A modeling-based approach to optimize COVID-19 vaccine dosing schedules for improved protection.

While the development of different vaccines slowed the dissemination of SARS-CoV-2, the occurrence of breakthrough infections has continued to fuel the COVID-19 pandemic. To secure at least partial protection in the majority of the population through 1 dose of a COVID-19 vaccine, delayed administration of boosters has been implemented in many countries. However, waning immunity and emergence of new variants of SARS-CoV-2 suggest that such measures may induce breakthrough infections due to intermittent lapses in protection. Optimizing vaccine dosing schedules to ensure prolonged continuity in protection could thus help control the pandemic. We developed a mechanistic model of immune response to vaccines as an in silico tool for dosing schedule optimization. The model was calibrated with clinical data sets of acquired immunity to COVID-19 mRNA vaccines in healthy and immunocompromised participants and showed robust validation by accurately predicting neutralizing antibody kinetics in response to multiple doses of COVID-19 mRNA vaccines. Importantly, by estimating population vulnerability to breakthrough infections, we predicted tailored vaccination dosing schedules to minimize breakthrough infections, especially for immunocompromised individuals. We identified that the optimal vaccination schedules vary from CDC-recommended dosing, suggesting that the model is a valuable tool to optimize vaccine efficacy outcomes during future outbreaks.

The CH24H metabolite, 24HC, blocks viral entry by disrupting intracellular cholesterol homeostasis.

Cholesterol-24-hydroxylase (CH24H or Cyp46a1) is a reticulum-associated membrane protein that plays an irreplaceable role in cholesterol metabolism in the brain and has been well-studied in several neuro-associated diseases in recent years. In the present study, we found that CH24H expression can be induced by several neuroinvasive viruses, including vesicular stomatitis virus (VSV), rabies virus (RABV), Semliki Forest virus (SFV) and murine hepatitis virus (MHV). The CH24H metabolite, 24-hydroxycholesterol (24HC), also shows competence in inhibiting the replication of multiple viruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). 24HC can increase the cholesterol concentration in multivesicular body (MVB)/late endosome (LE) by disrupting the interaction between OSBP and VAPA, resulting in viral particles being trapped in MVB/LE, ultimately compromising VSV and RABV entry into host cells. These findings provide the first evidence that brain cholesterol oxidation products may play a critical role in viral infection.

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.

MERS-CoV nsp1 regulates autophagic flux via mTOR signalling and dysfunctional lysosomes.

Autophagy, a cellular surveillance mechanism, plays an important role in combating invading pathogens. However, viruses have evolved various strategies to disrupt autophagy and even hijack it for replication and release. Here, we demonstrated that Middle East respiratory syndrome coronavirus (MERS-CoV) non-structural protein 1(nsp1) induces autophagy but inhibits autophagic activity. MERS-CoV nsp1 expression increased ROS and reduced ATP levels in cells, which activated AMPK and inhibited the mTOR signalling pathway, resulting in autophagy induction. Meanwhile, as an endonuclease, MERS-CoV nsp1 downregulated the mRNA of lysosome-related genes that were enriched in nsp1-located granules, which diminished lysosomal biogenesis and acidification, and inhibited autophagic flux. Importantly, MERS-CoV nsp1-induced autophagy can lead to cell death in vitro and in vivo. These findings clarify the mechanism by which MERS-CoV nsp1-mediated autophagy regulation, providing new insights for the prevention and treatment of the coronavirus.

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.

Genetic and Structural Analysis of SARS-CoV-2 Spike Protein for Universal Epitope Selection.

Evaluation of immunogenic epitopes for universal vaccine development in the face of ongoing SARS-CoV-2 evolution remains a challenge. Herein, we investigate the genetic and structural conservation of an immunogenically relevant epitope (C662-C671) of spike (S) protein across SARS-CoV-2 variants to determine its potential utility as a broad-spectrum vaccine candidate against coronavirus diseases. Comparative sequence analysis, structural assessment, and molecular dynamics simulations of C662-C671 epitope were performed. Mathematical tools were employed to determine its mutational cost. We found that the amino acid sequence of C662-C671 epitope is entirely conserved across the observed major variants of SARS-CoV-2 in addition to SARS-CoV. Its conformation and accessibility are predicted to be conserved, even in the highly mutated Omicron variant. Costly mutational rate in the context of energy expenditure in genome replication and translation can explain this strict conservation. These observations may herald an approach to developing vaccine candidates for universal protection against emergent variants of coronavirus.

Daratumumab for Refractory IgD Multiple Myeloma with Lung Cancer and Persistent Thrombocytopenia: a Case Report.

