Nicola Hooton
University of Alberta
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BMJ | 2006
Nina Buscemi; Ben Vandermeer; Nicola Hooton; Rena Pandya; Lisa Tjosvold; Lisa Hartling; Sunita Vohra; Terry P. Klassen; Glen B. Baker
Abstract Objective To conduct a systematic review of the efficacy and safety of exogenous melatonin in managing secondary sleep disorders and sleep disorders accompanying sleep restriction, such as jet lag and shiftwork disorder. Data sources 13 electronic databases and reference lists of relevant reviews and included studies; Associated Professional Sleep Society abstracts (1999 to 2003). Study selection The efficacy review included randomised controlled trials; the safety review included randomised and non-randomised controlled trials. Quality assessment Randomised controlled trials were assessed by using the Jadad Scale and criteria by Schulz et al, and non-randomised controlled trials by the Downs and Black checklist. Data extraction and synthesis One reviewer extracted data and another reviewer verified the data extracted. The inverse variance method was used to weight studies and the random effects model was used to analyse data. Main results Six randomised controlled trials with 97 participants showed no evidence that melatonin had an effect on sleep onset latency in people with secondary sleep disorders (weighted mean difference −13.2 (95% confidence interval −27.3 to 0.9) min). Nine randomised controlled trials with 427 participants showed no evidence that melatonin had an effect on sleep onset latency in people who had sleep disorders accompanying sleep restriction (−1.0 (−2.3 to 0.3) min). 17 randomised controlled trials with 651 participants showed no evidence of adverse effects of melatonin with short term use (three months or less). Conclusions There is no evidence that melatonin is effective in treating secondary sleep disorders or sleep disorders accompanying sleep restriction, such as jet lag and shiftwork disorder. There is evidence that melatonin is safe with short term use.
Journal of General Internal Medicine | 2005
Nina Buscemi; Ben Vandermeer; Nicola Hooton; Rena Pandya; Lisa Tjosvold; Lisa Hartling; Glen B. Baker; Terry P Klassen; Sunita Vohra
BACKGROUND: Exogenous melatonin has been increasingly used in the management of sleep disorders.PURPOSE: To conduct a systematic review of the efficacy and safety of exogenous melatonin in the management of primary sleep disorders.DATA SOURCES: A number of electronic databases were searched. We reviewed the bibliographies of included studies and relevant reviews and conducted hand-searching.STUDY SELECTION: Randomized controlled trials (RCTs) were eligible for the efficacy review, and controlled trials were eligible for the safety review.DATA EXTRACTION: One reviewer extracted data, while the other verified data extracted. The Random Effects Model was used to analyze data.DATA SYNTHESIS: Melatonin decreased sleep onset latency (weighted mean difference [WMD]: −11.7 minutes; 95% confidence interval [CI]: −18.2, −5.2)); it was decreased to a greater extent in people with delayed sleep phase syndrome (WMD: −38.8 minutes; 95% CI: −50.3, −27.3; n=2) compared with people with insomnia (WMD: −7.2 minutes; 95% CI: −12.0, −2.4; n=12). The former result appears to be clinically important. There was no evidence of adverse effects of melatonin.CONCLUSIONS: There is evidence to suggest that melatonin is not effective in treating most primary sleep disorders with short-term use (4 weeks or less); however, additional large-scale RCTs are needed before firm conclusions can be drawn. There is some evidence to suggest that melatonin is effective in treating delayed sleep phase syndrome with short-term use. There is evidence to suggest that melatonin is safe with short-term use (3 months or less).
