ArticleAmerican journal of translational research2025
Construction of a logistic model and GBM model for infection after spinal canal resection of intraspinal tumors.
Article in American journal of translational research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectivesTo identify risk factors for postoperative infection following intraspinal tumor (IT) resection, and to construct predictive models using a Logistic regression model and gradient boosting machine (GBM) algorithms.
methodsA retrospective study was conducted on 136 patients who developed postoperative infections after IT resection at Ziyang Central Hospital from November 2013 to October 2024. Logistic regression and GBM models were developed using R 4.3.2.
resultsLogistic regression analysis identified age >55 years, type II diabetes, operation time >3.3 h, interleukin-6 (IL-6)>5.5 ng/L, and procalcitonin (PCT)>0.3 ug/L as independent risk factors for infection after IT resection (
conclusionsThe identified risk factors and the predictive models offer valuable tools for early identification and prevention of postoperative infection following IT resection.
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