The differences in cytokine signatures between severe fever with thrombocytopenia syndrome (SFTS) and hemorrhagic fever with renal syndrome (HFRS).

Severe fever with thrombocytopenia syndrome (SFTS) virus and hantavirus are categorized under the Bunyavirales order. The severe disease progression in both SFTS and hemorrhagic fever with renal syndrome (HFRS) is associated with cytokine storms. This study aimed to explore the differences in cytokine profiles and immune responses between the two diseases. A cross-sectional, single-center study involved 100 participants, comprising 46 SFTS patients, 48 HFRS patients, and 6 healthy controls. The study employed the Luminex cytokine detection platform to measure 48 cytokines. The differences in cytokine profiles and immune characteristics between the two diseases were further analyzed using multiple linear regression, principal component analysis, and random forest method. Among the 48 cytokines tested, 30 showed elevated levels in SFTS and/or HFRS compared to the healthy control group. Furthermore, there were 19 cytokines that exhibited significant differences between SFTS and HFRS. Random forest analysis suggested that TRAIL and CTACK were predictive of SFTS, while IL2Ralpha, MIG, IL-8, IFNalpha2, HGF, SCF, MCP-3, and PDGFBB were more common with HFRS. It was further verified by the receiver operating characteristic with area under the curve >0.8 and P-values <0.05, except for TRAIL. Significant differences were observed in the cytokine profiles of SFTS and HFRS, with TRAIL, IL2Ralpha, MIG, and IL-8 being the top 4 cytokines that most clearly distinguished the two diseases. IMPORTANCE: SFTS and HFRS differ in terms of cytokine immune characteristics. TRAIL, IL-2Ralpha, MIG, and IL-8 were the top 4 that differed markedly between SFTS and HFRS.

Identification of CCL20 as a prognostic predictor for severe fever with thrombocytopenia syndrome based on plasma proteomics.

BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS), a lethal tick-borne hemorrhagic fever, prompted our investigation into prognostic predictors and potential drug targets using plasma Olink Proteomics. METHODS: Employing the Olink assay, we analyzed 184 plasma proteins in 30 survivors and 8 non-survivors of SFTS. Validation was performed in a cohort of 154 SFTS patients using enzyme-linked immunosorbent assay. We utilized the Drug Gene Interaction database to identify protein-drug interactions. RESULTS: Non-survivors exhibited 110 differentially expressed proteins (DEPs) compared to survivors, with functional enrichment in the cell chemotaxis-related pathway. Thirteen DEPs, including C-C motif chemokine 20 (CCL20), calcitonin gene-related peptide alpha and Pleiotrophin, were associated with multiple organ dysfunction syndrome. CCL20 emerged as the top predictor of death, demonstrating an area under the curve of 1 (P = .0004) and 0.9033 (P < .0001) in the discovery and validation cohort, respectively. Patients with CCL20 levels exceeding 45.74 pg/mL exhibited a fatality rate of 45.65%, while no deaths occurred in those with lower CCL20 levels. Furthermore, we identified 202 FDA-approved drugs targeting 37 death-related plasma proteins. CONCLUSIONS: Distinct plasma proteomic profiles characterize SFTS patients with different outcomes, with CCL20 emerging as a novel, sensitive, accurate, and specific biomarker for predicting SFTS prognosis.

High C-reactive protein to lymphocyte ratio predicts mortality outcomes of patients with severe fever with thrombocytopenia syndrome: A multicenter study in China.

