Thiazide Diuretic Dose and Risk of Kidney Stones in Older Adults: A Retrospective Cohort Study
Bibliographic record
Abstract
Background:Thiazide diuretics are commonly prescribed to prevent kidney stones. However, it is unclear whether higher doses confer greater benefit.Objective:To determine whether lower doses of thiazide diuretics confer a similar protective effect against kidney stone events as higher doses.Design:Population-based cohort study.Setting:Linked health administrative databases in Ontario, Canada.Patients:Older adults newly prescribed a thiazide diuretic between 2003 and 2014 were separated into 2 groups based on daily dose: low dose (⩽12.5 mg hydrochlorothiazide/chlorthalidone, or ⩽1.25 mg indapamide) or high dose.Measurements:The primary outcome was time to a kidney stone event, using diagnosis and procedure codes. A secondary outcome was kidney stone surgery.Methods:An association between thiazide diuretic dose and a kidney stone event was estimated using Cox proportional hazards regression.Results:A total of 536 of 105 239 patients (0.51%) experienced a kidney stone event. We did not detect a difference in kidney stone risk in the high-dose relative to the low-dose group (adjusted hazard ratio, 1.10; 95% confidence interval, 0.93-1.31). Results were similar when analysis was restricted to the more specific outcome of kidney stone surgery. Neither a history of prior kidney stones nor the type of thiazide diuretic modified the effect of diuretic dose on outcome.Limitations:Patients were >65 years old and we were unable to adjust for some potential confounders such as dietary factors.Conclusions:Lower dose thiazide diuretics appear to confer a similar protective effect as higher dose thiazides against the development of kidney stones.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".