Prediction Model for In-hospital Death of Patients with Cardiac Arrest

ZHANG Nan; LIN Qingting; ZHU Huadong

doi:10.12290/xhyxzz.2023-0378

Volume 14 Issue 5

Sep. 2023

Turn off MathJax

Article Contents

Abstract

References

Medical Journal of Peking Union Medical College Hospital > 2023 > 14(5): 1023-1030. > DOI: 10.12290/xhyxzz.2023-0378

ZHANG Nan, LIN Qingting, ZHU Huadong. Prediction Model for In-hospital Death of Patients with Cardiac Arrest[J]. Medical Journal of Peking Union Medical College Hospital, 2023, 14(5): 1023-1030. DOI: 10.12290/xhyxzz.2023-0378

Citation:

PDF (2334 KB)

Prediction Model for In-hospital Death of Patients with Cardiac Arrest

ZHANG Nan^{1, 2, 3},
LIN Qingting^{1, 2, 3},
ZHU Huadong^{1, 2, ,}

1.
Emergency Department, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
2.
State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
3.
Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China

Funds:

National High Level Hospital Clinical Research Funding 2022-PUMCH-B-110

More Information

Corresponding author:
ZHU Huadong, E-mail: zhuhuadong1970@126.com
Received Date: August 14, 2023
Accepted Date: September 18, 2023
Available Online: September 25, 2023
Issue Publish Date: September 29, 2023

Graphical Abstract

Abstract

Abstract

Objective To build a prediction model of the in-hospital death of patients with cardiac arrest.
Methods This study is a retrospective analysis based on the medical information mart for intensive care-Ⅳ (MIMIC-Ⅳ)2.0. We gathered the information of patients above 18 years old, with cardiac arrest and intensive care unit (ICU) experience. A stepwise multi-variate logistic regression analysis was performed to filter variables, variables with P values < 0.05 were kept and enter as predictors of in-hospital death of patients with cardiac arrest. The model was evaluated with receiver operating characteristic (ROC) curve for discriminative power and with calibration curve for consistency. Finally, an online dynamic nomogram calculator was built to calculate the risk of in-hospital death.
Results This study included 1772 patients with cardiac arrest. The mean age of those patients was (64.93±16.52) years old, and 963 (54.3%) patients suffered in-hospital death. The factors of the prediction model for in-hospital death of cardiac arrest patients constructed based on multi-variate logistic regression included: potential cardiac disease diagnosis, age adjusted Chalson comorbidity index(CCI), body mass index (BMI), vital signs, lowest lactic acid and lowest Glasgow coma scale (GCS) during the first 24 hours after entering ICU, cardiac ultrasound examination, invasive mechanical ventilation and vasopressin utilization. The sensitivity and specificity of the prediction model were 73.1%(95% CI: 0.702-0.759) and 71.6%(95% CI: 0.683-0.745), respectively. Area under the ROC curve was 0.806(95% CI: 0.786-0.826).
Conclusions The prediction model built in this study can properly predict the in-hospital death of patients with cardiac arrest.
- cardiac arrest,
- intensive care unit,
- in-hospital death,
- prediction model

FullText(HTML)

References (26)

