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find Author "HU Shibo" 1 results
  • Factors and prediction model for catheter obstruction in hyperthermic intraperitoneal chemotherapy: Based on machine learning

    ObjectiveTo explore the risk factors affecting catheter obstruction during hyperthermic intraperitoneal chemotherapy (HIPEC). MethodsBased on the inclusion and exclusion criteria, the patients who underwent HIPEC at the First Affiliated Hospital of Xi’an Jiaotong University from February 2023 to December 2023 were retrospectively collected. The data were analyzed using univariate analysis and machine learning. The statistical significance was defined as α=0.05. ResultsA total of 210 patients underwent HIPEC and met the inclusion criteria were included, 51 (24.3%) experienced catheter obstruction. The univariate analysis revealed that the inflow-outflow temperature gradient of the perfusate (ΔT of the perfusate), flow velocity of perfusate, neoadjuvant chemotherapy exposure, hypertension status, surgical approach, and HIPEC catheter length were associated with catheter obstruction (P<0.05). Subsequently, combining the results of the univariate analysis with feature values screened by machine learning, the following factors were selected, including HIPEC catheter length, ΔT of the perfusate, flow velocity of perfusate, age, gender, neoadjuvant chemotherapy exposure, fibrinogen level, hypertension status, surgical approach, and blood transfusion. A predictive model for HIPEC catheter obstruction based on these features was established, achieving an area under the receiver operating characteristic curve (95%CI) of 0.825 (0.757, 0.893). ConclusionThis study preliminarily identifies key factors influencing the incidence of catheter obstruction during HIPEC treatment, such as ΔT of the perfusate, flow velocity of perfusate, neoadjuvant chemotherapy exposure, surgical approach, HIPEC catheter length, and hypertension, continuously monitoring these factors, thereby reducing the risk of catheter obstruction.

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