O-030 * THE BURDEN OF DEATH FOLLOWING DISCHARGE AFTER LOBECTOMY
Bibliographic record
Abstract
Objectives: Pulmonary lobectomy is the most commonly performed surgery for lung cancer and remains the gold standard operative treatment. The reported surgical mortality from this procedure rarely differentiates between in-hospital mortality (IHM) and early post-discharge mortality (PDM). Within this study, we aim to examine the IHM and 90-day PDM over time and identify outcome predictors including patient characteristics, comorbidity, and system level factors. Methods: Data from 2005 to 2011 were acquired from a linked Ontario population-based database and we reported proportional mortality and cumulative survival attributable to IHM and PDM. Multivariate logistic and Cox regression analyses were performed to examine the role of variables associated with mortality. Results: Of 5389 patients who underwent lobectomy for non-small-cell lung cancer, median length of stay was 6 (1-30) days. IHM was 1.4% (n = 73) and PDM was an additional 1.9% (n = 101) within 90 days post-lobectomy discharge. Logistic regression suggests age [odds ratio (OR): 1.5 (1.3-1.8)], MI [OR: 3.6 (1.8-7.0)], CHF [OR: 5.8 (2.4-13.8)], COPD [OR: 1.9 (1.1-3.2)], preoperative PET [OR: 2.7 (1.1-7.0)], peptic ulcer disease [OR: 22.1 (4.1-117.4)], hemiplegia [OR: 15.8 (1.8-141.1)], primary lung cancer [OR: 0.5 (0.3-0.8)] and year of surgery [OR: 1.0 (0.8-1.0)] were predictive of IHM. Length of hospital stay [hazard ratio (HR): 1.1 (1.0-1.1)], male gender [HR: 1.5 (1.0-2.3)], age [HR: 1.1 (1.0-1.3)], metastatic cancer [HR: 2.6 (1.7-4.0)] were predictive of PDM. All other factors were not significant. Conclusions: PDM represents a substantive and under-reported burden of operative mortality. More than half of post-lobectomy mortality occurs post-discharge and the rate remained unchanged over the study while IHM fell with time, suggesting that the improvement seen in mortality is exclusive to the smaller IHM. Patient factors play a significant role in both IHM and PDM, which identifies the importance of appropriate patient selection and a need for continued investigation of risk factors of this significant mortality. Disclosure: No significant relationships.
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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 | 0.001 | 0.000 |
| 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".