Use Of Random Effects Research Articles

An Umbrella Review for Assessment of Treatment Effectiveness of Clear Aligners Compared to Conventional Fixed Appliances in Orthodontic Patients

Introduction Orthodontic improvements, mainly through the previous decade, have led to a substantial rise in patients’ esthetic needs. Traditional orthodontic procedures have been linked with a compromise in facial appearance, which increases concern among patients pursuing orthodontic treatment. Methods PubMed, MEDLINE, Google Scholar, and Cochrane Library of Systematic Reviews databases were searched using appropriate entry terms and Boolean operators. Search strategy was conducted till June 2022 for systematic reviews and meta-analyses. Publications were systematically assessed for eligibility, and two observers independently graded the methodologic quality using AMSTAR-2 tool. For each meta-analysis, we estimated the summary effect size by the use of random-effects and fixed-effects models and the 95% confidence interval. We estimated the between-study heterogeneity expressed by I 2 (defined as large for I 2 ≥50%), evidence of small-study effects (i.e., large studies had significantly more conservative results than smaller studies), and evidence of excess significance bias (i.e., more studies than expected with significant results). Results Overall, 16 unique systematic reviews and meta-analyses following the eligibility criteria were selected for umbrella review. The results of qualitative analysis of studies revealed that 4 studies had a critically low risk of bias, 11 showed low risk, and 1 study had moderate risk. The results of the meta-analysis favored clear aligners with respect to oral hygiene and root resorption parameters. When tooth movements were considered, the results favored conventional orthodontic treatment. Conclusion Clear aligner therapy (CAT) has significant advantages with regard to efficiency (treatment time, chair time) in mild-moderate malocclusion cases. The overall accuracy of CAT when compared to fixed orthodontic treatment was found to be 55-82%.

Invasive vs. conservative management of older patients with non-ST-elevation acute coronary syndrome: individual patient data meta-analysis.

Older patients with non-ST-elevation acute coronary syndrome (NSTEACS) are less likely to receive guideline-recommended care including coronary angiography and revascularization. Evidence-based recommendations regarding interventional management strategies in this patient cohort are scarce. This meta-analysis aimed to assess the impact of routine invasive vs. conservative management of NSTEACS by using individual patient data (IPD) from all available randomized controlled trials (RCTs) including older patients. MEDLINE, Web of Science and Scopus were searched between 1 January 2010 and 11 September 2023. RCTs investigating routine invasive and conservative strategies in persons >70 years old with NSTEACS were included. Observational studies or trials involving populations outside the target range were excluded. The primary endpoint was a composite of all-cause mortality and myocardial infarction (MI) at 1 year. One-stage IPD meta-analyses were adopted by use of random-effects and fixed-effect Cox models. This meta-analysis is registered with PROSPERO (CRD42023379819). Six eligible studies were identified including 1479 participants. The primary endpoint occurred in 181 of 736 (24.5%) participants in the invasive management group compared with 215 of 743 (28.9%) participants in the conservative management group with a hazard ratio (HR) from random-effects model of 0.87 (95% CI 0.63-1.22; P = .43). The hazard for MI at 1 year was significantly lower in the invasive group compared with the conservative group (HR from random-effects model 0.62, 95% CI 0.44-0.87; P = .006). Similar results were seen for urgent revascularization (HR from random-effects model 0.41, 95% CI 0.18-0.95; P = .037). There was no significant difference in mortality. No evidence was found that routine invasive treatment for NSTEACS in older patients reduces the risk of a composite of all-cause mortality and MI within 1 year compared with conservative management. However, there is convincing evidence that invasive treatment significantly lowers the risk of repeat MI or urgent revascularisation. Further evidence is needed from ongoing larger clinical trials.

Using model-based geostatistics for assessing the elimination of trachoma.

