A Novel Nomogram for Predicting Survival in Patients with Severe Acute Pancreatitis: An Analysis Based on the Large MIMIC-III Clinical Database

被引:7
|
作者
Han, Didi [1 ,2 ]
Xu, Fengshuo [1 ,2 ]
Li, Chengzhuo [1 ,2 ]
Zhang, Luming [3 ]
Yang, Rui [1 ,2 ]
Zheng, Shuai [1 ,4 ]
Wang, Zichen [5 ]
Lyu, Jun [1 ,2 ]
机构
[1] Jinan Univ, Dept Clin Res, Affiliated Hosp 1, Guangzhou 510630, Guangdong, Peoples R China
[2] Xi An Jiao Tong Univ, Sch Publ Hlth, Hlth Sci Ctr, Xian 710061, Shaanxi, Peoples R China
[3] Jinan Univ, Intens Care Unit, Affiliated Hosp 1, Guangzhou 510630, Peoples R China
[4] Shannxi Univ Chinese Med, Sch Publ Hlth, Xianyang, Shaanxi, Peoples R China
[5] Univ Calif Irvine, Dept Publ Hlth, Irvine, CA 92697 USA
关键词
BIG DATA; MORTALITY; RISK; EPIDEMIOLOGY; GUIDELINES; ETIOLOGY; OBESITY; SCORE;
D O I
10.1155/2021/9190908
中图分类号
R4 [临床医学];
学科分类号
1002 ; 100602 ;
摘要
Background. Severe acute pancreatitis (SAP) can cause various complications. Septic shock is a relatively common and serious complication that causes uncontrolled systemic inflammatory response syndrome, which is one of the main causes of death. This study aimed to develop a nomogram for predicting the overall survival of SAP patients during the initial 24 hours following admission. Materials and Methods. All the data utilized in this study were obtained from the MIMIC-III (Medical Information Mart for Intensive Care III) database. The data were analyzed using multivariate Cox regression, and the performance of the proposed nomogram was evaluated based on Harrell's concordance index (C-index) and the area under the receiver operating characteristic curve (AUC). The clinical value of the prediction model was tested using decision-curve analysis (DCA). The primary outcomes were 28-day, 60-day, and 90-day mortality rates. Results. The 850 patients included in the analysis comprised 595 in the training cohort and 255 in the validation cohort. The training cohort consisted of 353 (59.3%) males and 242 (40.7%) females with SAP. Multivariate Cox regression showed that weight, sex, insurance status, explicit sepsis, SAPSII score, Elixhauser score, bilirubin, anion gap, creatinine, hematocrit, hemoglobin, RDW, SPO2, and respiratory rate were independent prognostic factors for the survival of SAP patients admitted to an intensive care unit. The predicted values were compared using C-indexes, calibration plots, integrated discrimination improvement, net reclassification improvement, and DCA. Conclusions. We have identified some important demographic and laboratory parameters related to the prognosis of patients with SAP and have used them to establish a more accurate and convenient nomogram for evaluating their 28-day, 60-day, and 90-day mortality rates.
引用
收藏
页数:12
相关论文
共 50 条
  • [21] A nomogram for predicting neonatal apnea: a retrospective analysis based on the MIMIC database
    Huang, Huisi
    Shi, Yanhong
    Hong, Yinghui
    Zhu, Lizhen
    Li, Mengyao
    Zhang, Yue
    FRONTIERS IN PEDIATRICS, 2024, 12
  • [22] A nomogram to predict 28-day mortality in neonates with sepsis: a retrospective study based on the MIMIC-III database
    Liang, Yongzhou
    Zhao, Liqing
    Huang, Jihong
    Wu, Yurong
    TRANSLATIONAL PEDIATRICS, 2023, 12 (09) : 1690 - 1706
  • [23] Development and validation of a novel nomogram of 1-year mortality in the elderly with hip fracture: a study of the MIMIC-III database
    Chen, Qian
    Hao, Peng
    Wong, Chipiu
    Zhong, Xiaoxin
    He, Qing
    Chen, Yantao
    BMJ OPEN, 2023, 13 (05):
  • [24] Association between glucocorticoid administration and outcomes in patients with ARDS based on the MIMIC-III database
    Lu, Zhonghua
    Tang, Yan
    Liu, Mei
    Cao, Lijun
    Chen, Hu
    Yu, Weili
    Sun, Yun
    MEDICINE, 2024, 103 (32)
  • [25] Development and Internal Validation of a Nomogram to Predict Mortality During the ICU Stay of Thoracic Fracture Patients Without Neurological Compromise: An Analysis of the MIMIC-III Clinical Database
    Wang, Haosheng
    Ou, Yangyang
    Fan, Tingting
    Zhao, Jianwu
    Kang, Mingyang
    Dong, Rongpeng
    Qu, Yang
    FRONTIERS IN PUBLIC HEALTH, 2021, 9
  • [26] Association between BMI and outcomes in critically ill patients: an analysis of the MIMIC-III database
    Yu, Wenbo
    Jiang, Weiwei
    Yuan, Jihong
    Fan, Tao
    Xiao, Huiyan
    Sun, Lizhu
    Zhu, Yan
    Li, Wenfang
    Wu, Shaoshuai
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [27] Protocol Protocol for deep mining the correlation between acute pancreatitis and ferroptosis using the MIMIC-III database and STATA software
    Deng, Yueling
    Jiang, Tao
    Zhang, Sujie
    Liu, Fuyao
    STAR PROTOCOLS, 2024, 5 (02):
  • [28] Mean arterial pressure and mortality in patients with distributive shock: a retrospective analysis of the MIMIC-III database
    Jean-Louis Vincent
    Nathan D. Nielsen
    Nathan I. Shapiro
    Margaret E. Gerbasi
    Aaron Grossman
    Robin Doroff
    Feng Zeng
    Paul J. Young
    James A. Russell
    Annals of Intensive Care, 8
  • [29] Mean arterial pressure and mortality in patients with distributive shock: a retrospective analysis of the MIMIC-III database
    Vincent, Jean-Louis
    Nielsen, Nathan D.
    Shapiro, Nathan I.
    Gerbasi, Margaret E.
    Grossman, Aaron
    Doroff, Robin
    Zeng, Feng
    Young, Paul J.
    Russell, James A.
    ANNALS OF INTENSIVE CARE, 2018, 8
  • [30] Application of Neuromuscular Blockers in Patients with ARDS in ICU: A Retrospective Study Based on the MIMIC-III Database
    Pan, Xiaojun
    Liu, Jiao
    Zhang, Sheng
    Huang, Sisi
    Chen, Limin
    Shen, Xuan
    Chen, Dechang
    JOURNAL OF CLINICAL MEDICINE, 2023, 12 (05)