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Record W4408279246 · doi:10.1080/09540121.2025.2475210

Success rates of endodontic treatment in HIV positive (HIV +) and non-HIV patients - a systematic review

2025· review· en· W4408279246 on OpenAlexaboutno aff
Samantha Rodrigues Xavier, Caroline Fernandes e Silva, Wellington Luiz de Oliveira da Rosa, Fábio de Almeida Gomes, Fernanda Geraldo Pappen, Natália Marcumini Pola

Bibliographic record

VenueAIDS Care · 2025
Typereview
Languageen
FieldDentistry
TopicEndodontics and Root Canal Treatments
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsHuman immunodeficiency virus (HIV)MedicineDentistryPsychologyFamily medicine

Abstract

fetched live from OpenAlex

This systematic review assessed the success rates of endodontic treatment in HIV-positive (HIV+) patients. Registered in PROSPERO (CRD42020216495), the study addressed whether success rates differ between HIV+ and non-HIV patients. Two reviewers searched Medline-PubMed, Scopus, Web of Science, EMBASE, and Lilacs. Eligibility criteria included studies evaluating primary endodontic treatment success with at least 12 months of follow-up. Risk of bias was assessed using the Newcastle-Ottawa scale, and evidence certainty was measured with the GRADE approach. From 252 studies, four case-control studies (282 individuals) met the criteria. Three studies focused on teeth with pulp necrosis and chronic apical periodontitis, while one included pulp necrosis and irreversible pulpitis. The success rate was 89.67% for HIV+ patients and 94.13% for non-HIV patients, with no significant differences between groups. The evidence had a very low certainty level. Findings suggest similar endodontic treatment success rates in HIV+ and non-HIV individuals, but the low certainty of evidence must be considered.Registration number PROSPERO - CRD42020216495

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)0.010
metaresearch head score (Gemma)0.050
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.050
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0100.008
Bibliometrics0.0090.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.016
GPT teacher head0.331
Teacher spread0.315 · 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 designSystematic review
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

Citations0
Published2025
Admission routes1
Has abstractyes

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