Beta-Blockers, Trimethoprim-Sulfamethoxazole, and the Risk of Hyperkalemia Requiring Hospitalization in the Elderly
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The simultaneous use of beta adrenergic receptor blockers (beta-blockers) and trimethoprim-sulfamethoxazole (TMP-SMX) may confer a high risk of hyperkalemia. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Two nested case-control studies were conducted to examine the association between hospitalization for hyperkalemia and the use of TMP-SMX in older patients receiving beta-blockers. Linked health administrative records from Ontario, Canada, were used to assemble a cohort of 299,749 beta-blockers users, aged 66 years or older and capture data regarding medication use and hospital admissions for hyperkalemia. RESULTS: Over the study period from 1994 to 2008, 189 patients in this cohort were hospitalized for hyperkalemia within 14 days of receiving a study antibiotic. Compared with amoxicillin, the use of TMP-SMX was associated with a substantially greater risk of hyperkalemia requiring hospital admission (adjusted odds ratio, 5.1; 95% confidence interval [CI], 2.8 to 9.4). No such risk was identified with ciprofloxacin, norfloxacin, or nitrofurantoin. When dosing was considered, the association was greater at higher doses of TMP-SMX. When the primary analysis was repeated in a cohort of non-beta-blocker users, the risk of hyperkalemia comparing TMP-SMX to amoxicillin was not significantly different from that found among beta-blocker users. CONCLUSIONS: Although TMP-SMX is associated with an increased risk of hyperkalemia in older adults, these findings show no added risk when used in combination with beta-blockers.
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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 | 0.000 | 0.002 |
| 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) | 0.000 | 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 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".