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1.
ISPRS International Journal of Geo-Information ; 11(4):215, 2022.
Article in English | ProQuest Central | ID: covidwho-1809933

ABSTRACT

Population spatialization data is crucial to conducting scientific studies of coupled human–environment systems. Although significant progress has been made in population spatialization, the spatialization of different age populations is still weak. POI data with rich information have great potential to simulate the spatial distribution of different age populations, but the relationship between spatial distributions of POI and different age populations is still unclear, and whether it can be used as an auxiliary variable for the different age population spatialization remains to be explored. Therefore, this study collected and sorted out the number of different age populations and POIs in 2846 county-level administrative units of the Chinese mainland in 2010, divided the research data by region and city size, and explored the relationship between the different age populations and POIs. We found that there is a complex relationship between POI and different age populations. Firstly, there are positive, moderate-to-strong linear correlations between POI and population indicators. Secondly, POI has a different explanatory power for different age populations, and it has a higher explanatory power for the young and middle-aged population than the child and old population. Thirdly, the explanatory power of POI to different age populations is positively correlated with the urban economic development level. Finally, a small number of a certain kinds of POIs can be used to effectively simulate the spatial distributions of different age populations, which can improve the efficiency of obtaining spatialization data of different age populations and greatly save on costs. The study can provide data support for the precise spatialization of different age populations and inspire the spatialization of the other population attributes by POI in the future.

2.
Signal Transduct Target Ther ; 6(1): 427, 2021 12 16.
Article in English | MEDLINE | ID: covidwho-1795805

ABSTRACT

Abnormal glucose and lipid metabolism in COVID-19 patients were recently reported with unclear mechanism. In this study, we retrospectively investigated a cohort of COVID-19 patients without pre-existing metabolic-related diseases, and found new-onset insulin resistance, hyperglycemia, and decreased HDL-C in these patients. Mechanistically, SARS-CoV-2 infection increased the expression of RE1-silencing transcription factor (REST), which modulated the expression of secreted metabolic factors including myeloperoxidase, apelin, and myostatin at the transcriptional level, resulting in the perturbation of glucose and lipid metabolism. Furthermore, several lipids, including (±)5-HETE, (±)12-HETE, propionic acid, and isobutyric acid were identified as the potential biomarkers of COVID-19-induced metabolic dysregulation, especially in insulin resistance. Taken together, our study revealed insulin resistance as the direct cause of hyperglycemia upon COVID-19, and further illustrated the underlying mechanisms, providing potential therapeutic targets for COVID-19-induced metabolic complications.


Subject(s)
COVID-19/blood , Hyperglycemia/blood , Insulin Resistance , Lipid Metabolism , Lipids/blood , SARS-CoV-2/metabolism , Adult , Aged , Biomarkers/blood , COVID-19/complications , Female , Humans , Hyperglycemia/etiology , Male , Middle Aged , Retrospective Studies
3.
Atmospheric environment (Oxford, England : 1994) ; 2022.
Article in English | EuropePMC | ID: covidwho-1756150

ABSTRACT

Air pollution during the COVID-19 epidemic in Beijing and its surrounding regions has received substantial attention. We collected observational data, including air pollutant concentrations and meteorological parameters, during January and February from 2018 to 2021. A statistical and a numerical model were applied to identify the formation of air pollution and the impact of emission reduction on air quality. Relative humidity, wind speed, SO2, NO2, and O3 had nonlinear effects on the PM2.5 concentration in Beijing, among which the effects of relative humidity, NO2, and O3 were prominent. During the 2020 epidemic period, high pollution concentrations were closely related to adverse meteorological conditions, with different parameters having different effects on the three pollution processes. In general, the unexpected reduction of anthropogenic emissions reduced the PM2.5 concentration, but led to an increase in the O3 concentration. Multi-scenario simulation results showed that anthropogenic emission reduction could reduce the average PM2.5 concentration after the Chinese Spring Festival, but improvement during days with heavy pollution was limited. Considering that O3 enhances the PM2.5 levels, to achieve the collaborative improvement of PM2.5 and O3 concentrations, further research should explore the collaborative emission reduction scheme with VOCs and NOx to achieve the collaborative improvement of PM2.5 and O3 concentrations. The conclusions of this study provide a basis for designing a plan that guarantees improved air quality for the 2022 Winter Olympics and other international major events in Beijing.

