Changing Patterns in Medication Use with Increasing Probability of Death for Older Medicare Beneficiaries
Bibliographic record
Abstract
OBJECTIVES: To determine whether use of symptom relief drugs (e.g., antidepressants, anxiolytics, opioid analgesics, sleep aids) rises and use of two commonly prescribed classes of chronic medications (statins and osteoporosis drugs) falls with greater probability of death for older Medicare beneficiaries. DESIGN: Pooled cross-sectional study. SETTING: Noninstitutionalized older Medicare population in 2000 to 2005. PARTICIPANTS: Community-dwelling Medicare beneficiaries aged 65 and older (N=20,233). MEASUREMENTS: Use of medications measured according to dichotomous flags; intensity of use by annual medication fills. Annual probability of death modeled using logistic regression and stratified into seven groups with predicted probabilities of death that range from less than 5% to greater than 50%. Prevalence of use and intensity (mean prescription fills per month) were computed for each class of medication. RESULTS: For symptom relief medications, there is relatively constant use with increasing probability of death, along with greater intensity of use. For the two chronic medications, there was a monotonic decrease in use but at a relatively constant intensity. Decline in statin use ranged from 34.4% in the lowest mortality stratum to 17.6% for those in the highest (P<.001). Use of osteoporosis drugs fell from 10.4% to 6.6% over the same range (P<.001). CONCLUSION: Greater intensity of use of symptom relief medications with increasing probability of death is consistent with hypothesized use. The different profile for chronic medications suggests that the time to benefit is being considered regarding therapy initiation, which results in lower use.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
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".