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Sex differences in help-seeking behaviour among patients presenting with acute coronary syndrome

2025· article· en· W7127927802 on OpenAlexaff
S Saboktakin Rizi, Andrea Lee, L. Avery, E Friesen, K Pineda, J Ducas, S Liu

Bibliographic record

VenueEuropean Heart Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsSt. Boniface HospitalUniversity of WinnipegUniversity of Manitoba
Fundersnot available
KeywordsAcute coronary syndromeDyslipidemiaDiabetes mellitusEmergency departmentProspective cohort studyMedical historyCoronary heart diseaseYoung adult

Abstract

fetched live from OpenAlex

Abstract Background Acute coronary syndrome (ACS) is a leading global cause of morbidity and mortality. While door-to-balloon times have improved, delays from symptom onset (SO) to first medical contact (FMC) remain unchanged, likely due to complex patient behaviours. Furthermore, there may be sex-specific differences in how ACS symptoms are perceived and the subsequent help-seeking behaviour. Purpose To understand delays in seeking care for ACS, focusing on sex differences in symptom recognition, help-seeking behaviour, and reasons for delay. Methods A prospective survey at a single centre from June-August 2024 was conducted. All ACS patients were eligible for inclusion. Patients were excluded if unable to provide consent, did not speak English or did not have a clear SO time. Patients completed a survey assessing SO and FMC times, symptom perception, and reasons for delay. Chart review for medical history was completed. Results Of the 93 included patients, mean age was 65±13 years and 79% were male (M). Cardiac risk factors including hypertension (60%, 56% female (M) vs 59% M), diabetes (31%, 40% F vs 25% M), dyslipidemia (49%, 44% F vs 45% M) showed no significant sex-based differences. The median SO-FMC delay was 9.58 hours (IQR 2.02–27.82), with 9.87 hours and 8.48 hours (p=0.92) for females and males, respectively. While there were no significant sex differences in emergency medical services (EMS) use, patients that used EMS presented earlier (2.9 vs 12.75 hours, p=0.02). Only 6.45% (4% F vs 7% M, p=0.91) of patients presented within 1 hour and 30% (32% F vs 34% M, p=1.0) within 3 hours. Males were most likely to present within one hour (odds ratio=1.9, p=0.7) compared to females. Patients experienced a variety of symptoms such as chest/arm/jaw pain (40% F vs 37% M, p=1.0), nausea/vomiting (28% F vs 15% M, p=0.33), dizziness and syncope (20% F vs 15% M, p=0.62), shortness of breath (32% F vs 19% M, p=0.35), and feeling clammy and sweating (16% F vs 28% M, p=0.12). In study population, feeling clammy resulted in statistically significant earlier presentations (3.85 vs 17.58 hours, p=0.007). The most common reasons for delayed presentation were symptom misinterpretation as non-cardiac (34%, 56% F vs 27% M, p=0.016) and hesitation/denial (19%, 12% F vs 22% M, p=0.43). Other reasons included logistical barriers (15%, 12% F vs 16% M, p=0.8), and immediate symptom relief (4%, 0% F vs 6% M, p=0.5). In 27% of patients, there was no identifiable reason. Conclusions Significant SO-FMC delays persist in ACS patients. Sex-based differences exist in patient’s behaviour when presenting with ACS, with different symptoms prompting male and female patients to seek help. The most common reason for delay in females seems to be symptoms misinterpretation while denial is a major factor in male patients’ delays. Targeted education on sex-specific ACS symptom recognition may help reduce delays and improve timely medical care.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.034
GPT teacher head0.311
Teacher spread0.277 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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