4.
J Med Chem ; 65(6): 4590-4599, 2022 03 24.
Article in English | MEDLINE | ID: covidwho-1740391

ABSTRACT

Identification of anti-SARS-CoV-2 compounds through traditional high-throughput screening (HTS) assays is limited by high costs and low hit rates. To address these challenges, we developed machine learning models to identify compounds acting via inhibition of the entry of SARS-CoV-2 into human host cells or the SARS-CoV-2 3-chymotrypsin-like (3CL) protease. The optimal classification models achieved good performance with area under the receiver operating characteristic curve (AUC-ROC) values of >0.78. Experimental validation showed that the best performing models increased the assay hit rate by 2.1-fold for viral entry inhibitors and 10.4-fold for 3CL protease inhibitors compared to those of the original drug repurposing screens. Twenty-two compounds showed potent (<5 µM) antiviral activities in a SARS-CoV-2 live virus assay. In conclusion, machine learning models can be developed and used as a complementary approach to HTS to expand compound screening capacities and improve the speed and efficiency of anti-SARS-CoV-2 drug discovery.


Subject(s)
COVID-19 , SARS-CoV-2 , Antiviral Agents/pharmacology , COVID-19/drug therapy , Drug Repositioning , Humans , Protease Inhibitors/pharmacology
5.
Frontiers in medicine ; 9, 2022.
Article in English | EuropePMC | ID: covidwho-1710617

ABSTRACT

Background Coronavirus disease 2019 (COVID-19) can result in an endothelial dysfunction in acute phase. However, information on the late vascular consequences of COVID-19 is limited. Methods Brachial artery flow-mediated dilation (FMD) examination were performed, and inflammatory biomarkers were assessed in 86 survivors of COVID-19 for 327 days (IQR 318–337 days) after recovery. Comparisons were made with 28 age-matched and sex-matched healthy controls and 30 risk factor-matched patients. Results Brachial artery FMD was significantly lower in the survivors of COVID-19 than in the healthy controls and risk factor-matched controls [median (IQR) 7.7 (5.1–10.7)% for healthy controls, 6.9 (5.5–9.4)% for risk factor-matched controls, and 3.5(2.2–4.6)% for COVID-19, respectively, p < 0.001]. The FMD was lower in 25 patients with elevated tumor necrosis factor (TNF)-α [2.7(1.2–3.9)] than in 61 patients without elevated TNF-α [3.8(2.6–5.3), p = 0.012]. Furthermore, FMD was inversely correlated with serum concentration of TNF-α (r = −0.237, p = 0.007). Conclusion Survivors of COVID-19 have a reduced brachial artery FMD, which is inversely correlated with increased serum concentration of TNF-α. Prospective studies on the association of endothelial dysfunction with long-term cardiovascular outcomes, especially the early onset of atherosclerosis, are warranted in survivors of COVID-19.

6.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-325204

ABSTRACT

Objective: Our objective is to investigate and analyze the psychological status of medical staff in a designated community hospital for COVID-19. Methods. We conducted a survey on medical staff in a designated community hospital for COVID-19 among the during-pandemic group (n = 120) and the after-pandemic group (n = 34). The symptom checklist 90 (SCL-90) questionnaire was used as a self-report instrument for the measurement of psychopathological complaints. Results. The during-pandemic group consisted of 120 individuals, including doctors (n = 36), nurses (n = 69) and technicians (n = 15). The SCL-90 sum scores showed no difference among doctors, nurses, and technicians (P > 0.05), but the somatization (SOM) item-scores of nurses were significantly higher than those of doctors and technicians (all P < 0.05). Meanwhile, the paranoid ideation (PAR) item-scores of nurses were significantly higher than those of doctors (P < 0.05). The after-pandemic group consisted only of nurses (n = 34). The score of each dimension of SCL-90 in nurses after the pandemic were relatively lower than that in nurses during the pandemic. Conclusions. Our study showed that nurses suffered with more psychological symptoms when fighting against COVID-19. The emergence of COVID-19 was the main factor leading to psychological problems of nurses.

