Predictive Risk Factors at Admission and a "Burning Point" During Hospitalization Serve as Sequential Alerts for Critical Illness in Patients With COVID-19.

Background: We intended to establish a novel critical illness prediction system combining baseline risk factors with dynamic laboratory tests for patients with coronavirus disease 2019 (COVID-19). Methods: We evaluated patients with COVID-19 admitted to Wuhan West Union Hospital between 12 January and 25 February 2020. The data of patients were collected, and the illness severity was assessed. Results: Among 1,150 enrolled patients, 296 (25.7%) patients developed into critical illness. A baseline nomogram model consists of seven variables including age [odds ratio (OR), 1.028; 95% confidence interval (CI), 1.004-1.052], sequential organ failure assessment (SOFA) score (OR, 4.367; 95% CI, 3.230-5.903), neutrophil-to-lymphocyte ratio (NLR; OR, 1.094; 95% CI, 1.024-1.168), D-dimer (OR, 1.476; 95% CI, 1.107-1.968), lactate dehydrogenase (LDH; OR, 1.004; 95% CI, 1.001-1.006), international normalised ratio (INR; OR, 1.027; 95% CI, 0.999-1.055), and pneumonia area interpreted from computed tomography (CT) images (medium vs. small [OR, 4.358; 95% CI, 2.188-8.678], and large vs. small [OR, 9.567; 95% CI, 3.982-22.986]) were established to predict the risk for critical illness at admission. The differentiating power of this nomogram scoring system was perfect with an area under the curve (AUC) of 0.960 (95% CI, 0.941-0.972) in the training set and an AUC of 0.958 (95% CI, 0.936-0.980) in the testing set. In addition, a linear mixed model (LMM) based on dynamic change of seven variables consisting of SOFA score (value, 2; increase per day [I/d], +0.49), NLR (value, 10.61; I/d, +2.07), C-reactive protein (CRP; value, 46.9 mg/L; I/d, +4.95), glucose (value, 7.83 mmol/L; I/d, +0.2), D-dimer (value, 6.08 µg/L; I/d, +0.28), LDH (value, 461 U/L; I/d, +13.95), and blood urea nitrogen (BUN value, 6.51 mmol/L; I/d, +0.55) were established to assist in predicting occurrence time of critical illness onset during hospitalization. Conclusion: The two-checkpoint system could assist in accurately and dynamically predicting critical illness and timely adjusting the treatment regimen for patients with COVID-19.

A trial of arbidol hydrochloride in adults with COVID-19.

BACKGROUND: To date, there is no effective medicine to treat coronavirus disease 2019 (COVID-19), and the antiviral efficacy of arbidol in the treatment for COVID-19 remained equivocal and controversial. The purpose of this study was to evaluate the efficacy and safety of arbidol tablets in the treatment of COVID-19. METHODS: This was a prospective, open-label, controlled and multicenter investigator-initiated trial involving adult patients with confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Patients were stratified 1:2 to either standard-of-care (SOC) or SOC plus arbidol tablets (oral administration of 200 mg per time, three times a day for 14 days). The primary endpoint was negative conversion of SARS-CoV-2 within the first week. The rates and 95% confidential intervals were calculated for each variable. RESULTS: A total of 99 patients with laboratory-confirmed SARS-CoV-2 infection were enrolled; 66 were assigned to the SOC plus arbidol tablets group, and 33 to the SOC group. The negative conversion rate of SARS-CoV-2 within the first week in patients receiving arbidol tablets was significantly higher than that of the SOC group (70.3% [45/64] vs. 42.4% [14/33]; difference of conversion rate 27.9%; 95% confidence interval [CI], 7.7%-48.1%; P  = 0.008). Compared to those in the SOC group, patients receiving arbidol tablets had a shorter duration of clinical recovery (median 7.0 days vs. 12.0 days; hazard ratio [HR]: 1.877, 95% CI: 1.151-3.060, P = 0.006), symptom of fever (median 3.0 days vs. 12.0 days; HR: 18.990, 95% CI: 5.350-67.410, P < 0.001), as well as hospitalization (median 12.5 days vs. 20.0 days; P < 0.001). Moreover, the addition of arbidol tablets to SOC led to more rapid normalization of declined blood lymphocytes (median 10.0 days vs. 14.5 days; P > 0.05). The most common adverse event in the arbidol tablets group was the elevation of transaminase (5/200, 2.5%), and no one withdrew from the study due to adverse events or disease progression. CONCLUSIONS: SOC plus arbidol tablets significantly increase the negative conversion rate of SARS-CoV-2 within the first week anas, accelerate the recovery of COVID-19 patients. During the treatment with arbidol tablets, we find no significant serious adverse events. TRIAL REGISTRATION: Chinese Clinical Trial Registry, NCT04260594, www.clinicaltrials.gov/ct2/show/NCT04260594?term=NCT04260594&draw=2&rank=1.