Trachoma is the commonest infectious cause of blindness worldwide. Efforts are being made to eliminate trachoma as a public health problem globally. However, as prevalence decreases, it becomes more challenging to precisely predict prevalence. We demonstrate how model-based geostatistics (MBG) can be used as a reliable, efficient, and widely applicable tool to assess the elimination status of trachoma. We analysed trachoma surveillance data from Brazil, Malawi, and Niger. We developed geostatistical Binomial models to predict trachomatous inflammation-follicular (TF) and trachomatous trichiasis (TT) prevalence. We proposed a general framework to incorporate age and gender in the geostatistical models, whilst accounting for residual spatial and non-spatial variation in prevalence through the use of random effects. We also used predictive probabilities generated by the geostatistical models to quantify the likelihood of having achieved the elimination target in each evaluation unit (EU). TF and TT prevalence varied considerably by country, with Brazil showing the lowest prevalence and Niger the highest. Brazil and Malawi are highly likely to have met the elimination criteria for TF in each EU, but, for some EUs, there was high uncertainty in relation to the elimination of TT according to the model alone. In Niger, the predicted prevalence varied significantly across EUs, with the probability of having achieved the elimination target ranging from values close to 0% to 100%, for both TF and TT. We demonstrated the wide applicability of MBG for trachoma programmes, using data from different epidemiological settings. Unlike the standard trachoma prevalence survey approach, MBG provides a more statistically rigorous way of quantifying uncertainty around the achievement of elimination prevalence targets, through the use of spatial correlation. In addition to the analysis of existing survey data, MBG also provides an approach to identify areas in which more sampling effort is needed to improve EU classification. We advocate MBG as the new standard method for analysing trachoma survey outputs.

Pharmacological treatment for connective tissue disease-associated interstitial lung involvement: Protocol for an overview of systematic reviews and meta-analyses.

Interstitial lung disease (ILD) is the most important pulmonary manifestation of connective tissue diseases (CTDs) since it is associated with high morbidity and mortality. However, there is uncertainty on what constitutes the optimal treatment options from a variety of competing interventions. The aim of the overview is to summarize existing evidence of the effectiveness and harm of pharmacological therapies for adults with CTD-ILD. A literature search will be conducted in MEDLINE, the Cochrane Database of Systematic Reviews, DARE, the Centre for Reviews and Dissemination Health Technology Assessment database, Epistemonikos.org, KSR Evidence, and PROSPERO. We will search for systematic reviews with or without meta-analysis that examine pharmacological treatment for CTD-ILD. Updated supplemental search will also be undertaken to identify additional randomized controlled trials. The primary outcomes will be changes in lung function measures and adverse events. The methodological quality of the included reviews will be assessed using the AMSTAR 2 tool. The overall quality of the evidence will be evaluated using the GRADE rating. Summarized outcome data extracted from systematic reviews will be described in narrative form or in tables. For each meta-analysis we will estimate the summary effect size by use of random-effects and fixed-effects models with 95% confidence intervals, the between-study heterogeneity expressed by I², and the 95% prediction interval. If feasible, given sufficient data, network meta-analysis will be conducted to combine direct and indirect evidence of class and agent comparisons. While many factors are crucial in selecting an appropriate treatment for patients with CTD-ILD, evidence for the efficacy and safety of a drug is essential in guiding this decision. Thus, this overview will aid clinicians in balancing the risks versus benefits of the available therapies by providing high-quality evidence to support informed decision-making and may contribute to future guideline development. MedRxiv: DOI 10.1101/2022.01.25.22269807 PROSPERO: CRD42022303180.

Meta-Analysis of Bilateral Versus Single Internal Thoracic Artery Grafting in Patients ≥70 Years of Age

