Suhail A. R. Doi

Longitudinal impact of sleep on overweight and obesity in children and adolescents: a systematic review and bias-adjusted meta-analysis

Short sleep duration is considered a potential risk for overweight/obesity in childhood and adolescence. However, most of the evidence on this topic is obtained from cross‐sectional studies; therefore, the nature and extent of the longitudinal associations are unclear. This study explores the prospective association between short sleep and overweight/obesity in young subjects. The MEDLINE, EMBASE, Pubmed, and CINAHL databases were searched for English‐language articles, published until May 2014, reporting longitudinal association between sleep and body mass index (BMI) in children and adolescents. Recommendations of the Sleep Health Foundation were used to standardize reference sleep duration. Sleep category, with sleep duration less than the reference sleep, was considered as the short sleep category. Meta‐analysis was conducted to explore the association between short sleep and overweight/obesity. A review of 22 longitudinal studies, with subjects from diverse backgrounds, suggested an inverse association between sleep duration and BMI. Meta‐analysis of 11 longitudinal studies, comprising 24,821 participants, revealed that subjects sleeping for short duration had twice the risk of being overweight/obese, compared with subjects sleeping for long duration (odds ratio 2.15; 95% confidence interval: 1.64–2.81). This study provides evidence that short sleep duration in young subjects is significantly associated with future overweight/obesity.

A quality-effects model for meta-analysis

We introduce a quality-effects approach that combines evidence from a series of trials comparing 2 interventions. This approach incorporates the heterogeneity of effects in the analysis of the overall interventional efficacy. However, unlike the random-effects model based on observed between-trial heterogeneity, we suggest adjustment based on measured methodological heterogeneity between studies. We propose a simple noniterative procedure for computing the combined effect size under this model and suggest that this could represent a more convincing alternative to the random effects model.

Gestational weight gain in relation to offspring obesity over the life course: a systematic review and bias-adjusted meta-analysis.

Gestational weight gain (GWG) is considered one of the risk factors for future obesity in the offspring. However, the direction and strength of this association at different periods of offspring life is relatively unknown. This study investigates whether excess or inadequate maternal GWG during pregnancy influences the risk of offspring obesity at different stages in life. A systematic review of published articles was undertaken after a comprehensive search of different databases, and extracted data were meta‐analysed. To quantify offspring obesity estimates in relation to GWG, we stratified obesity estimates within three life stages of the offspring age: <5 years, 5 to <18 years and 18+ years. Our meta‐analysis showed that, compared with offspring of women with adequate GWG, offspring of women who gained inadequate gestational weight were at a decreased risk of obesity (relative risk [RR]: 0.86; 95% confidence interval [CI]: 0.78–0.94), and offspring of women who gained excess weight were at an increased risk of obesity (RR: 1.40; 95% CI: 1.23–1.59). These relationships were similar after stratification by life stage. Findings of this study therefore suggest that excess GWG does influence offspring obesity over the short‐ and long‐term, and should therefore be avoided.

Meta-analysis of heterogeneous clinical trials: An empirical example

Meta-analysis of heterogeneous clinical trials is currently sub-optimal. This is because there has been no improvement in the method of weighted averaging for such studies since the DL method in 1986. This article presents the argument for the use of situation specific weights to integrate results from such trials. An empirical example is given with data from a meta-analysis done 10 years earlier. Previously reported data on 21 studies that looked at the effect of working conditions on preterm births were re-analyzed. Several methods were used to estimate the overall effect sizes. Study specific scores were included in the weighting process when combining studies and it was shown that this model not only was more conservative than the model of DL but also retains the legitimacy of the pooled effect size. The inclusion of appropriate study specific scores in an appropriate meta-analysis model permits the quantification of the variation between studies based on something tangible as opposed to the random adjustments made by the random effects model to the pooled effect size. It is important that such differences are recognized by the wider research community so that meta-analyses remain a valid tool for synthesizing research.

