The association between the Nutrition‐Related index and morbidity following head and neck microsurgery
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: Despite consensus that preoperative nutritional assessment is of importance in the head and neck surgical oncology population, it remains unclear how exactly malnutrition is associated with perioperative morbidity especially among those undergoing microvascular surgery. We aimed to study this association to help inform preoperative risk stratification, guide the use of nutritional interventions, and ultimately help prevent malnutrition related morbidity. STUDY DESIGN: Database analysis. METHODS: Retrospective, linked analysis of the 2011 to 2016 National Surgical Quality Improvement Program. After identifying eligible patients and stratifying according to the Nutrition-Related Index, a univariate screen of preoperative demographic and clinical covariates was performed. Subsequently, propensity score matching was utilized to control for differences in baseline covariates. Perioperative complications and mortality were then analyzed using the propensity score-matched cohorts. RESULTS: Among 977 identified patients, 276 (28.2%) were malnourished. Malnourished patients had higher rates of comorbidity, were more likely to actively smoke, and were more likely to have primaries in the oropharynx or hypopharynx/larynx. After propensity score matching to control for confounders, malnourished patients had higher rates of pulmonary complications (21.5% vs. 11.6%, P < .01), higher rates of bleeding or need for transfusion (56.6% vs. 43.0%, P < .01), higher rates of venous thromboembolism (3.7% vs. 0.8%, P = .03), and a higher 30-day mortality rates (3.7% vs. 0.0%, P < .01). CONCLUSIONS: This nationwide analysis finds that 28.2% of patients undergoing surgery for head and neck cancers with free flap reconstruction are malnourished. Malnourishment was found to be independently associated with postoperative pulmonary complications, bleeding or need for transfusion, and 30-day mortality. LEVEL OF EVIDENCE: NA Laryngoscope, 130:375-380, 2020.
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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 | 0.000 |
| 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".