Analysis of influencing factors of severity in acute pancreatitis using big data mining

To evaluate the epidemiological characteristics of acute pancreatitis (AP) and explore potential relationships between these factors and severity.

Data-sets of 5,659 patients with AP from health statistics and the Information Center of Jiangsu province, between 2014 and 2016, were analyzed. A self-organizing map (SOM) neural network was used for data clustering.

Biliary acute pancreatitis (BAP) (86.7%) was the most frequent etiological factor. A total of 804 (14.2%) patients had severe acute pancreatitis (SAP). The mean age of patients was 53.7 + 17.3 (range 12~94y). Most of the AP patients were married (75.4%); 6% of mild /moderately severe AP (MAP/MASP) patients were unmarried, which was less than SAP patients (P=0.016). AP patients with blood type AB in the general population (8.8%) was significantly lower than that of AP cases (13.9%) (P=0.019) and SAP cases(18.7%) (P=0.007). The number of AP patients in southern Jiangsu was much higher than that in northern Jiangsu province, especially in Nanjing (1229, 21.7%). The proportion of acute alcoholic pancreatitis (AAP) in the north of Jiangsu (Xuzhou 18.4%) was much higher than that in southern Jiangsu (Suzhou 2.6%). The whole sample was divided into five classes by SOM neural network. If BAP patients were male, old, divorced, and blood type AB or B, they were more likely to develop SAP. Middle-age, unmarried or divorced male patients with blood type B/AB who suffered from HAP or AAP were also more likely to develop SAP.

The number of unmarried patients with MAP/MASP was smaller than that of SAP. Blood types AB and B were more frequent in AP, especially in SAP. The differences between southern Jiangsu and northern Jiangsu, in number of AP patients and the proportion of AAP, were significant. In class I and class IV, the ratio of SAP was much higher than in other classes and the whole sample.