The Associations of Two Novel Inflammation Biomarkers, SIRI and SII, with Mortality Risk in Patients with Chronic Heart Failure.

Background: The associations of two novel inflammation biomarkers, systemic inflammation response index (SIRI) and systemic immune inflammation index (SII), with mortality risk in patients with chronic heart failure (CHF) are not well-characterized. Methods: This retrospective cohort study included patients with CHF in two medical centers of Chinese People's Liberation Army General Hospital, Beijing, China. The outcomes of this study included in-hospital mortality and long-term mortality. Associations of SIRI and SII with mortality were assessed using multivariable regressions and receiver operating characteristic (ROC) analyses. Results: A total of 6232 patients with CHF were included in the present study. We documented 97 cases of in-hospital mortality and 1738 cases of long-term mortality during an average 5.01-year follow-up. Compared with patients in the lowest quartile of SIRI, those in the highest quartile exhibited 134% higher risk of in-hospital mortality (adjusted odds ratio, 2.34; 95% confidence interval [CI], 1.16-4.72) and 45% higher risk of long-term mortality (adjusted hazard ratio, 1.45; 95% CI, 1.25-1.67). Compared with patients in the lowest quartile of SII, those in the highest quartile exhibited 27% higher risk of long-term mortality (adjusted hazard ratio, 1.27; 95% CI, 1.11-1.46). In ROC analyses, SIRI showed better prognostic discrimination than C-reactive protein (area under the curve: 69.39 vs 60.91, P = 0.01, for in-hospital mortality; 61.82 vs 58.67, P = 0.03, for 3-year mortality), whereas SII showed similar prognostic value with C-reactive protein. Conclusion: SIRI and SII were significantly associated with mortality risk in patients with CHF. SIRI may provide better prognostic discrimination than C-reactive protein.

Impact of body mass index on long-term outcomes in patients undergoing percutaneous coronary intervention stratified by diabetes mellitus: a retrospective cohort study.

BACKGROUND: Patients with diabetes mellitus (DM) caused by obesity have increased in recent years. The impact of obesity on long-term outcomes in patients undergoing percutaneous coronary intervention (PCI) with or without DM remains unclear. METHODS: We retrospectively analysed data from 1918 patients who underwent PCI. Patients were categorized into four groups based on body mass index (BMI, normal weight: BMI < 25 kg/m2; overweight and obese: BMI ≥ 25 kg/m2) and DM status (presence or absence). The primary endpoint was the occurrence of major adverse cardiac and cerebrovascular events (MACCE; defined as all-cause death, myocardial infarction, stroke, and unplanned repeat revascularization). RESULTS: During a median follow-up of 7.0 years, no significant differences in MACCE, myocardial infarction, or stroke were observed among the four groups. Overweight and obese individuals exhibited lower all-cause mortality rates compared with normal-weight patients (without DM: hazard ratio [HR]: 0.54, 95% confidence interval [CI]: 0.37 to 0.78; with DM: HR: 0.57, 95% CI: 0.38 to 0.86). In non-diabetic patients, the overweight and obese group demonstrated a higher risk of unplanned repeat revascularization than the normal-weight group (HR:1.23, 95% CI:1.03 to 1.46). After multivariable adjustment, overweight and obesity were not significantly associated with MACCE, all-cause death, myocardial infarction, stroke, or unplanned repeat revascularization in patients with and without diabetes undergoing PCI. CONCLUSION: Overweight and obesity did not demonstrate a significant protective effect on long-term outcomes in patients with and without diabetes undergoing PCI.

First Report of Leaf Spot on Taraxacum mongolicum Caused by Alternaria solani in China.