Severe fever with thrombocytopenia syndrome (SFTS) is a life-threatening infectious disease caused by the SFTS virus (SFTSV). This study aimed to evaluate the predictive power of C-reactive protein to lymphocyte ratio (CLR) and establish an early-warning model for SFTS mortality. We retrospectively analyzed hospitalized SFTS patients in six clinical centers from May 2011 to 2022. The efficacy of CLR prediction was evaluated by the receiver operating characteristic (ROC) analysis. A nomogram was established and validated. Eight hundred and eighty-two SFTS patients (median age 64 years, 48.5% male) were enrolled in this study, with a mortality rate of 17.8%. The area under the ROC curve (AUC) of CLR was 0.878 (95% confidence interval [CI]: 0.850-0.903, p < 0.001), which demonstrates high predictive strength. The least absolute shrinkage and selection operator regression selected seven potential predictors. Multivariate logistic regression analysis determined three independent risk factors, including CLR, to construct the nomogram. The performance of the nomogram displayed excellent discrimination and calibration, with significant net benefits in clinical uses. CLR is a brand-new predictor for SFTS mortality. The nomogram based on CLR can serve as a convenient tool for physicians to identify critical SFTS cases in clinical practice.

High levels of C-reactive protein-to-albumin ratio (CAR) are associated with a poor prognosis in patients with severe fever with thrombocytopenia syndrome in early stage.

C-reactive protein-to-albumin ratio (CAR) can be used to assess the prognosis of various diseases. This study aimed to evaluate the relationship between CAR on the prognosis of patients with severe fever with thrombocytopenia syndrome (SFTS). This study included 155 SFTS patients from the Public Health Clinical Center of Dalian from January to December 2021. They were divided into survival and deceased groups based on the clinical prognosis. The independent risk factors for poor prognosis of SFTS patients at an early stage were determined by Cox regression. The efficacy of CAR prediction was assessed by the receiver operating characteristic (ROC) curve. A total of 155 patients were included in this study, with an average age of 61.98± 11.70 years, including 77 males and 65 females. The mortality rate of the patients enrolled in this study was 14.19%. Multivariate Cox regression indicated that CAR (hazard ratio = 2.585, 95% confidence interval [CI] 1.405-4.753, p = 0.002) could be an independent predictor for prognosis in SFTS patients at an early stage. CAR had an AUC of 0.781 (95% CI, 0.665-0.898, p = 0.000), a cutoff value of 0.57, a sensitivity of 0.77, and a specificity of 0.80, with better predictive efficacy, compared to neutrophil-to-lymphocyte ratio (NLR). High levels of CAR are associated with poor prognosis in SFTS patients, and CAR can be used as an independent predictor for SFTS patients.

Genomic, immunological, and clinical analysis of COVID-19 vaccine breakthrough infections in Beijing, China.

As the coronavirus disease 2019 (COVID-19) pandemic is still ongoing and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants are circulating worldwide, an increasing number of breakthrough infections are being detected despite the good efficacy of COVID-19 vaccines. Data on 88 COVID-19 breakthrough cases (breakthrough infections group) and 41 unvaccinated cases (unvaccinated group) from June 1 to August 22, 2021, were extracted from a cloud database established at Beijing Ditan Hospital to evaluate the clinical, immunological, and genomic characteristics of COVID-19 breakthrough infections. Among these 129 COVID-19 cases, 33 whole genomes were successfully sequenced, of which 23 were Delta variants, including 15 from the breakthrough infections group. Asymptomatic and mild cases predominated in both groups, but two patients developed severe disease in the unvaccinated group. The median time of viral shedding in the breakthrough infections group was significantly lower than that in the unvaccinated group (p = 0.003). In the breakthrough infections group, the IgG titers showed a significantly increasing trend (p = 0.007), and the CD4 + T lymphocyte count was significantly elevated (p = 0.018). For people infected with the Delta variant in the two groups, no significant difference was observed in either the quantitative reverse-transcription polymerase chain reaction results or viral shedding time. In conclusion, among vaccinated patients, the cases of COVID-19 vaccine breakthrough infections were mainly asymptomatic and mild, IgG titers were significantly increased and rose rapidly, and the viral shedding time was shorter.

Clinical manifestations of death with severe fever and thrombocytopenia syndrome: A meta-analysis and systematic review.

