A nomogram for predicting the risk of intra-abdominal hypertension in critically ill patients based on ultrasound and clinical data.

Abstract

Intra-abdominal hypertension (IAH) is a common complication in critically ill patients. This study aimed to identify independent risk factors for IAH and generate a nomogram to distinguish IAH from non-IAH in these patients. We retrospectively analyzed 89 critically ill patients and divided them into an IAH group [intra-abdominal pressure (IAP) ≥12 mmHg] and a non-IAH group (IAP <12 mmHg) based on the IAP measured from their bladders. Ultrasound and clinical data were also measured. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for IAH. The correlation between IAP and independent risk factors was also assessed. Of these 89 patients, 45 (51%) were diagnosed with IAH. Univariate analysis showed there were significant differences in the right renal resistance index (RRRI) of the interlobar artery, the right diaphragm thickening rate (RDTR), and lactic acid (Lac) between IAH and non-IAH groups (P<0.001). Multivariate logistic regression analysis revealed that increasing RRRI, RDTR, and Lactic acid (Lac) were independent risk factors for IAH (P=0.001, P=0.001, and P=0.039, respectively). IAP was significantly correlated with RRRI, RDTR, and Lac (r=0.741, r=-0.774, and r=0.396, respectively; P<0.001). The prediction model based on regression analysis results was expressed as follows: predictive score = -17.274 + 31.125 × RRRI - 29.074 × RDTR + 0.621 × Lac. Meanwhile, the IAH nomogram prediction model was established with an area under the receiver operating characteristic (ROC) curve of 0.956 (95% confidence interval: 0.909-1.000). The nomogram showed good calibration for IAH with the Hosmer-Lemeshow test (P=0.864) and was found to be applicable within a wide threshold probability range, especially that higher than 0.40. The noninvasive nomogram based on ultrasound and clinical data has good diagnostic efficiency and can predict the risk of IAH. This nomogram may provide valuable guidance for clinical interventions to reduce IAH morbidity and mortality in critically ill patients.