An amantadine hydrochloride dosing program adjusted for renal function during an influenza outbreak in elderly institutionalized patients.
Bibliographic record
Abstract
OBJECTIVE: We tested the hypothesis that individualized dosing of amantadine hydrochloride, based upon a patient's creatinine clearance, would maintain efficacy against influenza A infection while reducing adverse reactions to the drug. DESIGN: A prospective cohort study PARTICIPANTS: Residents of two nursing homes with a total population of 301 individuals INTERVENTION: Amantadine hydrochloride was administered prophylactically subsequent to a confirmed influenza A outbreak. The dose was individualized based upon the resident's calculated creatinine clearance. RESULTS: The concentration of amantadine hydrochloride in the circulation at steady-state in patients who had doses adjusted for their estimated creatinine clearance was not different by nursing home or by sex of the resident. The mean concentration was within the 95% CI for the target concentration of 1.6 micromol/L. Side effects were modest and did not require discontinuation of amantadine hydrochloride therapy. Only the presence of concurrent influenza-like illness was significantly associated with adverse events during amantadine hydrochloride therapy. CONCLUSIONS: Adjustment of doses for estimated creatinine clearance is feasible in a long term care facility when amantadine hydrochloride is indicated for influenza A prophylaxis. These data form the basis for a definitive study of amantadine hydrochloride efficacy in patients with reduced renal function. Concurrent influenza-like illness is likely to confound attempts to associate adverse reactions to the administration of amantadine hydrochloride therapy.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".