Predictive Risk Factors at Admission and a “Burning Point” During Hospitalization Serve as Sequential Alerts for Critical Illness in Patients With COVID-19

Background We intended to establish a novel critical illness prediction system combining baseline risk factors with dynamic laboratory tests for patients with coronavirus disease 2019 (COVID-19). Methods We evaluated patients with COVID-19 admitted to Wuhan West Union Hospital between 12 January and 25 February 2020. The data of patients were collected, and the illness severity was assessed. Results Among 1,150 enrolled patients, 296 (25.7%) patients developed into critical illness. A baseline nomogram model consists of seven variables including age [odds ratio (OR), 1.028;95% confidence interval (CI), 1.004–1.052], sequential organ failure assessment (SOFA) score (OR, 4.367;95% CI, 3.230–5.903), neutrophil-to-lymphocyte ratio (NLR;OR, 1.094;95% CI, 1.024–1.168), D-dimer (OR, 1.476;95% CI, 1.107–1.968), lactate dehydrogenase (LDH;OR, 1.004;95% CI, 1.001–1.006), international normalised ratio (INR;OR, 1.027;95% CI, 0.999–1.055), and pneumonia area interpreted from computed tomography (CT) images (medium vs. small [OR, 4.358;95% CI, 2.188–8.678], and large vs. small [OR, 9.567;95% CI, 3.982–22.986]) were established to predict the risk for critical illness at admission. The differentiating power of this nomogram scoring system was perfect with an area under the curve (AUC) of 0.960 (95% CI, 0.941–0.972) in the training set and an AUC of 0.958 (95% CI, 0.936–0.980) in the testing set. In addition, a linear mixed model (LMM) based on dynamic change of seven variables consisting of SOFA score (value, 2;increase per day [I/d], +0.49), NLR (value, 10.61;I/d, +2.07), C-reactive protein (CRP;value, 46.9 mg/L;I/d, +4.95), glucose (value, 7.83 mmol/L;I/d, +0.2), D-dimer (value, 6.08 μg/L;I/d, +0.28), LDH (value, 461 U/L;I/d, +13.95), and blood urea nitrogen (BUN value, 6.51 mmol/L;I/d, +0.55) were established to assist in predicting occurrence time of critical illness onset during hospitalization. Conclusion The two-checkpoint system could assist in accurately and dynamically predicting critical illness and timely adjusting the treatment regimen for patients with COVID-19.

Plasma Metabolomic Profiling of Patients Recovered From Coronavirus Disease 2019 (COVID-19) With Pulmonary Sequelae 3 Months After Discharge.

