Polypharmacy Is Associated With Accelerated Deterioration of Renal Function in Cardiovascular Outpatients
Bibliographic record
Abstract
BACKGROUND: Polypharmacy is associated with poor prognosis of patients with various diseases. However, it has not been precisely addressed how polypharmacy affects the clinical characteristics of the cardiovascular outpatients. The aim of this study is to search for the clinical characteristics related to the number of prescribed drugs in the cardiovascular outpatients. Also, we examine whether the number of the prescribed drugs affects the worsening of renal function. METHODS: This retrospective study was conducted using the data of 259 continuous cardiovascular outpatients who were examined complete blood count (CBC) and serum creatinine. RESULTS: In the univariate analysis, the number of prescribed drugs were associated with the number of cardiovascular diseases or their risk factors, age, white blood cells, platelet, body mass index, anemia, and chronic kidney disease stage 3b or higher. In the multivariable analysis, independent variables that significantly correlated with the number of prescribed drugs were the number of cardiovascular diseases or their risk factors, anemia, and chronic kidney disease stage 3b or higher. Among 259 patients, 208 patients received follow-up examination of serum creatinine. The number of prescribed drugs was the only factor that was associated with accelerated deterioration of renal function. CONCLUSIONS: Polypharmacy is associated not only with poor renal function but with accelerated deterioration of renal function. Polypharmacy may be causally related with renal dysfunction.
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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) | 0.001 | 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 | 0.001 |
| 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".