Systematic review and meta-analysis of evidence for increasing numbers of drugs in antiretroviral combination therapy

Objective: To assess the evidence for the effectiveness of increasing numbers of drugs in antiretroviral combination therapy.

Design: Systematic review, meta-analysis, and meta-regression of fully reported randomised controlled trials. All studies included compared quadruple versus triple therapy, triple versus double therapy, double versus monotherapy, or monotherapy versus placebo or no treatment.

Participants: Patients with any stage of HIV infection who had not received antiretroviral therapy.

Main outcome measures: Changes in disease progression or death (clinical outcomes); CD4 count and plasma viral load (surrogate markers).
Search strategy: Six electronic databases, including Medline, Embase, and the Cochrane Library, searched up to February 2001.

Results: 54 randomised controlled trials, most of good quality, with 66 comparison groups were included in the analysis. For both the clinical outcomes and surrogate markers, combinations with up to and including three (triple therapy) were progressively and significantly more effective. The odds ratio for disease progression or death for triple therapy compared with double therapy was 0.6 (95% confidence interval 0.5 to 0.8). Heterogeneity in effect sizes was present in many outcomes but was largely related to the drugs used and trial quality.

Conclusions: Evidence from randomised controlled trials supports the use of triple therapy. Research is needed on the effectiveness of quadruple therapies and the relative effectiveness of specific combinations of drugs.

Use of calcium or calcuim in combination with vitamin D supplementation to prevent fractures and bone loss in people aged 50 years and older: a meta-analysis

Background:  Whether calcium supplementation can reduce osteoporotic fractures is uncertain. We did a meta-analysis to include all the randomised trials in which calcium, or calcium in combination with vitamin D, was used to prevent fracture and osteoporotic bone loss.

Methods:  We identified 29 randomised trials (n=63 897) using electronic databases, supplemented by a hand-search of reference lists, review articles, and conference abstracts. All randomised trials that recruited people aged 50 years or older were eligible. The main outcomes were fractures of all types and percentage change of bone-mineral density from baseline. Data were pooled by use of a random-effect model.

Findings:  In trials that reported fracture as an outcome (17 trials, n=52 625), treatment was associated with a 12% risk reduction in fractures of all types (risk ratio 0·88, 95% CI 0·83–0·95; p=0·0004). In trials that reported bone-mineral density as an outcome (23 trials, n=41 419), the treatment was associated with a reduced rate of bone loss of 0·54% (0·35–0·73; p<0·0001) at the hip and 1·19% (0·76–1·61%; p<0·0001) in the spine. The fracture risk reduction was significantly greater (24%) in trials in which the compliance rate was high (p<0·0001). The treatment effect was better with calcium doses of 1200 mg or more than with doses less than 1200 mg (0·80 vs 0·94; p=0·006), and with vitamin D doses of 800 IU or more than with doses less than 800 IU (0·84 vs 0·87; p=0·03).

Interpretation:  Evidence supports the use of calcium, or calcium in combination with vitamin D supplementation, in the preventive treatment of osteoporosis in people aged 50 years or older. For best therapeutic effect, we recommend minimum doses of 1200 mg of calcium, and 800 IU of vitamin D (for combined calcium plus vitamin D supplementation).

Increased consumption of fruit and vegetables is related to a reduced risk of coronary heart disease: meta-analysis of cohort studies

Increased consumption of fruit and vegetables has been shown to be associated with a reduced risk of coronary heart disease (CHD) in many epidemiological studies, however, the extent of the association is uncertain. We quantitatively assessed the relation between fruit and vegetable intake and incidence of CHD by carrying out a meta-analysis of cohort studies. Studies were included if they reported relative risks (RRs) and corresponding 95% confidence interval (CI) of CHD with respect to frequency of fruit and vegetable intake. Twelve studies, consisting of 13 independent cohorts, met the inclusion criteria. There were 278 459 individuals (9143 CHD events) with a median follow-up of 11 years. Compared with individuals who had less than 3 servings/day of fruit and vegetables, the pooled RR of CHD was 0.93 (95% CI: 0.86–1.00, P=0.06) for those with 3–5 servings/day and 0.83 (0.77–0.89, P<0.0001) for those with more than 5 servings/day. Subgroup analyses showed that both fruits and vegetables had a significant protective effect on CHD. Our meta-analysis of prospective cohort studies demonstrates that increased consumption of fruit and vegetables from less than 3 to more than 5 servings/day is related to a 17% reduction in CHD risk, whereas increased intake to 3–5 servings/day is associated with a smaller and borderline significant reduction in CHD risk. These results provide strong support for the recommendations to consume more than 5 servings/day of fruit and vegetables.