Taraxacum mongolicum is a perennial herbaceous plant in the family Asteraceae, with a high edible and medicinal value and is widely planted in China. In August 2022, leaf spots were found on T. mongolicum in Tianjiazhai Town, Xining City, Qinghai Province, China (36°27'17.65″N, 101°47'19.65E, elevation: 2,408 m). The plants exhibited round or irregular brown spots, and the centers of some of the spots were gray (Fig. S1A). An investigation was performed over a hectare area, and the incidence of leaf spot reached 15%-30%, seriously affecting the quality and yield of T. mongolicum. Eleven T. mongolicum leaf spot samples were collected. To isolate the pathogenic fungus, approximately 0.5 cm×0.5 cm pieces of tissues were obtained using sterile scissors from the junction of infected and healthy tissues. The symptomatic leaves were surface-disinfected with 3% NaClO for 1.5 min and washed three times with sterile water. The disinfected pieces were dried and placed on water agar plates in an incubator for 2 days at 25°C. Subsequently, the leaf surface exhibited conidiophores and conidia. Eleven isolates were obtained by single spore isolation. The sparse aerial mycelia were dark grey to black brown in color on potato dextrose agar (PDA) (Fig. S2A), and produced dark, multi-septate conidia with 7-11 transverse septa and 1-2 longitudinal septa (Fig. S2C). Conidia with one or two beaks were long-ovoid, with an average length and width of 103.4 × 21.2 µm, and 80.7 × 3.9 µm of the beaks. One hundred and ten conidia were measured. The identification of 11 isolates was confirmed by multilocus sequence analyses of the internal transcribed spacer of ribosomal DNA (rDNA ITS) (White et al. 1990), and the glyceraldehyde-3-phosphate dehydrogenase (GAPDH) (Xu et al. 2022), actin (ACT) (Yang et al. 2020), histone 3 (HIS3) (Zheng et al. 2015), translation elongation factor 1-α (TEF1-α) (Carbone. 1999), and the second largest subunit of RNA polymerase II (RPB2) (Liu et al. 1999) genes. The sequences of all the isolates were deposited in Genbank (NCBI Accession Nos. ITS: OR105029-OR105039, ACT: OR135220-OR135230, GAPDH: OR135231-OR135241, HIS3: OR122992-OR123002, TEF1-α: PP055972-PP055982, and RPB2: PP055983-PP055993), and the sequence similarity of ITS, ACT, GAPDH, HIS3，TEF1-α and RPB2 were 100%, 98%, 100%, 99%, 100%, and 99% to the sequences of Alternaria solani, respectively. Combined sequences of ITS, GAPDH, TEF1-α, and RPB2 genes were concatenated and a maximum parsimony tree was constructed with PAUP* v. 4.0 alpha. The results indicated that 11 isolates were clustered together with A. solani (Fig. S2D). Therefore, 11 isolates were identified as A. solani based on their morphological and molecular characteristics. Eleven isolates were inoculated on their host to perform Koch's postulates. The isolates were grown on PDA for six days. Healthy one month old T. mongolicum seedlings were planted in 10 cm flowerpots (Fig. S1B) or the seedlings were moved to Petri dish (Fig. S1C), and their leaves were inoculated with 5 mL of hyphae suspension by smearing method. In addition, seedlings of the same age were treated with sterile water to serve as the control. The inoculated seedlings were moved into an artificial climatic box at 25℃, relative humidity was 70%, with 12 h light/12 h dark condition. Totally 80 seedlings were inoculated with isolates and 15 were used as the control. After 7 days, similar symptoms were observed on the plants inoculated with isolates, while control plants did not produce symptoms. The assays were conducted three times. Furthermore, isolates were re-isolated from the symptomatic leaves, and the colonial morphology was the same as the original isolates (Fig S2 A and B). The recovered isolates were identified as A. solani by amplifying and sequencing a portion of the HIS3 gene. Alternaria solani has been previously reported to cause early blight of potato and other Solanum crops (van der Waals et al. 2004; Zheng et al. 2015). To our knowledge, this is the first report of A. solani causing leaf spot of T. mongolicum in China. This disease must be considered in management practices, and our finding provided a basis for disease prevention and management.

Association between the triglyceride-glucose index and the risk of mortality among patients with chronic heart failure: results from a retrospective cohort study in China.

