Utility of a deep learning model and a clinical model for predicting bleeding after endoscopic submucosal dissection in patients with early gastric cancer

Table 2 Logistic regression analysis for predictors of bleeding after endoscopic submucosal dissection in development set

Variables		Multivariable
		OR	95%CI	P value	ß regression coefficient
Age		0.98	0.96–0.99	0.001	-0.024
Sex	Female/male	1.54	1.09–2.19	0.015	0.435
Hypertension	No/yes	1.35	1.00–1.82	0.049	0.299
Diabetes mellitus	No/yes	1.27	0.92–1.75	0.145	0.238
Liver cirrhosis	No/yes	0.59	0.18–1.95	0.385	-0.532
Chronic kidney disease	No/yes	1.78	1.12–2.84	0.015	0.578
Aspirin	No/yes	1.51	0.62–3.69	0.363	0.414
P2Y12RA	No/yes	2.26	1.05–4.88	0.037	0.818
Warfarin	No/yes	1.51	0.28–8.07	0.629	0.413
DOAC	No/yes	3.24	0.76–13.82	0.113	1.174
Cilostazol	No/yes	1.35	0.35–5.18	0.662	0.300
NSAIDs	No/yes	2.65	0.77–9.14	0.124	0.973
Preprocedure management of AT	No indication	1
	Interruption	0.63	0.24–1.67	0.353	-0.464
	Replacement orHeparin bridge	3.32	0.47–23.60	0.231	1.199
Multiple	No/yes	1.48	0.92–2.38	0.104	0.393
Location	Upper	1
	Middle	1.97	1.14–3.41	0.015	0.680
	Lower	1.11	0.64–1.91	0.711	0.103
Size		1.04	1.03–1.05	< 0.001	0.036
Undifferentiated type	No/yes	0.56	0.20–1.57	0.271	-0.579
Piecemeal	No/yes	0.98	0.30–3.22	0.976	-0.019
Albumin, g/dL		1.33	0.89–2.00	0.168	0.286
INR		2.04	0.37–11.08	0.410	0.711

Clinical model = 1/[1 + exp(-1 × [-0.024 × Age in years + 0.435 × Sex (0: female, 1: male) + 0.299 × Hypertension (0: no, 1: yes) + 0.578 × Chronic kidney disease (0: no, yes: 1) + 0.818 × P2Y12RA (0: no, 1: yes) + 0.680 × Middle location (0: no, 1: yes) + 0.036 × Size in mm])]. AT: Antithrombotic; DOAC: Direct oral anticoagulant; ESD: Endoscopic submucosal dissection; INR: International normalized ratio; NSAIDs, Non-steroidal anti-inflammatory drugs; P2Y12RA: P2Y12 receptor antagonist; OR: Odds ratio; CI: Confidence interval.