Severe hemorrhagic fever disease is caused by severe fever with thrombocytopenia syndrome virus (SFTSV) infection, which belongs to the Phlebovirus genus in the Bunyaviridae family. A comprehensive literature search of PubMed, Web of Science, Embase, Cochrane Library, Chinese National Knowledge Infrastructure databases, Wan Fang Data, Sinomed Database, and VIP database was conducted for articles which have described the clinical manifestation of deceased patients. Data from selected studies were pooled by using STATA VERSION 15.0 software. Finally, 29 articles comprising 4717 laboratory-confirmed SFTSV cases were included in this analysis. We found there were significant differences between the two groups for fatigue, headache, underlying disease, vomiting, diarrhea, skin bleeding, neurological symptoms, arrhythmia, diffuse intravascular coagulation, and multiple organ failure. There were some significant differences between the fatal and nonfatal groups, and we need to pay more attention to the above symptoms to distinguish between fatal and nonfatal patients.

High Levels of Circulating Cell-free DNA Are Associated With a Poor Prognosis in Patients With Severe Fever With Thrombocytopenia Syndrome.

BACKGROUND: The extensive geographical distribution and high mortality rate of severe fever with thrombocytopenia syndrome (SFTS) have made it an important threat to public health. Neutrophil extracellular traps (NETs) can be activated by a variety of pathogens and are associated with thrombocytopenia in viral infections. We aimed to identify NET production and its predictive value for disease progression and prognosis in patients with SFTS. METHODS: A prospective study was performed with a multicenter cohort of patients with SFTS (n = 112) to quantify serum NET levels. Three markers of NETs-namely, cell-free DNA (cfDNA), myeloperoxidase-DNA complexes, and lactoferrin-DNA complexes-were measured with PicoGreen double-stranded DNA assays and enzyme-linked immunosorbent assays. Receiver operating characteristic curves and multivariate regression analyses were performed to calculate the predictive value of cfDNA levels. RESULTS: SFTS was characterized by pronounced NET formation. The serum levels of NETs changed dynamically during disease progression, with an inverse pattern of the trends of platelet and neutrophil levels. High cfDNA levels were strongly associated with multiple pathological processes, including coagulopathy, myocardial damage, liver dysfunction, and the development of encephalopathy. A high level of cfDNA (>711.7 ng/mL) at the time of the initial diagnosis predicted severe illness in patients with SFTS (odds ratio, 8.285 [95% confidence interval, 2.049-33.503]; P = .003). CONCLUSIONS: This study has a high degree of clinical impact for identification of cfDNA as a useful predictive biomarker of clinical outcomes of SFTS.

Increased cTnI Predicts Early Death in Patients with Severe Fever with Thrombocytopenia: A Multicenter Study in North China.

Background: Myocardial injury is common in severe fever with thrombocytopenia syndrome (SFTS) patients. Currently, research on the prognostic value of cardiac troponin I (cTnI) for predicting the mortality of SFTS patients, especially death within 7 days is limited. Methods: Between May 2011 and October 2022, clinical and laboratory data on admission of consecutive SFTS cases were collected from six medical centres in China. The clinical endpoint was in-hospital all-cause death within seven days. Risk factors of myocardial injury and death were analysed using multivariable regression models. Prognostic models were established using Cox regression and performance of indicators was evaluated in terms of calibration, discrimination. Results: A total of 1379 laboratory-confirmed patients were enrolled, in which 686 subjects were included for analysis. The median age was 66 years, with 48.1% of male. Eighty-seven patients died within seven days and 396 patients diagnosed with myocardial injury during hospitalization. Non-survivors had significant higher levels of cardiac indices than survivors, including cTnI, aspartic transaminase (AST) and lactate dehydrogenase (LDH). Elevated levels of cTnI (HR = 1.058, 95% CI:1.032-1.085), AST (HR = 1.191, 95% CI:1.150-1.234) and LDH (HR = 1.019, 95% CI:1.009-1.029) predicted risk of early in-hospital mortality. cTnI model performed best, with area under curve of 0.850 (0.774-0.926) and concordance index of 0.842, respectively. Statistical differences were found between high and low levels of cTnI for mortality (P<0.001) using 0.35 ng/mL as the optimal cut-off. Conclusion: The risk of early in-hospital death can be predicted by cTnI. Clinical doctors should remind vigilant concerning the elevation of cardiac enzyme as soon as possible.

