Journal Articles

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    Standardization and other approaches to meta-analyze differences in means.
    (John Wiley and Sons Ltd, 2024-05-18) Hopkins WG; Rowlands DS
    Meta-analysts often use standardized mean differences (SMD) to combine mean effects from studies in which the dependent variable has been measured with different instruments or scales. In this tutorial we show how the SMD is properly calculated as the difference in means divided by a between-subject reference-group, control-group, or pooled pre-intervention SD, usually free of measurement error. When combining mean effects from controlled trials and crossovers, most meta-analysts have divided by either the pooled SD of change scores, the pooled SD of post-intervention scores, or the pooled SD of pre- and post-intervention scores, resulting in SMDs that are biased and difficult to interpret. The frequent use of such inappropriate standardizing SDs by meta-analysts in three medical journals we surveyed is due to misleading advice in peer-reviewed publications and meta-analysis packages. Even with an appropriate standardizing SD, meta-analysis of SMDs increases heterogeneity artifactually via differences in the standardizing SD between settings. Furthermore, the usual magnitude thresholds for standardized mean effects are not thresholds for clinically important differences. We therefore explain how to use other approaches to combining mean effects of disparate measures: log transformation of factor effects (response ratios) and of percent effects converted to factors; rescaling of psychometrics to percent of maximum range; and rescaling with minimum clinically important differences. In the absence of clinically important differences, we explain how standardization after meta-analysis with appropriately transformed or rescaled pre-intervention SDs can be used to assess magnitudes of a meta-analyzed mean effect in different settings.
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    Respiratory support in the emergency department a systematic review and meta-analysis
    (Wiley Periodicals LLC on behalf of Sigma Theta Tau International, 2024-03-22) O'Donnell J; Pirret A; Hoare K; Fenn R; McDonald E
    BACKGROUND: An estimated 20% of emergency department (ED) patients require respiratory support (RS). Evidence suggests that nasal high flow (NHF) reduces RS need. AIMS: This review compared NHF to conventional oxygen therapy (COT) or noninvasive ventilation (NIV) in adult ED patients. METHOD: The systematic review (SR) and meta-analysis (MA) methods reflect the Cochrane Collaboration methodology. Six databases were searched for randomized controlled trials (RCTs) comparing NHF to COT or NIV use in the ED. Three summary estimates were reported: (1) need to escalate care, (2) mortality, and (3) adverse events (AEs). RESULTS: This SR and MA included 18 RCTs (n = 1874 participants). Two of the five MA conclusions were statistically significant. Compared with COT, NHF reduced the risk of escalation by 45% (RR 0.55; 95% CI [0.33, 0.92], p = .02, NNT = 32); however, no statistically significant differences in risk of mortality (RR 1.02; 95% CI [0.68, 1.54]; p = .91) and AE (RR 0.98; 95% CI [0.61, 1.59]; p = .94) outcomes were found. Compared with NIV, NHF increased the risk of escalation by 60% (RR 1.60; 95% CI [1.10, 2.33]; p = .01); mortality risk was not statistically significant (RR 1.23, 95% CI [0.78, 1.95]; p = .37). LINKING EVIDENCE TO ACTION: Evidence-based decision-making regarding RS in the ED is challenging. ED clinicians have at times had to rely on non-ED evidence to support their practice. Compared with COT, NHF was seen to be superior and reduced the risk of escalation. Conversely, for this same outcome, NIV was superior to NHF. However, substantial clinical heterogeneity was seen in the NIV delivered. Research considering NHF versus NIV is needed. COVID-19 has exposed the research gaps and slowed the progress of ED research.