Prevalence and Clinical Relevance of Abnormal Ventilation in Lung Cancer Patients prior to Lung Resection
Bibliographic record
Abstract
INTRODUCTION: Despite the use of modern minimally invasive surgical techniques, post-operative complications following lung cancer resection remain common and challenging to predict. Pulmonary ventilation imaging modalities offer detailed regional assessment of airflow obstruction and are highly sensitive to subclinical airway and/or parenchymal disease. Nevertheless, ventilation imaging is seldom integrated into pre-operative lung function assessment and risk stratification procedures. Therefore, the objective of this thesis was to quantify the burden of ventilation defects observed by Technegas SPECT and 129Xe MRI before lung cancer resection and establish their association with the occurrence and clinical impact of post-operative complications. METHODS: Patients undergoing lung cancer resection at St. Joseph’s Healthcare Hamilton were recruited into a prospective, proof-of-concept, six-week observational study. Participants were evaluated prior to resection surgery to document baseline demographics and clinical characteristics, performed standard pulmonary function tests and sputum induction, and underwent Technegas SPECT and 129Xe MRI to assess ventilation. Abnormal ventilation was quantified as the ventilation defect percent (VDP) and was considered abnormal if VDP was ≥mean+2 standard deviations of a healthy population. Following surgery, participants were followed for 4 weeks to document the incidence of post-operative complications, as specified by the Ottawa TM&M categorization system, and the length of hospital stay. RESULTS: One hundred and twenty-three participants were enrolled, of whom 103 were evaluated pre-operatively and followed for post-operative outcomes. Of the 103 participants (69±8 years, 58% female), 89% (92/103) underwent minimally invasive surgery, and 74% (76/103) underwent lobectomy. Abnormal ventilation was observed pre-operatively by Technegas SPECT and 129Xe MRI for 59% (58/99) and 84% (82/98) of participants, respectively. In a subset of 69 participants in whom sputum was collected, 51% (35/69) had intraluminal inflammation. A total of 64 post-operative complications occurred; 16 (25%) were pulmonary, and 48 (75%) were pleural complications. A post-operative complication occurred in 42% (41/103) of participants. Pre-operative Technegas SPECT and 129Xe MRI VDP were higher for participants with post-operative complications compared to those without (Technegas SPECT: 26±17% vs 19±7%, p=0.02; 129Xe MRI: 13±12% vs 7±6% p=0.003) and were positively correlated with post-operative length of hospital stay (Technegas SPECT: r=0.43, p<0.0001; 129Xe MRI: r=0.49, p<0.0001). Multivariable regression models revealed that preoperative Technegas SPECT and 129Xe MRI VDP were predictors of post-operative complications (Technegas SPECT: Odds ratio=1.08, p=0.005; 129Xe MRI: Odds ratio=1.16, p=0.002) and post-operative length of hospital stay (Technegas SPECT: unstandardized β=0.13, p<0.001; 129Xe MRI: unstandardized β=0.24, p<0.001). CONCLUSIONS: Abnormal ventilation, quantified by Technegas SPECT and 129Xe MRI VDP, is prevalent prior to lung cancer resection and a predictor of post-operative complications and length of hospital stay.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".