Relationship of Carbon Monoxide Pulmonary Diffusing Capacity to Postoperative Cardiopulmonary Complications in Patients Undergoing Pneumonectomy
Bibliographic record
Abstract
This retrospective analytic study evaluated whether abnormal diffusing capacity for carbon monoxide (DLCO) is a predictor of postoperative morbidity and mortality in patients undergoing pneumonectomy for lung cancer. The medical records of patients undergoing pneumonectomy at Vancouver General Hospital between January 1992 and December 1997 were reviewed. Postoperative complications occurring within 30 days of resection were classified into mortality, and cardiovascular, pulmonary, and technical complications. A total of 151 pneumonectomy cases were reviewed. There were 100 men (66%) and 51 women (34%) with a mean age of 61 years. Complications occurred in 73 patients (48%), including mortality in eight (5%), cardiovascular morbidity in 50 (33%), pulmonary morbidity in 30 (20%), and technical morbidity in 22 (15%). Arrhythmia (21%) and pulmonary edema (13%) were the two major cardiovascular complications. Patients with complications had a greater smoking history, a longer hospital stay, a lower forced expiratory volume in 1 second (FEV1), a lower FEV1/forced vital capacity (FVC) ratio, a lower DLCO, and a lower DLCO/alveolar volume (VA) ratio than patients without complications. A DLCO of 70% predicted was the best functional predictor of postoperative complications, with a complication rate of 94% in patients with a DLCO of less than 70% predicted compared with 27% in patients with a DLCO of at least 70% predicted (sensitivity, 62%; specificity, 96%). However, technical morbidity was not related to preoperative lung function variables, including DLCO. Patients with a DLCO of at least 70% predicted had a low postpneumonectomy complication rate. Although cardiac arrhythmia was the major cause of morbidity, pulmonary edema was the major cause of mortality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".