BACKGROUND: The triglyceride-glucose (TyG) index has been demonstrated to be a reliable surrogate marker of insulin resistance (IR) and an effective predictive index of cardiovascular (CV) disease risk. However, its long-term prognostic value in patients with chronic heart failure (CHF) remains uncertain. METHODS: A total of 6697 consecutive patients with CHF were enrolled in this study. Patients were divided into tertiles according to their TyG index. The incidence of primary outcomes, including all-cause death and CV death, was recorded. The TyG index was calculated as ln [fasting triglycerides (mg/dL) × fasting blood glucose (mg/dL)/2]. RESULTS: During a median follow-up of 3.9 years, a total of 2158 (32.2%) all-cause deaths and 1305 (19.5%) CV deaths were documented. The incidence of primary events from the lowest to the highest TyG index tertiles were 50.61, 64.64, and 92.25 per 1000 person-years for all-cause death and 29.05, 39.40, and 57.21 per 1000 person-years for CV death. The multivariate Cox hazards regression analysis revealed hazard ratios for all-cause and CV deaths of 1.84 (95% CI 1.61-2.10; P for trend < 0.001) and 1.94 (95% CI 1.63-2.30; P for trend < 0.001) when the highest and lowest TyG index tertiles were compared. In addition, the predictive ability of the TyG index against all-cause death was more prominent among patients with metabolic syndrome and those with heart failure with preserved ejection fraction phenotype (both P for interaction < 0.05). Furthermore, adding the TyG index to the established model for all-cause death improved the C­statistic value (0.710 for the established model vs. 0.723 for the established model + TyG index, P < 0.01), the integrated discrimination improvement value (0.011, P < 0.01), the net reclassification improvement value (0.273, P < 0.01), and the clinical net benefit (probability range, 0.07-0.36). CONCLUSIONS: The TyG index was significantly associated with the risk of mortality, suggesting that it may be a reliable and valuable predictor for risk stratification and an effective prognostic indicator in patients with CHF.

Joint association of hyperuricemia and chronic kidney disease with mortality in patients with chronic heart failure.

Background: The joint association of hyperuricemia and chronic kidney disease (CKD) with mortality in patients with chronic heart failure (CHF) is not conclusive. Methods: This retrospective cohort study was conducted in Chinese People's Liberation Army General Hospital, Beijing, China. We included 9,367 patients with CHF, who were hospitalized between January 2011 and June 2019. The definitions of hyperuricemia and CKD were based on laboratory test, medication use, and medical record. We categorized patients with CHF into 4 groups according to the absence (-) or presence (+) of hyperuricemia and CKD. The primary outcomes included in-hospital mortality and long-term mortality. We used multivariate logistic regression and Cox proportional hazards regression to estimate the mortality risk according to the hyperuricemia/CKD groups. Results: We identified 275 cases of in-hospital mortality and 2,883 cases of long-term mortality in a mean follow-up of 4.81 years. After adjusting for potential confounders, we found that compared with the hyperuricemia-/CKD- group, the risks of in-hospital mortality were higher in the hyperuricemia+/CKD- group (odds ratio [OR], 95% confidence interval [CI]: 1.58 [1.01-2.46]), hyperuricemia-/CKD+ group (OR, 95% CI: 1.67 [1.10-2.55]), and hyperuricemia+/CKD+ group (OR, 95% CI: 2.12 [1.46-3.08]). Similar results were also found in long-term mortality analysis. Compared with the hyperuricemia-/CKD- group, the adjusted hazard ratios and 95% CI for long-term mortality were 1.25 (1.11-1.41) for hyperuricemia+/CKD- group, 1.37 (1.22-1.53) for hyperuricemia-/CKD+ group, and 1.59 (1.43-1.76) for hyperuricemia+/CKD+ group. The results remained robust in the sensitivity analysis. Conclusions: Hyperuricemia and CKD, both individually and cumulatively, are associated with increased mortality risk in patients with CHF. These results highlighted the importance of the combined control of hyperuricemia and CKD in the management of heart failure.

Efficacy of disease management program used among patients with chronic heart failure: protocol for a systematic review and network meta-analysis.