BACKGROUND: Elucidation of the molecular mechanisms involved in the pathogenesis of coronavirus disease 2019 (COVID-19) may help to discover therapeutic targets. METHODS: To determine the metabolomic profile of circulating plasma from COVID-19 survivors with pulmonary sequelae 3 months after discharge, a random, outcome-stratified case-control sample was analyzed. We enrolled 103 recovered COVID-19 patients as well as 27 healthy donors, and performed pulmonary function tests, computerized tomography (CT) scans, laboratory examinations, and liquid chromatography-mass spectrometry. RESULTS: Plasma metabolite profiles of COVID-19 survivors with abnormal pulmonary function were different from those of healthy donors or subjects with normal pulmonary function. These alterations were associated with disease severity and mainly involved amino acid and glycerophospholipid metabolic pathways. Furthermore, increased levels of triacylglycerols, phosphatidylcholines, prostaglandin E2, arginine, and decreased levels of betain and adenosine were associated with pulmonary CO diffusing capacity and total lung capacity. The global plasma metabolomic profile differed between subjects with abnormal and normal pulmonary function. CONCLUSIONS: Further metabolite-based analysis may help to identify the mechanisms underlying pulmonary dysfunction in COVID-19 survivors, and provide potential therapeutic targets in the future.

Inflammatory Profiles and Clinical Features of Coronavirus 2019 Survivors 3 Months After Discharge in Wuhan, China.

BACKGROUND: Postdischarge immunity and its correlation with clinical features among patients recovered from coronavirus disease 2019(COVID-19) are poorly described. This prospective cross-sectional study explored the inflammatory profiles and clinical recovery of patients with COVID-19 at 3 months after hospital discharge. METHODS: Patients with COVID-19 discharged from 4 hospitals in Wuhan, recovered asymptomatic patients (APs) from an isolation hotel, and uninfected healthy controls (HCs) were recruited. Viral nucleic acid and antibody detection, laboratory examination, computed tomography, pulmonary function assessment, multiplex cytokine assay, and flow cytometry were performed. RESULTS: The72 age-, sex- and body mass index-matched participants included 19 patients with severe/critical COVID-19 (SPs), 20 patients with mild/moderate COVID-19 (MPs), 16 APs, and 17 HCs. At 3 months after discharge, levels of proinflammatory cytokines and factors related to vascular injury/repair in patients recovered from COVID-19 had not returned to those of the HCs, especially among recovered SPs compared with recovered MPs and APs. These cytokines were significantly correlated with impaired pulmonary function and chest computed tomographic abnormalities. However, levels of immune cells had returned to nearly normal levels and were not significantly correlated with abnormal clinical features. CONCLUSION: Vascular injury, inflammation, and chemotaxis persisted in patients with COVID-19 and were correlated with abnormal clinical features 3 months after discharge, especially in recovered SPs.

Changes in glomerular filtration rate and metabolomic differences in severely ill coronavirus disease survivors 3 months after discharge.

To explore the recovery of renal function in severely ill coronavirus disease (COVID-19) survivors and determine the plasma metabolomic profile of patients with different renal outcomes 3 months after discharge, we included 89 severe COVID-19 survivors who had been discharged from Wuhan Union Hospital for 3 months. All patients had no underlying kidney disease before admission. At patient recruitment, renal function assessment, laboratory examination, chest computed tomography (CT) were performed. Liquid chromatography-mass spectrometry was used to detect metabolites in the plasma. We analyzed the longitudinally change in the estimated glomerular filtration rate (eGFR) based on serum creatinine and cystatin-c levels using the CKD-EPI equation and explored the metabolomic differences in patients with different eGFR change patterns from hospitalization to 3 months after discharge. Lung CT showed good recovery; however, the median eGFR significantly decreased at the 3-month follow-up. Among the 89 severely ill COVID-19 patients, 69 (77.5%) showed abnormal eGFR (<90 mL/min per 1.73 m2) at 3 months after discharge. Age (odds ratio [OR] = 1.26, 95% confidence interval [CI] = 1.08-1.47, p = 0.003), body mass index (OR = 1.97, 95% CI = 1.20-3.22, p = 0.007), and cystatin-c level (OR = 1.22, 95% CI = 1.07-1.39, p = 0.003) at discharge were independent risk factors for post-discharge abnormal eGFR. Plasma metabolomics at the 3-months follow-up revealed that ß-pseudouridine, uridine, and 2-(dimethylamino) guanosine levels gradually increased with an abnormal degree of eGFR. Moreover, the kynurenine pathway in tryptophan metabolism, vitamin B6 metabolism, cysteine and methionine metabolism, and arginine biosynthesis were also perturbed in survivors with abnormal eGFR.

