How are Chest Pain Symptoms Described in Female vs. Male Patients During Clinical Teaching of Family Medicine Residents?
Bibliographic record
Abstract
Context: Cardiovascular disease is the leading cause of death for female patients. Despite recent clinical practice guidelines about how female patients present with chest pain, many physicians may be misclassifying female patients’ symptoms as ‘atypical’. This can result in discrepancies in care for female vs male patients and put female patients at risk for poor outcomes. It is crucial to ensure that future family physicians are getting the right teaching about appropriately diagnosing and managing female patients’ chest pain. Objective: To examine how chest pain symptoms are discussed during workplace-based clinical teaching in family medicine residency training. Study Design: Secondary data analysis. Database: Archived (July 2010 to June 2022), de-identified electronic narrative workplace-based formative assessment forms (FieldNotes) from a mid-sized Canadian family medicine residency program. FieldNotes can be used as a proxy for workplace-based clinical teaching discussions. Population studied: Family medicine preceptors and residents. Instrument: FieldNotes include a narrative of feedback shared with a resident during a clinical teaching encounter, as well as a brief description of the patient and presentation. Narratives were searched for: ‘chest pain’, ‘heart’, ‘MI’, ‘STEMI’, ‘NSTEMI’. Identified FieldNotes were then further searched for the term ‘atypical’, and to determine the sex of the patient. Outcome Measures: Numbers of FieldNotes about chest pain; percentage of chest pain FieldNotes where symptoms were described as ‘atypical’; comparison of ‘atypical’ designation by sex of patient. Chi-square goodness of fit tested the assumption that the proportion of ‘atypical’ assignment was equal across sexes Results: Of all FieldNotes (N = 64942), 677 (1.04%) included narratives about chest pain. Of those FieldNotes, 76 (11.2%) indicated that the symptoms were ‘atypical’. ‘Atypical’ classification varied by patient gender (male = 11; female = 32; unspecified = 33). A significant difference was found for female patients with ‘atypical’ chest pain (X2 = 18.24; df = 2; p = 0.00011). Expected Outcomes: Chest pain symptoms were more likely to be described as ‘atypical’ when patients were female. This finding suggests a need for faculty development about approaches to female patients with chest pain that align with best clinical practice. This should lead to improvements in how family medicine residents are taught about chest pain in female patients.
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 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 | 0.005 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".