Women exposed to intimate partner violence : expectations and experiences when they encounter health care professionals : a meta-analysis of qualitative studies

Background The appropriate response of health care professionals to intimate partner violence is still a matter of debate. This article reports a meta-analysis of qualitative studies that answers 2 questions: (1) How do women with histories of intimate partner violence perceive the responses of health care professionals? and (2) How do women with histories of intimate partner violence want their health care providers to respond to disclosures of abuse?

Methods Multiple databases were searched from their start to July 1, 2004. Searches were complemented with citation tracking and contact with researchers. Inclusion criteria included a qualitative design, women 15 years or older with experience of intimate partner violence, and English language. Two reviewers independently applied criteria and extracted data. Findings from the primary studies were combined using a qualitative meta-analysis.

Results Twenty-nine articles reporting 25 studies (847 participants) were included. The emerging constructs were largely consistent across studies and did not vary by study quality. We ordered constructs by the temporal structure of consultations with health care professionals: before the abuse is discussed, at disclosure, and the immediate and further responses of the health care professional. Key constructs included a wish from women for responses from health care professionals that were nonjudgmental, nondirective, and individually tailored, with an appreciation of the complexity of partner violence. Repeated inquiry about partner violence was seen as appropriate by women who were at later stages of an abusive relationship.

Conclusion Women’s perceptions of appropriate and inappropriate responses partly depended on the context of the consultation, their own readiness to address the issue, and the nature of the relationship between the woman and the health care professional.

A meta-learning approach to automatic kernel selection for support vector machines

Appropriate choice of a kernel is the most important ingredient of the kernel-based learning methods such as support vector machine (SVM). Automatic kernel selection is a key issue given the number of kernels available, and the current trial-and-error nature of selecting the best kernel for a given problem. This paper introduces a new method for automatic kernel selection, with empirical results based on classification. The empirical study has been conducted among five kernels with 112 different classification problems, using the popular kernel based statistical learning algorithm SVM. We evaluate the kernels’ performance in terms of accuracy measures. We then focus on answering the question: which kernel is best suited to which type of classification problem? Our meta-learning methodology involves measuring the problem characteristics using classical, distance and distribution-based statistical information. We then combine these measures with the empirical results to present a rule-based method to select the most appropriate kernel for a classification problem. The rules are generated by the decision tree algorithm C5.0 and are evaluated with 10 fold cross validation. All generated rules offer high accuracy ratings.

Towards universal and statistical-driven heuristics for automatic classification of sports video events

Researchers worldwide have been actively seeking for the most robust and powerful solutions to detect and classify key events (or highlights) in various sports domains. Most approaches have employed manual heuristics that model the typical pattern of audio-visual features within particular sport events To avoid manual observation and knowledge, machine-learning can be used as an alternative approach. To bridge the gaps between these two alternatives, an attempt is made to integrate statistics into heuristic models during highlight detection in our investigation. The models can be designed with a modest amount of domain-knowledge, making them less subjective and more robust for different sports. We have also successfully used a universal scope of detection and a standard set of features that can be applied for different sports that include soccer, basketball and Australian football. An experiment on a large dataset of sport videos, with a total of around 15 hours, has demonstrated the effectiveness and robustness of our
aIlgorithms.

Using decision-tree to automatically construct learned-heuristics for events classification in sports video

Automatic events classification is an essential requirement for constructing an effective sports video summary. It has become a well-known theory that the high-level semantics in sport video can be “computationally interpreted” based on the occurrences of specific audio and visual features which can be extracted automatically. State-of-the-art solutions for features-based event classification have only relied on either manual-knowledge based heuristics or machine learning. To bridge the gaps, we have successfully combined the two approaches by using learning-based heuristics. The heuristics are constructed automatically using decision tree while manual supervision is only required to check the features and highlight contained in each training segment. Thus, fully automated construction of classification system for sports video events has been achieved. A comprehensive experiment on 10 hours video dataset, with five full-match soccer and five full-match basketball videos, has demonstrated the effectiveness/robustness of our algorithms.

