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Male circumcision for the prevention of heterosexually acquired HIV infection: a meta‐analysis of randomized trials involving 11 050 men<sup>*</sup>

2008· review· en· W2066902718 on OpenAlexaff
Edward J. Mills, Curtis Cooper, Aranka Anema, Gordon Guyatt

Bibliographic record

VenueHIV Medicine · 2008
Typereview
Languageen
FieldMedicine
TopicGenital Health and Disease
Canadian institutionsMcMaster UniversityOttawa HospitalUniversity of OttawaAIDS VancouverSt. Paul's Hospital
Fundersnot available
KeywordsMedicineMeta-analysisRandomized controlled trialRelative riskObservational studyConfidence intervalPopulationHuman immunodeficiency virus (HIV)DemographyMale circumcisionGynecologyInternal medicineFamily medicineEnvironmental healthHealth services

Abstract

fetched live from OpenAlex

OBJECTIVES: Observational studies and a small collection of randomized controlled trials (RCTs) suggest that male circumcision may significantly reduce HIV transmission between sero-discordant contacts. The Joint United Nations Programme on HIV/AIDS (UNAIDS) and World Health Organization have recently announced recommendations to scale up male circumcision in countries with generalized epidemics and low levels of male circumcision. However, no meta-analysis has been conducted to determine the effectiveness of this intervention. METHODS: We conducted a systematic review of medical literature, and included any RCTs assessing male circumcision to prevent heterosexually acquired HIV infection among males. We used the DerSimonian-Laird random effects method to pool study outcomes. We calculated the relative risk (RR), risk difference, number needed to treat (NNT) and I(2), all with 95% confidence intervals (CIs). RESULTS: We identified three RCTs that met our inclusion criteria, involving a total of 11 050 men. The pooled RR was 0.44 (95% CI 0.33-0.60, P<0.0001, I(2)=0%, 95% CI 0-35%). The risk difference was 0.014 (95% CI 0.07-0.21), yielding a NNT of 72 (95% CI 50-143). CONCLUSIONS: Male circumcision is an effective strategy for reducing new male HIV infections. Its impact on a population level will require consistently safe sexual practices to maintain the protective benefit.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.024
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.024
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.041
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0170.050
Bibliometrics0.0050.004
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.235
GPT teacher head0.438
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations111
Published2008
Admission routes1
Has abstractyes

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