Morbidity and Mortality of Surgical Lung Biopsy and Implications of Histopathologic Findings in Interstitial Lung Disease
Bibliographic record
Abstract
Rationale: Management and prognosis varies among different Interstitial Lung Diseases (ILDs), necessitating an accurate diagnosis. When pathology is needed for diagnosis, a surgical lung biopsy (SLB) is usually required. Existing limited data suggests high short-term mortality rates associated with SLB in ILD. The primary objective of this study was to evaluate the morbidity and mortality associated with SLB in ILD in a specialized center. Methods: We performed a single centre retrospective case series which included patients who underwent a SLB for ILD between 2005 and 2012 at the Toronto General Hospital. ILD was defined according to pathology report. Descriptive statistics were used to summarize the data. Crude 30 and 60-day post-operative mortality and hospital length of stay was determined for all study participants. Associations with hospital length of stay were evaluated using log-linear multivariable regression. Results: 3134 patients were screened to identify 75 patients who underwent a SLB and had ILD on pathology. Baseline characteristics are summarized in Table 1. The 30-day post-operative mortality rate was 2.7%, with no additional deaths at 60-days. Both patients who died were hospitalized and on supplemental oxygen, with one requiring mechanical ventilation at the time of SLB. Post-operative outcomes are shown in Table 2. Need for hospitalization and intubation at the time of procedure were significantly associated with longer hospital length of stay p<0.0001 and p=0.006, respectively. Conclusions: SLB was well tolerated in patients who were not critically ill at the time of procedure.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".