7.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-325038

ABSTRACT

In order to identify the clinical characteristics of patients with Corona Virus Disease 2019 (COVID-19) and find out the characteristic effects of 2019 New Coronavirus (SARS-CoV-2) infection on changes in clinical and laboratory data, we analyzed the medical records of 80 suspected cases who admitted in the national designated hospital due to the relevant clinical manifestations of SARS-CoV-2 infection from January 22 to February 13, 2020. 62 (77.5%) confirmed cases and 18 (22.5%) negative cases were confirmed by SARS-CoV-2 nucleic acid test. Epidemiological investigation and statistical analysis were carried out on the clinical and laboratory data of all suspected cases of COVID-19, the specific indicators were found, and the clinical characteristics of COVID-19 were described. Compared with the patients with negative nucleic acid test, the patients with positive nucleic acid test showed shorter time of onset of symptoms, higher plasma CO 2 level, lower eosinophil ratio, lower platelet count and hematocrit, lower serum sodium level, higher serum creatinine, higher blood urea and plasma albumin levels (all P <0.05). Our results might provide some suggestions in diagnosis, clinical treatment and prevention for COVID-19.

9.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-324802

ABSTRACT

Background: : Novel coronavirus disease(COVID-19)has become a worldwide pandemic and precise fatality data by age group are needed urgently. This study to delineate the clinical characteristics and outcome of COVID-19 patients aged ≥75 years and identify the risk factors of in-hospital death. Methods: : A total of 141 consecutive patients aged ≥75 years who were admitted to the hospital between 12 th and 19 th February 2020. In-hospital death, clinical characteristics and laboratory findings on admission were obtained from medical records. The final follow-up observation was 31 st March 2020. Results: : The median age was 81 years (84 female, 59.6%). Thirty-eight (27%) patients were classified as severe or critical cases. 18 (12.8%) patients had died in hospital and the remaining 123 were discharged. Patients who died were more likely to present with fever (38.9% vs. 7.3%);low percutaneous oxygen saturation(SpO 2 ) (55.6% vs. 7.3%);reduced lymphocytes (72.2% vs. 35.8%) and platelets (27.8% vs. 4.1%);and increased D-dimer (94.4% vs. 42.3%), creatinine (50.0% vs. 22.0%), lactic dehydrogenase (LDH) (77.8% vs. 30.1%), high sensitivity troponin I (hs-TnI) (72.2% vs. 14.6%), and N-terminal pro-brain natriuretic peptide (NT-proBNP) (72.2% vs. 6.5%;all P<0.05) than patients who recovered. Male sex (odds ratio [OR]=13.1, 95% confidence interval[CI] 1.1 to 160.1, P=0.044), body temperature >37.3°C (OR=80.5, 95% CI 4.6 to 1407.6, P=0.003), SpO 2 ≤90% (OR=70.1, 95% CI 4.6 to 1060.4, P=0.002), and NT-proBNP>1800ng/L (OR=273.5, 95% CI 14.7 to 5104.8, P<0.0001) were independent risk factors of in-hospital death. Conclusions: : In-hospital fatality among COVID-19 patients can be estimated by sex and on-admission measurements of body temperature, SpO 2 , and NT-proBNP.

