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Record W4295808117 · doi:10.1186/s12871-022-01831-1

The prevention of delirium in elderly surgical patients with obstructive sleep apnea (PODESA): a randomized controlled trial

2022· article· en· W4295808117 on OpenAlexafffundabout
Jean Wong, Helen R. Doherty, Mandeep Singh, Stephen Choi, Naveed Siddiqui, David K. Lam, Nishanthi Liyanage, George Tomlinson, Frances Chung

Bibliographic record

VenueBMC Anesthesiology · 2022
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsMount Sinai HospitalHealth Sciences CentreSunnybrook Health Science CentreToronto Western HospitalWomen's College HospitalUniversity of TorontoUniversity Health Network
FundersOntario Ministry of Health and Long-Term CareResMedAnesthesia Patient Safety Foundation
KeywordsMedicineDeliriumAnesthesiologyRandomized controlled trialObstructive sleep apneaPain medicineSleep apneaIntensive care medicinePhysical therapyInternal medicineAnesthesia

Abstract

fetched live from OpenAlex

BACKGROUND: Obstructive sleep apnea (OSA) is associated with neurocognitive impairment - a known risk factor for postoperative delirium. However, it is unclear whether OSA increases the risk of postoperative delirium and whether treatment is protective. The objectives of this study were to identify OSA with a home sleep apnea test (HSAT) and to determine whether auto-titrating positive airway pressure (APAP) reduces postoperative delirium in older adults with newly diagnosed OSA undergoing elective hip or knee arthroplasty. METHODS: We conducted a multi-centre, randomized controlled trial at three academic hospitals in Canada. Research ethics board approval was obtained from the participating sites and informed consent was obtained from participants. Inclusion criteria were patients who were [Formula: see text]0 years and scheduled for elective hip or knee replacement. Patients with a STOP-Bang score of ≥ 3 had a HSAT. Patients were defined as having OSA if the apnea-hypopnea index was ≥ 10/h. These patients were randomized 1:1 to either: 1) APAP for 72 h postoperatively or until discharge, or 2) routine care after surgery. The primary outcome was postoperative delirium, assessed twice daily with the Confusion Assessment Method for 72 h or until discharge or by chart review. The secondary outcome measures included length of stay, and perioperative complications occurring within 30 days after surgery. RESULTS: Of 549 recruited patients, 474 completed a HSAT. A total of 234 patients with newly diagnosed OSA were randomized. The mean age was 68.2 (6.2) years and 58.6% were male. Analysis was performed on 220 patients. In total, 2.7% (6/220) patients developed delirium after surgery: 4.4% (5/114) patients in the routine care group, and 0.9% (1/106) patients in the treatment group (P = 0.21). The mean length of stay for the APAP vs. the routine care group was 2.9 (2.9) days vs. 3.5 (4.5) days (P = 0.24). On postoperative night 1, 53.5% of patients used APAP for 4 h/night or more, this decreased to 43.5% on night 2, and 24.6% on night 3. There was no difference in intraoperative and postoperative complications between the two groups. CONCLUSIONS: We had an unexpectedly low rate of postoperative delirium thus we were unable to determine if postoperative delirium was reduced in older adults with newly diagnosed OSA receiving APAP vs. those who did not receive APAP after elective knee or hip arthroplasty. TRIAL REGISTRATION: This trial was retrospectively registered in clinicaltrials.gov NCT02954224 on 03/11/2016.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.009
GPT teacher head0.250
Teacher spread0.240 · 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 designRandomized trial
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

Citations10
Published2022
Admission routes3
Has abstractyes

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