Plasma Metabolomic Profiles in Recovered COVID-19 Patients without Previous Underlying Diseases 3 Months After Discharge.

BACKGROUND: It remains unclear whether discharged COVID-19 patients have fully recovered from severe complications, including the differences in the post-infection metabolomic profiles of patients with different disease severities. METHODS: COVID-19-recovered patients, who had no previous underlying diseases and were discharged from Wuhan Union Hospital for 3 months, and matched healthy controls (HCs) were recruited in this prospective cohort study. We examined the blood biochemical indicators, cytokines, lung computed tomography scans, including 39 HCs, 18 recovered asymptomatic (RAs), 34 recovered moderate (RMs), and 44 recovered severe/ critical patients (RCs). A liquid chromatography-mass spectrometry-based metabolomics approach was employed to profile the global metabolites of fasting plasma of these participants. RESULTS: Clinical data and metabolomic profiles suggested that RAs recovered well, but some clinical indicators and plasma metabolites in RMs and RCs were still abnormal as compared with HCs, such as decreased taurine, succinic acid, hippuric acid, some indoles, and lipid species. The disturbed metabolic pathway mainly involved the tricarboxylic cycle, purine, and glycerophospholipid metabolism. Moreover, metabolite alterations differ between RMs and RCs when compared with HCs. Correlation analysis revealed that many differential metabolites were closely associated with inflammation and the renal, pulmonary, heart, hepatic, and coagulation system functions. CONCLUSION: We uncovered metabolite clusters pathologically relevant to the recovery state in discharged COVID-19 patients which may provide new insights into the pathogenesis of potential organ damage in recovered patients.

Comparison of Residual Pulmonary Abnormalities 3 Months After Discharge in Patients Who Recovered From COVID-19 of Different Severity.

Background and Objectives: To investigate whether coronavirus disease 2019 (COVID-19) survivors who had different disease severities have different levels of pulmonary sequelae at 3 months post-discharge. Methods: COVID-19 patients discharged from four hospitals 3 months previously, recovered asymptomatic patients from an isolation hotel, and uninfected healthy controls (HCs) from the community were prospectively recruited. Participants were recruited at Wuhan Union Hospital and underwent examinations, including quality-of-life evaluation (St. George Respiratory Questionnaire [SGRQ]), laboratory examination, chest computed tomography (CT) imaging, and pulmonary function tests. Results: A total of 216 participants were recruited, including 95 patients who had recovered from severe/critical COVID-19 (SPs), 51 who had recovered from mild/moderate disease (MPs), 28 who had recovered from asymptomatic disease (APs), and 42 HCs. In total, 154 out of 174 (88.5%) recovered COVID-19 patients tested positive for serum SARS-COV-2 IgG, but only 19 (10.9%) were still positive for IgM. The SGRQ scores were highest in the SPs, while APs had slightly higher SGRQ scores than those of HCs; 85.1% of SPs and 68.0% of MPs still had residual CT abnormalities, mainly ground-glass opacity (GGO) followed by strip-like fibrosis at 3 months after discharge, but the pneumonic lesions were largely absorbed in the recovered SPs or MPs relative to findings in the acute phase. Pulmonary function showed that the frequency of lung diffusion capacity for carbon monoxide abnormalities were comparable in SPs and MPs (47.1 vs. 41.7%), while abnormal total lung capacity (TLC) and residual volume (RV) were more frequent in SPs than in MPs (TLC, 18.8 vs. 8.3%; RV, 11.8 vs. 0%). Conclusions: Pulmonary abnormalities remained after recovery from COVID-19 and were more frequent and conspicuous in SPs at 3 months after discharge.

Proteomics of extracellular vesicles in plasma reveals the characteristics and residual traces of COVID-19 patients without underlying diseases after 3 months of recovery.