Advances in the meta-analysis of heterogeneous clinical trials I: The inverse variance heterogeneity model

This article examines an improved alternative to the random effects (RE) model for meta-analysis of heterogeneous studies. It is shown that the known issues of underestimation of the statistical error and spuriously overconfident estimates with the RE model can be resolved by the use of an estimator under the fixed effect model assumption with a quasi-likelihood based variance structure - the IVhet model. Extensive simulations confirm that this estimator retains a correct coverage probability and a lower observed variance than the RE model estimator, regardless of heterogeneity. When the proposed IVhet method is applied to the controversial meta-analysis of intravenous magnesium for the prevention of mortality after myocardial infarction, the pooled OR is 1.01 (95% CI 0.71-1.46) which not only favors the larger studies but also indicates more uncertainty around the point estimate. In comparison, under the RE model the pooled OR is 0.71 (95% CI 0.57-0.89) which, given the simulation results, reflects underestimation of the statistical error. Given the compelling evidence generated, we recommend that the IVhet model replace both the FE and RE models. To facilitate this, it has been implemented into free meta-analysis software called MetaXL which can be downloaded from www.epigear.com.

Combining heterogenous studies using the random-effects model is a mistake and leads to inconclusive meta-analyses

methodological process used to arrive at the pooled point estimate in meta-analyses [11,12], an issue that has consistently been overlooked whenever this sort of discussion came up. The discussion took a new turn when Nuesch and Juni [13] asked a different but crucial question: ‘‘Which metaanalyses are conclusive?’’ using the magnesium metaanalysis as an example [14]. This time, these authors take us through funnel plots, tests of interaction, and trial sequential analysis (TSA) in an attempt to help us determine whether a meta-analysis should be trusted or could be considered conclusive. Although the analyses performed by the authors do provide some understanding of how metaanalytic models behave, we realized that the root cause (the models themselves) of faulty meta-analyses have again been overlooked. We will, therefore, attempt to address some of these issues using the same example given by Nuesch and Juni [13]. We should point out at the outset that it has conventionally been thought that a fixed-effects approach estimates the pooled effect under the assumption that the effect is the same in all individual studies, whereas a random-effects approach is used to describe the distribution of the effects in the individual studies (which are allowed to vary). We have, therefore, been advised in the process of writing this commentary that a fixed-effects approach should not be used in the presence of heterogeneous effects, and (conversely) the mean estimate from a randomeffects approach should not be used as a benchmark for the effects in each individual study. In this discussion, however, we take the stand of Senn [15] that a fixed-effects metaanalysis tests the null hypothesis that treatment effects are identical in all trials. When, and if, this is rejected, then the alternative hypothesis that may be asserted is, ‘‘there is at least one trial in which the treatment effects differed.’’ Indeed, we agree with Senn, who says that ‘‘the position of simultaneously holding that fixed effects meta-analyses are inappropriate but that ‘uninformative’ prior distributions for random effect variances must be used in connection with random effects meta-analyses seems untenable’’ [15] .W e,

Diabetes and cancer II: role of diabetes medications and influence of shared risk factors

An association between type 2 diabetes mellitus (DM) and cancer has long been postulated, but the biological mechanism responsible for this association has not been defined. In part one of this review, we discussed the epidemiological evidence for increased risk of cancer, decreased cancer survival, and decreased rates of cancer screening in diabetic patients. Here we review the risk factors shared by cancer and DM and how DM medications play a role in altering cancer risk. Hyperinsulinemia stands out as a major factor contributing to the association between DM and cancer, and modulation of circulating insulin levels by DM medications appears to play an important role in altering cancer risk. Drugs that increase circulating insulin, including exogenous insulin, insulin analogs, and insulin secretagogues, are generally associated with an increased cancer risk. In contrast, drugs that regulate insulin signaling without increasing levels, especially metformin, appear to be associated with a decreased cancer risk. In addition to hyperinsulinemia, the effect of DM medications on other shared risk factors including hyperglycemia, obesity, and oxidative stress as well as demographic factors that may influence the use of certain DM drugs in different populations are described. Further elucidation of the mechanisms behind the association between DM, cancer, and the role of DM medications in modulating cancer risk may aid in the development of better prevention and treatment options for both DM and cancer. Additionally, incorporation of DM medication use into cancer prediction models may lead to the development of improved risk assessment tools for diabetic patients.

Tumor-Related Hyponatremia

Hyponatremia is an important and common electrolyte disorder in tumor patients and one that has been reported in association with a number of different primary diagnoses. The correct diagnosis of the pathophysiological basis for each patient is important because it significantly alters the treatment approach. In this article, we review the epidemiology and presentation of patients with hyponatremia, the pathophysiologic groups for the disorder with respect to sodium and water balance and the diagnostic measures for determining the correct pathophysiologic groups. We then present the various treatment options based on the pathophysiologic groups including a mathematical approach to the use of hypertonic saline in management. In cancer patients, hyponatremia is a serious comorbidity that requires particular attention as its treatment varies by pathophysiologic groups, and its consequences can have a deleterious effect on the patient’s health.

