Obstetrical Anal Sphincter Injuries and the Need for Adequate Care
Bibliographic record
Abstract
BACKGROUND: An estimated 4% to 6.6% of women delivering vaginally sustain obstetrical anal sphincter injuries (OASI). Despite this, a gap exists in the provision of postpartum care to women globally. Given the negative impact of OASI, action is needed, and multidisciplinary perineal clinics can help. Consequently, such a clinic was established in 2011 at the Royal Alexandra Hospital (RAH), a tertiary care center in Edmonton, Alberta. OBJECTIVE: This study assesses the state of perineal clinics specializing in OASI internationally and locally by investigating the literature for descriptions of specialized perineal clinics for women with OASI, describing the RAH perineal clinic, and assessing the prevalence of OASI at the RAH in the context of the clinic. METHODS: A search of peer-reviewed literature was conducted on Medline and observations and interviews of RAH perineal clinic staff were conducted, as was a medical chart review. RESULTS: Articles describing only 10 perineal clinics specializing in OASI were found, with varying structures. The multidisciplinary RAH clinic, like one other clinic, has a strong physiotherapy focus, with education and Pilates classes and one-on-one appointments offered by pelvic floor physiotherapists. In 2016, of the 326 (6.9%) vaginal deliveries that resulted in OASI at the RAH, only 66.0% (215) were referred to the clinic. CONCLUSIONS: Multidisciplinary perineal clinics are needed globally. Despite the creation of the perineal clinic at the RAH, women continue to lack specialized care after OASI. It is crucial that healthcare professionals specializing in OASI share their experiences to establish best practices and create new, and improve existing, perineal clinics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".