BACKGROUND: A large number of studies have provided a variety of heart failure management program (HF-MP) intervention modes. It is generally believed that HF-MP is effective, but the question of which type of program works best, what level of support is needed for an intervention to be effective, and whether different subgroups of patients are best served by different types of programs is still confusing. METHODS: This study will search for published and unpublished randomized clinical trials in English examining HF-MP interventions in comparison with usual care. MEDLINE, Medlin In-Process and Non-Indexed, CENTRAL, CINAHL, EMBASE, and PsycINFO will be the databases. We will calibrate our eligibility criteria among the team. Each literature will be screened by at least two reviewers. Conflicts will be resolved through team discussion. A similar process will be used for data abstraction and quality appraisal. The results will be synthesized descriptively, and a network meta-analysis will be conducted if the studies are deemed methodologically, clinically, and statistically acceptable (e.g., I2 < 50%). Moreover, potential moderators of efficacy will be analyzed using a meta-regression. DISCUSSION: This study will reduce the clinical heterogeneity and statistical heterogeneity of review and meta-analysis through a more scientific classification method to determine the most effective HF-MP in different subgroups of heart failure patients with different human resource investments and different intervention methods, providing high-quality evidence and guidance for clinical practice. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42021258521.

Elevated Fasting Blood Glucose Levels Are Associated with Worse Clinical Outcomes in COVID-19 Patients Than in Pneumonia Patients with Bacterial Infections.

Aims: We investigate how fasting blood glucose (FBG) levels affect the clinical severity in coronavirus disease 2019 (COVID-19) patients, pneumonia patients with sole bacterial infection, and pneumonia patients with concurrent bacterial and fungal infections. Methods: We enrolled 2761 COVID-19 patients, 1686 pneumonia patients with bacterial infections, and 2035 pneumonia patients with concurrent infections. We used multivariate logistic regression analysis to assess the associations between FBG levels and clinical severity. Results: FBG levels in COVID-19 patients were significantly higher than in other pneumonia patients during hospitalisation and at discharge (all p < 0.05). Among COVID-19 patients, the odds ratios of acute respiratory distress syndrome (ARDS), respiratory failure (RF), acute hepatitis/liver failure (AH/LF), length of stay, and intensive care unit (ICU) admission were 12.80 (95% CI, 4.80−37.96), 5.72 (2.95−11.06), 2.60 (1.20−5.32), 1.42 (1.26−1.59), and 5.16 (3.26−8.17) times higher in the FBG ≥7.0 mmol/L group than in FBG < 6.1 mmol/L group, respectively. The odds ratios of RF, AH/LF, length of stay, and ICU admission were increased to a lesser extent in pneumonia patients with sole bacterial infection (3.70 [2.21−6.29]; 1.56 [1.17−2.07]; 0.98 [0.88−1.11]; 2.06 [1.26−3.36], respectively). The odds ratios of ARDS, RF, AH/LF, length of stay, and ICU admission were increased to a lesser extent in pneumonia patients with concurrent infections (3.04 [0.36−6.41]; 2.31 [1.76−3.05]; 1.21 [0.97−1.52]; 1.02 [0.93−1.13]; 1.72 [1.19−2.50], respectively). Among COVID-19 patients, the incidence rate of ICU admission on day 21 in the FBG ≥ 7.0 mmol/L group was six times higher than in the FBG < 6.1 mmol/L group (12.30% vs. 2.21%, p < 0.001). Among other pneumonia patients, the incidence rate of ICU admission on day 21 was only two times higher. Conclusions: Elevated FBG levels at admission predict subsequent clinical severity in all pneumonia patients regardless of the underlying pathogens, but COVID-19 patients are more sensitive to FBG levels, and suffer more severe clinical complications than other pneumonia patients.

Clinical characteristics of patients with confirmed and asymptomatic SARS-CoV-2 infection in China.

OBJECTIVE: To examine the clinical characteristics of patients with asymptomatic novel coronavirus disease 2019 (COVID-19) and compare them with those of patients with mild disease. DESIGN: A retrospective cohort study. SETTING: Multiple medical centers in Wuhan, Hubei, China. PARTICIPANTS: A total of 3,263 patients with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) infection between February 4, 2020, and April 15, 2020. MAIN OUTCOME MEASURES: Patient demographic characteristics, medical history, vital signs, and laboratory and chest computed tomography (CT) findings. RESULTS: A total of 3,173 and 90 patients with mild and moderate, and asymptomatic COVID-19, respectively, were included. A total of 575 (18.2%) symptomatic patients and 4 (4.4%) asymptomatic patients developed the severe illness. All asymptomatic patients recovered; no deaths were observed in this group. The median duration of viral shedding in asymptomatic patients was 17 (interquartile range, 9.25-25) days. Patients with higher levels of ultrasensitive C-reactive protein (odds ratio [OR] = 1.025, 95% confidence interval [CI], 1.01-1.04), lower red blood cell volume distribution width (OR = 0.68, 95% CI 0.51-0.88), lower creatine kinase Isoenzyme(0.94, 0.89-0.98) levels, or lower lesion ratio (OR = 0.01, 95% CI 0.00-0.33) at admission were more likely than their counterparts to have asymptomatic disease. CONCLUSIONS: Patients with younger ages and fewer comorbidities are more likely to be asymptomatic. Asymptomatic patients had similar laboratory characteristics and longer virus shedding time than symptomatic patients; screen and isolation during their infection were helpful to reduce the risk of SARS-CoV-2 transmission.

