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Early predictive factors of progression from severe type to critical ill type in patients with Coronavirus Disease 2019: A retrospective cohort study.
Li, Nan; Kong, Hao; Zheng, Xi-Zi; Li, Xue-Ying; Ma, Jing; Zhang, Hong; Wang, Dong-Xin; Li, Hai-Chao; Liu, Xin-Min.
  • Li N; Department of Anesthesiology and Critical Care Medicine, Peking University First Hospital, Beijing, China.
  • Kong H; Department of Anesthesiology and Critical Care Medicine, Peking University First Hospital, Beijing, China.
  • Zheng XZ; Department of Nephrology, Peking University First Hospital, Beijing, China.
  • Li XY; Department of Biostatistics, Peking University First Hospital, Beijing, China.
  • Ma J; Department of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China.
  • Zhang H; Department of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China.
  • Wang DX; Department of Anesthesiology and Critical Care Medicine, Peking University First Hospital, Beijing, China.
  • Li HC; Department of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China.
  • Liu XM; Department of Geriatrics, Peking University First Hospital, Beijing, China.
PLoS One ; 15(12): e0243195, 2020.
Article in English | MEDLINE | ID: covidwho-953970
ABSTRACT

BACKGROUND:

The current worldwide pandemic of Coronavirus Disease 2019 (COVID-19) has posed a serious threat to global public health, and the mortality rate of critical ill patients remains high. The purpose of this study was to identify factors that early predict the progression of COVID-19 from severe to critical illness.

METHODS:

This retrospective cohort study included adult patients with severe or critical ill COVID-19 who were consecutively admitted to the Zhongfaxincheng campus of Tongji Hospital (Wuhan, China) from February 8 to 18, 2020. Baseline variables, data at hospital admission and during hospital stay, as well as clinical outcomes were collected from electronic medical records system. The primary endpoint was the development of critical illness. A multivariable logistic regression model was used to identify independent factors that were associated with the progression from severe to critical illness.

RESULTS:

A total of 138 patients were included in the analysis; of them 119 were diagnosed as severe cases and 16 as critical ill cases at hospital admission. During hospital stay, 19 more severe cases progressed to critical illness. For all enrolled patients, longer duration from diagnosis to admission (odds ratio [OR] 1.108, 95% CI 1.022-1.202; P = 0.013), pulse oxygen saturation at admission <93% (OR 5.775, 95% CI 1.257-26.535; P = 0.024), higher neutrophil count (OR 1.495, 95% CI 1.177-1.899; P = 0.001) and higher creatine kinase-MB level at admission (OR 2.449, 95% CI 1.089-5.511; P = 0.030) were associated with a higher risk, whereas higher lymphocyte count at admission (OR 0.149, 95% CI 0.026-0.852; P = 0.032) was associated with a lower risk of critical illness development. For the subgroup of severe cases at hospital admission, the above factors except creatine kinase-MB level were also found to have similar correlation with critical illness development.

CONCLUSIONS:

Higher neutrophil count and lower lymphocyte count at admission were early independent predictors of progression to critical illness in severe COVID-19 patients.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Critical Illness / Disease Progression / COVID-19 Type of study: Cohort study / Diagnostic study / Observational study / Prognostic study Topics: Long Covid Limits: Female / Humans / Male / Middle aged Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2020 Document Type: Article Affiliation country: Journal.pone.0243195

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Critical Illness / Disease Progression / COVID-19 Type of study: Cohort study / Diagnostic study / Observational study / Prognostic study Topics: Long Covid Limits: Female / Humans / Male / Middle aged Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2020 Document Type: Article Affiliation country: Journal.pone.0243195