10.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-323668

ABSTRACT

Background: The coronavirus disease 2019 (COVID-19) epidemic is still ongoing, but the optimal treatment remains unclear. China adopted a series of measures, including widespread screening, strict quarantine and early treatment, combining western medicine with Chinese medicine, leading to rapid control of its spread. Nevertheless, the effects of ( combined ) Chinese medicine in reducing the toll of COVID-19 lack proof from statistics. Objective We conducted a retrospective data analysis to determine whether ( combined ) Chinese medicine is able to affect patient outcomes and to decrease the risk of death in COVID-19 patients. Methods The data were acquired by outputting the formatting information from the HIS system and then extracting and recording it in the database for complete cases. The demographics, disease onset, treatment, survival/death and all of the clinical classifications, groups and definitions were verified by specialists in the clinic, along with the research methodology and statistics, before conducting the statistical analysis. The characteristics of the cohort and the clinical symptoms and signs, prescriptions and outcomes were described and analyzed by the mean ± SD, median, interquartile range and composition ratio. Analysis of variance was used for comparisons between the measurement data sets;otherwise, the rank sum test was used. Counting data were compared between groups using the chi square test and Fisher’s exact test. Tendency matching was adopted to make the general data balance between groups. A Cox proportional hazard model was used to compare the risk of death among the different groups. Results Four centers were included in our study, and a total of 6,076 patients' clinical records were obtained after combining the data. We included 4567 cases for the descriptive statistics, and the crude case fatality rate was 3.0%. Compared with using only western medicine, (combined) Chinese medicine reduced the risk of death from COVID-19 after adjusting for other prognostic risk factors (HR = 0.135, 95% CI (0.088, 0.208)). Multivariate Cox regression also indicated that when applying the clinical classification of severe/critical, age ≥ 65 years old, coronary heart disease or chronic kidney disease and a time from onset to hospital admission of fewer than 14 days, all of these factors increased the risk of death. Conclusion (Combined) Chinese medicine can significantly reduce the risk of death from COVID-19, but the specific strategy/solution, effects and amount need further exploration in future studies.

11.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-321464

ABSTRACT

We employed the log-periodic power law singularity (LPPLS) methodology to systematically investigate the 2020 stock market crash in the U.S. equities sectors with different levels of total market capitalizations through four major U.S. stock market indexes, including the Wilshire 5000 Total Market index, the S&P 500 index, the S&P MidCap 400 index, and the Russell 2000 index, representing the stocks overall, the large capitalization stocks, the middle capitalization stocks and the small capitalization stocks, respectively. During the 2020 U.S. stock market crash, all four indexes lost more than a third of their values within five weeks, while both the middle capitalization stocks and the small capitalization stocks have suffered much greater losses than the large capitalization stocks and stocks overall. Our results indicate that the price trajectories of these four stock market indexes prior to the 2020 stock market crash have clearly featured the obvious LPPLS bubble pattern and were indeed in a positive bubble regime. Contrary to the popular belief that the COVID-19 led to the 2020 stock market crash, the 2020 U.S. stock market crash was endogenous, stemming from the increasingly systemic instability of the stock market itself. We also performed the complementary post-mortem analysis of the 2020 U.S. stock market crash. Our analyses indicate that the 2020 U.S. stock market crash originated from a bubble which began to form as early as September 2018;and the bubbles in stocks with different levels of total market capitalizations have significantly different starting time profiles. This study not only sheds new light on the making of the 2020 U.S. stock market crash but also creates a novel pipeline for future real-time crash detection and mechanism dissection of any financial market and/or economic index.

12.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-316927

ABSTRACT

In this paper, an n-patch SEIR epidemic model for the coronavirus disease 2019 (COVID-19) is presented. It is shown that there is unique disease-free equilibrium for this model. Then, the dynamic behavior is studied by the basic reproduction number. Some numerical simulations with three patches are given to validate the effectiveness of the theoretical results. The influence of quarantined rate and population migration rate on the basic reproduction number is also discussed by simulation.

13.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-310876

ABSTRACT

Objective: Exploring the relationship between diabetes mellitus targets and DPP4 of the receptor of novel coronavirus (2019-nCoV) through a protein interaction network to provide new perspective for clinical medication. Methods: : Diabetes mellitus targets were obtained from GeneCards database. Targets with a relevance score exceeding 20 were included, and DPP4 protein was added manually. The initial protein interaction network was obtained through String. The targets directly related to DPP4 were selected as the final analysis targets. Importing them into String again to obtain the protein interaction network. Module identification, GO analysis and KEGG pathway analysis were carried out respectively. The impact of DPP4 on the whole network was analyzed by scoring the module where it located. Results: : 43 DPP4-related proteins were finally selected from the diabetes mellitus targets and three functional modules were found by the cluster analysis. Module 1 was involved in insulin secretion and glucagon signaling pathway, module 2 and module 3 were involved in signaling receptor binding. The scoring results showed that LEP and apoB in module 1 were the highest, and the scores of INS, IL6 and ALB of cross module associated proteins of module 1 were the highest. Conclusions: : DPP4 is widely associated with key proteins in diabetes mellitus. COVID-19 may affect DPP4 in patients with diabetes mellitus, leading to high mortality of diabetes mellitus combined with COVID-19. DPP4 inhibitors and IL-6 antagonists can be considered to reduce the effect of COVID-19 infection on diabetic patients.

