Lithium Use, but Not Valproate Use, Is Associated With a Higher Risk of Chronic Kidney Disease in Older Adults With Mental Illness
Bibliographic record
Abstract
OBJECTIVE: Lithium is an essential mood disorder treatment; however, it remains unclear whether lithium increases chronic kidney disease (CKD) risk. There are few data on this in the elderly, even though older adults may be particularly susceptible to CKD. We wished to determine whether lithium is associated with increased CKD risk relative to valproate in older adults. METHODS: This nested case-control study analyzed province-wide administrative health data from mental health service users aged ≥ 66 years in Ontario, Canada, from 2003 to 2014. Five-year incident CKD risk was compared in lithium users, valproate users, and patients who used neither medication. ICD-10 was used to assign CKD diagnosis. We used conditional logistic regression to control for hypertension, diabetes mellitus, acute kidney injury, medications associated with lithium toxicity, and other potential confounders. RESULTS: 21,741 cases and 86,930 age- and sex-matched controls were identified, including 529 lithium users and 498 valproate users. After controlling for confounders, we found that lithium use was associated with increased risk of incident CKD (adjusted odds ratio [OR] = 1.76 [95% CI, 1.41-2.19]), while valproate use was not (adjusted OR = 1.03 [95% CI, 0.81-1.29]). CONCLUSIONS: Lithium is independently associated with an almost 2-fold increase in CKD risk in this community sample of older mental health service users. In the absence of clear information about certain contributing factors, such as inadequate monitoring and acute and chronic lithium level elevations, causes for this increase will need to be determined in future research.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".