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Development of a Predictive Model for Mortality in Hospitalized Patients With COVID-19.
Niu, Yuanyuan; Zhan, Zan; Li, Jianfeng; Shui, Wei; Wang, Changfeng; Xing, Yanli; Zhang, Changran.
  • Niu Y; Department of Respiratory Medicine, The Eastern Hospital of The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong Province, China.
  • Zhan Z; Department of Respiratory Medicine, Huanggang Central Hospital, Huanggang, Hubei Province, China.
  • Li J; Department of Radiation Oncology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China.
  • Shui W; Department of Respiratory Medicine, The Eastern Hospital of The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong Province, China.
  • Wang C; Department of Respiratory Medicine, Huanggang Central Hospital, Huanggang, Hubei Province, China.
  • Xing Y; Department of Respiratory Medicine, The Eastern Hospital of The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong Province, China.
  • Zhang C; Department of Respiratory Medicine, The Eastern Hospital of The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong Province, China.
Disaster Med Public Health Prep ; : 1-9, 2021 Jan 08.
Article in English | MEDLINE | ID: covidwho-1014945
Semantic information from SemMedBD (by NLM)
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COVID-19
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PROCESS_OF
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hospitalized patients
2. COVID-19 PROCESS_OF Patients
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COVID-19
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Patients
3. Hospitals LOCATION_OF Retrospective Studies
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Hospitals
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4. American College of Cardiology/American Heart Association Lesion Complexity Score C PROCESS_OF Patients
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American College of Cardiology/American Heart Association Lesion Complexity Score C
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7. Hospitals LOCATION_OF Retrospective Studies
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8. American College of Cardiology/American Heart Association Lesion Complexity Score C PROCESS_OF Patients
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American College of Cardiology/American Heart Association Lesion Complexity Score C
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ABSTRACT

INTRODUCTION:

Early identification of patients with novel corona virus disease 2019 (COVID-19) who may be at high mortality risk is of great importance.

METHODS:

In this retrospective study, we included all patients with COVID-19 at Huanggang Central Hospital from January 23 to March 5, 2020. Data on clinical characteristics and outcomes were compared between survivors and nonsurvivors. Univariable and multivariable logistic regression were used to explore risk factors associated with in-hospital death. A nomogram was established based on the risk factors selected by multivariable analysis.

RESULTS:

A total of 150 patients were enrolled, including 31 nonsurvivors and 119 survivors. The multivariable logistic analysis indicated that increasing the odds of in-hospital death associated with higher Sequential Organ Failure Assessment score (odds ratio [OR], 3.077; 95% confidence interval [CI] 1.848-5.122; P < 0.001), diabetes (OR, 10.474; 95% CI 1.554-70.617; P = 0.016), and lactate dehydrogenase greater than 245 U/L (OR, 13.169; 95% CI 2.934-59.105; P = 0.001) on admission. A nomogram was established based on the results of the multivariable analysis. The AUC of the nomogram was 0.970 (95% CI 0.947-0.992), showing good accuracy in predicting the risk of in-hospital death.

CONCLUSIONS:

This finding would facilitate the early identification of patients with COVID-19 who have a high-risk for fatal outcome.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study / Risk factors Language: English Journal: Disaster Med Public Health Prep Journal subject: Public Health Year: 2021 Document Type: Article Affiliation country: Dmp.2021.8

Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study / Risk factors Language: English Journal: Disaster Med Public Health Prep Journal subject: Public Health Year: 2021 Document Type: Article Affiliation country: Dmp.2021.8