Is environmental temperature related to renal symptoms, serum lithium levels, and other laboratory test results in current lithium users?
Bibliographic record
Abstract
OBJECTIVE: Lithium continues to be an important mood disorder treatment. Although patients exposed to higher environmental temperatures may have serum lithium level elevations due to dehydration, there is conflicting data in the literature. In addition, no study has assessed the association between temperature and other renal laboratory tests and symptoms in lithium users. METHODS: This is a cross-sectional analysis of 63 current lithium users who participated in the McGill Geriatric Lithium-induced Diabetes Insipidus Clinical Study. The relationship between mean daily temperature with diabetes insipidus symptoms, glomerular filtration rate, urine osmolality, serum sodium, lithium level, and lithium dose-level ratio was assessed. RESULTS: Although a higher temperature on the day of laboratory testing trended toward being independently associated with a lower lithium dose-level ratio (Beta = -0.17, p = 0.08), this was not found when using a dichotomous measure of temperature (T > 20°C). No association was observed between temperature and other renal parameters. CONCLUSIONS: The association of temperature with lithium levels, renal symptoms, and laboratory tests appears to be of relatively little clinical importance in lithium users in temperate climates. However, future research should re-examine patients living in climates with extreme temperatures (e.g., >40°C), who may theoretically be at higher risk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| 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 teacher head, 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".