osmoreceptors. The kidneys also 5) maintain the systemic acid-base balance, and 6) act as a site for gluconeogenesis. 10 Figure 4 Functions of the nephron. Diagrammatic representation of the direction of nephronal processes: ( 1 ) glomerular filtration, (2) tubular secretion and (3) tubular reabsorption. This image has been reprinted, with permission, from Vander's renal physiology. The kidneys are capable of autoregulating renal BP, irrespective of the changes to arterial BP (to a limit), which is initiated by the secretions of the Juxtaglomerular apparatus (JGA). The JGA consists of (1) macula densa, a group of specialized chemosensory epithelial cells found at the point of contact between the DCT and the glomerular AA. The macula densa can detect changes in the tubular fluid electrolyte levels (sodium and chloride ion) and tubular fluid volume. (2) juxtaglomerular granular cells (JGC): barosensory myocytes in the AA wall, which are stimulated by the nervous system to produce Renin, an enzyme that helps autoregulate renal BP and maintain renal function when homeostasis is affected (Sjaastad et al., 2016). The extra-glomerular mesangial/Lacis/Goormaghtigh cells, found between the macula densa and the glomerular capillaries (Dukes & Reece, 2004; Seldin & Giebisch, 1985, p. 297), also play a role in maintaining the glomerular filtration rate (GFR; described below), as well as the osmolarity of the filtrate (indirectly), through the contraction and relaxation of the specialized myocytes (Glaser, 2017). 11 2.2.1 Glomerular Filtration Rate (GFR) The glomerular filtration rate (GFR) is the rate at which the ultrafiltrate is formed (Dukes & Reece, 2004; Eaton & Pooler, 2009). The net filtration pressure across the glomerular apparatus is essential for maintaining the GFR. The filtration pressure is maintained by the difference in hydrostatic pressure and plasma-oncotic pressure between the sites involved, i.e., the glomerular capillaries and the Bowman’s space (Sjaastad et al., 2016, p. 560). The arterial BP influences the hydrostatic pressure in the glomerular capillaries. GFR is, thus, influenced by arterial BP (Eaton & Pooler, 2009) and the resistance offered by the renal arterioles (Finch, 2014; Sjaastad et al., 2016). The measurement of GFR helps monitor renal filtration and excretion, thereby providing information on renal function in a clinical setting (Von Hendy-Willson & Pressler, 2011). 2.2.2 Autoregulation of Renal Blood Flow (RBF) The GFR is regulated by intrinsic reno-protective mechanisms (Kanagasundaram, 2015) that stabilize RBF, irrespective of systemic BP under steady conditions to a certain level (Cupples & Braam, 2007). Any slight variation in homeostasis, such as a drop in MAP, which could potentially affect renal function by causing a change in renal perfusion, stimulates the autoregulatory mechanism in the kidneys. This mechanism, functional only when the renal BP is within certain bounds, i.e., ~ 75 mmHg to 160 mmHg in dogs (Cupples & Braam, 2007), drives the excretion or absorption of hormones, salts and water to help maintain normal kidney function and, thus, GFR (Eaton & Pooler, 2009), as shown in Figure 5. Furthermore, a MAP of 60-70 mmHg is required to ensure organ perfusion (Mazzaferro & Wagner, 2001). 12 Figure 5 Effect of arterial blood pressure (BP) on renal blood flow (RBF) and, consequentially, on GFR. Graph depicting the correlation between mean arterial blood pressure and renal blood flow. Changes in the BP within the autoregulatory range observes minimal variation in RBF due to the intrinsic renal autoregulatory mechanisms. However, if the BP falls below the lower threshold of this range, the renal autoregulatory mechanism would fail leading to decreased RBF and an increased risk of renal damage. This image has been reprinted, with permission, from Vander's renal physiology. The process of renal autoregulation is mainly mediated by two mechanisms (Dukes & Reece, 2004; Sjaastad et al., 2016): 1) myogenic manipulation (rapid), and 2) tubuloglomerular feedback (slow). The former is stimulated by arterial wall tension, releasing eicosanoids (Kanagasundaram, 2015) and inducing a change in the AA's myogenic membrane potential (Cupples & Braam, 2007). This enables the AA to vasoconstrict/-dilate, as required, to regulate renal BP and, thus, prevent any negative impact on renal function. The latter mechanism relies on the JGA to maintain a normal environment in the kidney, undeterred by any changes in the systemic BP to a certain extent. The macula densa (JGA) secretes mediators (renin) that cause vasoconstriction/vasodilation of the AA when blood flow is affected, thereby modulating RBF to bring GFR to baseline. Renin-Angiotensin-Aldosterone System (RAAS) The RAAS system is involved in BP regulation (Coleman & Elliott) and is stimulated by the tubuloglomerular feedback mechanism. A loss of arterial wall stretch incites the JGA, i.e., through reduced blood volume or lowered BP. The change in BP (reduced RBF) subsequently causes a drop in the GFR, leading to changes in the tubular fluid salt concentration (Jepson, 2016). These variations in the delivery of sodium (Na+) ions are detected by the macula densa cells (Sjaastad et al., 2016). Renin, secreted by the JGA, is responsible for converting angiotensinogen to angiotensin Ⅰ in the kidneys. Angiotensin Ⅰ is converted to Angiotensin Ⅱ in the presence of Angiotensin- Converting Enzyme (ACE), which is mainly present in the endothelial cell membrane of the lungs (Sjaastad et al., 2016). Angiotensin Ⅱ induces vasoconstriction of the renal AA, thereby increasing the hydrostatic pressure of the glomerular capillaries, leading to glomerular hyperfiltration. This increase in renal BP helps maintain homeostasis for a short duration; however, extended periods of these episodes requiring autoregulation will have detrimental effects, such as fibrosis/sclerosis of tissue (Finch, 2014). 2.3 FELINE RENAL DISEASE Prevalence Renal disease is a prevalent affliction in geriatric animals and is a significant cause of mortality in cats. It has been hypothesized that animals become susceptible to KD through exposure to subclinical injuries (Bland et al., 2014; Vaidya, Ferguson, & Bonventre, 2008). These injuries may cause maladaptive changes that disturb the delicate balance between the reparative and degenerative processes of renal parenchyma; initiating a “self-perpetuating vicious cycle” of kidney damage. While progress is being made in improving therapeutic protocols for KD, the mortality rate for cats affected with KD has not declined over the years (Segev, 2018a). The leading cause for the failure to effectively treat the condition is the inability to detect KD in its 13 14 preliminary stages of damage. Therefore, there is a need to educate owners on the signs of KD and improve our diagnostic tests to detect it in its initial phases to improve the responsiveness to treatment. Classification Renal disease can be broadly classified into acute kidney injury (AKI) and chronic kidney disease (CKD). Other categories, such as Acute-on-Chronic (Segev, 2018a) and chronic-on-acute kidney disease, have been identified, wherein either condition occurs in individuals with pre-existing KD. However, clinical cases are currently identified as either AKI or CKD as this helps determine the severity of KD, determine the prognosis and allow for subsequent treatment planning. Both AKI and CKD were initially believed to be separate disorders with different pathophysiology. However, over recent years, this belief has transmuted as the pathophysiology of the two conditions is, in fact, quite similar (Segev, 2018a, 2018b). Both conditions involve the impairment of nephrons, and there can be a bidirectional communication between the two disorders, i.e., AKI being an initiating cause for CKD (Schmiedt et al., 2016) and vice versa (Cowgill et al., 2016). Segev (2018a) suggested that active renal injury could be used to differentiate KD, i.e., an increase in active renal injury indicators hints at AKI, while its presence in lower concentrations may hint at a slower progressive KD. Grading/Staging Kidney Disease, i.e., both AKI and CKD, is generally staged or graded using International Renal Interest Society (IRIS) guidelines that uses conventional markers, such as serum creatinine (SCr) and symmetric dimethyl-arginine/SDMA (Segev, 2018b), to gauge the severity of the condition. The two conditions, i.e., AKI and CKD, differ in the rate of progression, ultrasonographic findings and histology. Clinical cases are generally identified as AKI if the renal parameters change significantly over a short period, i.e., hours or days (Schollum, 2012). They are identified as CKD if the parameters gradually develop and persist for over two to three months (Jepson, 2017). 