Search

ObjectiveTo perform a systematic review and individual participant data meta-analysis to identify preoperative factors associated with a good seizure outcome in children with Tuberous Sclerosis Complex undergoing resective epilepsy surgery.Data sourcesElectronic databases (MEDLINE, EMBASE, CINAHL and Web of Science), archives of major epilepsy and neurosurgery meetings, and bibliographies of relevant articles, with no language or date restrictions.Study selectionWe included case-control or cohort studies of consecutive participants undergoing resective epilepsy surgery that reported seizure outcomes. We performed title and abstract and full text screening independently and in duplicate. We resolved disagreements through discussion.Data extractionOne author performed data extraction which was verified by a second author using predefined data fields including study quality assessment using a risk of bias instrument we developed. We recorded all preoperative factors that may plausibly predict seizure outcomes.Data synthesisTo identify predictors of a good seizure outcome (i.e. Engel Class I or II) we used logistic regression adjusting for length of follow-up for each preoperative variable.ResultsOf 9863 citations, 20 articles reporting on 181 participants were eligible. Good seizure outcomes were observed in 126 (69%) participants (Engel Class I: 102(56%); Engel class II: 24(13%)). In univariable analyses, absence of generalized seizure semiology (OR = 3.1, 95%CI = 1.2-8.2, p = 0.022), no or mild developmental delay (OR = 7.3, 95%CI = 2.1-24.7, p = 0.001), unifocal ictal scalp electroencephalographic (EEG) abnormality (OR = 3.2, 95%CI = 1.4-7.6, p = 0.008) and EEG/Magnetic resonance imaging concordance (OR = 4.9, 95%CI = 1.8-13.5, p = 0.002) were associated with a good postoperative seizure outcome.ConclusionsSmall retrospective cohort studies are inherently prone to bias, some of which are overcome using individual participant data. The best available evidence suggests four preoperative factors predictive of good seizure outcomes following resective epilepsy surgery. Large long-term prospective multicenter observational studies are required to further evaluate the risk factors identified in this review.

Introduction: Physical activity (PA) is critical for disease prevention and maintaining functional ability with aging. Despite this, as many as 50% of older adults in populations worldwide are considered insufficiently active. There is a recognized need to mobilize policies targeted toward modifiable determinants of healthy aging like PA. This umbrella review aimed to summarize the evidence for determinants of PA in community-dwelling older adults. Methods: A research librarian searched six databases. Systematic and scoping reviews were included if they investigated community-dwelling people with a mean age of 60 + years and examined a relationship between a determinant and any type of PA. Two independent reviewers screened and extracted data from all reviews. JBI methodology and Critical Appraisal Checklist for Systematic Reviews and Research Syntheses were followed and information on the quality of the evidence was extracted. Results: From 17,277 records screened,11 reviews representing > 300 unique primary papers were ultimately included. Only 6% of studies included in all reviews had longitudinal designs. Included studies used a large variety of PA measures, with 76% using only self-report, 15% using only direct measures (e.g., accelerometry), 3% using both types, and 6% with no outcome measure reported. Only four reviews provided a definition of PA and there was substantial inconsistency in the way PA was categorised. Community level influences, which only included the physical environment, were the most commonly assessed (6/11) with more than 70% of the summarized relationships demonstrating null associations. Three out of four reviews reported a positive relationship between walkability and PA in general community-dwelling older adults. There was also evidence supporting relationships between presence of social support for PA, younger age, and men having higher PA from a single systematic review. None of the included reviews assessed the quality of evidence but over 60% performed a risk of bias assessment. Conclusions: Walkability, age, gender, and social support for PA were the most supported PA determinants identified. Further research should focus on interpersonal and intrapersonal influences and incorporate direct measures of PA with clear operational definitions. There is a need for longitudinal study designs to further understand determinants of PA behaviour trajectories. [ABSTRACT FROM AUTHOR]

The study attempts to evaluate the relationship between higher vs lower positive end-expiratory pressure (PEEP) in patients with acute lung injury and acute respiratory distress syndrome (ARDS). The results indicate that treatment with both levels of PEEP did not improve hospital outcomes; however, higher levels did improve survival rates among patients with ARDS.

Abstract Background Subgroup analyses in randomized trials examine whether effects of interventions differ between subgroups of study populations according to characteristics of patients or interventions. However, findings from subgroup analyses may be misleading, potentially resulting in suboptimal clinical and health decision making. Few studies have investigated the reporting and conduct of subgroup analyses and a number of important questions remain unanswered. The objectives of this study are: 1) to describe the reporting of subgroup analyses and claims of subgroup effects in randomized controlled trials, 2) to assess study characteristics associated with reporting of subgroup analyses and with claims of subgroup effects, and 3) to examine the analysis, and interpretation of subgroup effects for each study's primary outcome. Methods We will conduct a systematic review of 464 randomized controlled human trials published in 2007 in the 118 Core Clinical Journals defined by the National Library of Medicine. We will randomly select journal articles, stratified in a 1:1 ratio by higher impact versus lower impact journals. According to 2007 ISI total citations, we consider the New England Journal of Medicine, JAMA, Lancet, Annals of Internal Medicine, and BMJ as higher impact journals. Teams of two reviewers will independently screen full texts of reports for eligibility, and abstract data, using standardized, pilot-tested extraction forms. We will conduct univariable and multivariable logistic regression analyses to examine the association of pre-specified study characteristics with reporting of subgroup analyses and with claims of subgroup effects for the primary and any other outcomes. Discussion A clear understanding of subgroup analyses, as currently conducted and reported in published randomized controlled trials, will reveal both strengths and weaknesses of this practice. Our findings will contribute to a set of recommendations to optimize the conduct and reporting of subgroup analyses, and claim and interpretation of subgroup effects in randomized trials.

Abstract Background Incomplete ascertainment of outcomes in randomized controlled trials (RCTs) is likely to bias final study results if reasons for unavailability of patient data are associated with the outcome of interest. The primary objective of this study is to assess the potential impact of loss to follow-up on the estimates of treatment effect. The secondary objectives are to describe, for published RCTs, (1) the reporting of loss to follow-up information, (2) the analytic methods used for handling loss to follow-up information, and (3) the extent of reported loss to follow-up. Methods We will conduct a systematic review of reports of RCTs recently published in five top general medical journals. Eligible RCTs will demonstrate statistically significant effect estimates with respect to primary outcomes that are patient-important and expressed as binary data. Teams of 2 reviewers will independently determine eligibility and extract relevant information from each eligible trial using standardized, pre-piloted forms. To assess the potential impact of loss to follow-up on the estimates of treatment effect we will, for varying assumptions about the outcomes of participants lost to follow-up (LTFU), calculate (1) the percentage of RCTs that lose statistical significance and (2) the mean change in effect estimate across RCTs. The different assumptions we will test are the following: (1) none of the LTFU participants had the event; (2) all LTFU participants had the event; (3) all LTFU participants in the treatment group had the event; none of those in the control group had it (worst case scenario); (4) the event incidence among LTFU participants (relative to observed participants) increased, with a higher relative increase in the intervention group; and (5) the event incidence among LTFU participants (relative to observed participants) increased in the intervention group and decreased in the control group. Discussion We aim to make our objectives and methods transparent. The results of this study may have important implications for both clinical trialists and users of the medical literature.