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.

Safety Outcomes of Direct Discharge Home From ICUs: An Updated Systematic Review and Meta-Analysis (Direct From ICU Sent Home Study)*

Abstract: Objective: To evaluate the impact of direct discharge home (DDH) from ICUs compared with ward transfer on safety outcomes of readmissions, emergency department (ED) visits, and mortality. Data Sources: We searched MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, and Cumulative Index to Nursing and Allied Health Literature from inception until March 28, 2022. Study Selection: Randomized and nonrandomized studies of DDH patients compared with ward transfer were eligible. Data Extraction: We screened and extracted studies independently and in duplicate. We assessed risk of bias using the Newcastle-Ottawa Scale for observational studies. A random-effects meta-analysis model and heterogeneity assessment was performed using pooled data (inverse variance) for propensity-matched and unadjusted cohorts. We assessed the overall certainty of evidence for each outcome using the Grading Recommendations Assessment, Development and Evaluation approach. Data Synthesis: Of 10,228 citations identified, we included six studies. Of these, three high-quality studies, which enrolled 49,376 patients in propensity-matched cohorts, could be pooled using meta-analysis. For DDH from ICU, compared with ward transfers, there was no difference in the risk of ED visits at 30-day (22.4% vs 22.7%; relative risk [RR], 0.99; 95% CI, 0.95–1.02; p = 0.39; low certainty); hospital readmissions at 30-day (9.8% vs 9.6%; RR, 1.02; 95% CI, 0.91–1.15; p = 0.71; very low-to-low certainty); or 90-day mortality (2.8% vs 2.6%; RR, 1.06; 95% CI, 0.95–1.18; p = 0.29; very low-to-low certainty). There were no important differences in the unmatched cohorts or across subgroup analyses. CONCLUSIONS: Very low-to-low certainty evidence from observational studies suggests that DDH from ICU may have no difference in safety outcomes compared with ward transfer of selected ICU patients. In the future, this research question could be further examined by randomized control trials to provide higher certainty data.

Consumo de oxígeno (vo ) indirecto en militares con

Abstract: Background: To compare the average of indirectly measured oxygen consumption between military with acute mountain sickness (AMS) and military undiagnosed using the criteria of Lake Louise scale. Material and methods: A case control study with data collection between 2008 and 2009 on High Mountain 3050 MASL, Bogota DC, Colombia. 20m-shuttle run test for measuring maximum indirect oxygen consumption (VO ) and VO per weight (VO2/Kg) was performed. We applied the Louise 2 2 questionnaire for diagnosis of acute mountain sickness. We got 62 individuals with AMS and 61 individuals without the disease. We made a description of the vital variables and then a bivariate analysis with vital and relevant medical history variables with the VO and VO /Kg as dependent variable. 2 2 Results:Of 123 military, we got 62 individuals with AMS (cases) and 61 without the disease (controls), most of them with mild AMS (35%), with a median of exposure time of 10 days (QIR:10). Of the total, 30.1% had a history of smoking and the absence of cigarette consumption showed an OR: 2.33 CI 95% 1.05-5.17 with the presence of AMS. We calculated that the history of ascent to altitudes >3050 MASL has an OR: 0.41 (CI 95% 0.19-0.87) for the disease develop. No significant difference in maximum VO and VO /Kg between 2 2 sick and healthy individuals with p=0.46 and p=0.34 were found respectively. Conclusion: The measurement of maximum indirect VO don`t show any difference in military with and 2 without AMS at 3050 MASL, history of smoking and previous ascent in altitude are shown as important background for no developing symptoms of AMS. Further studies are needed to corroborate our findings of these two specific points.

6Ts teaching tips for evidence-based practitioners

Abstract: At the June 2005 McMaster Evidence-Based Practice Workshop, our group, led by librarian Jan Figurski and tutor trainee Rakesh Patel, developed a very useful teaching tool for our tutorials. We called it the 4Ts Teaching Tips. After such initial success, the rest of us further developed the tool into the 6Ts Teaching Tips at the June 2006 Workshop. The overall objective of this tool is to provide a touchstone to both plan and evaluate a teaching session. (1) The first T stands for Time management. A critical appraisal exercise or any teaching session requires careful planning about topics to be covered in a specified period of time. The first T also reminds teachers about leaving time for evaluation …

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 …