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Record W3032716350 · doi:10.1213/ane.0000000000004893

Preoperative Frailty Predicts Postoperative Neurocognitive Disorders After Total Hip Joint Replacement Surgery

2020· article· en· W3032716350 on OpenAlexaboutno aff
Lisbeth Evered, Sarah Vitug, David A. Scott, Brendan Silbert

Bibliographic record

VenueAnesthesia & Analgesia · 2020
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsNeurocognitiveMedicineTotal hip replacementHip replacementHip surgeryTotal joint replacementSurgeryArthroplastyPsychiatryCognition

Abstract

fetched live from OpenAlex

BACKGROUND: Frailty is a reduced capacity to recover from a physiologically stressful event. It is well established that preoperative frailty is associated with poor postoperative outcomes, but it is unclear if this includes cognitive decline following anesthesia and surgery. This retrospective observational study was a secondary analysis of data from a previous study (the Anaesthesia, Cognition, Evaluation [ACE] study). We aimed to identify if preoperative frailty or prefrailty is associated with preoperative and postoperative neurocognitive disorders or postoperative cognitive dysfunction. METHODS: The ACE study enrolled 300 participants aged ≥60 scheduled for elective total hip joint replacement and who underwent a full neuropsychological assessment at baseline and 3 and 12 months postoperatively. We applied patient data to 2 frailty models; both were based on an accumulation of deficits score: the reported Edmonton frail scale (REFS) and the comprehensive geriatric assessment-frailty index (CGA-FI) based on the comprehensive geriatric assessment. We calculated these 2 scores using baseline data collected from the medical history, demographic and clinical data as well as self-reported questionnaires. Some items on the REFS (3 of 18 or 17%) and the CGA-FI (37 of 51 or 27%) did not have an equivalent item in the ACE data. RESULTS: The mean age (standard deviation [SD]) was 70.1 years (6.6) with more women (197 [66%]). Using the REFS model, 40 of 300 (13.3%) patients were classified as vulnerable, mild, or moderately frail. Using the CGA-FI model, 69 of 300 (23%) were classified as intermediate or high frailty. The REFS and the CGA-FI were strongly correlated (r = 0.75; P < .01) with 34 of 300 (11%) meeting criteria for frailty by both the REFS and the CGA-FI.Frailty or prefrailty was associated with cognitive decline at 3 and 12 months using the REFS (odds ratio [OR], 1.51, 95% confidence interval [CI], 1.02-2.23 and OR, 2.00, 95% CI, 1.26-3.17, respectively) after adjusting for baseline mini-mental state examination (MMSE), smoking, hypertension, diabetes, history of acute myocardial infarction (AMI), and estimated intelligence quotient (IQ). Age did not modify this association. After adjusting for multiple comparisons, 3-month cognitive decline was no longer significantly associated with baseline frailty. CONCLUSIONS: This retrospective analysis demonstrates an association between baseline frailty and postoperative neurocognitive disorders, particularly using the more extensive REFS scoring method. This supports preoperative screening for frailty to risk-stratify patients, and identify and implement preventive strategies and to improve postoperative outcomes for older individuals.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.301
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.027
GPT teacher head0.251
Teacher spread0.224 · 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 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

Citations47
Published2020
Admission routes1
Has abstractyes

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