15 As mentioned before, it has been suggested that mild, transient/ongoing AKI could be a precursor for CKD (Chen et al., 2019; Cowgill, 2016; Cowgill et al., 2016; Katayama et al., 2020; Schmiedt et al., 2016; Vaidya, Ferguson, & Bonventre, 2008). While the study by Schmiedt et al. (2016) found experimentally induced AKI to have long- lasting malfunctioned reparative effects on feline kidneys, a strong correlation between mild AKI and CKD has yet to be proven (Bland et al., 2017; Cowgill et al., 2016). This uncertainty is, in part, because subclinical cases of renal injury frequently remain undetected and, thus, have not been longitudinally studied as clinical cases. Clinical signs of KD can be non-specific. These include polyuria, polydipsia, lethargy, vomition, cachexia, inappetence, dehydration, halitosis, melena, diarrhoea and uremic stomatitis. Other apparent complications observed in clinical cases include peritoneal/pleural oedema/effusion, hyphema, retinal detachment and acute blindness (Eatroff; Segev, 2018b; Syme, 2019). It has been suggested that owners sometimes fail to notice subtle signs of illness especially in cats, a species that can mask the disease. Owners are also prone to attribute some of the signs to the normal ageing process. Kidney diseases such as AKI and early CKD can be challenging to diagnose in cats among other species (Katayama et al., 2020; Syme, 2019). The mild or early stages of KD are less frequently diagnosed because the affected cats may remain asymptomatic (Cobrin et al., 2013; Lobetti & Lambrechts, 2000), until the damage is severe, leading to delayed presentation to a clinical setting. This is futher worsened by our reliance on insensitive diagnostic tests which are more suited to detect the later stages of KD. These traditional tests, such as serum creatinine (SCr) or blood urea nitrogen (BUN), require almost 75% of the renal mass to become dysfunctional before these markers are elevated to levels that alert clinicians to the presence of renal damage. De Loor et al. (2013) notes “kidney injury can be present in the absence of kidney function” (p. 998, para 1). This aptly describes the limitation associated with the use of conventional markers that are elevated over the reference range only when the GFR is affected and this allows cases of subclinical injury to go undiagnosed (Bland et al., 2014; Sargent et al., 2021; Vaidya, Ferguson, Collings, et al., 2008; van den Berg et al., 2018). This severe limitation prevents effective treatment of kidney damage or dysfunction in its early stages, primarily 16 since subclinical active renal injury is associated with increased mortality risk (Gumbert et al., 2020). Therefore, we must use markers that can identify kidney injury long before we see any change in GFR, i.e., before 75% of the nephrons become dysfunctional. 2.4 ACUTE KIDNEY INJURY (AKI) Synonym: Acute renal failure (ARF) Acute Kidney Injury is usually characterized by abrupt renal dysfunction (Chen et al., 2020; Sargent et al., 2021), set off by ischemic or toxicant-induced renal parenchymal injury that develops within three months (Cowgill, 2016; Kovarikova, 2015; Vaidya, Ferguson, & Bonventre, 2008). It is caused by “rapid hemodynamic, filtration, tubulointerstitial or outflow injury to the kidneys leading to accumulation of metabolic toxins (uremia toxins) and dysregulation of fluid, electrolyte, and acid-base balance” (Cowgill, 2016, p. 1). Acute Kidney Injury is presumed to have a high mortality rate (Cowgill, 2016) of ~ 50% across species (Dunaevich et al., 2020; Worwag & Langston, 2008). As mentioned before, the main limitation faced in a clinical environment is a delay in detection (Cobrin et al., 2013; Kovarikova, 2015; Vanmassenhove et al., 2013) which can prove to be critical, as early diagnosis can either reverse the damage or cease its progression (Senior, 2017). Intrinsic AKI can originate from either glomerular or tubular injury, with ischemia being the most common cause of the latter (Kanagasundaram, 2015). As different areas of the kidney have varying levels of susceptibility to injury, due to the unique vasculature and metabolic needs of the tubular cells, the minimum threshold for inciting renal injury is not known. Prevalence Eatroff (2020) indicated that due to the lack of information on AKI and its various possible aetiology, the exact prevalence of the condition cannot be determined. Furthermore, the current dilemma, with the use of conventional diagnostic tests (Segev, 2018a, 2018b), has led to underestimating the true prevalence of AKI in companion 17 animals. The mortality rate for AKI-affected individuals was 47% in a retrospective study by Worwag and Langston (2008), and the prognosis is generally poor (Dickerson et al., 2017). Pathophysiology Acute Kidney Injury develops through four distinct phases of injury, i.e., initiation, extension, maintenance, and recovery (Eatroff, 2020; Ross, 2011). It is at the initiation phase that occurs immediately after the injury, when interventional therapy is most effective at reversing the damage. However, we fail to detect kidney injury at this stage due to a delay in admission, absence of any clinical signs or seemingly ordinary results found upon screening. The extension phase is characterized by the continued series of pathological changes leading to cell death (Ross, 2011). It progresses to the maintenance phase, where scarring or irreversible tubular lesions are formed, resulting in tubular dysfunction. This is the stage when clinicopathological signs, such as azotemia (Ross, 2011), are apparent (Chen et al., 2017). Reparative mechanisms in the recovery stage are characterized by hypertrophy of nephrons which helps compensate for the loss of the function of damaged nephrons (Grauer, 1996) and this change is irreversible. Improving screening tests that can identify the initiation phase of AKI would significantly improve the prognosis for kidney injury. The kidneys are more susceptible to injury when compared to other organs due to their unique anatomic vasculature (Jepson, 2016). The pathophysiology involves (Lobetti & Lambrechts, 2000; Ross, 2011) vasoconstriction of the AA in response to injury, reduced renal blood flow (RBF), reduced energy stores (ATP), the effect of pro-inflammatory modulators and tubular cell damage; these adaptive changes can lead to apoptosis (Grauer, 1996; Vaidya, Ferguson, & Bonventre, 2008) and desquamation of brush border cells. Histopathological study revealed that AKI is characterized by cell death/necrosis, and intact cells were morphologically altered. The changes observed after apoptosis include the presence of cytoplasmic blebs and reduced brush border of the PCT cells (Schmiedt et al., 2016). Cellular damage results in increased intracellular calcium levels, which sets off 18 the activation of several other catabolic enzymes (Ross, 2011). Ischemia