Myocardial Infarction Care Among The Elderly: Declining Treatment With Increasing Age In Two Countries
Bibliographic record
Abstract
The elderly account for the majority of medical spending in many countries, raising concerns about potentially unnecessary spending, especially during the final months of life. Using a well-defined starting point (hospitalization for an initial acute myocardial infarction) with evidence-based postevent treatments, we examined age trends in treatments in the US and Norway, two countries with high levels of per capita medical spending. After accounting for comorbidities, we found marked decreases within both countries in the use of invasive treatments with age (for example, less use of percutaneous coronary interventions and surgery) and the use of relatively inexpensive medications (for example, less use of anticholesterol [statin] drugs for which generic versions are widely available). The treatment decreases with age were larger in Norway compared with those in the US. The less frequent treatment of the oldest of the old, without even use of basic medications, suggests potential age-related bias and a disconnect with the evidence on treatment value. Hospital organization and payment in both countries should incentivize greater equity in treatment use across ages.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".