Using machine learning to predict 30-day readmission and reoperation following resection of supratentorial high-grade gliomas: an ACS NSQIP study involving 9418 patients.

OBJECTIVE: High-grade gliomas (HGGs) are among the rarest yet most aggressive tumor types in neurosurgical practice. In the current literature, few studies have assessed the drivers of early outcomes following resection of these tumors and investigated their association with quality of care. The authors aimed to identify the clinical predictors for 30-day readmission and reoperation following HGG surgery using the American College of Surgeons (ACS) National Surgical Quality Improvement Project (NSQIP) database and sought to create web-based applications predicting each outcome. METHODS: Using the ACS NSQIP database, the authors conducted a retrospective, multicenter cohort analysis of patients who underwent resection of supratentorial HGGs between January 1, 2016, and December 31, 2020. Demographics and comorbidities were extracted. The primary outcomes were 30-day unplanned readmission and reoperation. A stratified 80:20 split of the available data was carried out. Supervised machine learning algorithms were trained to predict 30-day outcomes. RESULTS: A total of 9418 patients were included in our cohort. The observed rate of unplanned readmission within 30 days of surgery was 13.0% (n = 1221). In terms of predictors, weight, chronic steroid use, preoperative blood urea nitrogen level, and white blood cell count were associated with a higher risk of readmission. The observed rate of unplanned reoperation within 30 days of surgery was 5.2% (n = 489). In terms of predictors, increased weight, longer operative time, and more days between hospital admission and operation were associated with an increased risk of early reoperation. The random forest algorithm showed the highest predictive performance for early readmission (area under the curve [AUC] = 0.967), while the XGBoost algorithm showed the highest predictive performance for early reoperation (AUC = 0.985). Web-based tools for both outcomes were deployed (https://glioma-readmission.herokuapp.com/ and https://glioma-reoperation.herokuapp.com/). CONCLUSIONS: In this study, the authors provide the first nationwide analysis for short-term outcomes in patients undergoing resection of supratentorial HGGs. Multiple patient, hospital, and admission factors were associated with readmission and reoperation, confirmed by machine learning predicting patients' prognosis, leading to better planning preoperatively and subsequently improved personalized patient care.

Reconstruction of Palatal Defects Using a Composite Chondromucosal Nasoseptal Flap and Comparative Analysis.

OBJECTIVE: The use of composite chondromucosal nasal septal flaps (ccNSF) has been demonstrated to be effective in cadaveric studies for the anterior skull base and the orbit. However, their application in the clinical setting remains unexplored. Our study aims to introduce a new method for treating palatal defects using ccNSF. Additionally, we studied the average NSF area and compared it to the average palate area. METHODS: We collected 108 CT scans from the medical records of patients without head and neck pathologies from a tertiary medical institution. We quantified the quadrangular (septal) cartilage and palate areas. Furthermore, we included a clinical case in which we used the ccNSF for the palatal defect reconstruction. This was to compare the mean area between the palate and the septal cartilage. RESULTS: The ccNSF covered the palatal defect without any significant complications for the first 9 months of follow-up. A total of 102 CT scans met the inclusion criteria and were measured. We found that the mean quadrangular cartilage had a length of 2.50 (±0.52) cm, a width of 2.28 (±0.51) cm, and an area of 5.43 (±1.68) cm2. The mean palate length was 2.73 (±0.44) cm, with a width of 3.13 (±0.34) cm, and area of 7.87 (±1.43) cm2. CONCLUSIONS: The ccNSF proved successful in palatal defect reconstruction, resulting in positive outcomes and no major complications until the 9-month follow-up. The ccNSF is a useful flap that avoids the use of free flap transfer and its associated morbidities. LEVEL OF EVIDENCE: 4 Laryngoscope, 2024.