More and more patients suffered from Coronavirus disease 2019 (COVID-19) have got recovery gradually due to suitable intervention. Increasing data mainly studies the clinical characteristics of recovered COVID-19 patients, and their molecular changes especially proteome changes also play the same important role in understanding of biological characteristics of recovered COVID-19 patients as clinical characteristics do. In our study, we reported the whole lung-ground glass-CT value-average of mild/severe recovered patients 3 months after discharge without underlying diseases was significantly lower than that of healthy subjects. Then we isolated the extracellular vesicles (EVs) of plasma from 19 healthy subjects and 67 recovered COVID-19 patients. Mass Spectrometry was used to catalogue the proteins of these EVs compared to a defined group of controls. Identified 174 proteins were differentially expressed in the EVs of COVID-19 patients compared with healthy subjects, which involved in lipid metabolic process, response to cellular, and response to stress oxygen-containing compound. Besides, we identified several protein of plasma EVs in recovered patients associated with coagulation activity, inflammatory reaction, immune response, and low organ function. In addition, proteins correlating with clinical index such as alkaline phosphatase (ALP) and alanine aminotransferase (ALT) were also detected. Moreover, we also identified many unique or characteristic associations found in the recovered COVID-19 patients, which especially involved the kidney, serum electrolyte levels, and inflammation functions. This finding suggests that monitoring the situation of recovered patients might be useful, especially the indexes of coagulation, inflammation, immunity, and organ function, which can prevent bleeding, reinfection and organ dysfunction.

Characteristics of mental health implications and plasma metabolomics in patients recently recovered from COVID-19.

This study aimed to explore the associations between cerebral white matter (WM) alterations, mental health status, and metabolism in recovered COVID-19 patients. We included 28 recovered COVID-19 patients and 27 healthy controls between April 2020 and June 2020. Demographic data, the mental health scores, diffusion-tensor imaging (DTI) data, and plasma metabolomics were collected and compared between the two groups. Tract-based spatial statistics and graph theory approaches were used for DTI data analysis. Untargeted metabolomics analysis of the plasma was performed. Correlation analyses were performed between these characteristics. Recovered COVID-19 patients showed decreased fractional anisotropy, increased mean diffusivity and radial diffusivity values in widespread brain regions, and significantly lower global efficiency, longer shortest path length, and less nodal local efficiency in superior occipital gyrus (all, P < 0.05, Bonferroni corrected). Our results also demonstrated significantly different plasma metabolic profiling in recovered COVID-19 patients even at 3 months after their hospital discharge, which was mainly related to purine pathways, amino acids, lipids, and amine metabolism. Certain regions with cerebral WM alterations in the recovered patients showed significant correlations with different metabolites and the mental health scores. We observed multiple alterations in both WM integrity and plasma metabolomics that may explain the deteriorated mental health of recovered COVID-19 patients. These findings may provide potential biomarkers for the mental health evaluation for the recovered COVID-19 patients and potential targets for novel therapeutics.

Comparison of clinical characteristics among younger and elderly deceased patients with COVID-19: a retrospective study.

We aimed to compare the age-related clinical characteristics between younger and elderly deceased COVID-19 patients. This single-center retrospective study included 163 adult deceased COVID-19 patients who were admitted to Wuhan Union Hospital West Campus from January 12, 2020, to March 30, 2020. Demographic and clinical features were collected by reviewing the medical records. The median age of the 163 deceased patients was 69 (interquartile range [IQR], 62-78) years. They were classified as younger (age 18-69 years; 86/163, 52.8%) and elderly (≥70 years; 77/163, 47.2%) subjects. Younger deceased patients were more likely to develop fever (72/86 vs 54/77, P=0.039) than elderly deceased patients were while anorexia was (29/77 vs 19/86, P=0.029) more common in elderly deceased patients than in younger deceased patients. In multivariate analyses, age was a protective factor for acute cardiac injury of deceased COVID-19 patients (odds ratio [OR] 0.968, [95% confidence interval (CI), 0.940-0.997]; P=0.033) while chronic cardiac disease was a risk factor for acute cardiac injury of deceased COVID-19 patients (OR 2.660 [95%CI, 1.034-6.843]; P=0.042). Our study described the clinical characteristics of younger and elderly deceased COVID-19 patients and demonstrated that younger deceased patients were more likely to develop an acute cardiac injury.