Cardiac Adaptation to Prolonged High Altitude Migration Assessed by Speckle Tracking Echocardiography.

Objective: Exposure to high altitudes represents physiological stress that leads to significant changes in cardiovascular properties. However, long-term cardiovascular adaptions to high altitude migration of lowlanders have not been described. Accordingly, we measured changes in cardiovascular properties following prolonged hypoxic exposure in acclimatized Han migrants and Tibetans. Methods: Echocardiographic features of recently adapted Han migrant (3-12 months, n = 64) and highly adapted Han migrant (5-10 years, n = 71) residence in Tibet (4,300 m) using speckle tracking echocardiography were compared to those of age-matched native Tibetans (n = 75) and Han lowlanders living at 1,400 m (n = 60). Results: Short-term acclimatized migrants showed increased estimated pulmonary artery systolic pressure (PASP) (32.6 ± 5.1 mmHg vs. 21.1 ± 4.2 mmHg, p < 0.05), enlarged right ventricles (RVs), and decreased fractional area change (FAC) with decreased RV longitudinal strain (-20 ± 2.8% vs. -25.5 ± 3.9%, p < 0.05). While left ventricular ejection fraction (LVEF) was preserved, LV diameter (41.7 ± 3.1 mm vs. 49.7 ± 4.8 mm, p < 0.05) and LV longitudinal strain (-18.8 ± 3.2% vs. -22.9 ± 3.3%, p < 0.05) decreased. Compared with recent migrants, longer-term migrants had recovered RV structure and functions with slightly improved RV and LV longitudinal strain, though still lower than lowlander controls; LV size remained small with increased mass index (68.3 ± 12.7 vs. 59.3 ± 9.6, p < 0.05). In contrast, native Tibetans had slightly increased PASP (26.1 ± 3.4 mmHg vs. 21.1 ± 4.2 mmHg, p < 0.05) with minimally altered cardiac deformation compared to lowlanders. Conclusion: Right ventricular systolic function is impaired in recent (<1 year) migrants to high altitudes but improved during the long-term dwelling. LV remodeling persists in long-term migrants (>5 years) but without impairment of LV systolic or diastolic function. In contrast, cardiac size, structure, and function of native Tibetans are more similar to those of lowland dwelling Hans.

Integrated medical resource consumption stratification in hospitalized patients: an Auto Triage Management model based on accurate risk, cost and length of stay prediction.

Triage management plays important roles in hospitalized patients for disease severity stratification and medical burden analysis. Although progression risks have been extensively researched for numbers of diseases, other crucial indicators that reflect patients' economic and time costs have not been systematically studied. To address the problems, we developed an automatic deep learning based Auto Triage Management (ATM) Framework capable of accurately modelling patients' disease progression risk and health economic evaluation. Based on them, we can first discover the relationship between disease progression and medical system cost, find potential features that can more precisely aid patient triage in resource allocation, and allow treatment plan searching that has cured patients. Applying ATM in COVID-19, we built a joint model to predict patients' risk, the total length of stay (LoS) and cost when at-admission, and remaining LoS and cost at a given hospitalized time point, with C-index 0.930 and 0.869 for risk prediction, mean absolute error (MAE) of 5.61 and 5.90 days for total LoS prediction in internal and external validation data.

DeepKG: an end-to-end deep learning-based workflow for biomedical knowledge graph extraction, optimization and applications.

