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  • Author or Editor: Marc Ghanemx
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Using machine learning to predict 30-day readmission and reoperation following resection of supratentorial high-grade gliomas: an ACS NSQIP study involving 9418 patients

Abdul Karim Ghaith, Marc Ghanem, Cameron Zamanian, Antonio A. Bon-Nieves, Archis Bhandarkar, Karim Nathani, Mohamad Bydon, and Alfredo Quiñones-Hinojosa

OBJECTIVE

高级神经胶质瘤(HGGs)是最稀有的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.

开云体育世界杯赔率

使用ACS NSQIP数据库,作者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/andhttps://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.

InNeurosurgical Focus Volume 54 (2023): Issue 6 (Jun 2023): Machine Learning in Neurosurgery

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Surgical management of malignant melanotic nerve sheath tumors: an institutional experience and systematic review of the literature

Abdul Karim Ghaith, Sarah E. Johnson, Victor Gabriel El-Hajj, Oluwaseun O. Akinduro, Marc Ghanem, Gaetano De Biase, Loizos Michaelides, Antonio Bon Nieves, W. Richard Marsh, Bradford L. Currier, John L. Atkinson, Robert J. Spinner, and Mohamad Bydon

OBJECTIVE

Malignant melanotic nerve sheath tumors are rare tumors characterized by neoplastic melanin-producing Schwann cells. In this study, the authors report their institution’s experience in treating spinal and peripheral malignant melanotic nerve sheath tumors and compare their results with the literature.

开云体育世界杯赔率

Data were collected from 8 patients who underwent surgical treatment for malignant melanotic nerve sheath tumors between 1996 and 2023 at Mayo Clinic and 63 patients from the literature. Time-to-event analyses were performed for the combined group of 71 cases to evaluate the risk of recurrence, metastasis, and death based on tumor location and type of treatment received. Unpaired 2-sample t-tests and Fisher’s exact tests were used to determine statistical significance between groups.

RESULTS

Between 1996 and 2023, 8 patients with malignant melanotic nerve sheath tumors underwent surgery at the authors’ institution, while 63 patients were identified in the literature. The authors’ patients and those in the literature had the same mean age at diagnosis (43 years). At the authors’ institution, 5 patients (63%) experienced metastasis, 6 patients (75%) experienced long-term recurrence, and 5 patients (62.5%) died. In the literature, most patients (60.3%) were males, with a peak incidence between the 4th and 5th decades of life. Nineteen patients (31.1%) were diagnosed with Carney complex. Nerve root tumors accounted for most presentations (n = 39, 61.9%). Moreover, 24 patients (38.1%) had intradural lesions, with 54.2% (n = 13) being intramedullary and 45.8% (n = 11) extramedullary. Most patients underwent gross-total resection (GTR) (n = 41, 66.1%), followed by subtotal resection (STR) (n = 12, 19.4%), STR with radiation therapy (9.7%), and GTR with radiation therapy (4.8%). Sixteen patients (27.6%) experienced metastasis, 23 (39.7%) experienced recurrence, and 13 (22%) died. Kaplan-Meier analyses showed no significant differences among treatment approaches in terms of recurrence-free, metastasis-free, and overall survival (p > 0.05). Similar results were obtained when looking at the differences with respect to intradural versus nerve root location of the tumor (p > 0.05).

CONCLUSIONS

Malignant melanotic nerve sheath tumors are rare tumors with a high potential for malignancy. They carry a dismal prognosis, with a pooled local recurrence rate of 42%, distant metastasis rate of 27%, and mortality rate of 26%. The findings from this study suggest a trend favoring the use of GTR alone or STR with radiation therapy over STR alone. Mortality was similar regardless, which highlights the need for the development of effective treatment options to improve survival in patients with melanotic schwannomas.

InJournal of Neurosurgery: Spine Publish Before Print

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