BMJ | 2009
Lisa Hartling; Maria Ospina; Yuanyuan Liang; Donna M Dryden; Nicola Hooton; Jennifer Seida; Terry P Klassen
Objectives To evaluate the risk of bias tool, introduced by the Cochrane Collaboration for assessing the internal validity of randomised trials, for inter-rater agreement, concurrent validity compared with the Jadad scale and Schulz approach to allocation concealment, and the relation between risk of bias and effect estimates. Design Cross sectional study. Study sample 163 trials in children. Main outcome measures Inter-rater agreement between reviewers assessing trials using the risk of bias tool (weighted κ), time to apply the risk of bias tool compared with other approaches to quality assessment (paired t test), degree of correlation for overall risk compared with overall quality scores (Kendall’s τ statistic), and magnitude of effect estimates for studies classified as being at high, unclear, or low risk of bias (metaregression). Results Inter-rater agreement on individual domains of the risk of bias tool ranged from slight (κ=0.13) to substantial (κ=0.74). The mean time to complete the risk of bias tool was significantly longer than for the Jadad scale and Schulz approach, individually or combined (8.8 minutes (SD 2.2) per study v 2.0 (SD 0.8), P<0.001). There was low correlation between risk of bias overall compared with the Jadad scores (P=0.395) and Schulz approach (P=0.064). Effect sizes differed between studies assessed as being at high or unclear risk of bias (0.52) compared with those at low risk (0.23). Conclusions Inter-rater agreement varied across domains of the risk of bias tool. Generally, agreement was poorer for those items that required more judgment. There was low correlation between assessments of overall risk of bias and two common approaches to quality assessment: the Jadad scale and Schulz approach to allocation concealment. Overall risk of bias as assessed by the risk of bias tool differentiated effect estimates, with more conservative estimates for studies at low risk.
Annals of Internal Medicine | 2007
Justin A. Ezekowitz; Brian H. Rowe; Donna M Dryden; Nicola Hooton; Ben Vandermeer; Carol H. Spooner; Finlay A. McAlister
Left ventricular (LV) systolic dysfunction carries a high risk for sudden cardiac death (1). Implantable cardioverter defibrillators (ICDs) can potentially mitigate this risk by delivering rapid life-saving therapy and have been substantially refined since their initial development in the late 1970s (2). Randomized, controlled trials (RCTs) have tested the efficacy of ICDs in high-risk individuals. We previously reported a systematic review of 8 RCTs (3 RCTs of secondary prevention in survivors of sudden cardiac death; 5 RCTs of primary prevention in patients without a history of ventricular arrhythmias) demonstrating a 26% reduction in all-cause mortality and a 57% reduction in sudden cardiac death with ICDs (3). Since then, additional RCTs of primary prevention have been published, and questions have arisen about the generalizability of the RCT results for ICDs to clinical practice. In particular, it is uncertain whether the benefits of ICDs seen in the trials extend to nontrial populations and whether the risks associated with ICDs may be higher in clinical practice than reported in trials. Given the public policy implications, we extended our previous systematic review of the efficacy (that is, the risks and benefits of a therapy when tested under ideal circumstances) (4) of ICDs in patients with LV systolic dysfunction by updating it with recently published RCTs that examined efficacy. In addition, we expanded the review to include data from observational studies to determine the effectiveness (that is, the risks and benefits of a therapy when tested under usual clinical practice conditions) and safety of ICDs when used in clinical practice. Methods A study protocol meeting Cochrane criteria, including all of the elements described briefly in the following sections, was developed and followed by the study authors in conjunction with the Agency for Healthcare Research and Quality (AHRQ). Search Strategy We sought studies published between 1980 and 27 April 2007 by searching MEDLINE, Ovid MEDLINE In-Process & Other Non-Indexed Citations, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, Health Technology Assessment Database, EMBASE, Science Citation Index Expanded (via Web of Science), International Pharmaceutical Abstracts, PubMed, National Library of Medicine Gateway, OCLC ProceedingsFirst and PapersFirst, Computer Retrieval of Information on Scientific Projects, various trial registries (including the National Research Register [United Kingdom], Australian Clinical Trials Registry, ClinicalTrials.gov, and Current Controlled Trials), and U.S. Food and Drug Administration reports. In addition, we hand-searched abstracts from the annual Heart Rhythm Society