Development and validation of the PLNA score to predict cytokine storm in acute-phase SFTS patients: A single-center cohort study.

BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease known for its high mortality rate and its correlation with Cytokine Storms (CS). Timely detection of CS is crucial for improving the prognosis of the disease. The objective of this investigation was to develop a model for identifying cytokine storms in the acute phase of SFTS. METHODS: A total of 245 patients diagnosed with SFTS were included in this study between January 2020 and July 2022. Among them, 184 patients were part of the training set, while 61 patients were part of the validation set. Variables identified by LASSO were subsequently included in a multivariate logistic regression analysis to determine independent predictors. Subsequently, a nomogram was then developed to predict the likelihood of CS in SFTS patients. The predictive efficacy and clinical applicability of the nomogram model were further assessed through ROC analysis and the DCA curve. RESULTS: Following LASSO analysis, a total of 11 indicators were included in multivariate logistic regression analysis. The findings indicated that PLT (OR 0.865, P < 0.001), LDH (OR 1.002, P < 0.001), Na+ (OR 1.155, P = 0.005), and ALT (OR 1.019, P < 0.001) serve as independently predictors of CS in the acute phase of SFTS. Furthermore, a nomogram named the PLNA was constructed by integrating these four factors. The PLNA model exhibited favorable predictive accuracy with an AUC of 0.958. Moreover, the PLNA model exhibited excellent clinical applicability in both the training and validation sets, as evidenced by the DCA curve. CONCLUSIONS: The PLNA model, constructed using clinical indicators, can predict the probability of cytokine storm in the acute phase of SFTS patients.

MCP-3 as a prognostic biomarker for severe fever with thrombocytopenia syndrome: a longitudinal cytokine profile study.

Introduction: Severe fever with thrombocytopenia syndrome (SFTS) is characterized by a high mortality rate and is associated with immune dysregulation. Cytokine storms may play an important role in adverse disease regression, this study aimed to assess the validity of MCP-3 in predicting adverse outcomes in SFTS patients and to investigate the longitudinal cytokine profile in SFTS patients. Methods: The prospective study was conducted at Yantai Qishan Hospital from May to November 2022. We collected clinical data and serial blood samples during hospitalization, patients with SFTS were divided into survival and non-survival groups based on the clinical prognosis. Results: The levels of serum 48 cytokines were measured using Luminex assays. Compared to healthy controls, SFTS patients exhibited higher levels of most cytokines. The non-survival group had significantly higher levels of 32 cytokines compared to the survival group. Among these cytokines, MCP-3 was ranked as the most significant variable by the random forest (RF) model in predicting the poor prognosis of SFTS patients. Additionally, we validated the predictive effects of MCP-3 through receiver operating characteristic (ROC) curve analysis with an AUC of 0.882 (95% CI, 0.787-0.978, P <0.001), and the clinical applicability of MCP-3 was assessed favorably based on decision curve analysis (DCA). The Spearman correlation analysis indicated that the level of MCP-3 was positively correlated with ALT, AST, LDH, α-HBDH, APTT, D-dimer, and viral load (P<0.01). Discussion: For the first time, our study identified and validated that MCP-3 could serve as a meaningful biomarker for predicting the fatal outcome of SFTS patients. The longitudinal cytokine profile analyzed that abnormally increased cytokines were associated with the poor prognosis of SFTS patients. Our study provides new insights into exploring the pathogenesis of cytokines with organ damage and leading to adverse effects.