Clinical Characteristics and Outcomes of Severe or Critical COVID-19 Patients Presenting No Respiratory Symptoms or Fever at Onset.

It is difficult to identify suspected cases of atypical patients with coronavirus disease 2019 (COVID-19), and data on severe or critical patients are scanty. This retrospective study presents the clinical, laboratory, and radiological profiles, treatments, and outcomes of atypical COVID-19 patients without respiratory symptoms or fever at onset. The study examined ten atypical patients out of 909 severe or critical patients diagnosed with COVID-19 in Wuhan Union Hospital West Campus between 25 January 2020 and 10 February 2020. Data were obtained from the electronic medical records of severe or critical patients without respiratory symptoms or fever at onset. Outcomes were followed up to discharge or death. Among 943 COVID-19 patients, 909 (96.4%) were severe or critical type. Of the severe or critical patients, ten (1.1%) presented without respiratory symptoms or fever at admission. The median age of the ten participants was 63 years (interquartile range (IQR): 57-72), and seven participants were men. The median time from symptom onset to admission was 14 d (IQR: 7-20). Eight of the ten patients had chronic diseases. The patients had fatigue (n = 5), headache or dizziness (n = 4), diarrhea (n = 5), anorexia (n = 3), nausea or vomiting (n = 3), and eye discomfort (n = 1). Four patients were found to have lymphopenia. Imaging examination revealed that nine patients had bilateral pneumonia and one had unilateral pneumonia. Eventually, two patients died and eight were discharged. In the discharged patients, the median time from admission to discharge lasted 24 d (IQR: 13-43). In summary, some severe or critical COVID-19 patients were found to have no respiratory symptoms or fever at onset. All such atypical cases should be identified and quarantined as early as possible, since they tend to have a prolonged hospital stay or fatal outcomes. Chest computed tomography (CT) scan and nucleic acid detection should be performed immediately on close contacts of COVID-19 patients to screen out those with atypical infections, even if the contacts present without respiratory symptoms or fever at onset.

The Correlation Between Clinical Features and Viral RNA Shedding in Outpatients With COVID-19.

BACKGROUND: Patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can shed virus, thereby causing human-to-human transmission, and the viral RNA shedding is commonly used as a proxy measure for infectivity. METHODS: We retrospectively reviewed confirmed cases of COVID-19 who attended the fever clinic of Wuhan Union Hospital from January 14 to February 24. In terms of the viral RNA shedding (median values) at first visit, patients were divided into a high-viral RNA shedding group and a low-viral RNA shedding group. Univariate and multivariate logistic regression analysis were performed to investigate the correlation between viral RNA shedding and clinical features. RESULTS: A total of 918 consecutive COVID-19 patients were enrolled, and severe patients made up 26.1%. After univariate and multivariate logistic regression, advanced age (odds ratio [OR], 1.02; 95% CI, 1.01-1.03; P = .001), having severe chronic diseases (OR, 1.44; 95% CI, 1.03-2.01; P = .04), and severe illness (OR, 1.60; 95% CI, 1.12-2.28; P = .01) were independent risk factors for high viral RNA shedding. Shorter time interval from symptom onset to viral detection was a protective factor for viral RNA shedding (OR, 0.97; 95% CI, 0.94-0.99; P = .01). Compared with mild patients, severe patients have higher virus shedding over a long period of time after symptom onset (P = .01). CONCLUSIONS: Outpatients who were old, had severe illness, and had severe underlying diseases had high viral RNA shedding.

