Psychiatric and Cognitive Functioning After Metabolic and Bariatric Surgery: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
OBJECTIVE: To systematically review and meta-analyze psychiatric and cognitive outcomes following metabolic and bariatric surgery (MBS). [Correction added on 1 July 2025, after first online publication: The objective statement has been updated for clarity.] METHODS: Six databases were searched. Randomized controlled trials (RCTs) and nonrandomized studies (NRS) of people with obesity comparing MBS with any nonsurgical intervention or control condition were included. Main outcomes included symptoms of depression, anxiety, and non-normative eating, substance use disorder diagnosis, suicide death, and cognitive performance in attention, memory, and executive function. Evidence certainty was assessed with GRADE. Heterogeneity was explored with subgroup analyses of ≤ 2 years vs. > 2 years post-intervention. RESULTS: There were 79 studies (75 NRS and 4 RCTs) found, including 732,149 people with obesity who underwent MBS, and 7,670,770 who did not. Among RCTs, MBS may improve depressive symptoms (standardized mean difference [SMD] = -0.40, 95% CI -1.04, 0.24; very low certainty). Among NRS, there was low to very low certainty that MBS may improve depressive (SMD = 0.56, 95% CI -0.87, -0.26), anxiety (SMD = -0.60, 95% CI -1.00, -0.19), and non-normative eating symptoms (SMD = -0.75, 95% CI -0.97, -0.53) and cognitive performance in attention (SMD = -0.72, 95% CI -1.61, 0.17), but not executive function or memory. MBS may slightly increase suicide deaths (1/1000 more people, 95% CI 0 fewer to 3 more; very low certainty) and substance use disorders (4/100 more, 95% CI from 1 to 9 more; low certainty) > 2-years post-surgery. CONCLUSIONS: Compared to nonsurgical conditions, MBS may improve depression, anxiety, non-normative eating, and attention, but slightly increase suicides and substance use disorders. There was low to very low certainty in most outcomes, therefore additionalhigh-quality studies are needed to strengthen the evidence base.
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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 | 0.017 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.032 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 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".