Deborah J. Cook

Bio: Deborah J. Cook is an academic researcher from McMaster University. The author has contributed to research in topics: Intensive care & Intensive care unit. The author has an hindex of 173, co-authored 907 publications receiving 148928 citations. Previous affiliations of Deborah J. Cook include McMaster University Medical Centre & Queen's University.

A critical appraisal and systematic review of illness severity scoring systems in the intensive care unit

Abstract: In this document we critically review the development and use of general intensive care unit admission severity of illness scoring systems. Data sources for this review included a computerized bibliographic search and published proceedings from relevant conferences in critical care medicine. Current

Noninvasive respiratory support following extubation in critically ill adults: a systematic review and network meta-analysis

Abstract: Systematic review and network meta-analysis to investigate the efficacy of noninvasive respiratory strategies, including noninvasive positive pressure ventilation (NIPPV) and high-flow nasal cannula (HFNC), in reducing extubation failure among critically ill adults. We searched databases from inception through October 2021 for randomized controlled trials (RCTs) evaluating noninvasive respiratory support therapies (NIPPV, HFNC, conventional oxygen therapy, or a combination of these) following extubation in critically ill adults. Two reviewers performed screening, full text review, and extraction independently. The primary outcome of interest was reintubation. We used GRADE to rate the certainty of our findings. We included 36 RCTs (6806 patients). Compared to conventional oxygen therapy, NIPPV (OR 0.65 [95% CI 0.52–0.82]) and HFNC (OR 0.63 [95% CI 0.45–0.87]) reduced reintubation (both moderate certainty). Sensitivity analyses showed that the magnitude of the effect was highest in patients with increased baseline risk of reintubation. As compared to HFNC, no difference in incidence of reintubation was seen with NIPPV (OR 1.04 [95% CI 0.78–1.38], low certainty). Compared to conventional oxygen therapy, neither NIPPV (OR 0.8 [95% CI 0.61–1.04], moderate certainty) or HFNC (OR 0.9 [95% CI 0.66–1.24], low certainty) reduced short-term mortality. Consistent findings were demonstrated across multiple subgroups, including high- and low-risk patients. These results were replicated when evaluating noninvasive strategies for prevention (prophylaxis), but not in rescue (application only after evidence of deterioration) situations. Our findings suggest that both NIPPV and HFNC reduced reintubation in critically ill adults, compared to conventional oxygen therapy. NIPPV did not reduce incidence of reintubation when compared to HFNC. These findings support the preventative application of noninvasive respiratory support strategies to mitigate extubation failure in critically ill adults, but not in rescue conditions.

Randomized trials in single subjects: the N of 1 study.

Abstract: Large-scale randomized trials are not available for all disorders, and conventional "trials of therapy" are susceptible to bias. Randomized controlled trials (RCTs) in individual patients (N of 1 RCTs) may provide a solution. In an N of 1 RCT, a patient receives treatments in pairs (one period of the experimental therapy and one period of either an alternative treatment or placebo, in random order), both patient and clinician are kept blind to allocation, and treatment targets are monitored. This type of RCT is useful in chronic, stable conditions in which the proposed treatment has a short half-life. Treatment targets usually include quantitative measurement of symptoms tracked through patient diaries. Pairs of treatment periods are continued until effectiveness is proved or refuted. The N of 1 RCT is potentially of great use in psychopharmacology and in drug development. The practical approach presented here will allow clinicians to conduct their own N of 1 RCTs.

Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement

Abstract: David Moher and colleagues introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses

Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement.

Abstract: Systematic reviews and meta-analyses have become increasingly important in health care. Clinicians read them to keep up to date with their field,1,2 and they are often used as a starting point for developing clinical practice guidelines. Granting agencies may require a systematic review to ensure there is justification for further research,3 and some health care journals are moving in this direction.4 As with all research, the value of a systematic review depends on what was done, what was found, and the clarity of reporting. As with other publications, the reporting quality of systematic reviews varies, limiting readers' ability to assess the strengths and weaknesses of those reviews. Several early studies evaluated the quality of review reports. In 1987, Mulrow examined 50 review articles published in 4 leading medical journals in 1985 and 1986 and found that none met all 8 explicit scientific criteria, such as a quality assessment of included studies.5 In 1987, Sacks and colleagues6 evaluated the adequacy of reporting of 83 meta-analyses on 23 characteristics in 6 domains. Reporting was generally poor; between 1 and 14 characteristics were adequately reported (mean = 7.7; standard deviation = 2.7). A 1996 update of this study found little improvement.7 In 1996, to address the suboptimal reporting of meta-analyses, an international group developed a guidance called the QUOROM Statement (QUality Of Reporting Of Meta-analyses), which focused on the reporting of meta-analyses of randomized controlled trials.8 In this article, we summarize a revision of these guidelines, renamed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses), which have been updated to address several conceptual and practical advances in the science of systematic reviews (Box 1). Box 1 Conceptual issues in the evolution from QUOROM to PRISMA

Measuring inconsistency in meta-analyses

Abstract: Cochrane Reviews have recently started including the quantity I 2 to help readers assess the consistency of the results of studies in meta-analyses. What does this new quantity mean, and why is assessment of heterogeneity so important to clinical practice? Systematic reviews and meta-analyses can provide convincing and reliable evidence relevant to many aspects of medicine and health care.1 Their value is especially clear when the results of the studies they include show clinically important effects of similar magnitude. However, the conclusions are less clear when the included studies have differing results. In an attempt to establish whether studies are consistent, reports of meta-analyses commonly present a statistical test of heterogeneity. The test seeks to determine whether there are genuine differences underlying the results of the studies (heterogeneity), or whether the variation in findings is compatible with chance alone (homogeneity). However, the test is susceptible to the number of trials included in the meta-analysis. We have developed a new quantity, I 2, which we believe gives a better measure of the consistency between trials in a meta-analysis. Assessment of the consistency of effects across studies is an essential part of meta-analysis. Unless we know how consistent the results of studies are, we cannot determine the generalisability of the findings of the meta-analysis. Indeed, several hierarchical systems for grading evidence state that the results of studies must be consistent or homogeneous to obtain the highest grading.2–4 Tests for heterogeneity are commonly used to decide on methods for combining studies and for concluding consistency or inconsistency of findings.5 6 But what does the test achieve in practice, and how should the resulting P values be interpreted? A test for heterogeneity examines the null hypothesis that all studies are evaluating the same effect. The usual test statistic …