Prostatic Urethral Lift Improves Urinary Symptoms and Flow While Preserving Sexual Function for Men with Benign Prostatic Hyperplasia: A Systematic Review and Meta-analysis

CONTEXT Treatment for lower urinary tract symptoms resulting from benign prostatic hyperplasia (BPH) is varied, and significant side effects, particularly concerning sexual function, affect uptake. The prostatic urethral lift (PUL) procedure is a recent addition to the armamentarium for BPH treatment, with independent reports suggesting improvement of symptoms, sexual function, and urinary flow. OBJECTIVE We undertook a systematic review and meta-analysis of reported symptomatic, functional, and sexual outcomes following the PUL procedure. EVIDENCE ACQUISITION We performed a critical review of Medline, Embase, ScienceDirect, Cochrane Library, and Web of Science databases in May 2014 according to the Preferred Reporting Items for Systematic Review and Meta-Analysis statement. Quality assessment was performed using a modification of the Methodological Index for Non-Randomized Studies tool. All retrospective, prospective, and controlled trials were included for analysis. Symptom scores, sexual health scores, and functional outcomes were pooled and meta-analysed using quality and random-effects models. EVIDENCE SYNTHESIS Ten articles comprising six independent patient cohorts were included for analysis. Pooled estimates from between 452 and 680 patients suggested overall improvement following PUL, including symptoms (large gain; standardised mean gain range of 1.3-1.6, International Prostate Symptom Score difference of -7.2 to -8.7 points), maximum flow rate (3.8-4.0 ml/s), and quality of life (2.2-2.4 points). Sexual function was preserved with a small improvement estimated at 12 mo (standardised mean gain range of 0.3-0.4). Pooled estimates were mostly heterogeneous across study groups. CONCLUSIONS PUL is a well-tolerated, minimally invasive therapy for BPH that provides favourable symptom, sexual health, and functional outcomes during follow-up to 12 mo. Longer follow-up and larger randomised studies are required to further confirm these preliminary results. PATIENT SUMMARY We reviewed the early results of an innovative procedure directed towards the management of prostate enlargement. The results revealed a well-tolerated procedure that produces improvement in urinary symptoms and function while preserving sexual function.

Airways in out-of-hospital cardiac arrest : systematic review and meta-analysis

Abstract Objective. To determine the differences in survival for out-of-hospital advanced airway intervention (AAI) compared with basic airway intervention (BAI) in cardiac arrest. Background. AAI is commonly utilized in cardiac arrest in the out-of-hospital setting as a means to secure the airway. Observational studies and clinical trials of AAI suggest that AAI is associated with worse outcomes in terms of survival. No controlled trials exist that compares AAI to BAI. Methods. We conducted a bias-adjusted meta-analysis on 17 observational studies. The outcomes were survival, short-term (return of spontaneous circulation and to hospital admission), and longer-term (to discharge, to one month survival). We undertook sensitivity analyses by analyzing patients separately: those who were 16 years and older, nontrauma only, and attempted versus successful AAI. Results. This meta-analysis included 388,878 patients. The short-term survival for AAI compared to BAI were overall OR 0.84(95% CI 0.62 to 1.13), for endotracheal intubation (ETI) OR 0.79 (95% CI 0.54 to 1.16), and for supraglottic airways (SGA) OR 0.59 (95% CI 0.39 to 0.89). Long-term survival for AAI were overall OR 0.49 (95% CI 0.37 to 0.65), for ETI OR 0.48 (95% CI 0.36 to 0.64), and for SGA OR 0.35 (95% CI 0.28 to 0.44). Sensitivity analyses shows that limiting analyses to adults, non-trauma victims, and instances where AAI was both attempted and successful did not alter results meaningfully. A third of all studies did not adjust for any other confounding factors that could impact on survival. Conclusions. This meta-analysis shows decreased survival for AAIs used out-of-hospital in cardiac arrest, but are likely biased due to confounding, especially confounding by indication. A properly conducted prospective study or a controlled trial is urgently needed and are possible to do.