Activated partial thromboplastin time predicts mortality in patients with severe fever with thrombocytopenia syndrome: A multicenter study in north China.

Background: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease with high lethality. This study aimed to determine whether prolonged activated partial thromboplastin time (APTT) predicted SFTS mortality. Methods: SFTS patients were enrolled from 6 hospitals in the north China. Subjects were divided into training cohort and 5 externally validation cohorts. The least absolute shrinkage and selection operator Cox regression model was performed to screen potential prognostic factors. Risk factors were analyzed using multivariable regression models. Prognostic models were established by Cox regression and random survival forest (RSF) methods, and evaluated regarding discrimination, validity and clinical benefit. Time-dependent receiver operating characteristic (ROC) curve was used to evaluate the predictive effectiveness of variables. Results: 1332 SFTS cases were included, in which 211 patients died. Six potential prognostic factors were screened, and pulse, breath, APTT and aspartic transaminase (AST) were independently associated with mortality in both training cohort (Yantai, N = 791) and external validation cohort (N = 541). APTT was steadily correlated with the fatality (HR: 1.039-1.144; all P < 0.01) in each five sub-validation cohorts (Dandong, Dalian, Tai'an, Qingdao and Beijing). RSF model with variables of APTT, AST, pulse and breath had considerable prognostic effectiveness, which APTT showed the highest prognostic ability with the area under the curve of 0.848 and 0.787 for 7-day and 14-day survival, respectively. Survival differences were found between high and low levels of APTT for mortality using 50s as the optimal cut-off. Conclusions: SFTS patients have prolonged APTT, which is an independent risk factor for fatality. APTT≥50s was recommended as a biomarker to remind physicians to monitor and treat patients more aggressively to improve clinical prognosis.

The first reported cases of severe fever with thrombocytopenia syndrome virus from domestic sick camel to humans in China.

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne disease with an increasing annual incidence rate. In this case report, we presented two patients infected with the SFTS virus, suggesting a potential direct transmission route from camels to humans through blood contact. Both patients developed symptoms after engaging in the slaughtering of one sick camel, while their family members living in the same environment or co-diners remained unaffected. Subsequent detection revealed a high viral load of SFTS virus, reaching 1010 viral RNA copies/ml, in the sample obtained from the sick camel. Metagenomic sequencing did not identify any other pathogens. The SFTS virus was successfully isolated from both patient and camel samples. The complete nucleotide sequences obtained from the infected patients demonstrated a remarkable 100% similarity to those found in the camel, and genetic evolution analysis classified the virus as genotype A. Additionally, partial sequences of the SFTS virus were identified in ticks captured from the camel rearing environment, however, these sequences showed only 95.9% similarity to those found in camel and humans. Furthermore, immunoglobulin M and immunoglobulin G antibodies were detected in serum samples collected from the patient. Our findings provide evidence that camel may serve as a competent reservoir for transmitting the SFTS virus to humans. Further in vitro investigations into SFTS virus infections in large animals are warranted to understand their role in viral maintenance and transmission.

Assessing airborne transmission risks in COVID-19 hospitals by systematically monitoring SARS-CoV-2 in the air.

IMPORTANCE: Risk management and control of airborne transmission in hospitals is crucial in response to a respiratory virus pandemic. However, the formulation of these infection control measures is often based on epidemiological investigations, which are an indirect way of analyzing the transmission route of viruses. This can lead to careless omissions in infection prevention and control or excessively restrictive measures that increase the burden on healthcare workers. The study provides a starting point for standardizing transmission risk management in designated hospitals by systemically monitoring viruses in the air of typical spaces in COVID-19 hospitals. The negative results of 359 air samples in the clean and emergency zones demonstrated the existing measures to interrupt airborne transmission in a designated COVID-19 hospital. Some positive cases in the corridor of the contaminant zone during rounds and meal delivery highlighted the importance of monitoring airborne viruses for interrupting nosocomial infection.

