medRxiv preprint doi: https://doi.org/10.1101/2020.03.17.20037572
Note: this data analysis is for China. Many other countries have different emerging data.
Incidence, clinical characteristics and prognostic factor of patients with COVID-19: a systematic review and meta-analysis
Chaoqun Ma, MD1; Jiawei Gu, MD2; Pan Hou, MD1; Liang Zhang, MD1; Yuan Bai, MD1; Zhifu Guo, MD1; Hong Wu, MD1; Bili Zhang,
MD1 ; Pan Li, MD, MD1 ; Xianxian Zhao, MD, FACC, FESC1
1Department of Cardiology, Changhai Hospital, Second Military Medical University, 168 Changhai Rd, Shanghai, 200433, China.
2 Department of General Surgery, The Fifth People's Hospital of Shanghai, Fudan University, Shanghai, 801 Heqing Rd, 200240, China.
Items in both categories Virus and Diabetes are listed here:
- T1 Diabetes increased by 27% by second year of COVID – meta-analysis June 2023
- Diabetes 3X more likely if had COVID ICU (VDR was de-activated) - April 2023
- Active vitamin D is related to COVID and Diabetes in 15 ways – Dec 2022
- T1 Diabetic adults 5X more likely to get COVID (hint low vitamin D)– Nov 2022
- Vitamin D separately helps X or COVID, should help X with COVID (example: diabetes) – March 2022
- COVID-19 hospitalizations: 63% associated with diabetes, obesity, hypertension or heart failure – Feb 2021
- Diabetes has many bidirectional links with COVID-19 – March 2021
- 26 health factors increase the risk of COVID-19 – all are proxies for low vitamin D
- Excessive insulin decreases vitamin D in 4 ways – problems for diabetic COVID-19 – Dec 2020
- Hyperglycemic 2X more likely to have severe COVID-19 - Nov 2020
- Diabetes increases COVID-19 severity and COVID-19 creates Diabetes - Oct 2020
- COVID-19 deaths 4 to 7 X more likely if Diabetic, Hypertensive, or CVD - meta-analysis March 2020
Background: Recently, Coronavirus Disease 2019 (COVID-19) outbreak started in Wuhan, China. Although the clinical features of COVID-19 have been reported previously, data regarding the risk factors associated with the clinical outcomes are lacking.
Objectives: To summary and analyze the clinical characteristics and identify the predictors of disease severity and mortality.
Methods: The PubMed, Web of Science Core Collection, Embase, Cochrane and MedRxiv databases were searched through February 25, 2020. Meta-analysis of Observational Studies in Epidemiology (MOOSE) recommendations were followed. We extracted and pooled data using random-e= ects meta-analysis to summary the clinical feature of the confirmed COVID-19 patients, and further identify risk factors for disease severity and death. Heterogeneity was evaluated using the I2 method and explained with subgroup analysis and meta-regression.
Results: A total of 30 studies including 53000 patients with COVID-19 were included in this study, the mean age was 49.8 years (95% CI, 47.5-52.2 yrs) and 55.5% were male. The pooled incidence of severity and mortality were 20.2% (95% CI, 15.1-25.2%) and 3.1% (95% CI, 1.9-4.2%), respectively. The predictor for disease severity included
- old age 50 yrs, odds ratio [OR] = 2.61; 95% CI, 2.29-2.98),
- male (OR =1.348, 95% CI, 1.195-1.521),
- smoking (OR =1.734, 95% CI, 1.146-2.626) and
- any comorbidity (OR = 2.635, 95% CI, 2.098-3.309),
- especially chronic kidney disease (CKD, OR = 6.017; 95% CI, 2.192-16.514),
- chronic obstructive pulmonary disease (COPD, OR = 5.323; 95% CI, 2.613-10.847) and
- cerebrovascular disease (OR = 3.219; 95% CI, 1.486-6.972)
In terms of laboratory results, increased lactate dehydrogenase (LDH), C-reactive protein (CRP) and D-dimer and decreased blood platelet and lymphocytes count were highly associated with severe COVID-19 (all for P < 0.001). Meanwhile,
- old age (> 60 yrs, RR = 9.45; 95% CI, 8.09-11.04), followed by
- cardiovascular disease (RR =6.75; 95% CI, 5.40-8.43)
- hypertension (RR = 4.48; 95% CI, 3.69-5.45) and
- diabetes (RR = 4.43; 95% CI, 3.49-5.61)
were found to be independent prognostic factors for the COVID-19 related death.
Conclusions: To our knowledge, this is the first evidence-based medicine research to explore the risk factors of prognosis in patients with COVID-19, which is helpful to identify early-stage patients with poor prognosis and adapt effective treatment.