Democracy and economic growth : a meta-analysis

Despite a sizeable theoretical and empirical literature, no firm conclusions have been drawn regarding the impact of political democracy on economic growth. This article challenges the consensus of an inconclusive relationship through a quantitative assessment of the democracy-growth literature. It applies meta-regression analysis to the population of 483 estimates derived from 84 studies on democracy and growth. Using traditional meta-analysis estimators, the bootstrap, and Fixed and Random Effects meta-regression models, it derives several robust conclusions. Taking all the available published evidence together, it concludes that democracy does not have a direct impact on economic growth. However, democracy has robust, significant, and positive indirect effects through higher human capital, lower inflation, lower political instability, and higher levels of economic freedom. Democracies may also be associated with larger governments and less free international trade. There also appear to be country- and region-specific democracy-growth effects. Overall, democracy's net effect on the economy does not seem to be detrimental.

Aid effectiveness on growth : a meta study

The aid effectiveness literature contains about 100 papers that see aid as a treatment given to poor countries to generate development. 68 of these papers provide a total of 543 comparable estimates of the effect of aid on growth, which are the data of our meta-analysis. We consider two questions: (Q1) Are the estimates converging to a clear result over time as aid agencies gain experience, models become better and data accumulates? We find that the results do have a positive average, but it is small, insignificant and falling. (Q2) Can we identify the main factors that explain the large differences in the results? We find that much of the variation between studies can be attributed to publication outlet, institutional affiliation, data and specification differences. However, some of the difference between studies is real. In particular, the aid-growth effect is stronger for Asian countries. The meta-analysis indicates also the existence of indirect channels, which need to be further explored.

Preventing the onset of depressive disorders : a meta-analytic review of psychological interventions

OBJECTIVE: A growing number of studies have tested the efficacy of preventive interventions in reducing the incidence of depressive disorders. Until now, no meta-analysis has integrated the results of these studies. METHOD: The authors conducted a meta-analysis. After a comprehensive literature search, 19 studies were identified that met inclusion criteria. The studies had to be randomized controlled studies in which the incidence of depressive disorders (based on diagnostic criteria) in an experimental group could be compared with that of a control group. RESULTS: The mean incidence rate ratio was 0.78, indicating a reduction of the incidence of depressive disorders by 22% in experimental compared with control groups. Heterogeneity was low to moderate (I²=33%). The number needed to treat to prevent one case of depressive disorder was 22. Moderator analyses revealed no systematic differences between target populations or types of prevention (universal, selective, or indicated). The data included indications that prevention based on interpersonal psychotherapy may be more effective than prevention based on cognitive-behavioral therapy. CONCLUSIONS: Prevention of new cases of depressive disorders does seem to be possible. Prevention may become an important way, in addition to treatment, to reduce the enormous public health burden of depression in the coming years.

Performance modeling and analysis of heterogeneous meta-computing systems interconnection networks

The overall performance of a distributed system often depends on the effectiveness of its interconnection network. Thus, the study of the communication networks for distributed systems is very important, which is the focus of this paper. In particular, we address the problem of interconnection networks performance modeling for heterogeneous meta-computing systems. We consider the meta-computing system as a typical multi-cluster system. Since the heterogeneity is becoming common in such systems, we take into account network as well as cluster size heterogeneity to propose the model. To this end, we present an analytical network model and validate the model through comprehensive simulation. The results of the simulation demonstrated that the proposed model exhibits a good degree of accuracy for various system organizations and under different working conditions.

Publication selection bias in minimum-wage research? A meta-regression analysis

Card and Krueger's meta-analysis of the employment effects of minimum wages challenged existing theory. Unfortunately, their meta-analysis confused publication selection with the absence of a genuine empirical effect. We apply recently developed meta-analysis methods to 64 US minimum-wage studies and corroborate that Card and Krueger's findings were nevertheless correct. The minimum-wage effects literature is contaminated by publication selection bias, which we estimate to be slightly larger than the average reported minimum-wage effect. Once this publication selection is corrected, little or no evidence of a negative association between minimum wages and employment remains.