SUMMARY: DeepKG is an end-to-end deep learning-based workflow that helps researchers automatically mine valuable knowledge in biomedical literature. Users can utilize it to establish customized knowledge graphs in specified domains, thus facilitating in-depth understanding on disease mechanisms and applications on drug repurposing and clinical research. To improve the performance of DeepKG, a cascaded hybrid information extraction framework is developed for training model of 3-tuple extraction, and a novel AutoML-based knowledge representation algorithm (AutoTransX) is proposed for knowledge representation and inference. The system has been deployed in dozens of hospitals and extensive experiments strongly evidence the effectiveness. In the context of 144 900 COVID-19 scholarly full-text literature, DeepKG generates a high-quality knowledge graph with 7980 entities and 43 760 3-tuples, a candidate drug list, and relevant animal experimental studies are being carried out. To accelerate more studies, we make DeepKG publicly available and provide an online tool including the data of 3-tuples, potential drug list, question answering system, visualization platform. AVAILABILITY AND IMPLEMENTATION: All the results are publicly available at the website (http://covidkg.ai/). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Automated Analysis of Doppler Echocardiographic Videos as a Screening Tool for Valvular Heart Diseases.

OBJECTIVES: This study sought to develop a deep learning (DL) framework to automatically analyze echocardiographic videos for the presence of valvular heart diseases (VHDs). BACKGROUND: Although advances in DL have been applied to the interpretation of echocardiograms, such techniques have not been reported for interpretation of color Doppler videos for diagnosing VHDs. METHODS: The authors developed a 3-stage DL framework for automatic screening of echocardiographic videos for mitral stenosis (MS), mitral regurgitation (MR), aortic stenosis (AS), and aortic regurgitation (AR) that classifies echocardiographic views, detects the presence of VHDs, and, when present, quantifies key metrics related to VHD severities. The algorithm was trained (n = 1,335), validated (n = 311), and tested (n = 434) using retrospectively selected studies from 5 hospitals. A prospectively collected set of 1,374 consecutive echocardiograms served as a real-world test data set. RESULTS: Disease classification accuracy was high, with areas under the curve of 0.99 (95% CI: 0.97-0.99) for MS; 0.88 (95% CI: 0.86-0.90) for MR; 0.97 (95% CI: 0.95-0.99) for AS; and 0.90 (95% CI: 0.88-0.92) for AR in the prospective test data set. The limits of agreement (LOA) between the DL algorithm and physician estimates of metrics of valve lesion severities compared to the LOAs between 2 experienced physicians spanned from -0.60 to 0.77 cm2 vs -0.48 to 0.44 cm2 for MV area; from -0.27 to 0.25 vs -0.23 to 0.08 for MR jet area/left atrial area; from -0.86 to 0.52 m/s vs -0.48 to 0.54 m/s for peak aortic valve blood flow velocity (Vmax); from -10.6 to 9.5 mm Hg vs -10.2 to 4.9 mm Hg for average peak aortic valve gradient; and from -0.39 to 0.32 vs -0.31 to 0.32 for AR jet width/left ventricular outflow tract diameter. CONCLUSIONS: The proposed deep learning algorithm has the potential to automate and increase efficiency of the clinical workflow for screening echocardiographic images for the presence of VHDs and for quantifying metrics of disease severity.

High Fasting Blood Glucose Level With Unknown Prior History of Diabetes Is Associated With High Risk of Severe Adverse COVID-19 Outcome.