in the kidneys stimulates nitric oxide synthase enzyme. The resulting increase in nitric oxide can react with other breakdown products such as superoxide to form reactive compounds, affecting transport proteins and intercellular adhesion junctions, thereby disrupting tubular reparation and recovery (Ross, 2011). Further, the action of inflammatory mediators can worsen hypoxia (Vaidya, Ferguson, & Bonventre, 2008), further worsening the severity of the damage. This can lead to an imbalance in the solute levels, such as increasing sodium ions. The RAAS is stimulated, causing the vasoconstriction of the AA, resulting in lowered GFR (Ross, 2011). Thus, the inherent mechanisms of the kidney may be involved in a self-perpetuating cycle of renal injury and fibrosis. Risk Factors The risk factors for AKI include: age, renal ischemia (Grauer, 2005; Kanagasundaram, 2015; Schmiedt et al., 2016) or reperfusion injury (Eatroff; Keir & Kellum, 2015; Lobetti & Lambrechts, 2000), subclinical inflammation, pre- existing CKD (Long et al., 2016), nephrotoxin-induced injury, or dehydration, hypovolemia, fluid overload, hypovolemia, hypotension, infarction, underlying disorders, medications (Chertow et al., 1997), infectious disease and/ or sepsis (Senior, 2017). One potential prerenal cause for AKI is decreased or altered renal blood perfusion due to intraoperative hypotension resulting from prolonged surgery/ anaesthesia (Grauer, 1996; Senior, 2017). It was found that ischemia is a common risk factor for AKI in dogs (Mishra et al., 2003). An experimental study that induced renal ischemia for 15 or 30 mins in cats found signs of atrophy and inflammation of varying severity in the tubular sections of nephrons through histopathology at 120 days, with warmer body temperature at the time of episode being at higher risk of renal injury even when it is within the physiological range (Dickerson et al., 2017). This suggests that both the duration, as well as the severity, of ischemia along with the body temperature may influence the level of renal damage. Perioperative renal ischemia is less pronounced when compared to ischemia in other organs and vessels in humans (Chertow et al., 1997). The renal tubules function in an 19 environment with low oxygen tensions (Chakrabarti et al., 2012) and are, therefore, susceptible to hypoxia. Hypoxia can result in increased production of free radicals, which cause summative oxidative damage. The risk is further increased by their high metabolic demands (Jepson, 2016). In support of this, experimentally induced unilateral renal ischemia (60 mins) was shown to induce adaptive fibrotic changes over 70 days, with major changes occurring in the tubular regions, in both, the corticomedullary tubular sections and the Bowman’s capsule (Schmiedt et al., 2016). The previous study observed significant hyperplastic, regenerative and/or necrotic pathology of the epithelial cells in the corticomedullary tubular sections by days 3 and 6 post-ischemia. Thus, the PCT (straight) and loop of Henle (ascending limb) are more likely to undergo maladaptive, possibly chronic changes when subjected to reduced perfusion. Decreased renal perfusion is associated with decreased cardiac output, oncotic pressure, increased blood viscosity or decreased prostaglandin formation. A study in the dog model showed that increasing renal perfusion through a venous shunting procedure resulted in a reversal of renal damage and proved that an adequate amount of oxygen is essential for re-establishing the GFR (Morales et al., 2002). These studies demonstrate that a minimal level of oxygen must be maintained within the kidneys for the vital functioning of nephrons. Markers sensitive to renal damage rather than a change in function, are better suited to diagnose AKI (Segev, 2018a). Clinical signs may be intense, and this condition may involve multiple organ systems such as the pancreas, lungs and GIT (Segev, 2018b). Current grading and sub-grading of AKI are done following the guidelines set by IRIS (Cowgill, 2016), as shown in Table 1. These guidelines are based on the values of classical markers such as serum creatinine (SCr). These guidelines help determine the prognosis of the case and plan the treatment regimen accordingly. 20 Table 1 IRIS AKI grading criterion (Cowgill, 2016). AKI Grade Blood Creatinine Clinical Description Grade Ⅰ < 1.6 mg/dl (< 140 µmol/l) Non-azotemic AKI: - Documented AKI:(historic, clinical, laboratory or imaging evidence of AKI, clinical oliguria/anuria, volume responsiveness) and/or - Progressive non-azotemic increase in blood creatinine ≥ 0.3 mg/dl (≥ 26.4 µmol/l) within 48 hrs - Measured oliguria (<1 ml/kg/hr) or anuria over 6 hrs Grade Ⅱ 1.7-2.5 mg/dl (141-220 µmol/l) Mild AKI: - Documented AKI and static or progressive azotemia - Progressive azotemic: increase in blood creatinine; ≥ 0.3 mg/dl (≥ 26.4 µmol/l) within 48 hrs, or volume responsiveness - Measured oliguria ((<1 ml/kg/h) or anuria over 6 hrs Grade Ⅲ 2.6-5 mg/dl (221-439 µmol/l) Moderate to severe AKI: - Documented AKI and increasing severities of azotemia and functional renal failure Grade Ⅳ 5.1-10 mg/dl (440-880 µmol/l) Grade Ⅴ > 10 mg/dl (> 880 µmol/l) Clinical signs The signs observed in an AKI-affected animal include polyuria/ oliguria, depression, vomition, polydipsia, anorexia, and hypothermia. Seizures and muscle fasciculations may be seen in severe cases with uremic nephropathy (Senior, 2017). Polyureic AKI, i.e., in animals who have lost their ability to concentrate the ultrafiltrate, are more likely to have both glomerular and tubular injury. 21 Serum biochemistry findings include observing an increase in serum creatinine (SCr), blood urea nitrogen (BUN), phosphate, potassium, along with a decrease in calcium; Upon urine examination, the presence of active sediment with casts and inflammatory cells is indicative of AKI (Senior, 2017). As mentioned before, transient AKI can act as a precursor for KD later in life (Dunaevich et al., 2020; Vaidya, Ferguson, & Bonventre, 2008), as depicted in Figure 6. The auto- regulatory capacity of the kidneys fails once AKI sets in (Kanagasundaram, 2015). Unregulated renal pressure may place the tubular sections of the nephron in a vulnerable position. Even a slight change in the typical structure and/or function of renal tissue, such as delayed repair (Vaidya, Ferguson, & Bonventre, 2008), can set off a cycle of sustained or progressive damage. Furthermore, the inflammatory, fibrotic changes brought about by the damage tend to remain after repair (Schmiedt et al., 2016), leading to increased susceptibility to renal injury in the future (Kirita et al., 2020). Ongoing or episodic bouts of AKI progressing to CKD only become clinically symptomatic once the compensatory mechanisms of the kidneys are incapacitated (Chen et al., 2020). Figure 6 Spectrum of AKI and CKD pathophysiology. Mild damage to a normal kidney induced by a change in the renal environment can result in acute kidney injury. This can progress to irreversible chronic kidney damage. Reprinted from Cowgill et al. (2016). 22 The progression of AKI to CKD should be prevented as early as possible, especially since AKI can be potentially reversed, while the changes brought on by chronic fibrosis are irreversible (Chen et al., 2020). If kidney injury could be diagnosed early on, the pathological process can then be delayed or reversed with appropriate treatment and rehabilitation, inevitably improving the patient's quality of life. However, we require sensitive and specific, markers to aid in the detection and diagnosis of early KD. Such development can be introduced through focused species-specific studies to compare and introduce improved, validated renal biomarkers. 