The optimal choice of graft material in patients ≥70years of age undergoing coronary artery bypass grafting remains unknown. A systematic review of literature was conducted by searching PubMed, Embase, Web of Science, and Cochrane Library databases for original publications that compared bilateral internal thoracic artery (BITA) grafting with single internal thoracic artery grafting in patients ≥70years of age. Data were extracted by 2 independent investigators and meta-analyzed with the use of random effects. A total of 10 studies, including 11,185 patients, met the inclusion criteria. No differences in early mortality and morbidity, with the exemption of sternal wound complications which were more frequently observed in the BITA group (odds ratio 1.72, 95% 1.00 to 2.96 confidence interval [CI], p=0.05; propensity score-matched population odds ratio 1.58, 95% CI 1.09 to 2.29, p=0.02), were observed. Overall survival was superior in the overall patient population (hazard ratio [HR] 0.76, 95% CI 0.66 to 0.86, p <0.001), after applying a blanking period of 3months to the overall patient population (HR 0.77, 95% CI 0.64 to 0.92, p=0.005) as well as in the matched population (HR 0.72, 95% CI 0.58 to 0.89, p=0.002); in all cases, a benefit was readily seen within a few years after surgery. The difference in freedom from major adverse cardiac and cerebrovascular events failed to reach statistical significance (overall patient population HR 0.55, 95% CI 0.27 to 1.13, p=0.10; matched population HR 0.52, 95% CI 0.23 to 1.16, p=0.11). In conclusion, BITA grafting can be safely performed in patients ≥70years of age as late clinical benefits are expected to manifest themselves readily within a few years after surgery.

811 Statistical Analyses of Multiple Burn Wounds within an Animal

IntroductionPorcine animal models are frequently used to study the effects of various burn wound treatments and conditions. In these studies, multiple wounds are created on the dorsum of an anesthetized pig. Wounds within an animal are correlated, and the analysis of such a design should account for this dependence. Two recent studies are used as examples to illustrate the use of random effects for animal to account for the dependence of wound measurements within each pig.MethodsIn both studies, treatments were randomized to wound location, and neither contained repeated measurements within a wound.Study #1 investigated the effectiveness of enzymatic debridement. Forty 3-cm diameter partial-thickness burn wounds were created on the dorsum of 5 anesthetized pigs, arranged in 4 rows and 10 columns. Dorsal quadrants with 10 wounds each were created by combinations of two conditions: wounds that were wet or dry and wounds that were treated for either 72 or 96 hours. Debridement Efficiency Scores were calculated for each wound and evaluated for differences by inferential statistical comparisons between experimental treatments and conditions. The multilevel statistical model contained Treatment Group (5 levels), Treatment Time (2 levels: 72 hour and 96 hour), and Wet/Dry Condition (2 levels) as fixed effects, which were crossed to create a 3-way block, resulting in 2 wounds per animal for each Treatment, Wet/Dry, and Time combination. Random effects of animal and treatment block within animal were included in the model.Study #2 investigated the effectiveness of an experimental treatment applied at 3 different post-burn injury time points versus a standard of care (SOC). Up to 12 5-cm2 deep partial thickness wounds were created in 2 rows and 6 columns on each dorsum of 6 anesthetized pigs. Each treated wound was compared with a SOC wound located along the same cranio-caudal axis. Paired differences for wound closure % were calculated and analyzed with time as a fixed effect with a random effect for animal.ResultsFor Study #1, there were 200 total wounds, and for Study #2 there were 72 total wounds. These experimental units are not independent, as required by statistical testing. For both studies, there was graphical evidence that the burn wound measurements differed both within and between pigs. The statistical tests accounted for this variability by incorporating the effects due to pigs.ConclusionsMatching the statistical model to the experimental design is critical for correct interpretation of the results. Failure to use the correct model by assuming wounds within a pig are independent (and thereby ignoring any effect due to the pig) will result in erroneous statistical test results and less powerful tests of treatment differences.

Penalized Poisson model for network meta-analysis of individual patient time-to-event data.

Network meta-analysis (NMA) allows the combination of direct and indirect evidence from a set of randomized clinical trials. Performing NMA using individual patient data (IPD) is considered as a "gold standard" approach as it provides several advantages over NMA based on aggregate data. For example, it allows to perform advanced modeling of covariates or covariate-treatment interactions. An important issue in IPD NMA is the selection of influential parameters among terms that account for inconsistency, covariates, covariate-by-treatment interactions or nonproportionality of treatments effect for time to event data. This issue has not been deeply studied in the literature yet and in particular not for time-to-event data. A major difficulty is to jointly account for between-trial heterogeneity which could have a major influence on the selection process. The use of penalized generalized mixed effect model is a solution, but existing implementations have several shortcomings and an important computational cost that precludes their use for complex IPD NMA. In this article, we propose a penalized Poisson regression model to perform IPD NMA of time-to-event data. It is based only on fixed effect parameters which improve its computational cost over the use of random effects. It could be easily implemented using existing penalized regression package. Computer code is shared for implementation. The methods were applied on simulated data to illustrate the importance to take into account between trial heterogeneity during the selection procedure. Finally, it was applied to an IPD NMA of overall survival of chemotherapy and radiotherapy in nasopharyngeal carcinoma.