References

[1]	陈小凤, 聂时南, 季娟娟, 等. 心肺复苏预后影响因素的研究进展[J]. 临床急诊杂志, 2019, 20: 87-92. https://www.cnki.com.cn/Article/CJFDTOTAL-ZZLC201901019.htm
[2]	杜兰芳, 郑康, 冯璐, 等. 中国急诊医生对心脏骤停后脑保护认知及实践现况调查[J]. 中国急救医学, 2022, 42: 845-849. https://www.cnki.com.cn/Article/CJFDTOTAL-ZJJY202210004.htm
[3]	Ravindran R, Kwok CS, Wong CW, et al. Cardiac arrest and related mortality in emergency departments in the United States: Analysis of the nationwide emergency department sample[J]. Resuscitation, 2020, 157: 166-173. DOI: 10.1016/j.resuscitation.2020.10.005
[4]	Yan S, Gan Y, Jiang N, et al. The global survival rate among adult out-of-hospital cardiac arrest patients who received cardiopulmonary resuscitation: a systematic review and meta-analysis[J]. Crit Care, 2020, 24: 61. DOI: 10.1186/s13054-020-2773-2
[5]	Wong CX, Brown A, Lau DH, et al. Epidemiology of Sudden Cardiac Death: Global and Regional Perspectives[J]. Heart Lung Circ, 2019, 28: 6-14. DOI: 10.1016/j.hlc.2018.08.026
[6]	Andersen LW, Holmberg MJ, Berg KM, et al. In-Hospital Cardiac Arrest: A Review[J]. JAMA, 2019, 321: 1200-1210. DOI: 10.1001/jama.2019.1696
[7]	Mir T, Qureshi WT, Uddin M, et al. Predictors and outcomes of cardiac arrest in the emergency department and in-patient settings in the United States(2016-2018)[J]. Resuscitation, 2022, 170: 100-106. DOI: 10.1016/j.resuscitation.2021.11.009
[8]	Wang MT, Huang WC, Yen DH, et al. The Potential Risk Factors for Mortality in Patients After In-Hospital Cardiac Arrest: A Multicenter Study[J]. Front Cardiovasc Med, 2021, 8: 630102. DOI: 10.3389/fcvm.2021.630102
[9]	Bergum D, Haugen BO, Nordseth T, et al. Recognizing the causes of in-hospital cardiac arrest--A survival benefit[J]. Resuscitation, 2015, 97: 91-96. DOI: 10.1016/j.resuscitation.2015.09.395
[10]	Ebell MH, Afonso AM. Pre-arrest predictors of failure to survive after in-hospital cardiopulmonary resuscitation: a meta-analysis[J]. Fam Pract, 2011, 28: 505-515. DOI: 10.1093/fampra/cmr023
[11]	Sjoding MW, Luo K, Miller MA, et al. When do confounding by indication and inadequate risk adjustment bias critical care studies? A simulation study[J]. Crit Care, 2015, 19: 195. DOI: 10.1186/s13054-015-0923-8
[12]	Fouche PF, Carlson JN, Ghosh A, et al. Frequency of adjustment with comorbidity and illness severity scores and indices in cardiac arrest research[J]. Resuscitation, 2017, 110: 56-73. DOI: 10.1016/j.resuscitation.2016.10.020
[13]	Charlson ME, Carrozzino D, Guidi J, et al. Charlson Comorbidity Index: A Critical Review of Clinimetric Properties[J]. Psychother Psychosom, 2022, 91: 8-35. DOI: 10.1159/000521288
