BACKGROUND:Acute pancreatitis(AP)is a complex and heterogeneous disease.We aimed to design and validate a prognostic nomogram for improving the prediction of short-term survival in patients with AP.METHODS:The clinica...BACKGROUND:Acute pancreatitis(AP)is a complex and heterogeneous disease.We aimed to design and validate a prognostic nomogram for improving the prediction of short-term survival in patients with AP.METHODS:The clinical data of 632 patients with AP were obtained from the Medical Information Mart for Intensive Care(MIMIC)-IV database.The nomogram for the prediction of 30-day,60-day and 90-day survival was developed by incorporating the risk factors identified by multivariate Cox analyses.RESULTS:Multivariate Cox proportional hazard model analysis showed that age(hazard ratio[HR]=1.06,95%confidence interval[95%CI]1.03-1.08,P<0.001),white blood cell count(HR=1.03,95%CI 1.00-1.06,P=0.046),systolic blood pressure(HR=0.99,95%CI 0.97-1.00,P=0.015),serum lactate level(HR=1.10,95%CI 1.01-1.20,P=0.023),and Simplified Acute Physiology Score II(HR=1.04,95%CI 1.02-1.06,P<0.001)were independent predictors of 90-day mortality in patients with AP.A prognostic nomogram model for 30-day,60-day,and 90-day survival based on these variables was built.Receiver operating characteristic(ROC)curve analysis demonstrated that the nomogram had good accuracy for predicting 30-day,60-day,and 90-day survival(area under the ROC curve:0.796,0.812,and 0.854,respectively;bootstrap-corrected C-index value:0.782,0.799,and 0.846,respectively).CONCLUSION:The nomogram-based prognostic model was able to accurately predict 30-day,60-day,and 90-day survival outcomes and thus may be of value for risk stratification and clinical decision-making for critically ill patients with AP.展开更多
基金supported by the Clinical Research Funds of Shanghai Jiao Tong University Affiliated Sixth People’s Hospital(ynhg202125)。
文摘BACKGROUND:Acute pancreatitis(AP)is a complex and heterogeneous disease.We aimed to design and validate a prognostic nomogram for improving the prediction of short-term survival in patients with AP.METHODS:The clinical data of 632 patients with AP were obtained from the Medical Information Mart for Intensive Care(MIMIC)-IV database.The nomogram for the prediction of 30-day,60-day and 90-day survival was developed by incorporating the risk factors identified by multivariate Cox analyses.RESULTS:Multivariate Cox proportional hazard model analysis showed that age(hazard ratio[HR]=1.06,95%confidence interval[95%CI]1.03-1.08,P<0.001),white blood cell count(HR=1.03,95%CI 1.00-1.06,P=0.046),systolic blood pressure(HR=0.99,95%CI 0.97-1.00,P=0.015),serum lactate level(HR=1.10,95%CI 1.01-1.20,P=0.023),and Simplified Acute Physiology Score II(HR=1.04,95%CI 1.02-1.06,P<0.001)were independent predictors of 90-day mortality in patients with AP.A prognostic nomogram model for 30-day,60-day,and 90-day survival based on these variables was built.Receiver operating characteristic(ROC)curve analysis demonstrated that the nomogram had good accuracy for predicting 30-day,60-day,and 90-day survival(area under the ROC curve:0.796,0.812,and 0.854,respectively;bootstrap-corrected C-index value:0.782,0.799,and 0.846,respectively).CONCLUSION:The nomogram-based prognostic model was able to accurately predict 30-day,60-day,and 90-day survival outcomes and thus may be of value for risk stratification and clinical decision-making for critically ill patients with AP.