Bayesian non-parametric detection heterogeneity in ecological models

Detection heterogeneity is inherent to ecological data, arising from factors such as varied terrain or weather conditions, inconsistent sampling effort, or heterogeneity of individuals themselves. Incorporating additional covariates into a statistical model is one approach for addressing heterogeneity, but there is no guarantee that any set of measurable covariates will adequately address the heterogeneity, and the presence of unmodelled heterogeneity has been shown to produce biases in the resulting inferences. Other approaches for addressing heterogeneity include the use of random effects, or finite mixtures of homogeneous subgroups. Here, we present a non-parametric approach for modeling detection heterogeneity for use in a Bayesian hierarchical framework. We employ a Dirichlet process mixture which allows a flexible number of population subgroups without the need to pre-specify this number of subgroups as in a finite mixture. We describe this non-parametric approach, then consider its use for modeling detection heterogeneity in two common ecological motifs: capture–recapture and occupancy modeling. For each, we consider a homogeneous model, finite mixture models, and the non-parametric approach. We compare these approaches using simulation, and observe the non-parametric approach as the most reliable method for addressing varying degrees of heterogeneity. We also present two real-data examples, and compare the inferences resulting from each modeling approach. Analyses are carried out using the nimble package for R, which provides facilities for Bayesian non-parametric models.

Meta-analysis of prognostic factors of overall survival in patients undergoing oesophagectomy for oesophageal cancer

Currently, the American Joint Commission on Cancer (AJCC) staging system is used for prognostication for oesophageal cancer. However, several prognostically important factors have been reported but not incorporated. This meta-analysis aimed to characterize the impact of preoperative, operative, and oncological factors on the prognosis of patients undergoing curative resection for oesophageal cancer. This systematic review was performed according to PRISMA guidelines and eligible studies were identified through a search of PubMed, Scopus, and Cochrane CENTRAL databases up to 31 December 2018. A meta-analysis was conducted with the use of random-effects modeling to determine pooled univariable hazard ratios (HRs). The study was prospectively registered with the PROSPERO database (Registration: CRD42018157966). One-hundred and seventy-one articles including 73,629 patients were assessed quantitatively. Of the 122 factors associated with survival, 39 were significant on pooled analysis. Of these. the strongly associated prognostic factors were 'pathological' T stage (HR: 2.07, CI95%: 1.77-2.43, P< 0.001), 'pathological' N stage (HR: 2.24, CI95%: 1.95-2.59, P< 0.001), perineural invasion (HR: 1.54, CI95%: 1.36-1.74, P< 0.001), circumferential resection margin (HR: 2.17, CI95%: 1.82-2.59, P< 0.001), poor tumor grade (HR: 1.53, CI95%: 1.34-1.74, P< 0.001), and high neutrophil:lymphocyte ratio (HR: 1.47, CI95%: 1.30-1.66, P< 0.001). Several tumor biological variables not included in the AJCC 8th edition classification can impact on overall survival. Incorporation and validation of these factors into prognostic models and next edition of the AJCC system will enable personalized approach to prognostication and treatment.

Properties of h‐Likelihood Estimators in Clustered Data

SummaryWe study properties of the maximum h‐likelihood estimators for random effects in clustered data. To define optimality in random effects predictions, several foundational concepts of statistics such as likelihood, unbiasedness, consistency, confidence distribution and the Cramer–Rao lower bound are extended. Exact probability statements about interval estimators for random effects can be made asymptotically without a prior assumption. Using the binary‐matched pair example, we illustrated that the use of random effects recover information, leading to the boon on estimating treatment effects.

