Active clearance of chest tubes is associated with reduced postoperative complications and costs after cardiac surgery: a propensity matched analysis
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Chest tubes are routinely used to evacuate shed mediastinal blood in the critical care setting in the early hours after heart surgery. Inadequate evacuation of shed mediastinal blood due to chest tube clogging may result in retained blood around the heart and lungs after cardiac surgery. The objective of this study was to compare if active chest tube clearance reduces the incidence of retained blood complications and associated hospital resource utilization after cardiac surgery. METHODS: Propensity matched analysis of 697 consecutive patients who underwent cardiac surgery at a single center. 302 patients served as a baseline control (Phase 0), 58 patients in a training and compliance verification period (Phase 1) and 337 were treated prospectively using active tube clearance (Phase 2). The need to drain retained blood, pleural effusions, postoperative atrial fibrillation, ICU resource utilization and hospital costs were assessed. RESULTS: Propensity matched patients in Phase 2 had a reduced need for drainage procedures for pleural effusions (22% vs. 8.1%, p < 0.001) and reduced postoperative atrial fibrillation (37 to 25%, P = 0.011). This corresponded with fewer hours in the ICU (43.5 [24-79] vs 30 [24-49], p = < 0.001), reduced median postoperative length of stay (6 [4-8] vs 5 [4-6.25], p < 0.001) median costs reduced by $1831.45 (- 3580.52;82.38, p = 0.04) and the mean costs reduced by an average of $2696 (- 6027.59;880.93, 0.116). CONCLUSIONS: This evidence supports the concept that efforts to actively maintain chest tube patency in early recovery is useful in improving outcomes and reducing resource utilization and costs after cardiac surgery. TRIAL REGISTRATION: Clinicaltrial.gov, NCT02145858, Registered: May 23, 2014.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 it