2.5 CHRONIC KIDNEY DISEASE (CKD) Chronic Kidney Disease is a progressive disorder involving the kidneys that develops over a long period, typically over three months (Dunaevich et al., 2020), characterized by altered renal structure and function (Jepson, 2016; Sargent et al., 2021). The resulting damage may be irreparable. Unlike AKI, CKD can be either acquired or congenital in origin (Antunes Ribeiro et al., 2020; Reynolds & Lefebvre, 2013). Prevalence The prevalence of CKD increases with age (Biourge et al., 2020; Conroy et al., 2019; Geddes, 2013; Jepson, 2016; Kovarikova, 2015; Reynolds & Lefebvre, 2013; Roura, 2019) and is estimated to affect ~ 80% of cats over fifteen years of age, while it is reported to affect ~ 1-3% of the population across other age groups (Conroy et al., 2019; Paepe & Daminet, 2013; Roura, 2019). CKD has not been reported to be gender specific. Similar to AKI, the insensitivity of our current diagnostic tests have probably undervalued the true prevalence of CKD in the population (Conroy et al., 2019). Risk factors The factors influencing AKI also influence CKD development (Jepson, 2016). An interplay of several factors such as age, drugs, diet, genetic/hereditary factors, comorbidities 23 (infectious/inflammatory, neoplastic), a recent history of general anaesthesia, hypertension, proteinuria, vaccination, scarring, and active injury is associated with CKD development (Chen et al., 2020). The Dunaevich et al. (2020) study on dogs reported that 45% of the CKD cases had no known aetiology, while approximately 7% of all the CKD cases had an ischemic origin. The delayed diagnosis makes identifying CKD risk factors and aetiological causes challenging (Roura, 2019). Pathophysiology A histopathological study revealed CKD models to be characterized by hyperplastic arteriosclerosis, tubulointerstitial inflammation and fibrosis (Chakrabarti et al., 2013), followed by tubular mineralization in later stages (Antunes Ribeiro et al., 2020; Bland et al., 2017; Grauer, 2021). The autoregulatory system of the kidneys engages in the progression of CKD by inducing fibrotic and sclerotic changes in the glomerulus (Coleman & Elliott; Jepson, 2016). The uninjured functional nephrons adapt to compensate for the loss in function by undergoing hypertrophy, while the glomerulus remains in a constant state of hypertension and hyperfiltration (Biourge et al., 2020). These fibrotic changes affect the kidneys' filtration capacity, eventually decreasing the GFR once the compensatory mechanisms fail. Glomerular damage results in improper filtration of metabolic wastes and increased leakage of charged or high molecular weight (HMW) proteins into the ultrafiltrate, while tubular damage impairs the resorptive processes. This results in an accumulation of unfiltered toxic metabolites in the bloodstream with electrolyte imbalance as well as increased quantities of various molecules in the ultrafiltrate and, subsequently, the excreted urine. The increasing quantity of nitrogenous wastes (urea) in blood has lasting toxic consequences on the organ systems and this elevation is translated into increased BUN values in serum samples. Persistent uremia can injure the cellular components of blood, resulting in a decreased lifespan of erythrocytes. This, along with a decrease in the renal production and secretion of erythropoietin, leads to anaemia (Antunes Ribeiro et al., 2020). Several pathophysiological and haematological changes can, thus, be observed with the progression of KD. These changes, however, are revealed upon biochemical 24 examination only once most of the renal nephrons have been damaged, which finally potentiates clinical signs such as lethargy, vomition and other uremic effects. Clinical Signs The clinical signs of CKD are generally non-specific, made more difficult by the cat’s ability to mask the illness. Signs that may be observed include anorexia, lethargy, weight loss, polydipsia, polyuria, vomition and/or diarrhoea (Conroy et al., 2019; Dunaevich et al., 2020). Cat owners usually fail to observe changes in behaviour and other symptoms until they become overtly evident over time (Segev, 2018b), as was observed in a study by Conroy et al. (2019), where 66.6% were presented after the appearance of clinical signs. An alarming 24.8% of the cats diagnosed with CKD in the same study were asymptomatic. Some of the early outward manifestations of KD may be mistaken for signs of ageing (Robertson et al., 2018). This misconception is concerning since clinical symptoms appear only once a significant mass of the kidneys is damaged, primarily when the autoregulatory and compensatory mechanisms of the kidneys fail to maintain normal function (Reynolds & Lefebvre, 2013). Educating the owners on KD, along with its associated signs, is vital for improved screening and detection of the condition. Grading Kidney dysfunction in humans is clinically identified through proteinuria, hypertension, and azotemia (de Souza Rodrigues et al., 2017). In tandem with this, CKD has been classified into four stages by the International Renal Interest Society (IRIS) based on SCr and symmetric dimethylarginine (SDMA) concentrations, as displayed in Table 2. They are further sub-grouped based on systolic arterial pressure (SAP), urine protein to creatinine ratio (UP:C) and urine specific gravity (USG). As per the IRIS guidelines (similar to AKI), CKD staging helps ascertain the diagnosis/prognosis and plan the treatment protocol (Antunes Ribeiro et al., 2020; Paepe & Daminet, 2013). 25 Table 2 IRIS Staging of CKD (IRIS CKD Pocket Guide; IRIS Staging of CKD, 2019). * Serum creatinine † Symmetric dimethyl-arginine ‡ Urine protein creatinine ratio § Systolic arterial pressure Stage SCr* (mg/dl) SDMA† (µg/dl) UP:C‡ (Substage) SAP§ mmHg (Substage) Comments 1 < 1.6 (< 140 µmol/l) < 18 Non-proteinuric < 0.2 Borderline proteinuric 0.2-0.4 Proteinuric > 0.4 Normotensive < 140 (minimal risk of target organ damage). Prehypertensive 140-159 (low risk of target organ damage). Hypertensive 160-179 over 1-2 weeks (moderate risk of target organ damage). Severely hypertensive ≥ 180 for more than 1-2 weeks (high risk of target organ damage). Non-azotemic; normal to slightly increased blood SDMA; with/-out change in urine concentrating ability, abnormal renal palpation or imaging findings, proteinuria, abnormal biopsy results; serial increase in SCr or SDMA; Persistent SDMA value > 14 µg/dl; 2 1.6-2.8 (140-250 µmol/l) 18-25 Normal to mild azotemia; mild increase in SDMA; Clinical signs may be present or absent. 3 2.9-5.0 (251-440 µmol/l) 26-38 Moderate azotemia: absence of clinical signs is categorized as early stage 3 and clinical systemic signs as late stage 3. 4 > 5.0 (> 440 µmol/l) > 38 Uremic crisis (severe azotemia) and systemic clinical signs. 26 2.6 RISK FACTORS Several studies have been performed to identify the risk factors and aetiology for renal disease. However, the inability to identify the early stages of KD also prevents the diagnosis of the aetiology and other inciters for most clinical cases (Syme, 2019; Vanmassenhove et al., 2013). Therefore, it is essential to perform focused studies to determine all the major causal links to kidney damage. The current hypothesis suggests that even subtle insults caused by drugs, hypoxia, or ischemia could precipitate kidney injury. The perioperative environment, including surgical stress (Motayagheni et al., 2017), carries the risk of altered cardiovascular function, increasing the risk of renal hypoperfusion. With the surging commonality of elective surgeries for small animals, conscious use of anaesthetics is essential to prevent or reduce the risk of injury to the kidneys. 