14.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-309830

ABSTRACT

Recent emergence of novel coronavirus (SARS-CoV-2) all over the world has resulted more than 33,106 global deaths. To date well-established therapeutics modules for infected patients are unknown. In this present initiative, molecular interactions between FDA-approved antiviral drugs against the Hepatitis-C virus (HCV) have been investigated theoretically against the RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2. HCV and SARS-CoV-2 are both +ssRNA viruses. At 25o C beclabuvir, a non-nucleoside inhibitor of the RdRpHCV can efficiently bind to RdRp SARS-CoV-2 (ΔGAutoDock = -9.95 kcal mol-1) with an inhibition constant of 51.03 nM. Both the ΔGLondon and ΔGGBVI / WSA values were - 9.06 and - 6.67 kcal mol-1, respectively for binding of beclabuvir to RdRpSARS-CoV-2. In addition, beclabuvir has also shown better binding free energy with RdRpSARS-CoV-2 (ΔGvina = -8.0 kcal mol-1) than that observed with the Thumb 1 domain of RdRpHCV (ΔGvina = -7.1 kcal mol-1). InterProScan has suggested the RNA-directed 5'-3' polymerase activity exists within 549th to 776th amino acid residues of RdRpSARS-CoV, where the major amino acid residues interacting being I591, Y621, C624, D625, A690, N693, L760, D762, D763, and E813-N817. Molecular interaction suggests occupancy of beclabuvir inside the active site environment of the RdRpSARS-CoV-2, the enzyme essential for viral RNA synthesis. In conclusion, results suggest beclabuvir may serve as an anti-SARS-CoV-2 drug.

15.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-309829

ABSTRACT

At the very beginning of the new decade, the COVID-19 pandemic has badly hit modern human societies. SARS-CoV-2, the causative agent of COVID-19 carries dozens of new mutations in its genome. Herein, we made an effort to find new antiviral peptides (AVPs) against SARS-CoV-2. Gladly, with the help of Machine Learning algorithms, and Supported Vector Machine, we have invented three new AVPs against the SARS-CoV-2. Antiviral peptides viz. , Seq12, Seq12m, and Seq13m can block the receptor binding domain (RBD) of the SARS-CoV-2, necessary for communication with the angiotensin-converting enzyme 2 (ACE2). In addition, these AVPs retain their antiviral properties, even after the insertion of dozens of new mutations (Rosetta, and FoldX based) in the RBD. Further, Seq12, and Seq12m showed negligible cytotoxicity. Besides, the binding free energy calculated using MM-PB/GBSA method is also in agreement with the molecular docking studies performed using HADDOCK. Furthermore, the molecular interactions between AVPs and the viral membrane protein (M) also showed a thermodynamically favorable interaction, suggesting it could eventually inhibit the viral re-packaging process. In conclusion, this study suggests AVPs viz. , Seq12, Seq12m, and Seq13m embrace importance as a potential anti-SARS-CoV-2 therapeutic. These AVPs could also aid virus diagnostic tools in the future.

16.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-315599

ABSTRACT

Background: Intravenous immunoglobulin (IVIG) is commonly used to treat severe COVID-19, although the clinical outcomes remain unclear. This study evaluated the effectiveness of IVIG treatment for severe COVID-19. Methods: : This retrospective multi-center study evaluated 28-day mortality and time for SARS-CoV-2 RNA clearance in severe COVID-19 patients with or without IVIG treatment. Propensity score matching was used to control confounding factors. Logistic regression and competing risk analyses were performed. Results: : The study included 850 patients (421 patients received IVIG). No significant differences in 28-day mortality or time for SARS-CoV-2 RNA clearance were observed ( p =0.357 and p =0.123, respectively). High-dose of IVIG treatment (>10 g/day) (n=27) was associated with decreased 28-day mortality (OR: 0.33, 95% CI: 0.14–0.77;p =0.011). The IVIG group had prolonged median hospitalization, less shock, and higher incidences of acute respiratory distress syndrome, myocardial injury. Furthermore, IVIG-treated patients were more likely to require non-invasive mechanical ventilation and less likely to require invasive mechanical ventilation. Conclusions: : IVIG treatment for severe COVID-19 patients was not associated with significant improvements in 28-day mortality or time for SARS-CoV-2 RNA clearance. However, some improvements in 28-day survival were observed for high-dose IVIG treatment (>10 g/day).