O64 META-ANALYSIS OF PROGNOSTIC FACTORS FOR OVERALL SURVIVAL IN PATIENTS UNDERGOING OESOPHAGECTOMY FOR OESOPHAGEAL CANCERS

Abstract Aims The objective of this meta-analysis was to assess statistically the impact of patient-level, operative, and tumour characteristics on overall survival of patients undergoing curative resection for oesophageal cancer. Introduction Oesophageal cancer is staged using the American Joint Comission on Cancer (AJCC) staging system. Numerous other prognostically important histopathological and demographic characteristics have been reported. Methods This systematic review was performed according to PRISMA guidelines and eligible studies were identified through a search of PubMed, Scopus and Cochrane CENTRAL databases up to 31st December 2018. A meta-analysis was conducted with the use of random-effects modelling to determine pooled univariable hazard ratios (HRs) and prospectively registered with the PROSPERO database (Registration CRD42018130732). Results One-hundred and sixty-six articles including 70,299 patients were assessed quantitatively. Of the 122 factors associated with survival, 39 were significant on pooled analysis. Of these the strongly associated prognostic factors were T stage (HR: 2.07, CI95%: 1.77 - 2.43, p&lt;0.001), N stage (HR: 2.24, CI95%: 1.95 - 2.59, p&lt;0.001), perineural invasion (HR: 1.54, CI95%: 1.36 - 1.74, p&lt;0.001), circumferential resection margin (HR: 2.17, CI95%: 1.82 - 2.59, p&lt;0.001), poor tumour grade (HR: 1.53, CI95%: 1.34 - 1.74, p&lt;0.001), and high neutrophil:lymphocyte ratio (HR: 1.47, CI95%: 1.30 - 1.66, p&lt;0.001). Conclusion Several tumour biological variables not included in the AJCC 8th edition classification can impact on overall survival. These require incorporation into prognostic models to ensure a personalised approach to prognostication and treatment.

Effects of physical exercise during pregnancy on mothers’ and neonates’ health: a protocol for an umbrella review of systematic reviews and meta-analysis of randomised controlled trials

IntroductionA growing interest has emerged on the effects of exercise during gestation. Several systematic reviews and meta-analyses have shown that prenatal exercise could reduce the mothers’ risk for some disorders....

Dietary intake and blood concentrations of antioxidants and the risk of cardiovascular disease, total cancer, and all-cause mortality: a systematic review and dose-response meta-analysis of prospective studies

ABSTRACTBackgroundHigh dietary intake or blood concentrations (as biomarkers of dietary intake) of vitamin C, carotenoids, and vitamin E have been associated with reduced risk of cardiovascular disease, cancer, and mortality, but these associations have not been systematically assessed.ObjectiveWe conducted a systematic review and meta-analysis of prospective studies of dietary intake and blood concentrations of vitamin C, carotenoids, and vitamin E in relation to these outcomes.DesignWe searched PubMed and Embase up to 14 February 2018. Summary RRs and 95% CIs were calculated with the use of random-effects models.ResultsSixty-nine prospective studies (99 publications) were included. The summary RR per 100-mg/d increment of dietary vitamin C intake was 0.88 (95% CI: 0.79, 0.98, I2 = 65%, n = 11) for coronary heart disease, 0.92 (95% CI: 0.87, 0.98, I2 = 68%, n = 12) for stroke, 0.89 (95% CI: 0.85, 0.94, I2 = 27%, n = 10) for cardiovascular disease, 0.93 (95% CI: 0.87, 0.99, I2 = 46%, n = 8) for total cancer, and 0.89 (95% CI: 0.85, 0.94, I2 = 80%, n = 14) for all-cause mortality. Corresponding RRs per 50-μmol/L increase in blood concentrations of vitamin C were 0.74 (95% CI: 0.65, 0.83, I2 = 0%, n = 4), 0.70 (95% CI: 0.61, 0.81, I2 = 0%, n = 4), 0.76 (95% CI: 0.65, 0.87, I2 = 56%, n = 6), 0.74 (95% CI: 0.66, 0.82, I2 = 0%, n = 5), and 0.72 (95% CI: 0.66, 0.79, I2 = 0%, n = 8). Dietary intake and/or blood concentrations of carotenoids (total, β-carotene, α-carotene, β-cryptoxanthin, lycopene) and α-tocopherol, but not dietary vitamin E, were similarly inversely associated with coronary heart disease, stroke, cardiovascular disease, cancer, and/or all-cause mortality.ConclusionsHigher dietary intake and/or blood concentrations of vitamin C, carotenoids, and α-tocopherol (as markers of fruit and vegetable intake) were associated with reduced risk of cardiovascular disease, total cancer, and all-cause mortality. These results support recommendations to increase fruit and vegetable intake, but not antioxidant supplement use, for chronic disease prevention.