meetings and the reference lists of review articles and included studies; we also contacted authors of included studies for additional citations and information. Unpublished studies and individual-patient data were sought from device manufacturers, including Medtronic (Minneapolis, Minnesota), Guidant Corp. (Indianapolis, Indiana), and St. Jude Medical (St. Paul, Minnesota). The search was not limited by language or publication status. The search terms included Medtronic InSync, ELA medical, Guidant, St. Jude, implantable defibrillators, implantable cardioverter defibrillators, AICD, ICD, single chamber ICD, dual chamber ICD, congestive heart failure, CHF, chronic heart failure, and heart diseases. A full list of search strategies (adapted for each database) and search results are available at www.ahrq.gov/clinic/tp/defibtp.htm (5). Study Selection We selected original research studies that had at least 25 participants and reported mortality or peri- or postimplantation complications with ICDs in adult patients with LV systolic dysfunction (left ventricular ejection fraction [LVEF]0.35, regardless of whether the patients had heart failure symptoms). To address efficacy questions, we restricted the analyses to RCTs. To address effectiveness questions, we expanded our inclusion criteria to include observational studies with contemporaneous comparison groups (such as cohort studies) and RCTs that did not report efficacy outcomes. To address safety questions, we included evidence from both RCTs and observational studies (including those without contemporaneous control groups, such as case series and registry data). Data Extraction and Analysis Study selection, quality assessment, and data extraction were completed by several investigators in duplicate and independently, using the methods recommended by the Quality of Reporting of Meta-analyses (QUOROM) group (6). We assessed quality by using the methods of Schulz and colleagues (7), the 5-item Jadad scale (8), and the 27-point Downs and Black scale (9). Publication bias was assessed visually by using funnel plots and quantitatively by using the rank correlation test (10), the graphical test (11), and the trim-and-fill method (12). Random-effects models were used to calculate pooled relative risks (RRs) in Review Manager 4.2.5 (Cochrane Collaboration, Copenhagen, Denmark). The length of study follow-up versus all-cause mortality was plotted for each study, and inverse varianceweighted least-squares regression was used to create a best-fit line. Postimplantation complications were expressed per 100 patient-years (calculated by multiplying the frequency of events in each study by the duration of follow-up, and standardizing to a denominator of 100) and are unadjusted rates. All results were reported with 95% CIs and, where appropriate, SDs or SEs. Statistical heterogeneity was quantified by using the I 2 statistic (13). In addition to examining for differences in point estimates across study designs and study quality, we explored device efficacy in different patient subgroups by using meta-regression. Covariates tested included presence of cardiac resynchronization therapy, length of follow-up, ischemic etiology, New York Heart Association (NYHA) class, age, QRS interval, LVEF, and primary versus secondary prevention. Role of the Funding Source The funding source (AHRQ, U.S. Department of Health and Human Services) had no role in the collection, analysis, or interpretation of the data or in the decision to submit the manuscript for publication. Results Literature Search From 4439 citations (Figure 1), we identified 12 RCTs (8516 patients) for the ICD efficacy review (1426), 53 studies (26840 patients from 5 nonefficacy RCTs and 48 observational studies [25 retrospective and 23 prospective]) for the ICD effectiveness review (2778), and 64 studies (86809 patients from 11 efficacy RCTs, 10 RCTs without efficacy outcomes, and 43 observational studies [24 retrospective and 19 prospective]) for the ICD safety review (1417, 1927, 29, 30, 34, 3740, 4245, 47, 48, 52, 54, 60, 61, 6366, 69, 70, 7275, 78101). A full list of search strategies, search results, detailed quality assessments for each included study, and tests for publication bias are available at www.ahrq.gov/clinic/tp/defibtp.htm (5). No publication bias was seen on the funnel plots. Figure 1. Flow diagram of study identification and selection. RCTs with Efficacy Data The 12 efficacy RCTs varied in quality (ranging from 1 to 3 on the Jadad scale) and duration (ranging from 15 to 66 months). All but 2 trials (16, 19) evaluated single-chamber ICDs (although no trials reported protocol adherence to single-chamber vs. dual-chamber ICDs). All patients in the RCTs had LV systolic dysfunction: Mean LVEF ranged from 0.21 to 0.28 in the primary prevention trials and from 0.32 to 0.46 in the secondary prevention trials. Most patients also had