Background: We aimed to understand how glycaemic levels among COVID-19 patients impact their disease progression and clinical complications. Methods: We enrolled 2,366 COVID-19 patients from Huoshenshan hospital in Wuhan. We stratified the COVID-19 patients into four subgroups by current fasting blood glucose (FBG) levels and their awareness of prior diabetic status, including patients with FBG<6.1mmol/L with no history of diabetes (group 1), patients with FBG<6.1mmol/L with a history of diabetes diagnosed (group 2), patients with FBG≥6.1mmol/L with no history of diabetes (group 3) and patients with FBG≥6.1mmol/L with a history of diabetes diagnosed (group 4). A multivariate cause-specific Cox proportional hazard model was used to assess the associations between FBG levels or prior diabetic status and clinical adversities in COVID-19 patients. Results: COVID-19 patients with higher FBG and unknown diabetes in the past (group 3) are more likely to progress to the severe or critical stage than patients in other groups (severe: 38.46% vs 23.46%-30.70%; critical 7.69% vs 0.61%-3.96%). These patients also have the highest abnormal level of inflammatory parameters, complications, and clinical adversities among all four groups (all p<0.05). On day 21 of hospitalisation, group 3 had a significantly higher risk of ICU admission [14.1% (9.6%-18.6%)] than group 4 [7.0% (3.7%-10.3%)], group 2 [4.0% (0.2%-7.8%)] and group 1 [2.1% (1.4%-2.8%)], (P<0.001). Compared with group 1 who had low FBG, group 3 demonstrated 5 times higher risk of ICU admission events during hospitalisation (HR=5.38, 3.46-8.35, P<0.001), while group 4, where the patients had high FBG and prior diabetes diagnosed, also showed a significantly higher risk (HR=1.99, 1.12-3.52, P=0.019), but to a much lesser extent than in group 3. Conclusion: Our study shows that COVID-19 patients with current high FBG levels but unaware of pre-existing diabetes, or possibly new onset diabetes as a result of COVID-19 infection, have a higher risk of more severe adverse outcomes than those aware of prior diagnosis of diabetes and those with low current FBG levels.

Elevated glucose level leads to rapid COVID-19 progression and high fatality.

OBJECTIVES: We aimed to identify high-risk factors for disease progression and fatality for coronavirus disease 2019 (COVID-19) patients. METHODS: We enrolled 2433 COVID-19 patients and used LASSO regression and multivariable cause-specific Cox proportional hazard models to identify the risk factors for disease progression and fatality. RESULTS: The median time for progression from mild-to-moderate, moderate-to-severe, severe-to-critical, and critical-to-death were 3.0 (interquartile range: 1.8-5.5), 3.0 (1.0-7.0), 3.0 (1.0-8.0), and 6.5 (4.0-16.3) days, respectively. Among 1,758 mild or moderate patients at admission, 474 (27.0%) progressed to a severe or critical stage. Age above 60 years, elevated levels of blood glucose, respiratory rate, fever, chest tightness, c-reaction protein, lactate dehydrogenase, direct bilirubin, and low albumin and lymphocyte count were significant risk factors for progression. Of 675 severe or critical patients at admission, 41 (6.1%) died. Age above 74 years, elevated levels of blood glucose, fibrinogen and creatine kinase-MB, and low plateleta count were significant risk factors for fatality. Patients with elevated blood glucose level were 58% more likely to progress and 3.22 times more likely to die of COVID-19. CONCLUSIONS: Older age, elevated glucose level, and clinical indicators related to systemic inflammatory responses and multiple organ failures, predict both the disease progression and the fatality of COVID-19 patients.

Complete chloroplast genome of a high-quality forage in north China, Medicago ruthenica (Fabaceae：Trifolieae).

Medicago ruthenica is a well-known high-quality forage due to its good palatability and strong tolerance to drought, cold and saline-alkali stress. Here, the complete chloroplast genome sequence of M. ruthenica was reported. The chloroplast genome is 126,939 bp in length. This chloroplast genome has no inverted repeat (IR) regions, which is very common in the family Fabaceae. The M. ruthenica chloroplast genome encodes 107 genes, including 73 protein-coding genes, 30 tRNA genes, and 4 rRNA genes. Phylogenetic analysis result strongly suggested that M. ruthenica is a distinct lineage in Medicago, being sister to highly supported clade composed of three species (M. hybrida, M. papillosa and M. sativa).

Assisting scalable diagnosis automatically via CT images in the combat against COVID-19.

The pandemic of Coronavirus Disease 2019 (COVID-19) is causing enormous loss of life globally. Prompt case identification is critical. The reference method is the real-time reverse transcription PCR (RT-PCR) assay, whose limitations may curb its prompt large-scale application. COVID-19 manifests with chest computed tomography (CT) abnormalities, some even before the onset of symptoms. We tested the hypothesis that the application of deep learning (DL) to 3D CT images could help identify COVID-19 infections. Using data from 920 COVID-19 and 1,073 non-COVID-19 pneumonia patients, we developed a modified DenseNet-264 model, COVIDNet, to classify CT images to either class. When tested on an independent set of 233 COVID-19 and 289 non-COVID-19 pneumonia patients, COVIDNet achieved an accuracy rate of 94.3% and an area under the curve of 0.98. As of March 23, 2020, the COVIDNet system had been used 11,966 times with a sensitivity of 91.12% and a specificity of 88.50% in six hospitals with PCR confirmation. Application of DL to CT images may improve both efficiency and capacity of case detection and long-term surveillance.

