Potentially Inappropriate Medication Use in Older Adults in the Preoperative Period: A Retrospective Study of a Noncardiac Surgery Cohort
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Few studies have evaluated the prevalence of potentially inappropriate medications (PIMs) and its association with postoperative outcomes in a geriatric population in the preoperative setting. OBJECTIVES: The purpose of this study was to evaluate the prevalence of PIMs in an older elective surgery population and to explore associations between PIMs and postoperative length of stay (LOS) and emergency department (ED) visits in the 90 days post hospital discharge, depending on frailty status. METHODOLOGY: We performed a retrospective cohort study of older adults awaiting major elective noncardiac surgery and undergoing an evaluation in the preoperative clinic at a tertiary academic center between 2017 and 2018. We identified PIMs using MedSafer, a software tool built to improve the safety of prescribing. Frailty status was assessed using the 7-point Clinical Frailty Scale. We estimated the association between PIMs and postoperative LOS and ED visits in the 90 days post hospital discharge. RESULTS: The MedSafer software generated 394 recommendations on PIMs in 1619 medications for 252 patients. In total, 197 (78%) patients had at least one PIM. The cohort included 138 (51%) robust, 87 (32.2%) vulnerable and 45 (16.7%) frail patients. The association between PIMs and LOS was not significant for the robust and frail subgroups. For the vulnerable patients, every additional PIM increased LOS by 20% (incidence rate ratio 1.20; 95% confidence interval 0.90-1.44; p = 0.089) without reaching statistical significance. No association was found between PIMs and ED visits. CONCLUSION: PIMs identified by the MedSafer software were prevalent. Preoperative evaluation represents an opportunity to plan deprescribing of PIMs.
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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) | 0.002 | 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 it