Preoperative Omega-6/Omega-3 Fatty Acid Ratio Could Predict Postoperative Outcomes in Patients with Surgically Resected Non-Small-Cell Lung Cancer
Bibliographic record
Abstract
Introduction: The aim of this study was to determine whether preoperative nutritional status and inflammatory status, specifically polyunsaturated acids and the omega 6/3 ratio, would affect postoperative outcomes and complications in patients with lung cancer undergoing lung resection. Methods: This prospective observational study included 68 patients with early-stage non-small-cell lung cancer who were candidates for radical surgery. A complete nutritional assessment was performed. The primary study variable was postoperative complications and mortality in the first 30 days. Descriptive, bivariate, and logistic regression analyses were carried out. Results: A total of 50 men (73.53%) and 18 women (26.47%) underwent surgery, with a median age of 64.2 (±9.74) years. The mean omega 6/3 ratio was 17.39 (±9.45). A complication occurred in 39.7% of the study sample (n = 27), the most common being persistent air leak in 23.53% (n = 16). After performing the bivariate analysis, the only variable that remained significant was the omega 6/3 ratio; we observed that it had a prognostic value for persistent air leak (p = 0.001) independent of age, sex, comorbidity, preoperative respiratory function, and approach or type of surgery. The remaining nutritional and inflammatory markers did not have a statistically significant association (p > 0.05) with postoperative complications. However, this significance was not maintained in the multivariate analysis by a small margin (p = 0.052; 95% CI: 0.77–1.41). Conclusions: Omega 6/3 ratio may be a prognostic factor for air leak, independent of the patient’s clinical and pathological characteristics.
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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 | 0.000 | 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) | 0.001 | 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".