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Record W4389903889 · doi:10.1016/j.cjco.2023.12.014

Designing a Multidisciplinary Cardio-obstetrics Curriculum for General Cardiology and Obstetrics Residents: A National Survey of Educational Needs

2023· article· en· W4389903889 on OpenAlexafffundabout
Sarah Blissett, Lotus Alphonsus, Genevieve Eastabrook, Harrison Banner, Samuel C. Siu

Bibliographic record

VenueCJC Open · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Issues in Pregnancy
Canadian institutionsWestern University
FundersAcademic Medical Organization of Southwestern Ontario
KeywordsObstetrics and gynaecologyMultidisciplinary approachMedicineCurriculumMedical educationFamily medicinePregnancyPsychology

Abstract

fetched live from OpenAlex

Background: The increasing and potentially preventable cardiac events in pregnant patients have led to calls to enhance multidisciplinary cardio-obstetrics education. To design a multidisciplinary cardio-obstetrics curriculum for general cardiology and obstetrics and gynecology (OBGYN) residents, we need to define educational needs from the perspectives of both cardiology and OBGYN residents. Our study characterizes the educational needs of Canadian cardiology and OBGYN residents. Methods: Canadian cardiology and OBGYN residents were surveyed on clinical exposures, perceived needs for topics, unperceived needs for topics (multiple-choice questions) and preferences for educational formats. High priorities were defined as ≥ 50% of responses indicating a perceived need or ≥ 50% indicating an unperceived need. Results: A total of 154 residents participated (cardiology n = 44, OBGYN n = 110). Residents reported insufficient clinical exposure to nearly all cardiac disorders, with 33% of exposures occurring in multidisciplinary contexts. All topics aside from gestational hypertension were rated as high priority on perceived needs by both specialties. High-priority unperceived needs were congenital heart disease (both specialties), pre-existing acquired heart disease (both specialties), medication safety (OBGYN), peripartum management (OBGYN), and pregnancy-related heart disease (OBGYN). Cardiology and OBGYN residents shared preferences for in-person simulation, virtual simulation, and online modules. Conclusions: Residents in both specialties reported low clinical exposure to most cardiac disorders during pregnancy, identified high-priority perceived needs in multiple topics, and shared 2 high-priority unperceived needs. OBGYN residents identified 3 additional high-priority unperceived needs. These data can inform design of multidisciplinary cardio-obstetrics curricula for general cardiology and OBGYN residents.

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)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.067
GPT teacher head0.371
Teacher spread0.304 · 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 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

Citations2
Published2023
Admission routes3
Has abstractyes

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