Therapeutic benefits of pharmacologic and nonpharmacologic treatments for depressive symptoms after traumatic brain injury: a systematic review and network meta-analysis
Bibliographic record
Abstract
Background: Depression is a common morbidity after traumatic brain injury. This network meta-analysis investigated the efficacy and tolerability of pharmacologic and nonpharmacologic interventions for depression after traumatic brain injury. Methods: We extracted randomized controlled trials examining pharmacologic or nonpharmacologic interventions with placebo- or active-controlled designs from PubMed, the Cochrane Library and ScienceDirect, from inception to October 30, 2018. We based study selection and extraction of a predefined list of variables on the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines, and conducted meta-analysis procedures using random effects modelling. Primary outcomes were changes in depressive symptom severity after pharmacologic or nonpharmacologic treatment; the secondary outcome was tolerability, reflected in overall patient dropout rates. Results: Our analysis of 27 randomized controlled trials (10 pharmacologic, total n = 483, mean age = 37.9 yr; 17 nonpharmacologic, total n = 1083, mean age = 38.0 yr) showed that methylphenidate had significantly superior efficacy compared to placebo or control (standardized mean difference -0.91, 95% confidence interval [CI] -1.49 to -0.33). Sertraline was associated with significantly lower tolerability (i.e., a higher dropout rate) compared to placebo or control (odds ratio 2.65, 95% CI 1.27 to 5.54). No nonpharmacologic treatment was more effective than the others, and we found no significant differences in tolerability (i.e., dropout rates) among the nonpharmacologic treatments. Limitations: Heterogeneity in participant characteristics (e.g., comorbidities), study designs (e.g., trial duration) and psychopathology assessment tools, as well as small trial numbers for some treatment arms, could have been confounders. Conclusion: The present network meta-analysis suggests that methylphenidate might be the best pharmacologic intervention for depressive symptoms related to traumatic brain injury. None of the nonpharmacologic interventions was associated with better improvement in depressive symptoms than the others or than control conditions. None of the pharmacologic or nonpharmacologic treatments had inferior tolerability compared to placebo or controls except for sertraline, which had significantly lower tolerability than placebo.
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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 | 0.021 | 0.054 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.049 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".