Is tissue still the issue? Lobectomy for suspicious lung nodules without confirmation of malignancy
Bibliographic record
Abstract
BACKGROUND: Histologic confirmation of malignancy has been indicated for a suspicious lung nodule prior to resection. The purpose of this study was to determine whether or not foregoing routine tissue biopsy increased the incidence of lobectomy for benign lesions. METHODS: Retrospective cohort of 256 patients who underwent thoracoscopic or open lobectomy for a confirmed or suspected pulmonary malignancy, with or without tissue diagnosis. Clinical, radiographic, and pathologic data were compared. RESULTS: Among 256 patients, 127 had attempted biopsy (group A) and 129 had no biopsy procedure (group B). There was no significant difference in the incidence of benign resections between the groups (Group A = 4 (3.2%) benign pathology vs group B = 9 (7.0%; P = 0.16). Group B had significantly lower operative time (127.1 vs 112.3 minutes; P = 0.004) and intraoperative complications (23 vs 37 patients; P = 0.03). There was a trend toward longer hospital stay and surgical waiting time in group A (6.6 vs 5.2 days, P = 0.24; 92.4 vs 66.2 days; P = 0.14, respectively). CONCLUSION: Foregoing biopsies and proceeding to lobectomy in selected patients with suspicious lung nodules is safe, did not increase the incidence of resected benign pathology, and may decrease surgical wait time. Patients should be carefully evaluated and counseled.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".