A Dynamic Online Nomogram for Predicting Postoperative Acute Kidney Injury After Sleeve Gastrectomy

28 April 2026 : Clinical Research

Sainan Li^{BE 1,2}, Chengxiang Liu

^{C 1*}, Chen Zhu^{B 1}, Juan Zhou^{D 1}, Miao Zhang^{F 3}, Hong Chen^{E 1}, Ye Zhang^{G 4}, Zengxia Liu^{A 2}

DOI: 10.12659/MSM.951259

Med Sci Monit 2026; 32:e951259

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Table 2 Comparison of ORs and 95% confidence intervals between full logistic regression model and final model.

Variable		Full logistic regression model			Final logistic regression model
Variable		OR	95% CI	P value	OR	95% CI	P value
Gender	Female	1.233	0.651–2.388	0.526	-	-	-
Gender	Male
Smoking	Yes	1.999	0.772–4.647	0.127	-	-	-
Smoking	No
ASA grade	I~II
ASA grade	III~IV	1.833	1.055–3.097
Hypertension	Yes	1.773	0.88–3.387	0.094
Hypertension	No
eGFR (per 10 mL/min/1.73 m)		1.713	1.382–2.134
Proteinuria	Yes	1.696	0.948–2.922	0.0645
Proteinuria	No
Hemoglobin (per 10 g/L)		1.261	1.032–1.551
Total infusion (per 100 mL)		0.902	0.841–0.967
CV_SBP (per 10%)		1.669	1.115–2.371
OR – odds ratio; CI – confidence interval; ASA – American Society of Anesthesiologists physical status classification; eGFR – estimated glomerular filtration rate; CV_SBP – coefficient of variation of systolic blood pressure; Total infusion – total intraoperative infusion volume. Odds ratios for continuous variables are expressed per unit increase as indicated: eGFR per 10 mL/min/1.73 m, hemoglobin per 10 g/L, total infusion volume per 100 mL, and CV_SBP per 10%. Variables not retained in the final model are indicated by “-”.

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