2.6.1 General Anaesthesia and Surgery Several possible complications arise with the use of general anaesthetics and surgical procedures as an invariable consequence of their depressor effects. To list a few: hypovolemia, hypoxemia, decreased cardiac output and hypotension, all of which can affect vital organ function/structure (Duke-Novakovski et al., 2016; Mama & Rezende, 2015), and in the case of kidneys, possibly incite AKI (Eatroff et al., 2012). Perioperative AKI is induced surgically through hypoperfusion and inflammation (Gumbert et al., 2020). This type of injury is usually transient and generally goes undetected due to both the absence of overt clinical signs and the insensitivity of conventional point-of-care tests. Cats are susceptible to anaesthetic complications due to their innate physiology (Brodbelt, 2010; Brodbelt et al., 2007; Robertson et al., 2018). Levy et al. (2017) found that cats undergoing the spay/neuter procedure were at a higher risk of mortality (five-fold) when compared to dogs, with Brodbelt et al. (2007) reporting a 0.24% risk of anaesthesia-induced mortality in cats. It was observed in a study by Bland et al. (2017) that histopathology of renal sections of healthy controls (cats without KD) had evidence of mild injury possibly linked to sedation/anaesthesia or euthanasia. Similarly, Chen et al. (2019), as well as Worwag and Langston (2008), observed general anaesthesia-induced AKI in cats. The latter 27 retrospective study identified AKI onset (based on serum biochemistry) in two cats, with the cause being pinned on the recent use of anaesthesia. Senior or geriatric cats are more susceptible to anaesthesia-induced changes in respiratory and cardiovascular function (Robertson et al., 2018). These transient systemic changes can affect the blood supply to different organ systems, especially the kidneys. Furthermore, the metabolically active medullary components of the kidneys are susceptible to ischemia- induced pathology as the renal perfusion across the cortex and medullary region differ, as mentioned before. To re-emphasize, the cortex receives approximately 85-90% of the RBF, while the medulla receives around 7% of it (Mama & Rezende, 2015; Sjaastad et al., 2016). The inadvertent effects of general anaesthesia on the cardio-respiratory system are described below. Intraoperative systemic hypotension is observed when the mean arterial pressure (MAP) falls below 62 mmHg, or systolic arterial pressure (SAP) falls below 87 mmHg (Robertson et al., 2018; Ruffato et al., 2015). It is a common complication (Gaynor et al., 1999) seen in almost 3% of the cats subjected to general anaesthesia (McMillan & Darcy, 2016). A minimum SAP of 80 mmHg or a MAP of 60 mmHg is essential to ensure vital organ perfusion (Duke-Novakovski et al., 2016, p. 435; Mama, 2021), primarily since renal autoregulation works only when the arterial BP is within a specific range, as previously shown in Figure 5. When the arterial BP falls, the systemic autoregulatory mechanisms prioritize securing sufficient perfusion to the CNS and myocardium, decreasing renal perfusion. Therefore, general anaesthesia and surgery, causing hypotension with/-out hypovolemia (Grauer, 1996), can increase the risk of renal injury and dysfunction (Kongara et al., 2009). Furthermore, when the renal autoregulatory mechanism fails to perform (Mama & Rezende, 2015), the now compromised RBF, if found to persist, may worsen the risk of tubular and glomerular injury in the kidneys through the action of vasoconstrictors (on AA), aggravating deteriorative processes such as fibrosis (Gumbert et al., 2020). A study by Worwag and Langston (2008) retrospectively identified 2 cases (cats) that had suffered from AKI, post a hypotensive-hypovolemic episode. 28 Hypoventilation, a consequence of anaesthesia (Robertson et al., 2018), was reported in ~ 9.7% of cats in a teaching hospital (McMillan & Darcy, 2016). A decrease in oxygen levels can intensify renal tubule injury as these cells are highly active. Hypothermia is a complication associated with anaesthetic use across all age groups in cats (Brodbelt et al., 2007), with almost 7% of the caseload in a teaching hospital experiencing it according to a survey (McMillan & Darcy, 2016). It can delay drug clearance (Robertson et al., 2018). Thus, the adverse effects (if any) of these drugs on the respiratory and cardiovascular systems can persist until they have been eliminated from the body. Drug accumulation could result in mild renal injuries, as well. Anaesthetic agents Most anaesthetics cause changes in systemic physiological parameters such as BP, heart rate (HR) and respiratory rate (RR); however, these changes are short-lived. The transient nature of these changes, along with the constant peri-operative monitoring, ensures that the cardiovascular and respiratory functions are maintained at levels that minimize the risk of organ damage (Mama & Rezende, 2015). Knowing that even mild injury could be a precursor for more lethal damage, we must improve our understanding of the interaction between various anaesthetics and the renal system. Pre-anaesthetic medication such as phenothiazines (e.g., acepromazine) and subsequent general anaesthesia using volatile anaesthetics (e.g. isoflurane) can cause significant vasodilation with cardiac depression that may inevitably decrease cardiac output as well as MAP (Gumbert et al., 2020). A fall in the MAP below 60 mmHg can lead to the failure of the renal autoregulatory mechanism leading to decreased RBF (hypoperfusion) and potentially damaging the nephrons if the circumstances persist. This can embroil the kidneys into a state of progressive damage. Isoflurane is a commonly used inhalant anaesthetic used to maintain anaesthesia. Isoflurane allows for faster recovery (Sano et al., 2018); however, it can cause dose- dependent hypotension (Ramsey, 2011, p. 182), reduced cardiac output and stroke volume (Mazzaferro & Wagner, 2001), and respiratory depression (Poterack et al., 1991; Ramsey, 29 2011). Poterack et al. (1991) observed that when isoflurane was administered at 3% in cats, the HR decreased by 50%, SAP by 61%, MAP by 70% and abdominal aortic blood flow by 71%. This decrease in abdominal blood output may influence renal perfusion and lead to sustained pathological changes. Opioids, such as buprenorphine, butorphanol and morphine, are combined with other anaesthetics for their analgesic/sedative properties (Robertson et al., 2018). The duration of action for buprenorphine (4-6 hr) and morphine (2-4 hr) is longer in cats than in other animals due to the lack of a hepatic-origin metabolic enzyme (Ramsey, 2011). Thus, these opioids remain in systemic circulation for an extended period. These drugs may have a depressor effect on HR, cardiac output, and BP (Mazzaferro & Wagner, 2001). Acepromazine is a phenothiazine that causes sedation by depressing the CNS (Ramsey, 2011) and affects BP (Mazzaferro & Wagner, 2001). It can cause hypotension (Mazzaferro & Wagner, 2001; Ramsey, 2011; Robertson et al., 2018; Schwarz et al., 2014) by inducing systemic vasodilation, i.e., reduced vascular resistance. It has been shown to exacerbate hypotension when used in adjunct with low-level isoflurane in dogs (Sinclair & Dyson, 2012). A study on cats sedated with acepromazine and alfaxalone undergoing spay procedure reported hypotension in 71% of the cases, stabilized with fluid therapy (Schwarz et al., 2014). The use of acepromazine in combination with opioids (butorphanol) to sedate cats can reduce BP through the effect of vasodilation (phenothiazine-induced) by 30 minutes (Costa et al., 2021). Dexmedetomidine is an α2-agonist that has sedative, muscle relaxative and analgesic properties (Ramsey, 2011). It affects the cardiovascular system, thereby reducing heart rate (40%), stroke index and cardiac output (60%); however, it also causes vasoconstriction, inadvertently causing an increase in BP, systemic vascular resistance, and blood glucose (Pypendop et al., 2011; Robertson et al., 2018). We generally observe a biphasic effect on BP, i.e., an initial increase followed by a decrease in BP. It causes a dose-dependent decrease in MAP (Mazzaferro & Wagner, 2001). It was shown to have adverse hemodynamic effects when given to isoflurane-anaesthetized cats (Pypendop et al., 2011). 