Hyperglycemia is a strong predictor of poor prognosis in COVID-19.

The objective of this study is to explore the association between documented diabetes, fasting plasma glucose (FPG), and the clinical outcomes of Coronavirus disease 2019 (COVID-19). This retrospective study included 255 patients with COVID-19. Of these, 214 were admitted to isolation wards and 41were admitted to intensive care units (ICUs). Demographic, clinical, treatment, and laboratory data were collected and compared between ICU and non-ICU patients. Multivariable logistic regression models were used to explore the risk factors associated with poor clinical outcomes (ICU admission or death). There were significant changes in several clinical parameters in ICU patients (leukopenia, lymphopenia, elevated D-dimer, as well as higher levels of FPG, cardiac troponin, serum ferritin, IL-6, and high-sensitivity C-reactive protein)compared with non-ICU patients. The prevalence of known diabetes was substantially higher in ICU than non-ICU patients (31.7% vs. 17.8%, P = 0.0408). Multivariable regression analysis showed that a history of diabetes [odds ratio (OR), 0.099; 95% confidence interval (CI), 0.016-0.627; P = 0.014], high FPG at admission (OR, 1.587; 95% CI, 1.299-1.939, P < 0.001), high IL-6 (OR, 1.01; 95% CI, 1.002-1.018, P = 0.013), and D-dimer higher than 1 mg/L at admission (OR, 4.341; 95% CI, 1.139-16.547, P = 0.032) were independent predictors of poor outcomes. Cox proportional hazards analysis showed that compared with FPG < 7 mmol/L, FPG levels of 7.0-11.1 mmol/L and ≥ 11.1 mmol/L were associated with an increased hazard ratio (HR) for poor outcome (HR, 5.538 [95% CI, 2.269-13.51] and HR, 11.55 [95% CI, 4.45-29.99], respectively). Hyperglycemia and a history of diabetes on admission predicted poor clinical outcomes in COVID-19.

Liu SP ，Zhang Q ，Wang W ，Zhang M ，Liu C ，Xiao X ，Liu Z ，Hu WM ，Jin P ... -  《-》

Predictors of adverse prognosis in COVID-19: A systematic review and meta-analysis.

Identification of reliable outcome predictors in coronavirus disease 2019 (COVID-19) is of paramount importance for improving patient's management. A systematic review of literature was conducted until 24 April 2020. From 6843 articles, 49 studies were selected for a pooled assessment; cumulative statistics for age and sex were retrieved in 587 790 and 602 234 cases. Two endpoints were defined: (a) a composite outcome including death, severe presentation, hospitalization in the intensive care unit (ICU) and/or mechanical ventilation; and (b) in-hospital mortality. We extracted numeric data on patients' characteristics and cases with adverse outcomes and employed inverse variance random-effects models to derive pooled estimates. We identified 18 and 12 factors associated with the composite endpoint and death, respectively. Among those, a history of CVD (odds ratio (OR) = 3.15, 95% confidence intervals (CIs) 2.26-4.41), acute cardiac (OR = 10.58, 5.00-22.40) or kidney (OR = 5.13, 1.78-14.83) injury, increased procalcitonin (OR = 4.8, 2.034-11.31) or D-dimer (OR = 3.7, 1.74-7.89), and thrombocytopenia (OR = 6.23, 1.031-37.67) conveyed the highest odds for the adverse composite endpoint. Advanced age, male sex, cardiovascular comorbidities, acute cardiac or kidney injury, lymphocytopenia and D-dimer conferred an increased risk of in-hospital death. With respect to the treatment of the acute phase, therapy with steroids was associated with the adverse composite endpoint (OR = 3.61, 95% CI 1.934-6.73), but not with mortality. Advanced age, comorbidities, abnormal inflammatory and organ injury circulating biomarkers captured patients with an adverse clinical outcome. Clinical history and laboratory profile may then help identify patients with a higher risk of in-hospital mortality.

Figliozzi S ，Masci PG ，Ahmadi N ，Tondi L ，Koutli E ，Aimo A ，Stamatelopoulos K ，Dimopoulos MA ，Caforio ALP ，Georgiopoulos G ... -  《-》

Impaired Fasting Glucose and Diabetes Are Related to Higher Risks of Complications and Mortality Among Patients With Coronavirus Disease 2019.

Background: Diabetes correlates with poor prognosis in patients with COVID-19, but very few studies have evaluated whether impaired fasting glucose (IFG) is also a risk factor for the poor outcomes of patients with COVID-19. Here we aimed to examine the associations between IFG and diabetes at admission with risks of complications and mortality among patients with COVID-19. Methods: In this multicenter retrospective cohort study, we enrolled 312 hospitalized patients with COVID-19 from 5 hospitals in Wuhan from Jan 1 to Mar 17, 2020. Clinical information, laboratory findings, complications, treatment regimens, and mortality status were collected. The associations between hyperglycemia and diabetes status at admission with primary composite end-point events (including mechanical ventilation, admission to intensive care unit, or death) were analyzed by Cox proportional hazards regression models. Results: The median age of the patients was 57 years (interquartile range 38-66), and 172 (55%) were women. At the time of hospital admission, 84 (27%) had diabetes (and 36 were new-diagnosed), 62 (20%) had IFG, and 166 (53%) had normal fasting glucose (NFG) levels. Compared to patients with NFG, patients with IFG and diabetes developed more primary composite end-point events (9 [5%], 11 [18%], 26 [31%]), including receiving mechanical ventilation (5 [3%], 6 [10%], 21 [25%]), and death (4 [2%], 9 [15%], 20 [24%]). Multivariable Cox regression analyses showed diabetes was associated increased risks of primary composite end-point events (hazard ratio 3.53; 95% confidence interval 1.48-8.40) and mortality (6.25; 1.91-20.45), and IFG was associated with an increased risk of mortality (4.11; 1.15-14.74), after adjusting for age, sex, hospitals and comorbidities. Conclusion: IFG and diabetes at admission were associated with higher risks of adverse outcomes among patients with COVID-19.

