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Record W4305014665 · doi:10.1016/j.sexol.2022.08.001

Association between tampons and toxic shock syndrome in menstruating women: A systematic review and meta-analysis

2022· review· en· W4305014665 on OpenAlexaboutno aff
Helen Johana Ortiz-Rojas, Herney Andrés García‐Perdomo

Bibliographic record

VenueSexologies · 2022
Typereview
Languageen
FieldMedicine
TopicEctopic Pregnancy Diagnosis and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMeta-analysisMedicineRelative riskMEDLINEGynecologyInternal medicineConfidence interval

Abstract

fetched live from OpenAlex

Objective To determine the association between tampons and toxic shock syndrome (TSS) in menstruating women. Materials and methods We found only case and control Studies. We conducted a search strategy on each of the following databases: MEDLINE through Ovid, EMBASE, Cochrane Controlled Trials Register Center (CENTRAL), and LILACS. Then, we extracted data and assessed the risk of bias by the Newcastle-Ottawa Quality Assessment Scale. We also performed a meta-analysis of the included studies. Results Of 90 studies evaluated, after debugging the information, six studies were selected, which fulfilled the inclusion criteria. Findings in the meta-analysis show that the global estimate of the OR = 19.60; (95% CI: 8.31–46.24) indicates a conclusive significant effect in using tampons as a risk factor in TSS. The study presented a low level of heterogeneity (I 2 = 0%). Also, all studies showed a score greater than three, representing a low risk of bias. Conclusion Tampons use is considered a risk factor for Toxic Shock Syndrome.

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)0.008
metaresearch head score (Gemma)0.020
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.020
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0170.023
Bibliometrics0.0070.008
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.140
GPT teacher head0.364
Teacher spread0.224 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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