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Record W4313478243 · doi:10.1016/j.xagr.2022.100152

Measuring enhanced recovery in obstetrics: a narrative review

2022· review· en· W4313478243 on OpenAlexaff
Sarah Ciechanowicz, Janny Xue Chen Ke, Nadir Sharawi, Pervez Sultan

Bibliographic record

VenueAJOG Global Reports · 2022
Typereview
Languageen
FieldMedicine
TopicEnhanced Recovery After Surgery
Canadian institutionsProvidence Health CareUniversity of British ColumbiaDalhousie UniversitySt. Paul's Hospital
Fundersnot available
KeywordsMedicinePatient satisfactionBreastfeedingVaginal deliveryObstetricsPregnancyIntensive care medicineNursingPediatrics

Abstract

fetched live from OpenAlex

Enhanced recovery after cesarean delivery is a protocolized approach to perioperative care, with the aim to optimize maternal recovery after surgery. It is associated with improved maternal and neonatal outcomes, including decreased length of hospital stay, opioid consumption, pain scores, complications, increased maternal satisfaction, and increased breastfeeding success. However, the pace and enthusiasm of adoption of enhanced recovery after cesarean delivery internationally has not yet been matched with high-quality evidence demonstrating its benefit, and current studies provide low- to very low-quality evidence in support of enhanced recovery after cesarean delivery. This article provides a summary of current measures of enhanced recovery after cesarean delivery success, and optimal measures of inpatient and outpatient postpartum recovery. We summarize outcomes from 22 published enhanced recovery after cesarean delivery implementation studies and 2 meta-analyses. A variety of disparate metrics have been used to measure enhanced recovery after cesarean delivery success, including process measures (length of hospital stay, bundle compliance, preoperative fasting time, time to first mobilization, time to urinary catheter removal), maternal outcomes (patient-reported outcome measures, complications, opioid consumption, satisfaction), neonatal outcomes (breastfeeding success, Apgar scores, maternal-neonatal bonding), cost savings, and complication rates (maternal readmission rate, urinary recatheterization rate, neonatal readmission rate). A core outcome set for use in enhanced recovery after cesarean delivery studies has been developed through Delphi consensus, involving stakeholders including obstetricians, anesthesiologists, patients, and a midwife. Fifteen measures covering key aspects of enhanced recovery after cesarean delivery adoption are recommended for use in future enhanced recovery after cesarean delivery implementation studies. The use of these outcome measures could improve the quality of evidence surrounding enhanced recovery after cesarean delivery. Using evidence-based evaluation guidelines developed by the COSMIN (COnsensus-based Standards for the selection of health Measurement INstruments) group, the Obstetric Quality of Recovery score (ObsQoR) was identified as the best patient-reported outcome measure for inpatient postpartum recovery. Advances in our understanding of postpartum recovery as a multidimensional and dynamic construct have opened new avenues for the identification of optimum patient-reported outcome measures in this context. The use of standardized measures such as these will facilitate pooling of data in future studies and improve overall levels of evidence surrounding enhanced recovery after cesarean delivery. Larger studies with optimal study designs, using recommended outcomes including patient-reported outcome measures, will reduce variation and improve data quality to help guide future recommendations.

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)0.002
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.919
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.075
GPT teacher head0.349
Teacher spread0.274 · 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 designOther design
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

Citations22
Published2022
Admission routes1
Has abstractyes

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