Zhang J ，Kong W ，Xia P ，Xu Y ，Li L ，Li Q ，Yang L ，Wei Q ，Wang H ，Li H ，Zheng J ，Sun H ，Xia W ，Liu G ，Zhong X ，Qiu K ，Li Y ，Wang H ，Wang Y ，Song X ，Liu H ，Xiong S ，Liu Y ，Cui Z ，Hu Y ，Chen L ，Pan A ，Zeng T ... -  《-》

Baseline characteristics and risk factors for short-term outcomes in 132 COVID-19 patients with diabetes in Wuhan China: A retrospective study.

To investigate the clinical characteristics, laboratory findings and high- resolution CT (HRCT) features and to explore the risk factors for in-hospital death and complications of coronavirus disease 2019 (COVID-19) patients with diabetes. From Dec 31, 2019, to Apr 5, 2020, a total of 132 laboratory-confirmed COVID-19 patients with diabetes from two hospitals were retrospectively included in our study. Clinical, laboratory and chest CT data were analyzed and compared between the two groups with an admission glucose level of ≤11 mmol/L (group 1) and >11 mmol/L (group 2). Logistic regression analyses were used to identify the risk factors associated with in-hospital death and complications. Of 132 patients, 15 died in hospital and 113 were discharged. Patients in group 2 were more likely to require intensive care unit care (21.4% vs. 9.2%), to develop acute respiratory distress syndrome (ARDS) (23.2% vs. 9.2%) and acute cardiac injury (12.5% vs. 1.3%), and had a higher death rate (19.6% vs. 5.3%) than group 1. In the multivariable analysis, patients with admission glucose of >11 mmol/l had an increased risk of death (OR: 7.629, 95%CI: 1.391-37.984) and in-hospital complications (OR: 3.232, 95%CI: 1.393-7.498). Admission d-dimer of ≥1.5 μg/mL (OR: 6.645, 95%CI: 1.212-36.444) and HRCT score of ≥10 (OR: 7.792, 95%CI: 2.195-28.958) were associated with increased odds of in-hospital death and complications, respectively. In COVID-19 patients with diabetes, poorly-controlled blood glucose (>11 mmol/L) may be associated with poor outcomes. Admission hyperglycemia, elevated d-dimer and high HRCT score are potential risk factors for adverse outcomes and death.

Li Y ，Han X ，Alwalid O ，Cui Y ，Cao Y ，Liu J ，Gu J ，Wang L ，Fan Y ，Shi H ... -  《-》

Risk factors for adverse clinical outcomes with COVID-19 in China: a multicenter, retrospective, observational study.

Background: The risk factors for adverse events of Coronavirus Disease-19 (COVID-19) have not been well described. We aimed to explore the predictive value of clinical, laboratory and CT imaging characteristics on admission for short-term outcomes of COVID-19 patients. Methods: This multicenter, retrospective, observation study enrolled 703 laboratory-confirmed COVID-19 patients admitted to 16 tertiary hospitals from 8 provinces in China between January 10, 2020 and March 13, 2020. Demographic, clinical, laboratory data, CT imaging findings on admission and clinical outcomes were collected and compared. The primary endpoint was in-hospital death, the secondary endpoints were composite clinical adverse outcomes including in-hospital death, admission to intensive care unit (ICU) and requiring invasive mechanical ventilation support (IMV). Multivariable Cox regression, Kaplan-Meier plots and log-rank test were used to explore risk factors related to in-hospital death and in-hospital adverse outcomes. Results: Of 703 patients, 55 (8%) developed adverse outcomes (including 33 deceased), 648 (92%) discharged without any adverse outcome. Multivariable regression analysis showed risk factors associated with in-hospital death included ≥ 2 comorbidities (hazard ratio [HR], 6.734; 95% CI; 3.239-14.003, p < 0.001), leukocytosis (HR, 9.639; 95% CI, 4.572-20.321, p < 0.001), lymphopenia (HR, 4.579; 95% CI, 1.334-15.715, p = 0.016) and CT severity score > 14 (HR, 2.915; 95% CI, 1.376-6.177, p = 0.005) on admission, while older age (HR, 2.231; 95% CI, 1.124-4.427, p = 0.022), ≥ 2 comorbidities (HR, 4.778; 95% CI; 2.451-9.315, p < 0.001), leukocytosis (HR, 6.349; 95% CI; 3.330-12.108, p < 0.001), lymphopenia (HR, 3.014; 95% CI; 1.356-6.697, p = 0.007) and CT severity score > 14 (HR, 1.946; 95% CI; 1.095-3.459, p = 0.023) were associated with increased odds of composite adverse outcomes. Conclusion: The risk factors of older age, multiple comorbidities, leukocytosis, lymphopenia and higher CT severity score could help clinicians identify patients with potential adverse events.

Xu PP ，Tian RH ，Luo S ，Zu ZY ，Fan B ，Wang XM ，Xu K ，Wang JT ，Zhu J ，Shi JC ，Chen F ，Wan B ，Yan ZH ，Wang RP ，Chen W ，Fan WH ，Zhang C ，Lu MJ ，Sun ZY ，Zhou CS ，Zhang LN ，Xia F ，Qi L ，Zhang W ，Zhong J ，Liu XX ，Zhang QR ，Lu GM ，Zhang LJ ... -  《-》