17.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-314029

ABSTRACT

Coronavirus disease 2019 (COVID-19) was recently raised and starting from China to all over the world. The viral main protease (3-chymotrypsin-like cysteine enzyme) controls COVID-19 duplication and manages its life cycle, making it a drug discovery target. Therefore, herein, we analyzed the theoretical approaches of 10 structurally different hydrolysable tannins as natural anti-COVID-19 through binding with the main protease of 2019-nCoV using molecular docking modelling via Molecular Operating Environment (MOE v2009) software. Our results revealed that there are top three hits may serve as potential anti-COVID-19 lead molecules for further optimization and drug development to control COVID-19. Pedunculagin, tercatain, and punicalin were found to faithfully interact with the receptor binding site and catalytic dyad (Cys145 and His41) of COVID-19 main protease, showing their successfully inhibit the protease enzyme of 2019-nCoV. We anticipated that this study would pave way for tannins based novel small molecules as more efficacious and selective anti-COVID-19 therapeutic compounds.

18.
Cell Metab ; 34(3): 424-440.e7, 2022 03 01.
Article in English | MEDLINE | ID: covidwho-1676683

ABSTRACT

Coronavirus disease 2019 (COVID-19) represents a systemic disease that may cause severe metabolic complications in multiple tissues including liver, kidney, and cardiovascular system. However, the underlying mechanisms and optimal treatment remain elusive. Our study shows that impairment of ACE2 pathway is a key factor linking virus infection to its secondary metabolic sequelae. By using structure-based high-throughput virtual screening and connectivity map database, followed with experimental validations, we identify imatinib, methazolamide, and harpagoside as direct enzymatic activators of ACE2. Imatinib and methazolamide remarkably improve metabolic perturbations in vivo in an ACE2-dependent manner under the insulin-resistant state and SARS-CoV-2-infected state. Moreover, viral entry is directly inhibited by these three compounds due to allosteric inhibition of ACE2 binding to spike protein on SARS-CoV-2. Taken together, our study shows that enzymatic activation of ACE2 via imatinib, methazolamide, or harpagoside may be a conceptually new strategy to treat metabolic sequelae of COVID-19.


Subject(s)
COVID-19/drug therapy , Imatinib Mesylate/therapeutic use , Metabolic Diseases/drug therapy , Methazolamide/therapeutic use , SARS-CoV-2/drug effects , Angiotensin-Converting Enzyme 2/drug effects , Angiotensin-Converting Enzyme 2/metabolism , Animals , COVID-19/complications , COVID-19/metabolism , COVID-19/virology , Cells, Cultured , Chlorocebus aethiops , Down-Regulation/drug effects , HEK293 Cells , Human Umbilical Vein Endothelial Cells , Humans , Imatinib Mesylate/pharmacology , Male , Metabolic Diseases/metabolism , Metabolic Diseases/virology , Methazolamide/pharmacology , Mice , Mice, Inbred C57BL , Mice, Obese , Mice, Transgenic , SARS-CoV-2/physiology , Vero Cells , Virus Internalization/drug effects
19.
EBioMedicine ; 76: 103821, 2022 Feb.
Article in English | MEDLINE | ID: covidwho-1670420

