Abstract 9442: Acute Coronary Syndrome Treatment Delay in Low to Middle-Income Countries: A Systematic Review
Bibliographic record
Abstract
Introduction: Although morbidity and mortality rates are declining for acute coronary syndrome (ACS) in most high-income countries, it is rising at an alarming pace for low to middle-income countries (LMICs), largely due to pre-hospital treatment delays. Purpose: This systematic review was conducted to determine the mean length of time from symptom onset to treatment in LMICs and the sociodemographic, clinical, and health system characteristics that contribute to treatment delays. Methods: A comprehensive review of the English literature was conducted between January 1990 through May 2020 using predefined criteria. Time to treatment was defined from ACS symptom onset to first medical contact and then further dichotomized as less than (early) or greater than 12-hours (late) treatment. Twenty-nine peer-reviewed studies, which comprised 29,731 subjects with ACS symptoms residing in 14 LMICs. Sample sizes in the studies ranged from 50 to 20,937. Age ranged from 28-72 years and the majority were males. The Newcastle-Ottawa Assessment Scale was utilized to measure study quality. Results: The mean time from symptom onset to first medical contact was 12.7 hours, ranging from10-minutes to 96 hours. Being older age, female gender, illiterate, rural residence, having atypical chest pain and lack of ACS symptom knowledge were associated with longer delays. Those directly admitted to an emergency department with the capacity to provide coronary interventions received earlier treatment. Community facilities where ECG machines were available had lower prehospital delay time for referral to reperfusion therapy facilities. Lack of emergency medical systems, poor communication between the community and interventional facilities were also major contributors to ACS treatment delays. Conclusions: Pre-hospital delay time remains an important contributor to poorer clinical outcomes and higher mortality in LMICs. Country-wide referral plans are urgently needed to ensure timely transfer of patients from non-cardiac centers to interventional facilities. Health education through the different media outlets will raise awareness of ACS risk factors, accompanying signs and symptoms as well as the need to seek early treatment to improve clinical outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".