The International Society for Bipolar Disorders (ISBD) consensus guidelines for the safety monitoring of bipolar disorder treatments
Bibliographic record
Abstract
OBJECTIVES: Safety monitoring is an important aspect of bipolar disorder treatment, as mood-stabilising medications have potentially serious side effects, some of which may also aggravate existing medical comorbidities. This paper sets out the International Society for Bipolar Disorders (ISBD) guidelines for the safety monitoring of widely used agents in the treatment of bipolar disorder. These guidelines aim to provide recommendations that take into consideration the balance between safety and cost-effectiveness, to highlight iatrogenic and preventive clinical issues, and to facilitate the broad implementation of therapeutic safety monitoring as a standard component of treatment for bipolar disorder. METHODS: These guidelines were developed by an ISBD workgroup, headed by the senior author (MB), through an iterative process of serial consensus-based revisions. After this, feedback from a multidisciplinary group of health professionals on the applicability of these guidelines was sought to develop the final recommendations. RESULTS: General safety monitoring recommendations for all bipolar disorder patients receiving treatment and specific monitoring recommendations for individual agents are outlined. CONCLUSIONS: These guidelines are derived from evolving and often indirect data, with minimal empirical cost-effectiveness data available to provide guidance. These guidelines will therefore need to be modified to adapt to different clinical settings and health resources. Clinical acumen and vigilance remain critical ingredients for safe treatment practice.
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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 | 0.058 | 0.092 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".