Assessment of Adherence to Renal Dosing Guidelines in Long‐Term Care Facilities
Bibliographic record
Abstract
OBJECTIVE: We determined whether dosing guidelines based on creatinine clearance (Ccr) for renally excreted drugs are being applied when prescribing to long-term care residents DESIGN: A cross sectional chart review for the month of May 1999. PARTICIPANTS: Long-term care residents more than 65 years of age from four long-term care facilities in Southern Ontario who were prescribed a medication from a list of renally excreted drugs commonly prescribed in long-term care facilities. RESULTS: Approximately one in three prescriptions (34.1%) were considered inappropriate for the calculated Ccr of the residents. Overall, 42.3% of the residents who were prescribed a drug under review received at least one inappropriate prescription based on creatinine clearance. Logistic regression found that age (odds ratio (OR) = 1.06 per year; 95% confidence interval (CI) 1.03-1.09, P = .001), weight (OR = 0.96 per kg; 95% CI 0.94-0.98, P < .001), the total number of prescribed medications (OR = 1.10; 95% CI 1.04-1.17, P = .001), and the number of physicians prescribing in the facility (OR 1.02; 95% CI, 1.003-1.044, P = .03) were predictive for receiving an inappropriate prescription based on Ccr. CONCLUSIONS: Renal function is often overlooked when prescribing renally excreted drugs to older long-term care residents. These findings emphasize the need for consideration of Ccr when prescribing such drugs in this population.
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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 | 0.000 | 0.000 |
| 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".