Eosinophils and basophils in severe fever with thrombocytopenia syndrome patients: Risk factors for predicting the prognosis on admission.

BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS) virus (SFTSV) is an emerging tick-borne phlebovirus with a high fatality rate. Previous studies have demonstrated the poor prognostic role of eosinophils (EOS) and basophils (BAS) in predicting multiple viral infections. This study aimed to explore the role of EOS and BAS in predicting prognosis of patients with SFTS. METHODOLOGY: A total of 194 patients with SFTS who were admitted to Yantai City Hospital from November 2019 to November 2021 were included. Patients' demographic and clinical data were collected. According to the clinical prognosis, they were divided into survival and non-survival groups. Independent risk factors were determined by univariate and multivariate logistic regression analyses. FINDINGS: There were 171 (88.14%) patients in the survived group and 23 (11.86%) patients in the non-survived group. Patients' mean age was 62.39 ± 11.85 years old, and the proportion of males was 52.1%. Older age, neurological manifestations, hemorrhage, chemosis, and increased levels of laboratory variables, such as EOS% and BAS% on admission, were found in the non-survival group compared with the survival group. EOS%, BAS%, aspartate aminotransferase (AST), direct bilirubin (DBIL), and older age on admission were noted as independent risk factors for poor prognosis of SFTS patients. The combination of the EOS% and BAS% had an area under the curve (AUC) of (0.82; 95% CI: 0.725, 0.932, P = 0.000), which showed an excellent performance in predicting prognosis of patients with SFTS compared with neutrophil-to-lymphocyte ratio (NLR), and both exhibited a satisfactory performance in predicting poor prognosis compared with De-Ritis ratio (AST/alanine aminotransferase (ALT) ratio). EOS% and BAS% were positively correlated with various biomarkers of tissue damage and the incidence of neurological complications in SFTS patients. CONCLUSION: EOS% and BAS% are effective predictors of poor prognosis of patients with early-stage SFTS. The combination of EOS% and BAS% was found as the most effective approach.

Clinical features and corresponding immune function status of recurrent viral polymerase chain reaction positivity in patients with COVID-19 : A meta- analysis and systematic review.

INTRODUCTION: Coronavirus disease 2019 (COVID-19) was declared a global pandemic in March 2020. Since then, several studies have found COVID-19 patients with recurrent viral polymerase chain reaction (PCR) positivity. METHODS: On May 6, 2021, an exhaustive literature search of the Web of Science, PubMed, Cochrane Library, Chinese National Knowledge Infrastructure databases, Embase, Wan Fang Data, VIP database, Sinomed database, BioRxiv, MedRxiv, and Research Square was conducted to find describing the laboratory indicators of recurrent and non-recurrent viral PCR positivity in patients with COVID-19. The data were statistically analyzed using STATA version 15.0. RESULTS: In total, 22 studies-comprising 5154 laboratory-confirmed COVID-19 cases-were included in the analyses. Patients with less severe COVID-19 illness (i.e. those clinically classified as mild or common-type) seemed to exhibit recurrent PCR positivity more commonly than patients with more severe illness (i.e. those classified as severe or critical). There were also significant differences between the two groups in terms of the rates of headaches and dizziness, in addition to the levels of aspartate aminotransferase, C reactive protein, interleukin-6, and lactate dehydrogenase. Further, there were variations in the ratio of CD4+ T cells/CD8+ T cells on admission to the hospital. CONCLUSION: In comparison to COVID-19 patients with non-recurrent viral PCR positivity, patients with recurrent virus PCR positivity seem to experience more severe immune function suppression upon hospital admission.

Reactivation of SARS-CoV-2 infection following recovery from COVID-19.

