Risk of major cardiovascular and cerebrovascular complications after elective surgery in patients with sleep-disordered breathing
Bibliographic record
Abstract
BACKGROUND: There is limited and conflicting data on whether sleep-disordered breathing (SDB) is associated with postoperative major cardiovascular and cerebrovascular events (MACCE), and mortality. OBJECTIVES: To determine whether SDB is associated with increased risks of MACCE, mortality and length of hospital stay. DESIGN: Retrospective cohort analysis from the Nationwide Inpatient Sample. SETTING: Adults who underwent elective abdominal, orthopaedic, prostatic, gynaecological, thoracic, transplant, vascular or cardiac surgery in the United States of America between 2011 and 2014. PATIENTS: The study cohort included 1813 974 surgical patients, of whom 185 615 (10.2%) had SDB. Emergency or urgent surgical procedures were excluded. MAIN OUTCOME MEASURES: The incidences of MACCE, respiratory and vascular complications, in-hospital mortality and mean length of hospital stay were stratified by SDB. Linear and logistic regression models were constructed to determine the independent association between SDB and outcomes of interest. RESULTS: The incidences of MACCE [25.3 vs. 19.8%, odds ratio (OR) 1.20, P < 0.001] and respiratory complications (11.75 vs. 8.0%, OR 1.43, P < 0.001) were significantly higher in patients with SDB than in those without SDB. SDB was associated with higher rates of atrial fibrillation (14.7 vs. 10.8%, P < 0.001), other arrhythmias (6.0 vs. 5.4%, P < 0.001) and congestive heart failure (9.8 vs. 7.1%, P < 0.001). SDB patients had a lower rate of myocardial infarction (3.1 vs. 3.4%, OR 0.69, P < 0.001), lower mortality (0.6 vs. 1.3%, P < 0.001) and shorter length of hospital stay (4.8 vs. 5.2 days, P < 0.001). CONCLUSION: SDB was associated with increased risks of MACCE, and respiratory and vascular complications, but had a lower incidence of in-hospital mortality and shorter length of hospital stay.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".