Higher dose antiviral therapy for herpes infections is associated with a risk of serious adverse events in older adults with chronic kidney disease
Bibliographic record
Abstract
Antiviral use has been linked to encephalopathy and elevated serum creatinine concentrations in individuals with chronic kidney disease (CKD) in case reports. Using linked healthcare data in Ontario, we conducted a population-based cohort study on adults aged ≥66 years not receiving dialysis and newly prescribed oral acyclovir, valacyclovir, or famciclovir in the outpatient setting (2008-2022) at higher versus lower doses. The primary composite outcome, a hospital visit with encephalopathy or acute kidney injury (AKI) within 14 days of initiating antiviral treatment, was examined in a primary cohort. AKI was assessed in a secondary cohort of older adults with CKD with available linked hospital-based laboratory (lab) data. We used inverse probability of treatment weighting on the propensity score to balance comparison groups on baseline health. Weighted risk ratios (RR) and risk differences (RD) were obtained using modified Poisson and binomial regression. In the primary cohort, higher- versus lower-dose antiviral was not associated with an increased 14-day risk of hospital visit with encephalopathy or AKI. However, Higher- versus lower-dose antiviral was associated with a higher risk of a hospital visit with AKI when assessed using lab values (weighted number of events, 70 of 8407 [0.83%] versus 18 of 8230 [0.22%], respectively; weighted RR, 3.83 [95% CI, 1.87-7.87]; weighted RD, 0.62% [95% CI, 0.37%-0.86%]). In older adults with CKD, starting an antiviral at a higher versus lower dose was associated with a higher risk of AKI, although the absolute risk of this event was <1%.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".