Incidence of and Risk Factors for Pulmonary Complications after Nonthoracic Surgery
Bibliographic record
Abstract
The prediction of postoperative pulmonary complications is an underinvestigated field. We conducted a prospective cohort study (with postoperative pulmonary complications ascertained by an investigator blinded to perioperative variables) to determine the risk factors for pulmonary complications after elective nonthoracic surgery. Of 1,055 consecutive patients attending the Pre-Admission Clinic of a university hospital (mean age 55 years, 50% men, 15% with history of obstructive airways disease), 28 (2.7%) suffered a postoperative pulmonary complication within 7 days of surgery: 13 patients developed respiratory failure requiring ventilatory support, 9 pneumonia, 5 atelectasis requiring bronchoscopic intervention, and 1 pneumothorax requiring intervention. Mean lengths of stay were substantially prolonged for those patients who developed pulmonary complications within 7 days of surgery: 27.9 days versus 4.5 days, p = 0.006. Eight variables were statistically significantly associated with pulmonary complications on bivariate analyses. Multivariate analyses revealed that four were independently associated with increased risk of pulmonary complications: age (odds ratio [OR] 5.9 for age >/= 65 years, p < 0.001), positive cough test (OR 3.8, P = 0.01), perioperative nasogastric tube (OR 7.7, p < 0.001), and duration of anesthesia (OR 3.3 for operations lasting at least 2.5 hours, p = 0.008). Thus, several perioperative factors predict an increased risk for pulmonary complications after elective nonthoracic surgery.
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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 | 0.001 | 0.006 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".