Lung surgery: identifying the subgroup at risk for sputum retention
Bibliographic record
Abstract
OBJECTIVES: Sputum retention after lung surgery is a potentially lethal condition, which can progress to atelectasis, pneumonia and respiratory failure requiring ventilatory support. Previous studies have concentrated on the treatment of postoperative respiratory complications but few have studied the risk factors for sputum retention. This prospective study was designed to identify the risk factors which may lead to the development of sputum retention after lung surgery. METHODS: Three hundred sixty-one patients underwent lung surgery between January 1997 and December 1999 in a specialist Thoracic Surgery Unit (pneumonectomy, lobectomy, wedge or segmental resection, bullectomy, etc). Preoperative and intraoperative data collected prospectively included potential risk factors: chronic obstructive airway disease (COAD), forced expiratory volume in 1 s (FEV1)<50%, current smokers, ischaemic heart disease (IHD), cerebrovascular disease (CVA), resection of phrenic or recurrent laryngeal nerve, or absence of regional analgesia. Univariate and multivariate analysis was performed. RESULTS: Sputum related complications occurred in 108 patients (30%). There were 17 deaths of which nine were due to complications related to sputum retention. Univariate analysis confirmed current smokers (n=128), COAD (n=103), IHD (n=41), prior history of CVA (n=16), FEV1<50% (n=48), and absence of regional anaesthesia as significant risk factors (P<0.01). The multivariate analysis confirmed current smokers, IHD and absence of regional anaesthesia as risk factors. CONCLUSIONS: A subgroup of lung surgery patients at high risk for postoperative sputum retention can be predicted by the presence of one of the following criteria: current smokers, history of COAD, CVA, or IHD, and absence of regional analgesia. Prophylactic measures should be considered in this group to reduce the incidence of sputum retention.
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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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| 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".