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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: Substantial incremental increase in FEV1 in response to increasing doses of beta-agonists beyond those commonly used in clinical practice is restricted to a minority of patients, and lack of reproducibility limits the clinical usefulness of establishing the optimal dose of Beta-agonist for a given patient.

22 citations

Journal ArticleDOI
TL;DR: The screen log became a communication tool that fostered research‐oriented continuous quality improvement initiatives for the management of concurrently conducted randomized trials in the ICU and was used as an instrument to monitor trial execution.
Abstract: Objective:To develop and evaluate a screen log for monitoring enrollment in multiple randomized clinical trials conducted in a single center.Setting:University-affiliated 20-bed tertiary care medical-surgical intensive care unit (ICU).Patients:Consecutive ICU patients admitted between April 1995 and

22 citations

Journal Article
TL;DR: The aim of this study was to investigate the terms and justifications for and the meanings of psychosocial patient characteristics used in cardiac procedure guidelines, selecting English-language guidelines published since 1990 and chapters in textbooks published since 1989.
Abstract: Background: Cardiac procedure guidelines often include psychosocial criteria for selecting patients that potentially introduce social value judgements into clinical decisions and decisions about the rationing of care. The aim of this study was to investigate the terms and justifications for and the meanings of psychosocial patient characteristics used in cardiac procedure guidelines. Methods: We selected English-language guidelines published since 1990 and chapters in textbooks published since 1989. These guidelines amalgamated multiple sources of evidence and expertise and made recommendations regarding patient selection for specific procedures. A multidisciplinary team of physicians and social scientists extracted passages regarding psychosocial criteria and developed categories and conceptual relationships to describe and interpret their content. Results: Sixty-five papers met the criteria for inclusion in the study. Forty-five (69%) mentioned psychosocial criteria as procedure indications or contraindications. The latter fell into several categories, including behavioural and psychological issues, relationships with significant others, financial resources, social roles and environmental circumstances. Interpretation: Psychosocial characteristics are portrayed as having 2 roles in patient selection: as risk factors intrinsic to the candidate or as indicators of need for special intervention. Guidelines typically simply list psychosocial contraindications without clarifying their specific nature or providing any justification for their use. Psychosocial considerations can help in the evaluation of patients for cardiac procedures, but they become ethically controversial when used to restrict access. The use of psychosocial indications and contraindications could be improved by more precise descriptions of the psychosocial problem at issue, explanations regarding why the criterion matters and justification of the characteristic using a biological rationale or research evidence.

21 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