Bayesian cure-rate survival model with spatially structured censoring

We propose a Bayesian spatial model for time-to-event data in which we allow the censoring mechanism to depend on covariates and have a spatial structure. The survival model incorporates a cure rate fraction and assumes that the time-to-event follows a Weibull distribution, with covariates such as race, stage, grade, marital status and age at diagnosis being linked to its scale parameter. With right censoring being a primary concern, we consider a joint logistic regression model for the death versus censoring indicator, allowing dependence on covariates and including a spatial structure via the use of random effects. We apply the models to examine prostate cancer data from the Surveillance, Epidemiology, and End Results (SEER) registry, which displays marked spatial variation.

Modeling Linguistic Variables With Regression Models: Addressing Non-Gaussian Distributions, Non-independent Observations, and Non-linear Predictors With Random Effects and Generalized Additive Models for Location, Scale, and Shape.

As statistical approaches are getting increasingly used in linguistics, attention must be paid to the choice of methods and algorithms used. This is especially true since they require assumptions to be satisfied to provide valid results, and because scientific articles still often fall short of reporting whether such assumptions are met. Progress is being, however, made in various directions, one of them being the introduction of techniques able to model data that cannot be properly analyzed with simpler linear regression models. We report recent advances in statistical modeling in linguistics. We first describe linear mixed-effects regression models (LMM), which address grouping of observations, and generalized linear mixed-effects models (GLMM), which offer a family of distributions for the dependent variable. Generalized additive models (GAM) are then introduced, which allow modeling non-linear parametric or non-parametric relationships between the dependent variable and the predictors. We then highlight the possibilities offered by generalized additive models for location, scale, and shape (GAMLSS). We explain how they make it possible to go beyond common distributions, such as Gaussian or Poisson, and offer the appropriate inferential framework to account for ‘difficult’ variables such as count data with strong overdispersion. We also demonstrate how they offer interesting perspectives on data when not only the mean of the dependent variable is modeled, but also its variance, skewness, and kurtosis. As an illustration, the case of phonemic inventory size is analyzed throughout the article. For over 1,500 languages, we consider as predictors the number of speakers, the distance from Africa, an estimation of the intensity of language contact, and linguistic relationships. We discuss the use of random effects to account for genealogical relationships, the choice of appropriate distributions to model count data, and non-linear relationships. Relying on GAMLSS, we assess a range of candidate distributions, including the Sichel, Delaporte, Box-Cox Green and Cole, and Box-Cox t distributions. We find that the Box-Cox t distribution, with appropriate modeling of its parameters, best fits the conditional distribution of phonemic inventory size. We finally discuss the specificities of phoneme counts, weak effects, and how GAMLSS should be considered for other linguistic variables.

Generalized Linear Mixed Models for Dependent Compound Risk Models

In ratemaking, calculation of a pure premium has traditionally been based on modeling frequency and severity in an aggregated claims model. For simplicity, it has been a standard practice to assume the independence of loss frequency and loss severity. In recent years, there is sporadic interest in the actuarial literature exploring models that departs from this independence. In this article, we extend the work of Garrido et al. (2016) which uses generalized linear models (GLMs) that account for dependence between frequency and severity and simultaneously incorporate rating factors to capture policyholder heterogeneity. In addition, we quantify and explain the contribution of the variability of claims among policyholders through the use of random effects using generalized linear mixed models (GLMMs). We calibrated our model using a portfolio of auto insurance contracts from a Singapore insurer where we observed claim counts and amounts from policyholders for a period of six years. We compared our results with the dependent GLM considered by Garrido et al. (2016), Tweedie models, and the case of independence. The dependent GLMM shows statistical evidence of positive dependence between frequency and severity. Using validation procedures, we find that the results demonstrate a more superior model when random effects are considered within a GLMM framework.