30 When dexmedetomidine is combined with ketamine, it provides short-duration anaesthesia in cats and analgesia/sedation with opioids. It is quickly metabolized and, thus, the animal recovers faster from anaesthesia. The combination of Dexmedetomidine with alfaxalone and butorphanol was shown to reduce BP, diastolic arterial pressure (DAP) and MAP, in cats after thirty minutes (Cremer & Ricco, 2018). The combination of dexmedetomidine with ketamine and butorphanol in healthy cats was shown to decrease the partial pressure of oxygen and, in turn, increase the risk of hypoxemia, i.e., when the partial pressure of oxygen falls below 80 mmHg (Cremer & Ricco, 2018). Ketamine is a dissociative anaesthetic agent (sympathomimetic) with analgesic properties and a quick recovery rate (Fish, 2008, p. 9). It has positive ionotropic-chronotropic effects on the cardiovascular system (Da Silva Mello et al., 2019; Fish, 2008, p. 10; Sano et al., 2018), along with broncho-dilatory effects (Cremer & Ricco, 2018). It is reported to increase the MAP in cats (Da Silva Mello et al., 2019; Sano et al., 2018). Premedicated induction using a combination of dexmedetomidine, ketamine and butorphanol (DKT), administered intramuscularly (IM), produces rapid sedation, analgesia and anaesthesia. This protocol is commonly used for minor procedures such as spays or neuters. Its rapid onset makes it an excellent option to streamline surgeries for places with a high volume of cases, as seen in shelters (Ko & Berman, 2010). A combination of DKT premedicated induction (IM), followed by inhalant anaesthesia to maintain the depth of anaesthesia during surgeries such as ovariohysterectomy (OHE) provides smooth induction, maintenance, and recovery. The main disadvantage of using this anaesthetic combination is the associated drop in MAP, where there is no control over the depth of anaesthesia after IM administration of DKT (Ko et al.2009). Alfaxalone is a neuro-steroid known for its dose-dependent properties such as rapid induction and short-action (Fish, 2008, p. 11). Its use can cause respiratory depression at high doses (Cremer & Ricco, 2018) and severe hypotension in cats (Fish, 2008). Some of the adverse effects of this agent include ataxia, muscle fasciculations, paddling and vomiting during recovery in cats when used as the sole anaesthetic agent. 31 The occurrence of any of the above-mentioned systemic changes in response to anaesthetic drugs and surgery, resulting in decreased oxygen deliverance, increased oxidative damage, and more, can cause renal lesions that may not be clinically apparent (Katayama et al., 2019); however, these subclinical changes may play a role in the pathophysiology of progressive KD. This hypothesis was supported by Lobetti and Lambrechts (2000), who suggested that while most organs may tolerate transient hypotension, it is not so with the kidneys. Any renal structural and functional change can lead to irreversible damage (Grauer, 1996). A study on female dogs undergoing routine spay procedures found signs of active tubular damage postoperatively. The damage was detected by noting the presence of renal casts on urine sediment examination and an increase in the concentration of Gamma-glutamyl transferase/GGT, a relatively new renal marker, within 24 hrs postoperatively (Lobetti & Lambrechts, 2000). Interestingly, in this study, the older renal markers such as SCr and BUN remained within the reference range, suggesting that novel markers might be a more sensitive or an early indicator of mild renal structural damage. What is important to note is that this increase in renal marker concentration supports the theory that general anaesthesia and surgery are capable of causing asymptomatic (externally) renal damage that remains undiagnosed when we use the traditional renal markers to monitor for KD. A study by Chen et al. (2019) reported AKI-induced by general anaesthesia in two cats, diagnosed by the steady increase in SCr value by 0.3 mg/dl within 48 hrs; however, these incidences might have been a more severe form of renal injury. These studies provide evidence to suggest that general anaesthesia and surgery can cause acute injury to renal tissue, which, as deduced from the literature cited above, can go undetected with the use of our current panel of renal markers in a clinical setting. These renal changes may be identified by using more sensitive markers such as GGT and other structure-specific markers rather than function-sensitive ones. 32 2.6.2 Intravenous Fluid Administration Intravenous (IV) fluid administration during general anaesthesia and surgery is recommended to maintain normovolemia and normotension (Zuurbier et al., 2002). It increases venous return, thereby preventing hypotension and reducing the risk of renal hypoperfusion (Brodbelt, 2010; Gumbert et al., 2020; Lobetti & Lambrechts, 2000; Robertson et al., 2018; Sinclair & Dyson, 2012). The administration of fluids in mouse models increased MAP without affecting HR (Zuurbier et al., 2002). Similarly, fluid resuscitation in dogs with hypotension helped increase the SAP to the normal range with no significant effect on heart rate (Powell, 2013). The administration of fluid during surgery has also reduced recovery time (Griffin et al., 2016). Interestingly, studies by Brodbelt et al. (2007) and Brodbelt (2010) observed that cats receiving fluids were at a higher risk (4-fold) of anaesthetic death than those who didn’t. But variables such as fluid overloading, presence of comorbidities, surgical procedure, systemic dysfunction and age must be considered to determine the actual effect of perioperative fluid therapy (Brodbelt, 2010). Griffin et al. (2016) highlighted the guidelines for neuter shelters which mention that while peripheral venous access should remain available for all subjects during surgery, IV fluids should be administered only in high-risk patients. Excess fluids can cause complications such as overloading the circulatory system (Brodbelt et al., 2007), leading to hypervolemia (Sano et al., 2018), oedema/effusion, and disruption of homeostasis. The Lobetti and Lambrechts (2000) study on dogs reported that intraoperative IV fluid is not essential in elective surgeries such as ovariohysterectomy (OHE). However, there were signs of active kidney damage that were undetected by traditional markers in the study. This study did not compare the effect of IV fluid administration in control animals. These signs of ongoing, transient renal damage require further study to determine whether it could have long-lasting effects, i.e., to know whether fluid administration is reno-protective in function or reno-offensive. 