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Record W4220791149 · doi:10.1016/j.ijcha.2022.100978

Before the door: Comparing factors affecting symptom onset to first medical contact for STEMI patients between a high and low-middle income country

2022· article· en· W4220791149 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueIJC Heart & Vasculature · 2022
Typearticle
Languageen
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsPopulation Health Research InstituteMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsMedicineObservational studyDemographicsMyocardial infarctionEmergency medicineSingle CenterMedical emergencyInternal medicineDemography

Abstract

fetched live from OpenAlex

Background: Early reperfusion in patients with ST-segment elevation myocardial infarction (STEMI) has been associated with preservation of left ventricular function and decrease in mortality. Symptom onset to first medical contact (FMC) time consumes the majority of total ischemic time, and remains one of the main reasons that patients do not receive timely care. With FMC to reperfusion time being effectively reduced in many parts of the world, the focus is now shifting to reducing symptom onset to FMC times. Methods: This mixed-methods observational study was designed to elucidate factors affecting symptom onset to FMC time at a regional cardiac center in a low-middle income country (LMIC) and a high-income country (HIC). A review of the Aswan Heart Center and Hamilton General Hospital STEMI registry in Egypt and Canada was conducted, and retrospective semi-structured questionnaires carried out for a convenience sample of 158 patients. Results: Gender, symptom type and severity were none-modifiable factors found between early and late presenters. Modifiable factors found were actions of bystanders, actions of patients, transportation method and time. Emotional factors also showed differences between the two groups. Conclusion: While some concepts are generalizable, contextual differences in demographics, risk factors, access and knowledge are identified. These factors can be used to inform tailored knowledge translation strategies to help reduce symptom onset to FMC in both LMIC and HIC.

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.

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)0.001
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 score0.060
Threshold uncertainty score0.755

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.020
GPT teacher head0.293
Teacher spread0.273 · 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