Construction and validation of a machine learning algorithm-based predictive model for difficult colonoscopy insertion

Table 3 Multivariate Logistic regression analysis of factors associated with difficulty in colonoscope insertion base on the training set (n = 481)

Characteristics	B	SE	χ² value	P value	Odds ratio	Lower	Upper
Intercept	-3.945	0.473	-8.338	< 0.001	0.019	0.007	0.048
Abdominal circumference (cm)
< 77.5
77.5-91.9	0.639	0.292	2.191	0.028	1.895	1.065	3.350
≥ 92.0	0.240	0.279	0.859	0.390	1.271	0.730	2.188
Constipation	0.813	0.284	2.865	0.004	2.254	1.289	3.931
History of colorectal polyps	0.690	0.266	2.599	0.009	1.994	1.181	3.353
History of pelvic and abdominal surgery	0.396	0.250	1.580	0.114	1.485	0.904	2.418
Hypertension	-0.551	0.317	-1.736	0.083	0.576	0.303	1.055
Diabetes	0.740	0.341	2.170	0.030	2.096	1.066	4.081
Self-rating anxiety scale (scores)	0.069	0.013	5.218	< 0.001	1.071	1.044	1.100