33 2.7 DIAGNOSIS OF RENAL DYSFUNCTION An ideal renal marker would have all the properties listed in Box 1 (Chen et al., 2019; Cianciolo et al., 2016; Cobrin et al., 2013; Hokamp & Nabity, 2016; Kovarikova, 2015, 2018; Quimby, 2015; Segev, 2018a): Box 1 Properties of an ideal renal marker • High sensitivity and specificity • Present in urine and/or serum • Non-invasive • Allow for early and rapid detection • Structure-specific (tubular or glomerular KD) • Determine the severity of damage • Monitor progression of KD • Provide information on the reparative process • Help determine the aetiology • Evaluate prognosis/possible outcome • Inexpensive and readily available as a point-of-care assay • Determine the effectiveness of treatment • Validated use • Low intra-individual variability • Constant production and plasma concentration • No protein-binding, tubular secretion/resorption without catabolism, extra-renal clearance • Not affected by extra-renal factors such as age, muscle mass, diet etc. 2.7.1 Conventional Indicators of Renal Dysfunction The current diagnostic tests used to detect KD involve analysing blood and urine parameters (Hokamp & Nabity, 2016). Serum creatinine (SCr), blood urea nitrogen (BUN), and SDMA are indirect GFR indicators measured using blood samples. Urinary parameters analysed while screening for kidney dysfunction include urine protein creatinine ratio (UP:C) and USG. Aside from the tests mentioned here, geriatric cats (> 14 yrs old) can be monitored for progression of renal dysfunction by analyzing serum phosphorus (sP), serum calcium (ionized), and testing the urine concentrating ability (isosthenuria) of the cats (McGrotty, 2008). Apart from the blood and urine tests, imaging techniques such as ultrasonography can support the diagnosis based on the kidneys' size, architecture, and echogenicity. An additional observation noted was the decrease in urinary pH associated with AKI and CKD 34 compared to healthy cats (Jing et al., 2020). The gold standard for diagnosing CKD is the renal biopsy, which reveals renal tubular tissue fibrosis and other morphological abnormalities upon histopathological sectioning and examination (Antunes Ribeiro et al., 2020; Cianciolo et al., 2016; Segev, 2018b). It must be noted that changes in the traditional renal markers do not provide information on the renal injury but rather indicate renal dysfunction (Vaidya et al., 2008). 2.7.1.1 Direct GFR Indicators Estimation of GFR is the most accurate and sensitive index of renal function since it is “directly proportional to functional renal mass” (Cobrin et al., 2013; De Loor et al., 2013; Finch, 2014; Heiene & Lefebvre, 2013; Kovarikova, 2015; Sargent et al., 2021; Von Hendy- Willson & Pressler, 2011). The GFR is measured by monitoring the plasma clearance rate using compounds such as inulin (gold standard), exogenous creatinine or iohexol, all of which are inert molecules that are neither reabsorbed nor secreted by nephrons and can, thus, be used to monitor the functional capacity of kidneys. This ensures that the plasma clearance remains strongly correlated to renal clearance (Kovarikova, 2018; Von Hendy- Willson & Pressler, 2011). However, the methods used to determine GFR are time-consuming, complicated, expensive, and impractical for clinical use (Cobrin et al., 2013; Von Hendy-Willson & Pressler, 2011), wherein rapid diagnosis is crucial for ensuring a better prognosis. The use of GFR is further limited by the effect of extra-renal factors such as “patient signalment, circadian variation, hydration status, diet and use of sedation” (Von Hendy-Willson & Pressler, 2011). The estimation of GFR would prove to be much more useful were it more accessible, with improved assays that could be used to determine the GFR immediately. Unlike in humans, using an estimated GFR (eGFR) formula has proven unreliable in cats, partly because of the play of multiple unknown factors which affect GFR, leading to an underestimated eGFR (Finch et al., 2018; Geddes, 2013). By improving our understanding of the risk factors associated with kidney damage in cats, eGFR formulas can be updated and used as a tool for predicting KD. 35 2.7.1.2 Indirect GFR Indicators Endogenous SCr, BUN and now SDMA are commonly used renal markers that are inversely proportional to GFR, i.e., an increase in these markers signifies a reduced renal function. They are easier to measure when compared to GFR and are, thus, preferred tools to monitor kidneys in a clinical setting. They can be analyzed at point-of-care with the right equipment and are inexpensive. Unfortunately, several limitations are associated with the use of these conventional markers. These biomarkers are influenced by several extrarenal factors such as hypovolemia, diet, underlying comorbidities and altered filtration leading to inaccurate GFR estimation (De Loor et al., 2013). Details on each of these markers are described below. Serum Creatinine (SCr) Creatinine is a byproduct of enzyme-independent phosphocreatine metabolism in the muscle (Geddes, 2013; Lefebvre et al., 2015) and is considered a marker of renal function (Segev, 2018a). It is presumed to be produced at a constant rate and is excreted by the kidneys through filtration as well as tubular secretion (Moran & Myers, 1985), without re- absorption (Lefebvre et al., 2015). SCr is currently a universally accepted renal biomarker (Segev, 2018a). It is a good indicator of long-term survival in cats with AKI and CKD (Chen et al., 2020; Moran & Myers, 1985). The risk of mortality increases with acute elevation in SCr in AKI-affected individuals (Kanagasundaram, 2015). Unfortunately, SCr is an imperfect marker (Hokamp & Nabity, 2016; Kovarikova, 2015; Quimby, 2015) because its elevated levels are observed only once substantial renal damage has occurred. Serum creatinine has been observed to remain within the reference range until approximately 75% of the nephrons are non-functional (Hokamp & Nabity, 2016; Kovarikova, 2015), as seen in Figure 7 (Stage three). This is a severe constraint that comes with the use of SCr, especially when it comes to diagnosing early or mild KD. Mishra et al. (2003) found that when subclinical ischemic renal injury was induced in a mouse model, 36 the SCr levels remained similar to that of the control animals, unlike other newer renal biomarkers (Neutrophil gelatinase-associated lipocalin). Figure 7 Renal filtration performance across the stages of CKD. This chart shows the decreasing renal filtration ability and nephronal functionality with increasing severity of CKD. Image reprinted from Boehringer Ingelheim International. Serum creatinine has a curvilinear, exponential relation with GFR (Geddes, 2013; Lefebvre et al., 2015; Sargent et al., 2021), as shown in Figure 8. In the initial stages of KD, an abrupt fall in GFR will only see minimal changes in SCr concentration (Segev, 2018a; Vaidya, Ferguson, & Bonventre, 2008). However, in the later stages, even slight changes in GFR can result in a significant elevation in SCr concentration (Kovarikova, 2018; Vaidya, Ferguson, & Bonventre, 2008). The SCr concentration is highly increased in 37 more severe forms of AKI, where the renal function is significantly reduced (Scheemaeker et al., 2020). Furthermore, its concentration is affected by several extra-renal factors. Figure 8 Curvilinear relation between SCr and GFR as seen in dogs (Lefebvre et al., 2015). In the early stages of renal disease, even if the GFR were to fall drastically, SCr would remain within normal limits due to the compensatory and adaptive mechanisms of the kidney. However, in the advanced stages of renal damage, even a minor change in GFR would see a large change in SCr as the compensatory mechanisms fail. The limitations associated with the use of SCr to monitor kidney function are listed in Box 2 (Finch, 2014; Hall et al., 2014; Hokamp & Nabity, 2016; Lefebvre et al., 2015; McBride et al., 2019; Pressler, 2015; Quimby, 2015; Segev, 2018a; Vaidya, Ferguson, & Bonventre, 2008). Box 2 Limitations associated with SCr • Not indicative of early stages of renal dysfunction • Does not increase until at least 75% of the renal mass is dysfunctional • Does not provide information on the site of lesion/damage • Does not provide information on the severity of the disease until a steady state of dysfunction is maintained • Wide reference range • High individuality in small companion animals • Variations across animal breeds and analytical laboratories • Influenced by extra-renal factors like muscle mass and age • Unreliable for monitoring kidney function in cachexic or wasting cats as well as in kittens. • Influenced by diet, hydration status and blood volume of the subject. • Circadian variation (cats). 