The Preference, Effect, and Prognosis of Intra-Aortic Balloon Counterpulsation in Acute Myocardial Infarction Complicated by Cardiogenic Shock Patients: A Retrospective Cohort Study.

BACKGROUNDS: Intra-aortic balloon counterpulsation is increasingly used in acute myocardial infarction complicated by cardiogenic shock. The aim of this study was to explore the preference, effect, and prognosis of intra-aortic balloon counterpulsation in acute myocardial infarction complicated by cardiogenic shock patients. METHODS: Data of acute myocardial infarction complicated by cardiogenic shock patients at the Fourth Medical Center of PLA General Hospital were collected retrospectively. A propensity score was calculated with a logistic regression which contained clinically meaningful variables and variables selected by Lasso and then used to match the control group. The cumulative incidence curve and Gray's test were employed to analyse the effect and prognosis of intra-aortic balloon counterpulsation on mortality. RESULTS: A total of 1962 acute myocardial infarction cases admitted between May 2015 and November 2018 were identified, and 223 cases with acute myocardial infarction complicated by cardiogenic shock were included as the study cohort, which contained 34 cases that received IABP and 189 cases that did not receive IABP. Patients with higher alanine aminotransferase (OR = 1.93, 95% CI 1.29-2.98), higher triglyceride (OR = 3.71, 95% CI 1.87-7.95), and higher blood glucose (OR = 1.08, 95% CI 0.99-1.18) had a higher probability of receiving intra-aortic balloon counterpulsation. In the propensity score matching analysis, 34 cases received intra-aortic balloon counterpulsation and 102 matched controls were included in the comparison. By comparing the cumulative incidence of in-hospital mortality, there was no statistically significant difference between the intra-aortic balloon counterpulsation group and matched control group (P = 0.454). CONCLUSION: The use of intra-aortic balloon counterpulsation may not improve the prognosis of the acute myocardial infarction complicated by cardiogenic shock patients.

Characteristics of complete chloroplast genome of a high-quality forage on Qinghai-Tibet Plateau, Medicago archiducis-nicolai Sirj. (Fabaceae：Trifolieae).

Medicago archiducis-nicolai Sirj. is a well-known high-quality forage as its good palatability and strong tolerance to drought, cold and saline-alkali stress. Here, the complete chloroplast genome sequence of M. archiducis-nicolai was reported. The size of the complete chloroplast genome is 127,072 bp in length. The chloroplast genome has no inverted repeat (IR) regions, which is very common in the family Fabaceae. The M. archiducis-nicolai chloroplast genome encodes 106 genes: 72 protein-coding genes, 30 tRNAs, and 4 rRNAs. The phylogenetic analysis result strongly suggested that M. archiducis-nicolai is a distinct lineage in Medicago, being sister to highly supported clade composed of three species (M. hybrida, M. papillosa and M. sativa).

Modulation of Thermally Activated Delayed Fluorescence in Waterborne Polyurethanes via Charge-Transfer Effect.

Here, we designed several waterborne polyurethanes (WPUs) with efficient thermally activated delayed fluorescence (TADF) via serving charge-transfer (CT) states as a mediate bridge between singlet and triplet states to boost reverse intersystem crossing (RISC). By tuning substituents of diphenyl sulfone (DS), we found that O,O'- and S,S'-substituted DS covalently incorporated in WPUs solely show typical fluorescence emission with lifetimes in the nanosecond range. Interestingly, TADF appears by replacing the substituent with the nitrogen atom, of which lifetimes are up to ≈10 microseconds and ≈1 millisecond in air and vacuum, respectively, even though the energy gap between singlet and triplet states (ΔEST ) is still large for generating TADF. To explain this phenomenon, an energy level mode based on CT states and an 3 (n-π*) receiver state was proposed. By the rational modulation of CT states, it is possible to tune the ΔEST to render TADF-based materials suitable for versatile applications.