The impact of post-traumatic stress disorder in pharmacological intervention outcomes for adults with bipolar disorder: a protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Recent data indicates high prevalence of post-traumatic stress disorder (PTSD) in bipolar disorder (BD). PTSD may play a role in poor treatment outcomes and quality of life for people with BD. Despite this, few studies have examined the pharmacological treatment interventions and outcomes for this comorbidity. This systematic review will bring together currently available evidence regarding the impact of comorbid PTSD on pharmacological treatment outcomes in adults with BD. Methods A systematic search of Embase, MEDLINE Complete, PsycINFO, and the Cochrane Central Register of Controlled Trials (CENTRAL) will be conducted to identify randomised and non-randomised studies of pharmacological interventions for adults with diagnosed bipolar disorder and PTSD. Data will be screened and extracted by two independent reviewers. Literature will be searched from the creation of the databases until April 1 2021. Risk of bias will be assessed using the Newcastle-Ottawa Scale and the Cochrane Collaborations Risk of Bias tool. A meta-analysis will be conducted if sufficient evidence is identified in the systematic review. The meta-analysis will employ a random-effects model and be evaluated using the I 2 statistic. Discussion This review and meta-analysis will be the first to systematically explore and integrate the available evidence on the impact of PTSD on pharmacological treatments and outcome in those with BD. The results and outcomes of this systematic review will provide directions for future research and be published in relevant scientific journals and presented at research conferences. Systematic review registration The protocol has been registered at the International Prospective Register of Systematic Reviews (PROSPERO; registration number: CRD42020182540).
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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 | 0.072 | 0.113 |
| Meta-epidemiology (narrow) | 0.007 | 0.005 |
| Meta-epidemiology (broad) | 0.022 | 0.036 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.064 | 0.008 |
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".