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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.


Papers
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Journal ArticleDOI
TL;DR: Although the baseline safety climate score was encouraging, room for improvement exists and future research will analyze the responsiveness of the SCS scale to change, following recently instituted initiatives such as a new graduate integration program, an improved medication dispensing system, newly installed lifting devices, and the critical care response team.

27 citations

Journal ArticleDOI
01 Dec 2001-Chest
TL;DR: Multidisciplinary, patient-centered, holistic, and non-pulmonary approaches to weaning may provide additional safe, effective adjunctive methods of hastening liberation from mechanical ventilation.

27 citations

Journal ArticleDOI
TL;DR: Clinical features of HIT and interpretation of laboratory tests for HIT antibodies from the perspective of the intensive care unit are described.

27 citations

Journal ArticleDOI
TL;DR: Identifying and appraising qualitative research evidence on the experience of making life-support decisions in critical care settings and finding room for improvement exists regarding both the quality and transparency of reported methodology is suggested.
Abstract: Objective:The objective of this study is to identify and appraise qualitative research evidence on the experience of making life-support decisions in critical care.Data Sources:In six databases and supplementary sources, we sought original research published from January 1990 through June 2008 repor

27 citations

Journal ArticleDOI
TL;DR: 13 strategies that may improve the process of obtaining informed consent from substitute decision-makers and be generalisable to other settings and studies are identified.

27 citations


Cited by
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Journal ArticleDOI
TL;DR: Moher et al. as mentioned in this paper introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses, which is used in this paper.
Abstract: David Moher and colleagues introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses

62,157 citations

Journal Article
TL;DR: The QUOROM Statement (QUality Of Reporting Of Meta-analyses) as mentioned in this paper was developed to address the suboptimal reporting of systematic reviews and meta-analysis of randomized controlled trials.
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

46,935 citations

Journal ArticleDOI
04 Sep 2003-BMJ
TL;DR: A new quantity is developed, I 2, which the authors believe gives a better measure of the consistency between trials in a meta-analysis, which is susceptible to the number of trials included in the meta- analysis.
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 …

45,105 citations

Journal ArticleDOI
TL;DR: A structured summary is provided including, as applicable, background, objectives, data sources, study eligibility criteria, participants, interventions, study appraisal and synthesis methods, results, limitations, conclusions and implications of key findings.

31,379 citations