INTRODUCTION: Many individuals test positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA after recovering from the coronavirus disease (COVID-19), but the incidence of reactivation is unknown. We, therefore, estimated the incidence of reactivation among individuals who had recovered from COVID-19 and determined its predictors. METHODS: In this retrospective cohort study, patients with COVID-19 were followed up for at least 14 days after two consecutive negative SARS-CoV-2 polymerase chain reaction test results obtained ≥24 h apart, and the frequency of SARS-CoV-2 reactivation was assessed. RESULTS: Of the 109 patients, 29 (27%) experienced reactivation, and seven (24%) of these were symptomatic. The mean period for the real-time PCR tests for SARS-CoV-2 from negative to positive results was 17 days. Compared with patients without reactivation, those with reactivation were significantly younger and more likely to have a lymphocyte count of <1500/µL (odds ratio [OR]: 0.34, 95% confidence interval [CI]: 0.12-0.94) and two or fewer symptoms (OR: 0.20, 95% CI: 0.07-0.55) during the initial episode. CONCLUSION: Risk-stratified surveillance should be conducted among patients who have recovered from COVID-19.

Predictive Value of Triglyceride-Glucose Index for In-hospital Mortality in Patients With Severe Fever With Thrombocytopenia Syndrome: A Multi-Center Observational Study.

Background: Triglyceride-glucose (TyG) index has been proposed as a reliable indicator for insulin resistance and proved to be closely associated with the severity and mortality risk of infectious diseases. It remains indistinct whether TyG index performs an important role in predicting in-hospital mortality in patients with severe fever with thrombocytopenia syndrome (SFTS). Methods: The current study retrospectively recruited patients who were admitted for SFTS from January to December 2019 at five medical centers. TyG index was calculated in accordance with the description of previous study: Ln [fasting triglyceride (TG) (mg/dl) × fasting blood glucose (FBG) (mg/dl)/2]. The observational endpoint of the present study was defined as the in-hospital death. Results: In total, 79 patients (64.9 ± 10.5 years, 39.2% female) who met the enrollment criteria were enrolled in the current study. During the hospitalization period, 17 (21.5%) patients died in the hospital. TyG index remained a significant and independent predictor for in-hospital death despite being fully adjusted for confounders, either being taken as a nominal [hazard ratio (HR) 5.923, 95% CI 1.208-29.036, P = 0.028] or continuous (HR 7.309, 95% CI 1.854-28.818, P = 0.004) variate. TyG index exhibited a moderate-to-high strength in predicting in-hospital death, with an area under the receiver operating characteristic curve (AUC) of 0.821 (95% CI 0.712-0.929, P < 0.001). The addition of TyG index displayed significant enhancement on the predictive value for in-hospital death beyond a baseline model, manifested as increased AUC (baseline model: 0.788, 95% CI 0.676-0.901 vs. + TyG index 0.866, 95% CI 0.783-0.950, P for comparison = 0.041), increased Harrell's C-index (baseline model: 0.762, 95% CI 0.645-0.880 vs. + TyG index 0.813, 95% CI 0.724-0.903, P for comparison = 0.035), significant continuous net reclassification improvement (NRI) (0.310, 95% CI 0.092-0.714, P = 0.013), and significant integrated discrimination improvement (0.111, 95% CI 0.008-0.254, P = 0.040). Conclusion: Triglyceride-glucose index, a novel indicator simply calculated from fasting TG and FBG, is strongly and independently associated with the risk of in-hospital death in patients with SFTS.

COVID-19 Cases from the First Local Outbreak of the SARS-CoV-2 B.1.1.7 Variant in China May Present More Serious Clinical Features: A Prospective, Comparative Cohort Study.