Small area estimation by multilevel models applied to the Vietnam Living Standards Surveys

This paper discusses a methodology to obtain small area estimates in the context of the Vietnam Household Living Standards Surveys (VHLSS). Focusing on the use of random effects in small area regression models, a multilevel model is proposed for small area estimation at the commune level in Vietnam which incorporates random effects at the commune, district and province levels. The model estimates the commune-level mean (logarithm of) household expenditure per capita from a set of independent variables which are available both in the 1999 Census and in the VHLSS of 2002. Following ideas given in work by Moura [4,5], the small area estimation for VHLSS communes is performed by plugging the population means of the independent variables into the regression equation, inclusive of suitable random effects both in the intercept and in the coefficient of the dummy variable for the urban location of a household. The small area estimation for non-VHLSS communes is calculated in the same way, with random effects estimated by averaging random effects of nearest VHLSS communes. We also mention how to measure the accuracy of our small area estimators, and find that including random effects in the model clearly improves the accuracy of the small area estimation. A useful by-product of the analysis is the generation of Location Impact Factors (LIF), which yield a measure of the effect of geographical location when covariates such as education of head of household or household size have been accounted for. To the best of our knowledge, the idea of using LIF measures along with small area estimates for poverty targeting is novel.

Association of Microvascular Dysfunction With Late-Life Depression

ImportanceThe etiologic factors of late-life depression are still poorly understood. Recent evidence suggests that microvascular dysfunction is associated with depression, which may have implications for prevention and treatment. However, this association has not been systematically reviewed.ObjectiveTo examine the associations of peripheral and cerebral microvascular dysfunction with late-life depression.Data SourcesA systematic literature search was conducted in MEDLINE and EMBASE for and longitudinal studies published since inception to October 16, 2016, that assessed the associations between microvascular dysfunction and depression.Study SelectionThree independent researchers performed the study selection based on consensus. Inclusion criteria were a study population 40 years of age or older, a validated method of detecting depression, and validated measures of microvascular function.Data Extraction and SynthesisThis systematic review and meta-analysis has been registered at PROSPERO (CRD42016049158) and is reported in accordance with the PRISMA and MOOSE guidelines. Data extraction was performed by an independent researcher.Main Outcomes and MeasuresThe following 5 estimates of microvascular dysfunction were considered in participants with or without depression: plasma markers of endothelial function, albuminuria, measurements of skin and muscle microcirculation, retinal arteriolar and venular diameter, and markers for cerebral small vessel disease. Data are reported as pooled odds ratios (ORs) by use of the generic inverse variance method with the use of random-effects models.ResultsA total of 712 studies were identified; 48 were included in the meta-analysis, of which 8 described longitudinal data. Data from 43 600 participants, 9203 individuals with depression, and 72 441 person-years (mean follow-up, 3.7 years) were available. Higher levels of plasma endothelial biomarkers (soluble intercellular adhesion molecule–1: OR, 1.58; 95% CI, 1.28-1.96), white matter hyperintensities (OR, 1.29; 95% CI, 1.19-1.39), cerebral microbleeds (OR, 1.18; 95% CI, 1.03-1.34), and cerebral (micro)infarctions (OR, 1.30; 95% CI, 1.21-1.39) were associated with depression. Among the studies available, no significant associations of albuminuria and retinal vessel diameters with depression were reported. Longitudinal data showed a significant association of white matter hyperintensities with incident depression (OR, 1.19; 95% CI, 1.09-1.30).Conclusions and RelevanceThis meta-analysis shows that both the peripheral and cerebral forms of microvascular dysfunction are associated with higher odds of (incident) late-life depression. This finding may have clinical implications because microvascular dysfunction might provide a potential target for the prevention and treatment of depression.

