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The utility of the Montreal cognitive assessment (MoCA) in detecting cognitive impairment in surgical populations – A systematic review and meta-analysis

2024· review· en· W4400854720 on OpenAlex
Mercy O. Danquah, Ellene Yan, Jun Won Lee, Kaylyssa Philip, Aparna Saripella, Yasmin Alhamdah, David He, Marina Englesakis, Frances Chung

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Clinical Anesthesia · 2024
Typereview
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsMount Sinai HospitalUniversity of SaskatchewanToronto Western HospitalUniversity Health NetworkUniversity of Toronto
FundersCanadian Institutes of Health ResearchUniversity Health Network FoundationResMed FoundationMinistry of Health, Ontario
KeywordsMontreal Cognitive AssessmentMedicineDeliriumPerioperativeMeta-analysisCognitive impairmentCardiac surgeryInternal medicineAdverse effectSurgeryPsychiatryDisease

Abstract

fetched live from OpenAlex

STUDY OBJECTIVE: To determine the diagnostic accuracy of the Montreal Cognitive Assessment (MoCA) in detecting cognitive impairment (CI) and assess the association of MoCA scores with adverse postoperative outcomes in surgical populations. DESIGN: Systematic review and meta-analysis. SETTING: Perioperative setting. PATIENTS: Adults undergoing elective or emergent surgery screened for CI preoperatively using the MoCA. MEASUREMENTS: The outcomes included the diagnostic accuracy of the MoCA in screening for CI and the pooled prevalence of CI in various surgical populations. CI and its association with adverse events including delirium, hospital length-of-stay (LOS), postoperative complications, discharge destination, and mortality was determined. MAIN RESULTS: Twenty-six studies (5059 patients, 18 non-cardiac studies, 8 cardiac studies) were included. With a MoCA cut-off score of <26, the prevalence of preoperative CI was 48% (95% CI: 41%-54%). The MoCA had 0.87 (95% CI: 0.79-0.93) sensitivity, 0.72 (95% CI: 0.62-0.80) specificity, PPV of 0.74 (95% CI: 0.65-0.81), and NPV of 0.86 (95% CI: 0.77-0.92) when validated against Petersen criteria, the Diagnostic and Statistical Manual of Mental Disorders, or the National Institute on Aging and the Alzheimer's Association criteria to identify CI. Using the MoCA as a screening tool, the LOS was 3.75 (95% CI: -0.03-7.53, P = 0.05, not significant) days longer in the CI group after non-cardiac surgeries and 3.33 (95% CI: 1.24-5.41, P < 0.002) days longer after cardiac surgeries than the non-cognitively impaired group. CONCLUSIONS: MoCA had been validated in the surgical population. MoCA with a cut-off score of <26 was shown to have 87% sensitivity and 72% specificity in identifying CI. A positive screen in MoCA was associated with a 3-day longer hospital LOS in cardiac surgery in the CI group than in the non-CI group.

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 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)0.011
metaresearch head score (Gemma)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.584
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0110.007
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.189
GPT teacher head0.493
Teacher spread0.304 · 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