Long‐term treatment of bipolar disorder type I: A systematic and critical review of clinical guidelines with derived practice algorithms
Bibliographic record
Abstract
OBJECTIVES: This systematic review aimed at providing a critical, comprehensive synthesis of international guidelines' recommendations on the long-term treatment of bipolar disorder type I (BD-I). METHODS: MEDLINE/PubMed and EMBASE databases were searched from inception to January 15th, 2019 following PRISMA and PICAR rules. International guidelines providing recommendations for the long-term treatment of BD-I were included. A methodological quality assessment was conducted with the Appraisal of Guidelines for Research and Evaluation-AGREE II. RESULTS: The final selection yielded five international guidelines, with overall good quality. The evaluation of applicability was the weakest aspect across the guidelines. Differences in their updating strategies and the rating of the evidence, particularly for meta-analyses, randomized clinical trials (RCTs) and observational studies, could be responsible of some level of heterogeneity among recommendations. Nonetheless, the guidelines recommended lithium as the 'gold standard' in the long-term treatment of BD-I. Quetiapine was another possible first-line option as well as aripiprazole (for the prevention of mania). Long-term treatment should contemplate monotherapy, at least initially. Clinicians should check regularly for efficacy and side effects and if necessary, switch to first-line alternatives (i.e. Valproate), combine first-line compounds with different mechanisms of action or switch to second-line options or combinations. CONCLUSIONS: The possibility to monitor improvements in long-term outcomes, namely relapse prevention and inter-episode subthreshold depressive symptoms, based on the application of their recommendations is an unmet need of clinical guidelines. In terms of evidence of clinical guidelines, there is a need for more efficacious treatment strategies for the prevention of bipolar depression.
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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 | 0.035 | 0.119 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.020 | 0.014 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".