Mental health quality of life after bariatric surgery: A systematic review and meta‐analysis of randomized clinical trials
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recent literature has raised concerns regarding the risk of adverse psychiatric events among bariatric surgery patients. However, the relationship between weight loss therapy and psychiatric outcomes is confounded by baseline psychosocial characteristics in observational studies. To understand the impact of bariatric surgery on the risk of adverse mental health outcomes, we conducted a systematic review and meta-analysis of randomized controlled trials that compared surgical and non-surgical treatments and assessed mental health quality of life (QoL). We evaluated the PubMed, EMBASE, Web of Science PsycINFO, Clinicaltrials.gov and Cochrane databases through 7 March 2018. Pooled standardized mean differences (SMDs) for mental health QoL scores were estimated using random effects models. Eleven randomized trials with 731 participants were included in the final analyses. Surgery was not associated with an improvement in mental health QoL from baseline as compared to non-surgical intervention (SMD: 0.02, 95% confidence interval [CI] -0.22 to 0.25). Final mental health QoL scores were similar for surgically and non-surgically treated patients (SMD: 0.37, 95% CI -0.07 to 0.81). Subgroup analyses assessing the effect of specific surgical interventions, and varying lengths of follow-up did not identify a beneficial effect of bariatric surgery on mental health QoL outcomes. These results, in conjunction with the fact that individuals who choose bariatric surgery tend to have high-risk baseline characteristics, suggest that intensive mental health follow-up following surgery should be routinely considered.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.349 | 0.243 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.153 | 0.058 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it