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Record W4389515622 · doi:10.1016/j.xagr.2023.100296

Asian-White disparities in obstetric anal sphincter injury: a systematic review and meta-analysis

2023· review· en· W4389515622 on OpenAlexaffabout
Meejin Park, Susitha Wanigaratne, Rohan D’Souza, Roxana Geoffrion, Sarah Williams, Giulia M. Muraca

Bibliographic record

VenueAJOG Global Reports · 2023
Typereview
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsImpactHamilton Health SciencesSickKids FoundationMcMaster UniversityUniversity of British ColumbiaHospital for Sick Children
Fundersnot available
KeywordsMedicineOdds ratioObservational studyMeta-analysisSubgroup analysisCochrane LibraryDemographyObstetricsInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Obstetrical anal sphincter injury describes a severe injury to the perineum and perianal muscles after birth. Obstetrical anal sphincter injury occurs in approximately 4.4% of vaginal births in the United States; however, racial and ethnic inequities in the incidence of obstetrical anal sphincter injury have been shown in several high-income countries. Specifically, an increased risk of obstetrical anal sphincter injury in individuals who identify as Asian vs those who identify as White has been documented among residents of the United States, Australia, Canada, Western Europe, and the Scandinavian countries. The high rates of obstetrical anal sphincter injury among the Asian diaspora in these countries are higher than obstetrical anal sphincter injury rates reported among Asian populations residing in Asia. A systematic review and meta-analysis of studies in high-income, non-Asian countries was conducted to further evaluate this relationship. DATA SOURCES: MEDLINE, Ovid, Embase, EmCare, and the Cochrane databases were searched from inception to March 2023 for original research studies. STUDY ELIGIBILITY CRITERIA: Observational studies using keywords and controlled vocabulary terms related to race, ethnicity and obstetrical anal sphincter injury. All observational studies, including cross-sectional, case-control, and cohort were included. 2 reviewers followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and the Meta-analysis of Observational Studies in Epidemiology recommendations. METHODS: Meta-analysis was performed using RevMan (version 5.4; Cochrane Collaboration, London, United Kingdom) for dichotomous data using the random effects model and the odds ratios as effect measures with 95% confidence intervals. Subgroup analysis was performed among Asian subgroups. The risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal tools. Meta-regression was used to determine sources of between-study heterogeneity. Results: A total of 27 studies conducted in 7 countries met the inclusion criteria encompassing 2,337,803 individuals. The pooled incidence of obstetrical anal sphincter injury was higher among Asian individuals than White individuals (pooled odds ratio, 1.64; 95% confidence interval, 1.48-1.80). Subgroup analyses showed that obstetrical anal sphincter injury rates were highest among South Asians and among population-based vs hospital-based studies. Meta-regression showed that moderate heterogeneity remained even after accounting for differences in studies by types of Asian subgroups included, study year, mode of delivery included, and study setting. Conclusion: Obstetrical anal sphincter injury is more frequent among Asian versus white birthing individuals in multiple high-income, non-Asian countries. Qualitative and quantitative research to elucidate underlying causal mechanisms responsible for this relationship are warranted.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.738
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0170.004
Bibliometrics0.0010.006
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.068
GPT teacher head0.375
Teacher spread0.307 · 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 teacher head, not a consensus.

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

Citations6
Published2023
Admission routes2
Has abstractyes

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