Development and validation of a risk factor-based system to predict short-term survival in adult hospitalized patients with COVID-19: a multicenter, retrospective, cohort study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has become a public health emergency of global concern. We aimed to explore the risk factors of 14-day and 28-day mortality and develop a model for predicting 14-day and 28-day survival probability among adult hospitalized patients with COVID-19. METHODS: In this multicenter, retrospective, cohort study, we examined 828 hospitalized patients with confirmed COVID-19 hospitalized in Wuhan Union Hospital and Central Hospital of Wuhan between January 12 and February 9, 2020. Among the 828 patients, 516 and 186 consecutive patients admitted in Wuhan Union Hospital were enrolled in the training cohort and the validation cohort, respectively. A total of 126 patients hospitalized in Central Hospital of Wuhan were enrolled in a second external validation cohort. Demographic, clinical, radiographic, and laboratory measures; treatment; proximate causes of death; and 14-day and 28-day mortality are described. Patients' data were collected by reviewing the medical records, and their 14-day and 28-day outcomes were followed up. RESULTS: Of the 828 patients, 146 deaths were recorded until May 18, 2020. In the training set, multivariate Cox regression indicated that older age, lactate dehydrogenase level over 360 U/L, neutrophil-to-lymphocyte ratio higher than 8.0, and direct bilirubin higher than 5.0 µmol/L were independent predictors of 28-day mortality. Nomogram scoring systems for predicting the 14-day and 28-day survival probability of patients with COVID-19 were developed and exhibited strong discrimination and calibration power in the two external validation cohorts (C-index, 0.878 and 0.839). CONCLUSION: Older age, high lactate dehydrogenase level, evaluated neutrophil-to-lymphocyte ratio, and high direct bilirubin level were independent predictors of 28-day mortality in adult hospitalized patients with confirmed COVID-19. The nomogram system based on the four factors revealed good discrimination and calibration, suggesting good clinical utility.

Fasting blood glucose at admission is an independent predictor for 28-day mortality in patients with COVID-19 without previous diagnosis of diabetes: a multi-centre retrospective study.

AIMS/HYPOTHESIS: Hyperglycaemia is associated with an elevated risk of mortality in community-acquired pneumonia, stroke, acute myocardial infarction, trauma and surgery, among other conditions. In this study, we examined the relationship between fasting blood glucose (FBG) and 28-day mortality in coronavirus disease 2019 (COVID-19) patients not previously diagnosed as having diabetes. METHODS: We conducted a retrospective study involving all consecutive COVID-19 patients with a definitive 28-day outcome and FBG measurement at admission from 24 January 2020 to 10 February 2020 in two hospitals based in Wuhan, China. Demographic and clinical data, 28-day outcomes, in-hospital complications and CRB-65 scores of COVID-19 patients in the two hospitals were analysed. CRB-65 is an effective measure for assessing the severity of pneumonia and is based on four indicators, i.e. confusion, respiratory rate (>30/min), systolic blood pressure (≤90 mmHg) or diastolic blood pressure (≤60 mmHg), and age (≥65 years). RESULTS: Six hundred and five COVID-19 patients were enrolled, including 114 who died in hospital. Multivariable Cox regression analysis showed that age (HR 1.02 [95% CI 1.00, 1.04]), male sex (HR 1.75 [95% CI 1.17, 2.60]), CRB-65 score 1-2 (HR 2.68 [95% CI 1.56, 4.59]), CRB-65 score 3-4 (HR 5.25 [95% CI 2.05, 13.43]) and FBG ≥7.0 mmol/l (HR 2.30 [95% CI 1.49, 3.55]) were independent predictors for 28-day mortality. The OR for 28-day in-hospital complications in those with FBG ≥7.0 mmol/l and 6.1-6.9 mmol/l vs <6.1 mmol/l was 3.99 (95% CI 2.71, 5.88) or 2.61 (95% CI 1.64, 4.41), respectively. CONCLUSIONS/INTERPRETATION: FBG ≥7.0 mmol/l at admission is an independent predictor for 28-day mortality in patients with COVID-19 without previous diagnosis of diabetes. Glycaemic testing and control are important to all COVID-19 patients even where they have no pre-existing diabetes, as most COVID-19 patients are prone to glucose metabolic disorders. Graphical abstract.