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Record W4406024246 · doi:10.1002/alz.089860

Examining Depression in Older Surgical Patients: An Observational Cohort Study

2024· article· en· W4406024246 on OpenAlexaffabout
Yasmin Alhamdah, Ellene Yan, Nina Butris, Paras Kapoor, Leif E. Lovblom, David He, Frances Chung

Bibliographic record

VenueAlzheimer s & Dementia · 2024
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsMount Sinai HospitalToronto General HospitalToronto Western HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsGeriatric Depression ScaleDepression (economics)MedicineTelephone interviewCognitionMontreal Cognitive AssessmentPhysical therapyPopulationCohortDementiaCohort studyPsychiatryCognitive impairmentInternal medicineDiseaseDepressive symptoms

Abstract

fetched live from OpenAlex

BACKGROUND: Depression affects individuals across various ages but is of significance in the older surgical population due to its adverse impact on cognitive function, surgical recovery, and overall functional disability. This study aimed to determine the overall prevalence and trajectory of depression in older surgical patients preoperatively, and at 30-, 90- and 180-days postoperatively. METHOD: This study is a prespecified sub-study and analysis of the Postoperative Functional Disability in Unrecognized Cognitive Impairment Study. Participants ≥ 65 years undergoing elective non-cardiac surgery were recruited. Participants completed the 15-item Geriatric Depression Scale (GDS) through an online survey preoperatively and postoperatively at 30-, 90- and 180-days. A cut-off of ≥ 5 was used to define depression. Participants also completed four cognitive screening tools: the Telephone Montreal Cognitive Assessment and Modified Telephone Interview for Cognitive Status over the telephone and the Ascertain Dementia Eight-item Questionnaire and Center for Disease Control and Prevention cognitive question through survey. Cognitive impairment (CI) was defined as meeting the cut-off on one of the cognitive screening tools. Linear mixed-effects models were used for trajectory analysis. RESULT: Among 307 participants (mean ± SD age: 72.9 ± 5.5; 56.0% female), 62 (20.2%) screened positive for preoperative depression. Forty-five (14.7%) had mild depression (GDS score 5-8), 11 (3.6%) had moderate depression (GDS score 9-11), and 6 (2.0%) had severe depression (GDS score 12-15). Those who were depressed had significantly lower mean GDS scores at 90- and 180-days postoperatively vs. preoperatively (5.38 ± 0.37 and 5.41 ± 0.35 respectively vs. 7.52 ± 0.28, P≤0.05). While the value at 30-days was lower than that preoperatively, it was not significant. Non-depressed participants had significantly higher 30-days postoperative mean GDS score vs. preoperatively (2.09 ± 0.16 vs. 1.42 ± 0.14, P≤0.05). The mean GDS scores decreased over time in both groups (P for time <0.0001) with significant difference in the trajectories (P for interaction <0.0001). Of those with preoperative depression, 63% screened positive for CI on ≥1 cognitive screening tool vs. 33% without depression. CONCLUSION: Depression is prevalent in older surgical patients. Our novel study findings enable better understanding of depression in the older surgical population.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.065
GPT teacher head0.332
Teacher spread0.267 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2024
Admission routes2
Has abstractyes

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