预测急性胰腺炎病程严重程度的数学模型

I. Kolosovych, M. Bystrytska, I. Hanol
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The study was based on the results of an examination of 280 patients with acute pancreatitis, who were divided into two groups: the main group (n=187) – patients with a severe course and a comparison group (n=93) – patients with a mild and moderate course of the disease. To develop a mathematical model, the following indicators were analyzed and compared: duration of the disease before hospitalization, body mass index, number of leukocytes, C-reactive protein, blood glucose, procalcitonin, interleukin-6, immunoglobulin M to Helicobacter pylori, thrombin-antithrombin III complex, activity of tissue plasminogen activator, serum calcium, albumin corrected calcium, vitamin D. \nResults. Based on the obtained results, we developed a mathematical model for predicting the severity of the course of acute pancreatitis and revealed a correlation between the calculated scores (according to the mathematical model) and the APACHE II scale (severe course of 8 points and more). 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引用次数: 0

摘要

背景。急性胰腺炎的一个特点是发生并发症的风险高(50%的患者发生并发症),其死亡率可达15%,严重的病程在40-70%之间。事实证明,及时确定疾病的严重程度,选择适当的治疗策略,早期诊断和预防并发症可显著提高治疗效果。目的:建立结合钙磷代谢指标、凝血因子和幽门螺杆菌血清学检查数据预测急性胰腺炎病程严重程度的现代数学模型。材料和方法。这项研究基于对280名急性胰腺炎患者的检查结果,这些患者被分为两组:主要组(n=187)——重症患者,对照组(n=93)——轻度和中度病程患者。建立数学模型,对住院前病程、体重指数、白细胞数、c反应蛋白、血糖、降钙素原、白细胞介素-6、对幽门螺杆菌免疫球蛋白M、凝血酶-抗凝血酶III复合物、组织纤溶酶原激活物活性、血清钙、白蛋白校正钙、维生素d进行分析比较。根据所获得的结果,我们建立了预测急性胰腺炎病程严重程度的数学模型,并揭示了计算得分(根据数学模型)与APACHE II量表(严重病程8分及以上)之间的相关性。通过多元回归分析的方法逐步建立模型,指标数量从12个逐渐减少到8个,再减少到6个,我们提出了一个预测急性胰腺炎严重病程的高精度数学模型(R=0.82;R2 = 0.66;p < 0.0001)。所获得的数据表明,急性胰腺炎患者的“严重病程”因素与维生素D、免疫球蛋白M对幽门螺杆菌的含量和组织纤溶酶原激活物的活性有关,并证实了早期检测这些因素的必要性。因此,所建立的数学模型信息量大,可用于医学实践中对急性胰腺炎重症病程的早期预测。结论。急性胰腺炎患者的“严重病程”因素依赖于维生素D、对幽门螺杆菌免疫球蛋白M和组织纤溶酶原激活物活性的含量,并证实在疾病早期对其进行检测的必要性。采用多元回归分析方法,建立了预测急性胰腺炎重症病程的数学模型(R=0.82;R2 = 0.66;p < 0.0001)。
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MATHEMATICAL MODEL FOR PREDICTING THE SEVERITY OF THE COURSE OF ACUTE PANCREATITIS
Background. A feature of acute pancreatitis is the high risk of developing complications (occurring in 50% of patients), the mortality rate of which reaches 15%, and with a severe course varies within 40-70%. It has been proven that timely determination of the severity of the disease, selection of appropriate treatment tactics, early diagnosis of complications and their prevention significantly improve treatment results. Aim: to develop a modern mathematical model for predicting the severity of the course of acute pancreatitis, taking into account indicators of calcium-phosphorus metabolism, hemocoagulation factors and serological examination data for Helicobacter pylori. Materials and methods. The study was based on the results of an examination of 280 patients with acute pancreatitis, who were divided into two groups: the main group (n=187) – patients with a severe course and a comparison group (n=93) – patients with a mild and moderate course of the disease. To develop a mathematical model, the following indicators were analyzed and compared: duration of the disease before hospitalization, body mass index, number of leukocytes, C-reactive protein, blood glucose, procalcitonin, interleukin-6, immunoglobulin M to Helicobacter pylori, thrombin-antithrombin III complex, activity of tissue plasminogen activator, serum calcium, albumin corrected calcium, vitamin D. Results. Based on the obtained results, we developed a mathematical model for predicting the severity of the course of acute pancreatitis and revealed a correlation between the calculated scores (according to the mathematical model) and the APACHE II scale (severe course of 8 points and more). The step-by-step creation of a model by the method of multiple regression analysis with a gradual decrease in the number of indicators from 12 to 8 and to 6 allowed us to propose a mathematical model that has high accuracy for predicting the severe course of acute pancreatitis (R=0.82; R2=0.66; p< 0.0001). The obtained data demonstrate the dependence of the "severe course" factor on the content of vitamin D, immunoglobulin M to Helicobacter pylori and the activity of tissue plasminogen activator and substantiate the need for their early determination in patients with acute pancreatitis. Therefore, the developed mathematical model is highly informative and can be used in medical practice for early prediction of the severe course of acute pancreatitis. Conclusions. The dependence of the «severe course» factor in patients with acute pancreatitis on the content of vitamin D, immunoglobulin M to Helicobacter pylori and the activity of tissue plasminogen activator has been proven, and the need for their determination in the early period of the disease is substantiated. Using the method of multiple regression analysis, a mathematical model was developed that has high accuracy for predicting the severe course of acute pancreatitis (R=0.82; R2=0.66; p<0.0001).
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