Assessment of the Predictive Value of the Modified Frailty Index for Clavien-Dindo Grade IV Critical Care Complications in Major Head and Neck Cancer Operations
Bibliographic record
Abstract
IMPORTANCE: Functional status and physiologic deficits independent of age are being recognized for surgical risk stratification. Frailty is expressed as a combination of decreased physiologic reserve and multisystem impairments distinct from normal aging processes. OBJECTIVE: To assess the predictive value of the Modified Frailty Index (mFI) for Clavien-Dindo grade IV (CDIV) (intensive care unit-level complications) and grade V (mortality) after major head and neck oncologic surgery. DESIGN, SETTING, AND PARTICIPANTS: Retrospective analysis of prospectively collected American College of Surgeons National Surgical Quality Improvement Program data. All major head and neck cancer operations data were obtained from the January 1, 2006, to December 31, 2013, American College of Surgeons National Surgical Quality Improvement Program databases. Fifteen variables composed a previously validated mFI, with higher mFIs identifying more frail patients. Clavien-Dindo grade IV and mortality were defined using a preexisting mapping scheme from the Canadian Study of Health and Aging. Multivariable logistic regression analyses were performed. MAIN OUTCOMES AND MEASURES: The primary outcome measures were Clavien-Dindo Grade IV critical care complications and Grade V complications (mortality). Second outcomes included morbidity, readmission, and reoperation. RESULTS: There were 1193 major head and neck operations in the American College of Surgeons National Surgical Quality Improvement Program databases, with 86 (7.2%) CDIV complications. The mean (SD) age of all patients was 63.4 (12.4) years, and 67.7% (807 of 1193) were male. Clavien-Dindo grade IV significantly increased from 4.6% (22 of 483) to 100% (1 of 1) from nonfrail to the frailest patients (R2 = 0.79, P < .001). Mortality increased with the mFI (but not significantly) from 0.8% (4 of 483) to 3.6% (2 of 55) (R2 = 0.46, P = .42). Overall morbidity was not significantly associated or correlated with the mFI. On cross tabulation, increases in the mFI led to more CDIV complications in patients undergoing glossectomy (P = .03), mandibulectomy (P = .02), or laryngectomy (P = .002). Patients undergoing pharyngectomy or esophagectomy did not have significant increases in CDIV complications by the mFI. The coefficients of determination for each category were R2 = 0.62 for glossectomy, R2 = 0.72 for mandibulectomy, R2 = 0.97 for laryngectomy, R2 = 0.94 for pharyngectomy, and R2 = 1.00 for esophagectomy. On multivariable analysis, the mFI was associated with CDIV complications (odds ratio, 1.65; 95% CI, 1.15-2.37) but not mortality (odds ratio, 0.78; 95% CI, 0.34-1.76). CONCLUSIONS AND RELEVANCE: The mFI is predictive of postoperative critical care support after surgery for head and neck cancer. Specifically, increases in mFIs were strongly associated with CDIV complications for glossectomy, mandibulectomy, and laryngectomy. Classifying patients by their functional status using the mFI may help predict outcomes after head and neck oncologic surgery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".