Different trends in the age-standardized incidence of ST-elevation and non-ST-elevation myocardial infarction in the province of Quebec, Canada between 2013 and 2021
Bibliographic record
Abstract
Abstract Introduction Age-standardized incident trends in coronary heart disease (CHD) have shown a significant decline of 15% between 2013 and 2021 in the province of Quebec, Canada. The effect of the pandemic years has shown that ratios of the observed on expected age-standardized incident rates of CHD were slightly lower for 2020-2021, the first year of the pandemic whereas it was non-significant for 2021-2022, the second year of the pandemic. Purpose To describe how incident trends in acute myocardial infarction (AMI) and specifically between 2 subtypes: ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI) have contributed to the decrease observed in CHD between 2013 and 2021, which includes 2 years of pandemic. Methods Using linked health administrative data for the whole population aged ≥20 years, starting in 1996 and updated annually, incident AMI were attributed if the International Classification of Disease tenth revision (ICD-10) code I21 was present in the hospital data, as a primary or in any secondary positions. STEMI and NSTEMI were defined with the presence of the ICD-10 code R94.30 and R94.31, respectively, in the hospital data in any secondary position. The 2011 Quebec standard population was used for age-standardization and 99% confidence intervals (CIs) were calculated using the gamma method. The temporal differences were considered to be significant if the CIs did not overlap. Results Crude incident rate of AMI was 3.17 per 1,000 in 2021. This included 0.64 per 1,000 for STEMI and 2.41 per 1,000 for NSTEMI, corresponding to 20,810 AMI, of which 4,280 were STEMI and 16,085 were NSTEMI (445 AMI were unclassified). The proportions of STEMI and NSTEMI between 2013 and 2021 were stable with a mean of 23% and 75%, respectively. Between 2013 and 2021, age-standardized incidence rates of AMI were stable with 2.78 per 1,000, [99% CI: 2.73-2.84] and 2.80 per 1,000, [2.75-2.85], respectively (Figure 1). However, different significant trends were observed: there was an 8% increase in incidence rates until 2018 (3.01 per 1,000, [2.96-3.06]) followed by a decrease, and then a notable increase in 2021. As illustrated in figure 1, a constant and significant decrease of 15% in the age-standardized incidence of STEMI was observed between 2013 (0.68 per 1,000, [0.66-0.71]) and 2021 (0.58 per 1,000, [0.56-0.60]) whereas NSTEMI increased globally of 11% between the same years (1.85 per 1,000, [1.81-1.90] and 2.06 per 1,000, [2.02-2.10]) and followed a similar trend as all AMI. Conclusion The decrease in the incidence of CHD could be attributed to the decrease in STEMI only since NSTEMI increased globally between 2013 and 2021 which explains the non-significant changes in the incident trends of all AMI. This suggests that public health efforts might have more effectively addressed factors leading to STEMI, as opposed to NSTEMI. The pandemic seems to have had varied impacts on different AMI subtypes.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 | 0.000 |
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 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".