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Record W4403505229 · doi:10.1177/1753495x241290681

Patient-reported outcomes in research on critically ill obstetric patients

2024· article· en· W4403505229 on OpenAlexaffabout
Julien Viau-Lapointe, Clara Juandó‐Prats, Roberto Zapata, Julia Kfouri, Joyamor Ortuno-Nacho, Rizwana Ashraf, Rohan D’Souza, José Rojas‐Suarez, Stephen E. Lapinsky

Bibliographic record

VenueObstetric Medicine · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsImpactMcMaster UniversityMount Sinai HospitalUniversité de MontréalHôpital Maisonneuve-RosemontPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsMedicineCritically illIntensive care medicineEmergency medicine

Abstract

fetched live from OpenAlex

Background Research benefits from the incorporation of patient-important outcomes. We interviewed individuals after a critical illness during pregnancy to identify outcomes for the development of a core outcome set (COS). Methods Participants were identified through intensive care unit (ICU) admissions in Toronto, Canada, and Barranquilla, Colombia. Interviewers used a semi-structured guide, and discussions were recorded and transcribed. Transcripts underwent inductive thematic analysis to delineate themes and patient-important outcomes. Results Twelve individuals were interviewed. Twenty-six patient-important outcomes were elicited, which represented the core outcome areas of mortality ( n = 1), physiological/clinical outcomes ( n = 7), functioning and life impact ( n = 13), resource use ( n = 4) and adverse events ( n = 1). These related to five identified themes of mental well-being, quality of care delivered, clinicians’ communication, regaining functional independence and mother–newborn separation. Conclusions This qualitative study identified patient-important outcomes from persons with lived experience of critical illness in pregnancy which will inform the development of a COS.

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)0.005
metaresearch head score (Gemma)0.154
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.577
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.154
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.011
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.245
GPT teacher head0.514
Teacher spread0.269 · 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 designNot applicable
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

Citations4
Published2024
Admission routes2
Has abstractyes

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