tetano
Editor, Senior Moderator
Aging (Albany NY)
. 2020 Dec 9;12.
doi: 10.18632/aging.202261. Online ahead of print.
Predicting severe or critical symptoms in hospitalized patients with COVID-19 from Yichang, China
Xin Chen[SUP] 1 [/SUP], Feng Peng[SUP] 1 [/SUP], Xiaoni Zhou[SUP] 2 [/SUP], Jiang Zhu[SUP] 1 [/SUP], Xin Chen[SUP] 3 [/SUP], Yingying Gong[SUP] 3 [/SUP], Wang Shupeng[SUP] 3 [/SUP], Wenquan Niu[SUP] 4 [/SUP]
Affiliations
Abstract
Objectives: We aimed to identify potential risk factors for severe or critical coronavirus disease 2019 (COVID-19) and establish a prediction model based on significant factors. Methods: A total of 370 patients with COVID-19 were consecutively enrolled at The Third People's Hospital of Yichang from January to March, 2020. COVID-19 was diagnosed according to the COVID-19 diagnosis and treatment plan released by the National Health and Health Committee of China. Effect-size estimates are summarized as odds ratio (OR) and 95% confidence interval (CI). Results: 326 patients were diagnosed with mild or ordinary COVID-19, and 44 with severe or critical COVID-19. After propensity score matching and statistical adjustment, eight factors were significantly associated with severe or critical COVID-19 (p <0.05) relative to mild or ordinary COVID-19. Due to strong pairwise correlations, only five factors, including diagnostic delay (OR, 95% CI, p: 1.08, 1.02 to 1.17, 0.048), albumin (0.82, 0.75 to 0.91, <0.001), lactate dehydrogenase (1.56, 1.14 to 2.13, 0.011), white blood cell (1.27, 1.08 to 1.50, 0.004), and neutrophil (1.40, 1.16 to 1.70, <0.001), were retained for model construction and performance assessment. The nomogram model based on the five factors had good prediction capability and accuracy (C-index: 90.6%). Conclusions: Our findings provide evidence for the significant contribution of five independent factors to the risk of severe or critical COVID-19, and their prediction was reinforced in a nomogram model.
Keywords: COVID-19; nomogram; prediction; risk; severe or critical symptom.
. 2020 Dec 9;12.
doi: 10.18632/aging.202261. Online ahead of print.
Predicting severe or critical symptoms in hospitalized patients with COVID-19 from Yichang, China
Xin Chen[SUP] 1 [/SUP], Feng Peng[SUP] 1 [/SUP], Xiaoni Zhou[SUP] 2 [/SUP], Jiang Zhu[SUP] 1 [/SUP], Xin Chen[SUP] 3 [/SUP], Yingying Gong[SUP] 3 [/SUP], Wang Shupeng[SUP] 3 [/SUP], Wenquan Niu[SUP] 4 [/SUP]
Affiliations
- PMID: 33318316
- DOI: 10.18632/aging.202261
Abstract
Objectives: We aimed to identify potential risk factors for severe or critical coronavirus disease 2019 (COVID-19) and establish a prediction model based on significant factors. Methods: A total of 370 patients with COVID-19 were consecutively enrolled at The Third People's Hospital of Yichang from January to March, 2020. COVID-19 was diagnosed according to the COVID-19 diagnosis and treatment plan released by the National Health and Health Committee of China. Effect-size estimates are summarized as odds ratio (OR) and 95% confidence interval (CI). Results: 326 patients were diagnosed with mild or ordinary COVID-19, and 44 with severe or critical COVID-19. After propensity score matching and statistical adjustment, eight factors were significantly associated with severe or critical COVID-19 (p <0.05) relative to mild or ordinary COVID-19. Due to strong pairwise correlations, only five factors, including diagnostic delay (OR, 95% CI, p: 1.08, 1.02 to 1.17, 0.048), albumin (0.82, 0.75 to 0.91, <0.001), lactate dehydrogenase (1.56, 1.14 to 2.13, 0.011), white blood cell (1.27, 1.08 to 1.50, 0.004), and neutrophil (1.40, 1.16 to 1.70, <0.001), were retained for model construction and performance assessment. The nomogram model based on the five factors had good prediction capability and accuracy (C-index: 90.6%). Conclusions: Our findings provide evidence for the significant contribution of five independent factors to the risk of severe or critical COVID-19, and their prediction was reinforced in a nomogram model.
Keywords: COVID-19; nomogram; prediction; risk; severe or critical symptom.