Psychiatric and physical outcomes of long-term use of lithium in older adults with bipolar disorder and major depressive disorder: A cross-sectional multicenter study
Bibliographic record
Abstract
OBJECTIVE: Although lithium is widely used in current practice to treat bipolar disorder (BD) and treatment-resistant major depressive disorder (MDD) among older adults, little is known about its efficacy and tolerability in this population, which is generally excluded from randomized clinical trials. The objective of this study was to evaluate the efficacy and tolerability of long-term use of lithium among older adults with BD and MDD. METHOD: Data from the Cohort of individuals with Schizophrenia and mood disorders Aged 55 years or more (CSA) were used. Two groups of patients with BD and MDD were compared: those who were currently receiving lithium versus those who were not. The effects of lithium on psychiatric (i.e., depressive symptoms severity, perceived clinical severity, rates of psychiatric admissions in the past-year), geriatric (overall and cognitive functioning) and physical outcomes (i.e., rates of non-psychiatric medical comorbidities and general hospital admissions in the past-year) were evaluated. All analyses were adjusted for age, sex, duration of disorder, diagnosis, smoking status, alcohol use, and use of antipsychotics, antiepileptics or antidepressants. RESULTS: Among the 281 older participants with BD or MDD, 15.7% were taking lithium for a mean duration of 12.5(SD = 11.6) years. Lithium use was associated with lower intensity of depressive symptoms, reduced perceived clinical global severity and lower benzodiazepine use (all p < 0.05), without being linked to greater rates of medical comorbidities, except for hypothyroidism. LIMITATIONS: Data were cross-sectional and data on lifetime history of psychotropic medications was not assessed. CONCLUSION: Our results suggest that long-term lithium use may be efficient and relatively well-tolerated in older adults with BD or treatment-resistant MDD.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".