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Record W2035835116 · doi:10.1097/aog.0b013e3181888fd8

Mode of Delivery: Toward Responsible Inclusion of Patient Preferences

2008· article· en· W2035835116 on OpenAlexaff
Margaret Olivia Little, Anne Drapkin Lyerly, Lisa M. Mitchell, Elizabeth Armstrong, Lisa H. Harris, Rebecca Kukla, Miriam Kuppermann

Bibliographic record

VenueObstetrics and Gynecology · 2008
Typearticle
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsUniversity of Victoria
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Heart, Lung, and Blood Institute
KeywordsMedicineInclusion (mineral)Mode (computer interface)Social psychologyHuman–computer interaction

Abstract

fetched live from OpenAlex

Deciding when and how to incorporate patient preferences regarding mode of delivery is challenging for both obstetric providers and policymakers. An analysis of current guidelines in four clinical scenarios (prior cesarean, twin delivery, breech presentation, and maternal request for cesarean) indicates that some guidelines are highly prescriptive whereas others are more flexible, based on physicians' discretion or (less frequently) patient preferences, without consistency or explicit rationale for when such flexibility is permissible, advisable, or obligatory. Although patient-choice advocates have called for more patient-responsive guidelines, concerns also have been raised, especially in the context of discussions of cesarean delivery on maternal request, about the dangers of unfettered patient-preference-driven clinical decisions. In this article, we outline a framework for the responsible inclusion of patient preferences into decision making regarding approach to delivery. We conclude, using this framework, that more explicit incorporation of patient preferences is called for in the first three scenarios and indicate why expanding access to cesarean delivery on maternal request is more complicated and would require more data and further consideration.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.422
Threshold uncertainty score0.223

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.042
GPT teacher head0.313
Teacher spread0.271 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations67
Published2008
Admission routes1
Has abstractyes

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