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Record W3042660524 · doi:10.1213/ane.0000000000005005

Postoperative Critical Events Associated With Obstructive Sleep Apnea: Results From the Society of Anesthesia and Sleep Medicine Obstructive Sleep Apnea Registry

2020· article· en· W3042660524 on OpenAlexaff
Norman Bolden, Karen L. Posner, Karen B. Domino, Dennis Auckley, Jonathan L. Benumof, Seth T. Herway, David R. Hillman, Shawn L. Mincer, Frank J. Overdyk, David Samuels, Lindsay L. Warner, Toby N. Weingarten, Frances Chung

Bibliographic record

VenueAnesthesia & Analgesia · 2020
Typearticle
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersNational Center for Advancing Translational Sciences
KeywordsMedicineObstructive sleep apneaAnesthesiaBody mass indexOdds ratioPerioperativeConfidence intervalContinuous positive airway pressureApneaPolysomnographyPediatricsInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Obstructive sleep apnea (OSA) patients are at increased risk for pulmonary and cardiovascular complications; perioperative mortality risk is unclear. This report analyzes cases submitted to the OSA Death and Near Miss Registry, focusing on factors associated with poor outcomes after an OSA-related event. We hypothesized that more severe outcomes would be associated with OSA severity, less intense monitoring, and higher cumulative opioid doses. METHODS: Inclusion criteria were age ≥18 years, OSA diagnosed or suspected, event related to OSA, and event occurrence 1992 or later and <30 days postoperatively. Factors associated with death or brain damage versus other critical events were analyzed by tests of association and odds ratios (OR; 95% confidence intervals [CIs]). RESULTS: Sixty-six cases met inclusion criteria with known OSA diagnosed in 55 (83%). Patients were middle aged (mean = 53, standard deviation [SD] = 15 years), American Society of Anesthesiologists (ASA) III (59%, n = 38), and obese (mean body mass index [BMI] = 38, SD = 9 kg/m); most had inpatient (80%, n = 51) and elective (90%, n = 56) procedures with general anesthesia (88%, n = 58). Most events occurred on the ward (56%, n = 37), and 14 (21%) occurred at home. Most events (76%, n = 50) occurred within 24 hours of anesthesia end. Ninety-seven percent (n = 64) received opioids within the 24 hours before the event, and two-thirds (41 of 62) also received sedatives. Positive airway pressure devices and/or supplemental oxygen were in use at the time of critical events in 7.5% and 52% of cases, respectively. Sixty-five percent (n = 43) of patients died or had brain damage; 35% (n = 23) experienced other critical events. Continuous central respiratory monitoring was in use for 3 of 43 (7%) of cases where death or brain damage resulted. Death or brain damage was (1) less common when the event was witnessed than unwitnessed (OR = 0.036; 95% CI, 0.007-0.181; P < .001); (2) less common with supplemental oxygen in place (OR = 0.227; 95% CI, 0.070-0.740; P = .011); (3) less common with respiratory monitoring versus no monitoring (OR = 0.109; 95% CI, 0.031-0.384; P < .001); and (4) more common in patients who received both opioids and sedatives than opioids alone (OR = 4.133; 95% CI, 1.348-12.672; P = .011). No evidence for an association was observed between outcomes and OSA severity or cumulative opioid dose. CONCLUSIONS: Death and brain damage were more likely to occur with unwitnessed events, no supplemental oxygen, lack of respiratory monitoring, and coadministration of opioids and sedatives. It is important that efforts be directed at providing more effective monitoring for OSA patients following surgery, and clinicians consider the potentially dangerous effects of opioids and sedatives-especially when combined-when managing OSA patients postoperatively.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.023
GPT teacher head0.278
Teacher spread0.255 · 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

Citations78
Published2020
Admission routes1
Has abstractyes

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