BACKGROUND: Immunoglobulin D multiple myeloma (IgD-MM) is a rare but aggressive disease. The safety and effectiveness of anti-CD38 monoclonal antibody (daratumumab) have not been known in either IgD-MM or MM complicated with secondary neoplasm. METHODS: A fragile IgD-MM patient had an aggressively relapsed disease concurrent with lung cancer and severe thrombocytopenia, which led to a dilemma for management. After a failure of ixazomib-based chemotherapy, a salvage therapy with daratumumab unexpectedly induced complete remission and platelet recovery, and the patient successfully proceeded to lung cancer surgery. CONCLUSIONS: Our case indicates daratumumab is both safe and effective for refractory IgD-MM with severe complications.

Prevalence of Dementia in China in 2015: A Nationwide Community-Based Study.

Objective: This study aims to estimate the prevalence of dementia and Alzheimer's disease (AD) and associated risk factors among the general Chinese population. Methods: We carried out a nationwide study including 24,117 participants aged 60 years and older in China using a multistage clustered sampling. Dementia and AD were diagnosed according to the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders and the criteria issued by the National Institute of Neurological and Communicative Disorders and Stroke-Alzheimer's Disease and Related Disorders Association. Face-to-face interviews were administered by the trained interviewers to obtain information on demographics, lifestyle factors, and previous diseases. Results: The overall weighted prevalence of dementia was 4.22% (95%CI 2.27-6.17%) for people aged 60 years and older, was higher in women than in men and increased with age. Daily tea drinking and daily exercises were the protective factors for both dementia and AD. Engaging in social and intellectual activities was significantly associated with a lower risk of dementia and AD. Conclusions: A large number of population with dementia posed a significant challenge to China where the population is rapidly aging. The increase of public awareness, building more care facilities, and training dementia specialists and professional caregivers are all urgently needed and should be the future priorities of dementia care in China.

MERS-CoV nsp1 impairs the cellular metabolic processes by selectively downregulating mRNAs in a novel granules.

MERS-CoV infection can damage the cellular metabolic processes, but the underlying mechanisms are largely unknown. Through screening, we found non-structural protein 1 (nsp1) of MERS-CoV could inhibit cell viability, cell cycle, and cell migration through its endonuclease activity. Transcriptome sequencing revealed that MERS-CoV nsp1 specifically downregulated the mRNAs of ribosomal protein genes, oxidative phosphorylation protein genes, and antigen presentation genes, but upregulated the mRNAs of transcriptional regulatory genes. Further analysis shown nsp1 existed in a novel ribonucleosome complex formed via liquid-liquid phase separation, which did not co-localize with mitochondria, lysosomes, P-bodies, or stress granules. Interestingly, the nsp1-located granules specifically contained mRNAs of ribosomal protein genes and oxidative phosphorylation genes, which may explain why MERS-CoV nsp1 selectively degraded these mRNAs in cells. Finally, MERS-CoV nsp1 transgenic mice showed significant loss of body weight and an increased sensitivity to poly(I:C)-induced inflammatory death. These findings demonstrate a new mechanism by which MERS-CoV impairs cell viability, which serves as a potential novel target for preventing MERS-CoV infection-induced pathological damage.Abbreviations: (Middle East respiratory syndrome coronavirus (MERS-CoV), Actinomycin D (Act D), liquid-liquid phase separation (LLPS), stress granules (SGs), Mass spectrometry (IP-MS), RNA Binding Protein Immunoprecipitation (RIP)).

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.

The Pathogenic Features of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2): Possible Mechanisms for Immune Evasion?

Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) is a newly emerging, highly transmitted and pathogenic coronavirus that has caused global public health events and economic crises. As of March 4, 2021, more than 100 million people have been infected, more than 2 million deaths have been reported worldwide, and the numbers are continuing to rise. To date, a specific drug for this lethal virus has not been developed to date, and very little is currently known about the immune evasion mechanisms of SARS-CoV-2. The aim of this review was to summarize and sort dozens of published studies on PubMed to explore the pathogenic features of SARS-CoV-2, as well as the possible immune escape mechanisms of this virus.

Is the worst of the COVID-19 global pandemic yet to come? Application of financial mathematics as candidate predictive tools.