A systematic review and meta-analysis of in situ versus composite bilateral internal thoracic artery grafting

ObjectivesThis meta-analysis examines whether there is any advantage of coronary artery bypass graft with bilateral internal thoracic artery (BITA) as an in situ versus composite graft. MethodsWe searched MEDLINE and EMBASE Databases from 1996 to 2016 for studies that compared coronary artery bypass graft with BITA as in situ versus composite graft. Data were extracted by 2 independent investigators and meta-analyzed with the use of random effects. ResultsTwo randomized controlled trials (RCTs; n = 705), 2 matched (n = 1688), and 4 unadjusted observational studies (n = 3517) met inclusion criteria. Composite grafting trended towards greater distal anastomoses (+0.22, 95% confidence interval, −0.01 to +0.45 anastomoses/patient; P = .06 [4 unadjusted observational studies]) and greater distal anastomoses using an internal thoracic artery (+0.80, 95% confidence interval, 0.41-1.18 anastomoses/patient; P < .001 [1 RCT]). There were no differences in perioperative or longer-term composite cardiovascular outcomes comparing in situ versus composite BITA or individual outcomes of mortality, repeat revascularization, myocardial infarction, and cardiovascular mortality. Pooled results differed by study type with pooled results from lower-risk-of-bias RCTs typically showing increases in events rates, and pooled results from higher-risk-of-bias unadjusted observational studies typically showing decreases in event rates of in situ versus composite BITA. Post hoc subgroup analysis suggested possible improvements in all-cause mortality and revascularization for in situ BITA in studies with short-term (<5 years) versus longer-term follow-up, regardless of study type. ConclusionsOur meta-analysis found that use of BITA as a composite graft configuration facilitated greater internal thoracic artery revascularization but both grafting strategies offer similar clinical outcomes. Our study supports the use of in situ and composite BITA for select patients but high-quality, long-term prospective trials are needed.

Knowledge will set you free

Purpose– The purpose of this paper is to combine notions from the POST Model of Economic Geography and Learning Theory from International Business to study how firms may enhance their responsiveness to institutional processes and changes through different forms of international learning. Focussing on one form of institutional changes, namely pro-market reforms, the paper analyzes how firms may boost the potential benefits from such changes through international strategies that increase their access to knowledge spillovers and absorptive capacity. These strategies include international product diversification, enhancing innovation capabilities, informal institutional exposure, accumulated internationalization knowledge, and overall experiential knowledge.Design/methodology/approach– The hypotheses are tested using generalized least squares models with AR(1) panel-specific autocorrelation and heteroskedasticity correction. Based on the preliminary analyses performed in these studies, the author also executes a Hausman test, Bartlett’s test, and James/Alexander’s test. The results of these analyses indicate that the use of random effects is appropriate; that moderating effects are present; and that multivariate analyses using these moderators are suitable, respectively.Findings– The results indicate that pro-market reforms have a positive and significant effect on the profitability of firms from developing countries. Furthermore, they provide support for the positive moderating effects of international product diversification, innovation capabilities, informal institutional exposure, accumulated internationalization knowledge, and overall experiential knowledge. Together, these findings suggest that through their international strategic decisions, MNEs can enhance their access to knowledge and become more responsive to institutional changes in their home market.Research limitations/implications– This paper contributes to the economic geography literature by linking the POST Model with the classification of types of knowledge from Learning Theory. The paper analyzes how characteristics of place, organization, space, and time play a different role for each of the three basic types of knowledge that is relevant for international firms: institutional, business, and internationalization. Furthermore, the paper contributes to the literature on reforms and firm profitability by delving deeper into the moderating effect of strategic decisions on the relationship between reforms and firm performance. This allows us to have a deeper comprehension of how various sources of international learning may enhance the responsiveness of firms to institutional changes.Originality/value– The paper provides several important contributions to the international strategy literature. First, it contributes to Learning Theory by combining it with the POST Model of Economic Geography to study how each of the three sources of knowledge (and their subcomponents) can be further broken down into factors of place, organization, space, and time. Second, it contributes to the literature of institutional change by studying how knowledge acquired through vastly different means can provide firms with sources of competitive advantage over other local competitors when responding to institutional changes in their home market. Third, it contributes to the literature on reforms and profitability by studying five novel moderators of this relationship.