[14]	Andrew E, Nehme Z, Bernard S, et al. The influence of comorbidity on survival and long-term outcomes after out-of-hospital cardiac arrest[J]. Resuscitation, 2017, 110: 42-47. DOI: 10.1016/j.resuscitation.2016.10.018
[15]	Hirlekar G, Jonsson M, Karlsson T, et al. Comorbidity and survival in out-of-hospital cardiac arrest[J]. Resuscitation, 2018, 133: 118-123. DOI: 10.1016/j.resuscitation.2018.10.006
[16]	Jentzer JC, Anavekar NS, Mankad SV, et al. Changes in left ventricular systolic and diastolic function on serial echocardiography after out-of-hospital cardiac arrest[J]. Resuscitation, 2018, 126: 1-6. DOI: 10.1016/j.resuscitation.2018.01.050
[17]	Andersen LW, Kim WY, Chase M, et al. The prevalence and significance of abnormal vital signs prior to in-hospital cardiac arrest[J]. Resuscitation, 2016, 98: 112-117. DOI: 10.1016/j.resuscitation.2015.08.016
[18]	Burstein B, Vallabhajosyula S, Ternus B, et al. The Prognostic Value of Lactate in Cardiac Intensive Care Unit Patients With Cardiac Arrest and Shock[J]. Shock, 2021, 55: 613-619.
[19]	Schurr JW, Noubani M, Santore LA, et al. Survival and Outcomes After Cardiac Arrest With VA-ECMO Rescue Therapy[J]. Shock, 2021, 56: 939-947.
[20]	Soar J, Böttiger BW, Carli P, et al. European Resuscitation Council Guidelines 2021: Adult advanced life support[J]. Resuscitation, 2021, 161: 115-151.
[21]	付阳阳, 刘丹瑜, 金魁, 等. 关于机械通气对心肺复苏患者通气效果的回顾性研究[J]. 临床急诊杂志, 2019, 20: 343-347. https://www.cnki.com.cn/Article/CJFDTOTAL-ZZLC201905002.htm
[22]	Wang HE, Schmicker RH, Daya MR, et al. Effect of a Strategy of Initial Laryngeal Tube Insertion vs Endotracheal Intubation on 72-Hour Survival in Adults With Out-of-Hospital Cardiac Arrest: A Randomized Clinical Trial[J]. JAMA, 2018, 320: 769-778.
[23]	Nadolny K, Bujak K, Obremska M, et al. Glasgow Coma Scale score of more than four on admission predicts in-hospital survival in patients after out-of-hospital cardiac arrest[J]. Am J Emerg Med, 2021, 42: 90-94.
[24]	Rhodes A, Evans LE, Alhazzani W, et al. Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock: 2016[J]. Intensive Care Med, 2017, 43: 304-377.
[25]	Sacha GL, Lam SW, Wang L, et al. Association of Catecholamine Dose, Lactate, and Shock Duration at Vasopres-sin Initiation With Mortality in Patients With Septic Shock[J]. Crit Care Med, 2022, 50: 614-623.
[26]	Russell JA, Gordon AC, Williams MD, et al. Vasopressor Therapy in the Intensive Care Unit[J]. Semin Respir Crit Care Med, 2021, 42: 59-77.

