Effectiveness and outcome predictors of long-term lithium prophylaxis in unipolar major depressive disorder
Bibliographic record
Abstract
OBJECTIVE: To determine the effectiveness of lithium prophylaxis in unipolar major depressive disorder (MDD) and to identify predictors of outcome including comedication. METHODS: In this long-term naturalistic study, clinical data from 55 patients with MDD (DSM-III-R) were collected prospectively in an outpatient clinic specializing in the treatment of affective disorders. OUTCOME MEASURES: Change in hospital admission rate (number and duration) during prophylaxis compared with the period before prophylaxis, Morbidity-Index during prophylaxis and time to first recurrence after initiation of lithium treatment. RESULTS: During an average follow-up period of 6.7 years, a significant decline in the number of days spent in hospital (p<0.001; 52 d/yr less; 95; CI 31-73 d) and a low Morbidity-Index (mean 0.07) was observed. Only in 6 patients did medication have to be changed because of side-effects (n=4) or a lack of efficacy (n=2). None of the independent variables we analyzed proved to be important in predicting the outcome of lithium prophylaxis. Comedication was necessary in 21 patients. The overall outcome of their prophylactic treatment, however, did not differ from the group that did not receive comedication in the symptom-free intervals. CONCLUSIONS: The results of this study, with its long observation period and the inclusion of comedication as a confounding variable, indicate that lithium is a potent prophylactic agent for unipolar MDD in a naturalistic setting. In contrast to the findings of others, age was not associated with the outcome of prophylaxis, and latency did not predict outcome. Contrary to doubts that have been raised in recent years with regard to the effectiveness of lithium in everyday clinical practice, lithium appears to be a safe and potent alternative to antidepressants.
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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 | 0.006 |
| 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".