Thirty‐day risk of digoxin toxicity among older adults co‐prescribed trimethoprim‐sulfamethoxazole versus amoxicillin: A population‐based cohort study
Bibliographic record
Abstract
IMPORTANCE: Trimethoprim-sulfamethoxazole (TMP-SMX) may increase digoxin concentration, a medication with a narrow therapeutic index. Small changes in digoxin concentration could predispose individuals to the risk of toxicity. OBJECTIVE: To characterize the risk of digoxin toxicity in older adults taking digoxin following co-prescription of TMP-SMX compared with co-prescription of amoxicillin. DESIGN, SETTINGS, AND PARTICIPANTS: Retrospective population-based cohort study in Ontario, Canada (2002-2020) using linked health care data. Participants comprised 47,961 older adults taking digoxin (58% women; median age 80 years [interquartile range 74-86]) who were newly treated with TMP-SMX (n = 10,273) compared with those newly treated with amoxicillin (n = 37,688). EXPOSURE: Co-prescription of TMP-SMX versus amoxicillin in older adults concurrently taking digoxin. MAIN OUTCOME AND MEASURE: The primary outcome was a hospital encounter (i.e., hospital admission or emergency department visit) with digoxin toxicity within 30 days of the antibiotic prescription. Inverse probability of treatment weighting on the propensity score was used to balance comparison groups on indicators of baseline health. Weighted risk ratios (RR) were obtained using modified Poisson regression and weighted risk differences (RD) using binomial regression. The number needed to harm (NNH) was calculated as 1/RD. RESULTS: A hospital encounter with digoxin toxicity occurred in 49/10,273 (0.48%) patients treated with TMP-SMX versus 32/37,688 (0.08%) in those treated with amoxicillin (weighted RR, 5.71 [95% confidence interval (CI), 3.19 to 10.24]; weighted RD, 0.39% [95% CI, 0.25% to 0.53%]; NNH 256 [95% CI, 233 to 400]). CONCLUSION AND RELEVANCE: In older adults taking digoxin, the 30-day risk of a hospital encounter with digoxin toxicity was nearly 6 times higher in those co-prescribed TMP-SMX versus amoxicillin, although the absolute risk difference was low (0.4%). Physicians should prescribe an alternative antibiotic when clinically appropriate. If TMP-SMX must be co-prescribed with digoxin (if the benefit is believed to outweigh the risk), digoxin should be dose-reduced on an individual basis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".