Systematic Review and Meta-Analysis of L-Methylfolate Augmentation in Depressive Disorders
Bibliographic record
Abstract
Abstract Objectives Partial response to pharmacotherapy is common in major depressive disorder (MDD) and many patients require alternative pharmacotherapy or augmentation, including adjunctive L-methylfolate. Given that L-methylfolate augmentation is rarely included in major clinical practice guidelines, we sought to systematically review evidence for L-methylfolate augmentation in adults with MDD and to examine its efficacy meta-analytically. Methods We systematically searched PubMed for articles up to December 31, 2020, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) recommendations. Included studies were published in peer-reviewed, English-language journals and examined L-methylfolate adjunctive therapy in depressive disorders or its effect on antidepressant response. A fixed- and random-effects meta-analysis and risk of bias assessment using the Cochrane Risk of Bias Tool were conducted. Results Qualitative assessment of nine articles (N=6,707 patients) suggests that adjunctive L-methylfolate improved antidepressant response. In the meta-analysis of categorical Hamilton Rating Scale for Depression-17 response, (three studies, N=483) adjunctive L-methylfolate was associated with a small effect versus antidepressant monotherapy (relative risk: 1.25, 95% confidence interval [CI]=1.08 to 1.46, p=0.004). A meta-analysis of four studies (N=507) using a continuous measure of depressive symptoms showed a similar effect of adjunctive L-methylfolate (standardized mean difference=− 0.38, 95% CI=− 0.59 to−0.17, p=0.0003). Conclusion Adjunctive L-methylfolate may have modest efficacy in antidepressant-treated adults with MDD.
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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 | 0.023 | 0.059 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.040 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".