Lithium Treatments: Single and Multiple Daily Dosing
Bibliographic record
Abstract
OBJECTIVE: To review the feasibility and effectiveness of single daily dosing of lithium in patients with affective disorder and to discuss advantages and disadvantages of this schedule of administration. METHOD: A comprehensive search of the literature was conducted using a combination of electronic databases and a search of reference lists and relevant journals. English-language articles were selected for the review if they discussed the issues comparing multiple and single daily dosing schedules of lithium. RESULTS: We found 9 comparative studies. Single daily dosing of lithium causes transient higher peak lithium concentrations; however, no comparative study revealed a significant difference in side effects between multiple and single daily dosing groups. Numerous reports concluded that taking lithium in a single dose prevents, or at least limits, the increase in urine output (and the reduction of osmolality) and subsequent thirst. There is no evidence that a single lithium dosing schedule preserves glomerular function. CONCLUSION: According to the presented data, it could be reasonable to use lithium as a single evening dose in patients who can tolerate this schedule because no studies have suggested any benefit from administration of multiple daily doses. Possible advantages of single daily dosing, especially in improved compliance, could not be veiled by disadvantages of transient and mild postabsorptive side effects.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".