[1]	ZHANG Zijiao, DING Shunjing, ZHAO Di, LIANG Jun, LEI Jianbo. Clinical Prediction Models Based on Traditional Methods and Machine Learning for Predicting First Stroke： Status and Prospects[J]. Medical Journal of Peking Union Medical College Hospital. DOI: 10.12290/xhyxzz.2024-1116
[2]	WANG Ziyi, LU Cuncun, HUANG Jiayi, ZHANG Jinglei, SHANG Wenru, CUI Lu, LIU Wendi, DENG Xiuxiu, ZHAO Xiaoxiao, YANG Kehu, LI Xiuxia. Investigation and Evaluation of Systematic Reviews of Prediction Models Published in Chinese Journals: Methodological and Reporting Quality[J]. Medical Journal of Peking Union Medical College Hospital, 2024, 15(4): 927-935. DOI: 10.12290/xhyxzz.2023-0418
[3]	ZHANG Zuyu, WEI Hong, LIU Qian, WANG Yaoqiang, FAN Xueyan, LUO Ruiying, LUO Changjiang. Establishment of a LASSO-Logistic Regression-based Risk Prediction Model for Early Recurrence of Siewert Ⅱ/Ⅲ Adenocarcinoma of Esophagogastric Junction Post-Surgery[J]. Medical Journal of Peking Union Medical College Hospital, 2024, 15(3): 604-615. DOI: 10.12290/xhyxzz.2023-0502
[4]	OUYANG Jing, CHANG Hong, YANG Mengjiao, ZHANG Meng, TIAN Meng, ZHENG Ya, WANG Yuping, CHEN Zhaofeng. Establishment and Validation of A Prediction Model for the Occurrence of Acute Kidney Disease in Patients with Liver Cirrhosis[J]. Medical Journal of Peking Union Medical College Hospital, 2024, 15(1): 89-98. DOI: 10.12290/xhyxzz.2023-0394
[5]	ZHANG Zuyu, WEI Hong, LIU Qian, WANG Yaoqiang, FAN Xueyan, LUO Ruiying, LUO Changjiang. Establishment of a LASSO Regression-Based Risk Prediction Model for Early Recurrence of SiewertⅡ/Ⅲ Adenocarcinoma of Esophagogastric Junction Post-Surgery[J]. Medical Journal of Peking Union Medical College Hospital. DOI: 10.12290/j.issn.1674-9081.2023-0502
[6]	GONG Huanhuan, KE Xiaowei, WANG Aimin, LI Xiangmin. An Interpretable Machine Learning Model for Predicting In-hospital Death Risk in Patients with Cardiac Arrest: Based on US Medical Information Mart for Intensive Care Database Ⅳ 2.0[J]. Medical Journal of Peking Union Medical College Hospital, 2023, 14(3): 528-535. DOI: 10.12290/xhyxzz.2022-0733
[7]	YANG Wenlei, LIU Fangfang, XU Ruiping, YANG Wei, HE Yu, LIU Zhen, ZHOU Fuyou, HENG Fanxiu, HOU Bolin, ZHANG Lixin, CHEN Lei, ZHANG Fan, CAI Fen, XU Huawen, LIN Miaoping, LIU Mengfei, PAN Yaqi, LIU Ying, HU Zhe, CHEN Huanyu, HE Zhonghu, KE Yang. Development and Validation of A Prognosis Prediction Model for Esophageal Squamous Cell Carcinoma Patients Treated with Esophagectomy: A Multicenter Real-world Cohort Study[J]. Medical Journal of Peking Union Medical College Hospital, 2023, 14(1): 101-113. DOI: 10.12290/xhyxzz.2022-0496
[8]	SUN Fangcan, HAN Bing, GAO Yan, SHEN Minhong, CHEN Youguo, ZHONG Wen. Validation of Six Predictive Models for Adverse Outcomes of Hypertensive Disorders of Pregnancy in Eastern and Western China[J]. Medical Journal of Peking Union Medical College Hospital, 2022, 13(5): 837-844. DOI: 10.12290/xhyxzz.2021-0778
[9]	ZHANG Gumuyang, XU Lili, MAO Li, LI Xiuli, JIN Zhengyu, SUN Hao. CT-based Radiomics to Predict Recurrence of Bladder Cancer after Resection in One Year: A Preliminary Study[J]. Medical Journal of Peking Union Medical College Hospital, 2021, 12(5): 698-704. DOI: 10.12290/xhyxzz.2021-0511
[10]	Shan-shan YOU, Yu-xin JIANG, Qing-li ZHU, Jing ZHANG, He LIU, Meng-su XIAO, Qing DAI, Qiang SUN. A Breast Cancer Risk Prediction Model Based on the Clinical Characteristics and Sonographic Features[J]. Medical Journal of Peking Union Medical College Hospital, 2014, 5(1): 26-30. DOI: 10.3969/j.issn.1674-9081.2014.01.007

Cited By

Get Citation

PDF

XML

Article Metrics

Article views (361) PDF downloads (76)

Address：	Room 302,Third Floor,Building 7, No. 1 Shuaifuyuan, Wangfujing, Dongcheng District, Beijing 100730, China
Tel：	010-69154261/4262
E - mail：	medj@pumch.cn mjpumch@126.com
Copyright of website：	Editorial Office of Medical Journal of Peking Union Medical College Hospital

Prediction Model for In-hospital Death of Patients with Cardiac Arrest

Abstract

References

Related Articles

Catalog

Article Metrics

Related

Prediction Model for In-hospital Death of Patients with Cardiac Arrest

Abstract

References

Related Articles

Catalog

Article Metrics

Related

Export File

Citation

Format

Content