Machine learning for modeling and identifying risk factors of pancreatic fistula

Table 2 Correlation matrix

Correlated groups parameters	No fistula-0; biochemical leak-1; fistula-2		No fistula and biochemical leak- 0; fistula B/C-1		No fistula-0; biochemical leak and fistula B/C-1
	r value	P value	r value	P value	r value	P value
Age	-0.23	0.021a	-0.24	0.014b	-0.21	0.031a
Enterostomy	-0.05	0.637	-0.06	0.536	-0.04	0.676
Roux anastomosis	-0.2	0.064	-0.09	0.409	-0.22	0.04
Blood vessel resection	-0.13	0.226	-0.2	0.071	-0.12	0.288
Disease stage	-0.12	0.251	-0.11	0.3	-0.12	0.259
Blood amylase 3-5 days	0.25	0.017b	0.24	0.024a	0.24	0.02a
Drain amylase 3-5 days	0.74	8.37 × 10-9b	0.51	0.0004b	0.7	1.56 × 107b
Leukocytes 2-3 days	0.16	0.121	0.09	0.371	0.17	0.1
Tumor morphology	0.16	0.127	0.12	0.222	0.16	0.117
Tumor size, mm3	-0.01	0.934	-0.06	0.571	0.004b	0.975
Perineural invasion	-0.31	0.002b	-0.18	0.062	-0.33	0.001b
Vascular invasion	-0.32	0.001b	-0.17	0.088	-0.35	0.0003b
BMI	-0.04	0.239	0.001	0.672	-0.04	0.382
Pancreatic duct diameter	-0.08	0.437	0.03	0.743	-0.11	0.293

^aP < 0.05.

^bP < 0.0167 (Bonferroni correction, P < α/3).

BMI: Body mass index. The qualitative parameters were studied in numerical equivalent. For disease stages I, IIa, IIb, III, and IV the values were considered 1, 2, 2.5, 3, and 4, respectively. Tumor morphological types were divided into numerical classes by prognosis, from positive to negative: Benign tumor-0, neuroendocrine tumor-1, and adenocarcinoma-2[12,57].