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Record W4393948346 · doi:10.1111/obr.13743

Preoperative depression and outcomes after metabolic and bariatric surgery: A systematic narrative review

2024· review· en· W4393948346 on OpenAlexafffund
Calvin Diep, Yuanxin Xue, Maggie Xiao, Bianca Pivetta, Julian F. Daza, James J. Jung, Duminda N. Wijeysundera, Karim S. Ladha

Bibliographic record

VenueObesity Reviews · 2024
Typereview
Languageen
FieldMedicine
TopicBariatric Surgery and Outcomes
Canadian institutionsSt. Michael's HospitalToronto General HospitalPublic Health OntarioUniversity of Toronto
FundersUniversity of TorontoOntario Ministry of Health and Long-Term CareMinistry of Health, Ontario
KeywordsMedicineDepression (economics)MEDLINEPerioperativeMeta-analysisSleeve gastrectomyWeight lossCohort studyProspective cohort studyQuality of life (healthcare)Randomized controlled trialPhysical therapySurgeryInternal medicineGastric bypassObesity

Abstract

fetched live from OpenAlex

Preoperative depression is prevalent among patients undergoing metabolic and bariatric surgery (MBS) and is a potentially modifiable risk factor. However, the impact of preoperative depression on MBS outcomes has not been systematically reviewed. A search of MEDLINE, Embase, Cochrane, and PsychINFO (inception to June 2023) was conducted for studies reporting associations between preoperative depression and any clinical or patient-reported outcomes after MBS. Eighteen studies (5 prospective and 13 retrospective) reporting on 5933 participants were included. Most participants underwent gastric bypass or sleeve gastrectomy. Meta-analyses were not conducted due to heterogeneity in reported outcomes; findings were instead synthesized using a narrative and tabular approach. Across 13 studies (n = 3390) the associations between preoperative depression and weight loss outcomes at 6-72 months were mixed overall. This may be related to differences in cohort characteristics, outcome definitions, and instruments used to measure depression. A small number of studies reported that preoperative depression was associated with lower quality of life, worse acute pain, and more perioperative complications after surgery. Most of the included studies were deemed to be at high risk of bias, resulting in low or very low certainty of evidence according to the Risk of Bias In Non-randomized Studies - of Exposure (ROBINS-E) tool. While the impact of preoperative depression on weight loss after MBS remains unclear, there is early evidence that depression has negative consequences on other patient-important outcomes. Adequately powered studies using more sophisticated statistical methods are needed to accurately estimate these associations.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.508
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0160.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.043
GPT teacher head0.343
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations8
Published2024
Admission routes2
Has abstractyes

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