38 The use of SCr is being reviewed for optimized utilization of the biomarker. Previous research has suggested that even slight variations in SCr, within the reference range, could be indicative of a significant drop in GFR and, thus, kidney function (as cited in Hokamp et al., 2016; Hokamp & Nabity, 2016). Therefore, serial or trending measurement of SCr in an individual animal (fasted) could provide more rapid information on reducing function. The exception for SCr use is in wasting individuals with end-stage renal damage, where even serial measurements would prove unreliable as creatinine levels would be affected by the increased catabolism in the muscles. Furthermore, serial measurement requires frequent sampling and knowledge of the baseline SCr for the individual, which might prove cumbersome for pet owners. The reliability of SCr may be improved with the introduction of age- and breed-specific reference ranges (Hokamp & Nabity, 2016). IRIS board members have suggested that persistent upper range values of SCr in normovolemic cats hint at a renal dysfunction and have recommended monitoring these individuals closely (Grauer, 2019). Therefore, while SCr is useful in monitoring KD in its later stages, its use can be improved, and other more reliable early indicators with more characteristics of an ideal marker should be introduced to make up for its limitations. Blood Urea Nitrogen (BUN) Urea is produced from the breakdown of ammonia in the liver (Geddes, 2013). It is positively correlated with SCr (Lefebvre et al., 2015) as both are metabolites excreted in urine; however, unlike creatinine, BUN is reabsorbed by the tubules. A steadier rise in BUN than SCr indicates a poor prognosis for the patient (Inaguma et al., 2018). BUN is commonly monitored in conjunction with other biochemical analytes such as SCr, USG, UP:C and SDMA. While BUN has been shown to have a higher sensitivity than SCr, it has a lower specificity (Finch, 2014), as it is a product of protein catabolism and is, thus, affected by extra-renal factors such as diet, hydration status, biological variability, hepatic function, tubular re- 39 absorption, and GIT haemorrhage (Finch, 2014). It is, therefore, an unreliable marker for sole monitoring of renal function (Geddes, 2013). Kidney disease, specifically CKD, is positively correlated with age. An increased prevalence is positively associated with the positive predictive value/PPV (Finch, 2014) and, thus, SCr and BUN can be used for screening purposes in senior cats. Symmetric Dimethyl-arginine (SDMA) Methylated arginine is a byproduct of protein metabolism. It is mainly found in three forms within the body: Monomethylarginine (MMA), Asymmetric dimethylarginine (ADMA) and symmetric dimethylarginine/SDMA (Chen et al., 2017). SDMA is the most reliable indicator as it is primarily filtered and excreted by the renal system (Brown, 2016). It is an inert protein metabolite (Grauer, 2019) found in several tissues. It is a good addition to the conventional panel of renal markers (Sargent et al., 2021) as it can detect chronic renal dysfunction as early as when ~ 30-40% of the nephrons are affected. SDMA in cats was found to increase over the reference range before SCr in 80.9% of the CKD cases by a mean of 17 months (Hall et al., 2014; Hokamp & Nabity, 2016). Unlike SCr, SDMA is not influenced by age, weight, body condition (Perez-Lopez et al., 2020), breed, sex, diet, muscle mass (Chen et al., 2017; Segev, 2018a), inflammation, weight loss, comorbidities such as diabetes, or reduced analytical variability (Hokamp & Nabity, 2016; Sargent et al., 2021). SDMA also has a uniform reference range (Hall et al., 2014; Hokamp & Nabity, 2016; Segev, 2018a) and is excreted primarily in urine in unbound form without being subjected to tubular reabsorption. It is believed to be synthesized at a constant rate (Hokamp & Nabity, 2016); these properties make the use of SDMA more advantageous than SCr. However, further studies on the effects of protein catabolism need to be conducted to improve our understanding of its influence on SDMA. Symmetric dimethyl-arginine shows a positive correlation with SCr and GFR in geriatric cats with KD (Brans et al., 2021; Hall et al., 2014), unlike healthy animals (weaker association). It was found to have a stronger correlation with plasma iohexol clearance 40 (GFR) than SCr. The sensitivity of SDMA (76-94%) was found to be similar to that of SCr (71-88%); however, its specificity (75-76%) was lower than that of SCr (94-96%). So, the question remains as to whether SDMA is genuinely better than the other classical renal markers in detecting renal dysfunction. Therefore, more studies are required to compare the use of SDMA against other markers. 2.7.1.2.1 Other Variables Urine Specific Gravity (USG) Renal injury can result in loss of the ability to concentrate urine, especially when the tubular components of the nephrons are damaged. Therefore, determining the specific gravity of urine, in addition to the use of the conventional renal markers, can help identify renal azotemia (De Loor et al., 2013). If the animal is dehydrated and unable to conserve blood volume through urine concentration, it is likely to be suffering from KD (Watson et al., 2015). Contrary to general expectations, a study on dogs by Antunes Ribeiro et al. (2020) found that the USG did not vary significantly between the different stages of KD. However, cats differ from dogs in their urine concentrating ability. A study involving thirteen cats presumed to be afflicted with AKI had USG, ranging from 1.005 to 1.065 (Bland et al., 2019). Similarly, a study involving ten cats suffering from CKD found that all had USG < 1.036 (Paepe et al., 2015), however, changes in USG are absent in the early stages of the renal damage because cats are capable of retaining their urine concentrating ability, unlike other species (Geddes, 2013; Paepe & Daminet, 2013). There have been similar observations in studies on cats with KD, with most being isosthenuric, i.e., a USG ranging from 1.007 to 1.015 (Bland et al., 2014; Jing et al., 2020; Paepe & Daminet, 2013). 41 Serum Electrolytes Several changes in the serum levels of certain electrolytes such as phosphorus, calcium (Segev, 2018b) and potassium (Paepe & Daminet, 2013) can be seen in AKI and CKD. Hyperphosphatemia is seen in both AKI (Paepe & Daminet, 2013) and CKD; however, this increase in phosphorus levels is more gradual in the latter (Segev, 2018b). It is also correlated with tubular fibrosis (Grauer, 2021). An increase in plasma phosphorus levels by even 1 mg/dl is associated with an increased risk of progression by ~ 41% (Chakrabarti et al., 2012). Urine protein-creatinine ratio (UPCR or UP:C) Proteinuria is characterized by fibrosis of interstitial tissue and hypertrophy of the glomeruli (Chakrabarti et al., 2013). Injury to the GFB causes a change in the structure of endothelial cells or podocytes (Menon et al., 2012). Therefore, glomerular damage is one of the causes of proteinuria as it enables the escape of macromolecules from the vascular lumen and into the Bowman’s space. Albumin is a globular protein that is generally absent in urine due to the selective permeability of the glomerulus. The small amount which enters the tubular fluid is reabsorbed in the PCT in healthy animals, and, thus, albuminuria (albumin in the urine) indicates glomerular and/ or tubular damage. Studies in humans have shown that an elevated UP:C is linked to adverse outcomes/poor prognosis (Cianciolo et al., 2016). Urine protein concentration (UPC) is a quantitative index of total protein in the urine (Eatroff; Paepe & Daminet, 2013) which helps monitor glomerular filtration (Sargent et al., 2021). UP:C was found to vary between the different stages of CKD, with ~ 90% of the cases (dogs) being proteinuric (Antunes Ribeiro et al., 2020). The same study found an increase in UP:C across the stages. An increase in UP:C of 0.1