The Elliott Wave principle is a time-honored, oft-used method for predicting variations in the financial markets. It is based on the notion that human emotions drive financial decisions. In the fight against the COVID-19 global pandemic, human emotions are similarly decisive, for instance in that they determine one's willingness to be vaccinated, and/or to follow preventive measures including the personal wearing of masks, the application of social distancing protocols, and frequent handwashing. On this basis, we postulated that the Elliott Wave Principle may similarly be used to predict the future evolution of the COVID-19 pandemic. We demonstrated that this method reproduces the data pattern for various countries and the world (daily new cases). Potential scenarios were then extrapolated, from the best-case corresponding to a rapid, full vaccination of the population, to the utterly disastrous case of slow vaccination, and poor adherence to preventive protocols.

Association Between Longitudinal Change in Abnormal Fasting Blood Glucose Levels and Outcome of COVID-19 Patients Without Previous Diagnosis of Diabetes.

This retrospective study examined changes in fasting blood glucose (FBG) levels during hospitalization and their effect on risk of death for Coronavirus disease 2019 (COVID-19) patients without previously diagnosed diabetes. A model with low- and high-stable pattern trajectories was established based on a longitudinal change in FBG levels. We analyzed FBG trajectory-associated clinical features and risk factors for death due to COVID-19. Of the 230 enrolled patients, 44 died and 87.83% had a low-stable pattern (average FBG range: 6.63-7.54 mmol/L), and 12.17% had a high-stable pattern (average FBG range: 12.59-14.02 mmol/L). There were statistical differences in laboratory findings and case fatality between the two FBG patterns. Multivariable logistic regression analysis showed that increased neutrophil count (odds ratio [OR], 25.43; 95% confidence interval [CI]: 2.07, 313.03), elevated direct bilirubin (OR, 5.80; 95%CI: 1.72, 19.58), elevated creatinine (OR, 26.69; 95% CI: 5.82, 122.29), lymphopenia (OR, 8.07; 95% CI: 2.70, 24.14), and high-stable FBG pattern (OR, 8.79; 95% CI: 2.39, 32.29) were independent risk factors for higher case fatality in patients with COVID-19 and hyperglycemia but no history of diabetes. FBG trajectories were significantly associated with death risk in patients with COVID-19 and no diabetes.

Innate Immunity Plays a Key Role in Controlling Viral Load in COVID-19: Mechanistic Insights from a Whole-Body Infection Dynamics Model.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a pathogen of immense public health concern. Efforts to control the disease have only proven mildly successful, and the disease will likely continue to cause excessive fatalities until effective preventative measures (such as a vaccine) are developed. To develop disease management strategies, a better understanding of SARS-CoV-2 pathogenesis and population susceptibility to infection are needed. To this end, mathematical modeling can provide a robust in silico tool to understand COVID-19 pathophysiology and the in vivo dynamics of SARS-CoV-2. Guided by ACE2-tropism (ACE2 receptor dependency for infection) of the virus and by incorporating cellular-scale viral dynamics and innate and adaptive immune responses, we have developed a multiscale mechanistic model for simulating the time-dependent evolution of viral load distribution in susceptible organs of the body (respiratory tract, gut, liver, spleen, heart, kidneys, and brain). Following parameter quantification with in vivo and clinical data, we used the model to simulate viral load progression in a virtual patient with varying degrees of compromised immune status. Further, we ranked model parameters through sensitivity analysis for their significance in governing clearance of viral load to understand the effects of physiological factors and underlying conditions on viral load dynamics. Antiviral drug therapy, interferon therapy, and their combination were simulated to study the effects on viral load kinetics of SARS-CoV-2. The model revealed the dominant role of innate immunity (specifically interferons and resident macrophages) in controlling viral load, and the importance of timing when initiating therapy after infection.

Resurgence of Positive qRT-PCR Test Results in Patients Recovered from COVID-19: Case Reports.

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a newly emerging coronavirus. This virus poses a great threat to human society and has been marked as the third introduction of a highly pathogenic coronavirus into the human population. This is following severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) in the 21st-century. While China has achieved initial success in controlling the spread of COVID-19 and treating those infected with SARS-CoV-2, up to 14% of COVID-19 convalescents can still be detected with virus nucleic acid. Thus, there is an urgent need for more information to understand this new virus. Here we report the detailed clinical characteristics of three cases of COVID-19 convalescents that had repeated positive quantitative reverse transcription-polymerase chain reaction (qRT-PCR) test results for over three months. This may arouse concerns regarding the present quarantine protocol after convalescence and provide a reference for governments to consider when to reopen the community.

Factors associated with asymptomatic infection in health-care workers with severe acute respiratory syndrome coronavirus 2 infection in Wuhan, China: a multicentre retrospective cohort study.