ABSTRACT

BACKGROUND: Although acute cardiac injury (ACI) is a known COVID-19 complication, whether ACI acquired during COVID-19 recovers is unknown. This study investigated the incidence of persistent ACI and identified clinical predictors of ACI recovery in hospitalized patients with COVID-19 2.5 months post-discharge. METHODS: This retrospective study consisted of 10,696 hospitalized COVID-19 patients from March 11, 2020 to June 3, 2021. Demographics, comorbidities, and laboratory tests were collected at ACI onset, hospital discharge, and 2.5 months post-discharge. ACI was defined as serum troponin-T (TNT) level >99th-percentile upper reference limit (0.014ng/mL) during hospitalization, and recovery was defined as TNT below this threshold 2.5 months post-discharge. Four models were used to predict ACI recovery status. RESULTS: There were 4,248 (39.7%) COVID-19 patients with ACI, with most (93%) developed ACI on or within a day after admission. In-hospital mortality odds ratio of ACI patients was 4.45 [95%CI: 3.92, 5.05, p<0.001] compared to non-ACI patients. Of the 2,880 ACI survivors, 1,114 (38.7%) returned to our hospitals 2.5 months on average post-discharge, of which only 302 (44.9%) out of 673 patients recovered from ACI. There were no significant differences in demographics, race, ethnicity, major commodities, and length of hospital stay between groups. Prediction of ACI recovery post-discharge using the top predictors (troponin, creatinine, lymphocyte, sodium, lactate dehydrogenase, lymphocytes and hematocrit) at discharge yielded 63.73%-75.73% accuracy. INTERPRETATION: Persistent cardiac injury is common among COVID-19 survivors. Readily available patient data accurately predict ACI recovery post-discharge. Early identification of at-risk patients could help prevent long-term cardiovascular complications. FUNDING: None.


Subject(s)
COVID-19/pathology , Heart Injuries/diagnosis , Troponin I/metabolism , Aged , Aged, 80 and over , COVID-19/complications , COVID-19/virology , Female , Heart Injuries/epidemiology , Heart Injuries/etiology , Heart Injuries/mortality , Hospital Mortality , Humans , Incidence , L-Lactate Dehydrogenase/metabolism , Logistic Models , Lymphocyte Count , Male , Middle Aged , New York/epidemiology , Patient Discharge , Retrospective Studies , SARS-CoV-2/isolation & purification
20.
Sci Rep ; 12(1): 188, 2022 01 07.
Article in English | MEDLINE | ID: covidwho-1612207

ABSTRACT

Patients with diabetes are more likely to be infected with Coronavirus disease 2019 (COVID-19), and the risk of death is significantly higher than ordinary patients. Dipeptidyl peptidase-4 (DPP4) is one of the functional receptor of human coronavirus. Exploring the relationship between diabetes mellitus targets and DPP4 is particularly important for the management of patients with diabetes and COVID-19. We intend to study the protein interaction through the protein interaction network in order to find a new clue for the management of patients with diabetes with COVID-19. Diabetes mellitus targets were obtained from GeneCards database. Targets with a relevance score exceeding 20 were included, and DPP4 protein was added manually. The initial protein interaction network was obtained through String. The targets directly related to DPP4 were selected as the final analysis targets. Importing them into String again to obtain the protein interaction network. Module identification, gene ontology (GO) analysis and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were carried out respectively. The impact of DPP4 on the whole network was analyzed by scoring the module where it located. 43 DPP4-related proteins were finally selected from the diabetes mellitus targets and three functional modules were found by the cluster analysis. Module 1 was involved in insulin secretion and glucagon signaling pathway, module 2 and module 3 were involved in signaling receptor binding. The scoring results showed that LEP and apoB in module 1 were the highest, and the scores of INS, IL6 and ALB of cross module associated proteins of module 1 were the highest. DPP4 is widely associated with key proteins in diabetes mellitus. COVID-19 may affect DPP4 in patients with diabetes mellitus, leading to high mortality of diabetes mellitus combined with COVID-19. DPP4 inhibitors and IL-6 antagonists can be considered to reduce the effect of COVID-19 infection on patients with diabetes.


Subject(s)
COVID-19/metabolism , Diabetes Mellitus, Type 2/metabolism , Dipeptidyl Peptidase 4/metabolism , Protein Interaction Maps , SARS-CoV-2/physiology , COVID-19/complications , COVID-19/drug therapy , Diabetes Mellitus, Type 2/complications , Diabetes Mellitus, Type 2/drug therapy , Dipeptidyl-Peptidase IV Inhibitors/therapeutic use , Drug Discovery , Humans , Protein Interaction Maps/drug effects
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