symptoms of heart failure: 50% had NYHA class II symptoms at baseline; 36%, class III symptoms; and 3%, class IV symptoms. Eleven percent of trial participants were in NYHA class I at baseline (Appendix Table 1). The mean age of RCT participants was 61 years (SD, 4), 74% were male, and 59% had ischemic heart disease. Appendix Table 1. Description of Randomized Trials Included in the Review Use of ICDs reduced all-cause mortality in patients with LV systolic dysfunction by 20% (95% CI, 10% to 29%; I 2= 44.4%) (Figure 2), largely because of a 54% relative reduction (CI, 37% to 63%; I 2= 0%) in sudden cardiac deaths. In patients with LV systolic dysfunction, ICDs were equally beneficial in reducing all-cause mortality in both primary prevention trials (RR, 0.81 [CI, 0.69 to 0.95]; I 2= 53.1% across 9 RCTs) and secondary prevention trials (RR, 0.77 [CI, 0.65 to 0.91]; I 2= 13.2% across 3 RCTs) (P for this indirect comparison= 0.56). Figure 2. Effect of implantable cardioverter defibrillator ( ICDs ) on all-cause mortality in randomized trials. A single trial included cardiac resynchronization therapy in both study groups for its comparison of ICDs versus control (19). All-cause mortality (RR, 0.83 [CI, 0.66 to 1.05]) was similar to that reported from the remainder of the studies, which did not contain cardiac resynchronization therapy in either study group (RR, 0.79 [CI, 0.69 to 0.91]) (P for indirect comparison= 0.92). Only 1 trial reported a statistically significant difference in the effect of ICDs across NYHA classes: The mortality benefits were greater in patients with NYHA class II symptoms than in those with NYHA class III symptoms in the Sudden Cardiac Death in Heart Failure Trial (P< 0.001 for interaction term of NYHA class and mortality) (22). In a series of univariate meta-regression sensitivity analyses, none of the covariates we examined (duration of follow-up, primary vs. secondary prevention, ischemic cause, presence of cardiac resynchronization therapy, NYHA class, mean age, mean LVEF, or mean QRS duration) contributed to the moderate statistical heterogeneity observed in our meta-analysis of all-cause mortality. In addition, our estimate of treatment effect was not associated with study quality. Implantable cardioverter defibrillators
Statistical Methods in Medical Research | 2009
Ben Vandermeer; Liza Bialy; Nicola Hooton; Lisa Hartling; Terry P Klassen; Bradley C. Johnston; Natasha Wiebe
The objectives of this study were to establish and describe a database of Cochrane and non-Cochrane meta-analyses of safety data and to determine under what conditions exact methods differ from asymptotic methods in meta-analyses of safety data. A sample of Cochrane (n = 500) and non-Cochrane (n = 200) systematic reviews was randomly selected and a database of safety meta-analyses established. Point estimates and confidence intervals for each meta-analysis were recalculated using exact methods and compared to the results of asymptotic methods. Cochrane reviews were nearly four times as likely as non-Cochrane reviews to contain meta-analyses of safety data (35% compared to 9%). More than 50% of safety meta-analyses contained an outcome with a rare event rate (<5%) and 30% contained at least one study with no events in one arm of the study. For rare event meta-analyses, exact point estimates differed substantially from asymptotic estimates 46% of the time, compared to 17% for those without rare events. Exact confidence intervals differed substantially from asymptotic ones 67% of the time compared to only 19% for those without rare events. The magnitude of differences was also correlated with the number of studies and the summary statistic used to combine the data. Asymptotic methods will not always be a good approximation for exact methods in safety meta-analyses. Event rates and number of studies should be closely examined when choosing the statistical method for combining rare event data.
JAMA | 2007
Finlay A. McAlister; Justin A. Ezekowitz; Nicola Hooton; Ben Vandermeer; Carol Spooner; Donna M Dryden; Richard L. Page; Mark A. Hlatky; Brian H. Rowe
Evidence report/technology assessment | 2007
Maria Ospina; Kenneth Bond; Mohammad Karkhaneh; Lisa Tjosvold; Ben Vandermeer; Yuanyuan Liang; Liza Bialy; Nicola Hooton; Nina Buscemi; Donna M Dryden; Terry P. Klassen
Chest | 2007
Jeremy Beach; Kelly Russell; Sandra Blitz; Nicola Hooton; Carol H. Spooner; Catherine Lemière; Susan M. Tarlo; Brian H. Rowe
Vaccine | 2005
Janet E. McElhaney; Jonathan W. Hooton; Nicola Hooton; R. Chris Bleackley
Psychology of Religion and Spirituality | 2009
Kenneth Bond; Maria Ospina; Nicola Hooton; Liza Bialy; Donna M Dryden; Nina Buscemi; David S. Shannahoff-Khalsa; Jeffrey Dusek; Linda E. Carlson
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University of Texas Health Science Center at San Antonio
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