OBJECTIVES: To describe the fraction of asymptomatic health-care workers (HCWs) in two designated hospitals for coronavirus disease 2019 (COVID-19) treatment in Wuhan and explore the factors associated with asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. METHODS: All HCWs in Wuhan Union Hospital and Wuhan Red Cross Hospital with either positive SARS-CoV-2 nucleic acid or positive antibody test before 18 April 2020 were included. Exposure, epidemiological and demographic information were retrospectively collected by a structured questionnaire. Medical records were also reviewed for clinical characteristics and CT images of HCWs. RESULTS: As of 18 April 2020, a total of 424 HCWs were identified. Among them, 276 (65.1%) were symptomatic and 148 (34.9%) were asymptomatic. Fifty-five (19.9%) families of the symptomatic HCWs and 16 (10.8%) families of the asymptomatic HCWs were infected with SARS-CoV-2. HCWs with infected family members tended to be symptomatic (OR 2.053, 95% CI 1.130-3.730; p 0.018). Multivariable logistic regression analysis exhibited that performing tracheal intubation or extubation (OR 4.057, 95% CI 1.183-13.909; p 0.026) was associated with an increased likelihood of symptomatic SARS-CoV-2 infection, whereas consistent use of N95 respirators (OR 0.369, 95% CI 0.201-0.680; p 0.001) and eye protection (OR 0.217, 95% CI 0.116-0.404; p < 0.001) were associated with an increased likelihood of asymptomatic SARS-CoV-2 infection. CONCLUSIONS: Asymptomatic SARS-CoV-2 infection in HCWs comprised a considerable proportion of HCW infections during the pandemic of COVID-19. Those who performed tracheal intubation or extubation were most likely to develop related symptoms, whereas those taking aggressive measures, including consistent use of N95 masks and eye protection, tended to be asymptomatic cases.

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.

Haematological characteristics and risk factors in the classification and prognosis evaluation of COVID-19: a retrospective cohort study.

BACKGROUND: COVID-19 is an ongoing global pandemic. Changes in haematological characteristics in patients with COVID-19 are emerging as important features of the disease. We aimed to explore the haematological characteristics and related risk factors in patients with COVID-19. METHODS: This retrospective cohort study included patients with COVID-19 admitted to three designated sites of Wuhan Union Hospital (Wuhan, China). Demographic, clinical, laboratory, treatment, and outcome data were extracted from electronic medical records and compared between patients with moderate, severe, and critical disease (defined according to the diagnosis and treatment protocol for novel coronavirus pneumonia, trial version 7, published by the National Health Commission of China). We assessed the risk factors associated with critical illness and poor prognosis. Dynamic haematological and coagulation parameters were investigated with a linear mixed model, and coagulopathy screening with sepsis-induced coagulopathy and International Society of Thrombosis and Hemostasis overt disseminated intravascular coagulation scoring systems was applied. FINDINGS: Of 466 patients admitted to hospital from Jan 23 to Feb 23, 2020, 380 patients with COVID-19 were included in our study. The incidence of thrombocytopenia (platelet count <100 × 109 cells per L) in patients with critical disease (42 [49%] of 86) was significantly higher than in those with severe (20 [14%] of 145) or moderate (nine [6%] of 149) disease (p<0·0001). The numbers of lymphocytes and eosinophils were significantly lower in patients with critical disease than those with severe or moderate disease (p<0·0001), and prothrombin time, D-dimer, and fibrin degradation products significantly increased with increasing disease severity (p<0·0001). In multivariate analyses, death was associated with increased neutrophil to lymphocyte ratio (≥9·13; odds ratio [OR] 5·39 [95% CI 1·70-17·13], p=0·0042), thrombocytopenia (platelet count <100 × 109 per L; OR 8·33 [2·56-27·15], p=0·00045), prolonged prothrombin time (>16 s; OR 4·94 [1·50-16·25], p=0·0094), and increased D-dimer (>2 mg/L; OR 4·41 [1·06-18·30], p=0·041). Thrombotic and haemorrhagic events were common complications in patients who died (19 [35%] of 55). Sepsis-induced coagulopathy and International Society of Thrombosis and Hemostasis overt disseminated intravascular coagulation scores (assessed in 12 patients who survived and eight patients who died) increased over time in patients who died. The onset of sepsis-induced coagulopathy was typically before overt disseminated intravascular coagulation. INTERPRETATION: Rapid blood tests, including platelet count, prothrombin time, D-dimer, and neutrophil to lymphocyte ratio can help clinicians to assess severity and prognosis of patients with COVID-19. The sepsis-induced coagulopathy scoring system can be used for early assessment and management of patients with critical disease. FUNDING: National Key Research and Development Program of China.

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.