The SARS-CoV-2 B.1.1.7 variant has increased sharply in numbers worldwide and is reported to be more contagious than the nonvariant. Little is known regarding the detailed clinical features of B.1.1.7 variant infection. Data on 74 COVID-19 cases from two outbreaks in two districts of Beijing, China were extracted from a cloud database, including 41 cases from Shunyi District (Shunyi B.1.470 group) and 33 from Daxing (Daxing B.1.1.7 group) from December 25, 2020 to January 17, 2021. We conducted a comparison of the clinical characteristics. Seven clinical indicators of the Daxing B.1.1.7 group were significantly higher than those of the Shunyi group, including the proportion with fever over 38°C, the levels of C-reactive protein (CRP), serum amyloid A (SAA), creatine kinase (CK), d-dimer (DD), and CD4+ T lymphocytes (CD4+ T), and the proportion with ground-glass opacity (GGO) in the lung (P values of ≤0.05). After adjusting for age, B.1.1.7 variant infection was a risk factor for elevated CRP (P = 0·045), SAA (P = 0·011), CK (P = 0·034), and CD4+ T (P = 0.029) and for the presence of GGO (P = 0.005). The median threshold cycle (CT) value of reverse transcriptase quantitative PCR (RT-qPCR) tests of the N gene target in the Daxing B.1.1.7 group was significantly lower (P = 0.036) than that in the Shunyi B.1.470 group. Clinical features, including a more serious inflammatory response, pneumonia, and a possibly higher viral load, were detected in the cases infected with B.1.1.7 SARS-CoV-2. The B.1.1.7 variant may have increased pathogenicity. IMPORTANCE The SARS-CoV-2 B.1.1.7 variant, which was first identified in the United Kingdom, has increased sharply in numbers worldwide and was reported to be more contagious than the nonvariant. To our knowledge, no studies investigating the detailed clinical features of COVID-19 cases infected with the B.1.1.7 variant have been published. Local epidemics have rarely occurred in China, but occasionally, a small clustered outbreak triggered by an imported SARS-CoV-2 strain with only one chain of transmission could happen. From late 2020 to early 2021, two clustered COVID-19 outbreaks occurred in Beijing, one of which was caused by the B.1.1.7 variant. The COVID-19 patients from the two outbreaks received similar clinical tests, diagnoses, and treatments. We found that the B.1.1.7 variant infection could lead to a more serious inflammatory response, acute response process, more severe pneumonia, and probably higher viral loads. This therefore implies that the B.1.1.7 variant may have increased pathogenicity.

A nomogram to predict mortality in patients with severe fever with thrombocytopenia syndrome at the early stage-A multicenter study in China.

BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS) caused by the SFTS virus is an emerging infectious disease that was first identified in the rural areas of China in 2011. Severe cases often result in death due to multiple organ failure. To date, there are still numerous problems remain unresolved in SFTS, including unclear pathogenesis, lack of specific treatment, and no effective vaccines available. AIM: To analyze the clinical information of patients with early-stage SFTS and to establish a nomogram for the mortality risk. METHODS: Between April 2011 and December 2018, data on consecutive patients who were diagnosed with SFTS were prospectively collected from five medical centers distributed in central and northeastern China. Multivariable Cox analyses were used to identify the factors independently associated with mortality. A nomogram for mortality was established using those factors. RESULTS: During the study period, 429 consecutive patients were diagnosed with SFTS at the early stage of the disease (within 7 days of fever), among whom 69 (16.1%) died within 28 days. The multivariable Cox proportional hazard regression analysis showed that low lymphocyte percentage, early-stage encephalopathy, and elevated concentration of serum LDH and BUN were independent risk factors for fatal outcomes. Received-operating characteristic curves for 7-, 14-, and 28-days survival had AUCs of 0.944 (95% CI: 0.920-0.968), 0.924 (95% CI: 0.896-0.953), and 0.924 (95% CI: 0.895-0.952), respectively. Among low-risk patients, 6 patients died (2.2%). Among moderate-risk patients, 25 patients died (24.0%, hazard ratio (HR) = 11.957). Among high-risk patients, the mortality rate was 69.1% (HR = 57.768). CONCLUSION: We established a simple and practical clinical scoring system, through which we can identify critically ill patients and provide intensive medical intervention for patients as soon as possible to reduce mortality.