[Analysis of acute exacerbation from focal usual interstitial pneumonia following to lung cancer resection].
Bibliographic record
Abstract
To evaluate the susceptibility of patient with focal interstitial pneumonia (IP) to postoperative acute exacerbation, and to determine whether measuring serum level of several markers is useful for early detection of postoperative IP or not, we analyzed a total of 753 patients with primary lung cancer underwent thoracotomy. Twelve (1.6%) had postoperative IP. Eight of the 12 died due to IP and 9 of the 12 had focal IP findings on chest computed tomography (CT). Chest CT of 477 patients were reviewed retrospectively, and 51 (10.7%) had IP findings (diffuse 2.1%, focal 8.6%). Postoperative IP occurred in 17.6% of patients with IP findings, but only in 0.7% without such findings (p<0.01). Values of serum KL-6 decreased after lung resection. There were no changes in the value of serum TNF-alpha, IL-1beta, thrombomodulin and sICAM-1 after surgery. We conclude that focal IP is a risk factor of postoperative IP, and that it is not useful to measure serum markers for early detection of postoperative IP.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".