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Bayesian diagnostic meta-analysis dataset of pelvic examination in pelvic inflammatory disease

Citation

Iwata, Hiroyoshi (2020), Bayesian diagnostic meta-analysis dataset of pelvic examination in pelvic inflammatory disease , Dryad, Dataset, https://doi.org/10.5061/dryad.7d7wm37sv

Abstract

Pelvic inflammatory disease (PID) is not merely a transient sexually transmitted disease. It can lead to chronic pain, ectopic pregnancy, and infertility. Although the Centers for Disease Control and Prevention have established minimum diagnostic criteria, including pelvic examination, the diagnostic value of pelvic tenderness has recently garnered controversy. Our meta-analysis aimed to confirm whether pelvic examination can help diagnose PID among at-risk women.

Design

A Bayesian meta-analysis of studies reporting diagnostic data of patients at risk for PID.

Setting

We searched MEDLINE, EMBASE, CENTRAL, CINAHL, Google, and Google Scholar for eligible articles. 

Participants

Female patients at risk for PID.

Main results

The literature search produced 5,395 articles. After quality assessment, 16 studies and their 4,083 participants were eligible for synthesis on pelvic tenderness.

Methods

We performed a literature search with MEDLINE (PubMed), EMBASE, CINAHL, and CENTRAL on 17 April 2019, followed by a manual search using Google and Google Scholar. This study was created following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) statement and its flow chart. Studies with inappropriate reference standards, review studies, letters, editorials, gray literature, duplicate or series publications, and non-human studies were excluded. Study participants were outpatients, inpatients, and emergency patients suspected of PID.  Two independent teams performed the screening.

 

Funding

The Jikei University Research Fund for Graduate Students, Award: 2019-02

The Jikei University Research Fund for Graduate Students, Award: 2019-02