Establishment of risk prediction nomograph model for sepsis related acute respiratory distress syndrome

Abstract

To explore the risk factors of acute respiratory distress syndrome (ARDS) in patients with sepsis and to construct a risk nomogram model. The clinical data of 234 sepsis patients admitted to the intensive care unit (ICU) of Tianjin Hospital from January 2019 to May 2022 were retrospectively analyzed. The patients were divided into non-ARDS group (156 cases) and ARDS group (78 cases) according to the presence or absence of ARDS. The gender, age, hypertension, diabetes, coronary heart disease, smoking history, history of alcoholism, temperature, respiratory rate (RR), mean arterial pressure (MAP), pulmonary infection, white blood cell count (WBC), hemoglobin (Hb), platelet count (PLT), prothrombin time (PT), activated partial thromboplastin time (APTT), fibrinogen (FIB), D-dimer, oxygenation index (PaO2/FiO2), lactic acid (Lac), procalcitonin (PCT), brain natriuretic peptide (BNP), albumin (ALB), blood urea nitrogen (BUN), serum creatinine (SCr), acute physiology and chronic health evaluation II (APACHE II), sequential organ failure assessment (SOFA) were compared between the two groups. Univariate and multivariate Logistic regression were used to analyze the risk factors of sepsis related ARDS. Based on the screened independent risk factors, a nomogram prediction model was constructed, and Bootstrap method was used for internal verification. The receiver operator characteristic curve (ROC curve) was drawn, and the area under the ROC curve (AUC) was calculated to verify the prediction and accuracy of the model. There were no significant differences in gender, age, hypertension, diabetes, coronary heart disease, smoking history, alcoholism history, temperature, WBC, Hb, PLT, PT, APTT, FIB, PCT, BNP and SCr between the two groups. There were significant differences in RR, MAP, pulmonary infection, D-dimer, PaO2/FiO2, Lac, ALB, BUN, APACHE II score and SOFA score (all P < 0.05). Multivariate Logistic regression analysis showed that increased RR, low MAP, pulmonary infection, high Lac and high APACHE II score were independent risk factors for sepsis related ARDS [RR: odds ratio (OR) = 1.167, 95% confidence interval (95%CI) was 1.019-1.336; MAP: OR = 0.962, 95%CI was 0.932-0.994; pulmonary infection: OR = 0.428, 95%CI was 0.189-0.966; Lac: OR = 1.684, 95%CI was 1.036-2.735; APACHE II score: OR = 1.577, 95%CI was 1.202-2.067; all P < 0.05]. Based on the above independent risk factors, a risk nomograph model was established to predict sepsis related ARDS (accuracy was 81.62%, sensitivity was 66.67%, specificity was 89.10%). The predicted values were basically consistent with the measured values, and the AUC was 0.866 (95%CI was 0.819-0.914). Increased RR, low MAP, pulmonary infection, high Lac and high APACHE II score are independent risk factors for sepsis related ARDS. Establishment of a risk nomograph model based on these factors may guide to predict the risk of ARDS in sepsis patients.