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1.
Front Public Health ; 10: 861062, 2022.
Article in English | MEDLINE | ID: covidwho-1776092

ABSTRACT

Background and Objective: According to the WHO, diabetes mellitus is a long-term condition marked by high blood sugar levels. The consequences might be far-reaching. According to current increases in mortality, diabetes has risen to number 10 among the leading causes of mortality worldwide. When used to predict diabetes using unbalanced datasets from testing, machine learning (ML) classifiers and established approaches for encoding categorical data have exhibited a broad variety of surprising outcomes. Early studies also made use of an artificial neural network to extract features without obtaining a grasp of the sequence information. Methods: This study offers a deep learning-based decision support system (DSS), utilizing bidirectional long/short-term memory (BiLSTM), to accurately predict diabetic illness from patient data. In order to predict diabetes, the BiLSTM hybrid model was used after balancing the data set. Results: Unlike earlier studies, this proposed model's trial findings were promising, with an accuracy of 93.07%, 93% precision, 92% recall, and a 92% F1-score. Conclusions: Using a BILSTM model for classification outperforms current approaches in the diabetes detection domain.


Subject(s)
Diabetes Mellitus , Algorithms , Decision Support Systems, Clinical , Diabetes Mellitus/diagnosis , Humans , Machine Learning , Neural Networks, Computer
2.
BMC Geriatr ; 22(1): 99, 2022 02 04.
Article in English | MEDLINE | ID: covidwho-1702303

ABSTRACT

BACKGROUND: Older adults (≥65 years) with diabetes and multiple chronic conditions (MCC) (> 2 chronic conditions) experience reduced function and quality of life, increased health service use, and high mortality. Many community-based self-management interventions have been developed for this group, however the evidence for their effectiveness is limited. This paper presents the protocol for a randomized controlled trial (RCT) comparing the effectiveness and implementation of the Aging, Community and Health Research Unit-Community Partnership Program (ACHRU-CPP) to usual care in older adults with diabetes and MCC and their caregivers. METHODS: We will conduct a cross-jurisdictional, multi-site implementation-effectiveness type II hybrid RCT. Eligibility criteria are: ≥65 years, diabetes diagnosis (Type 1 or 2) and at least one other chronic condition, and enrolled in a primary care or diabetes education program. Participants will be randomly assigned to the intervention (ACHRU-CPP) or control arm (1:1 ratio). The intervention arm consists of home/telephone visits, monthly group wellness sessions, multidisciplinary case conferences, and system navigation support. It will be delivered by registered nurses and registered dietitians/nutritionists from participating primary care or diabetes education programs and program coordinators from community-based organizations. The control arm consists of usual care provided by the primary care setting or diabetes education program. The primary outcome is the change from baseline to 6 months in mental functioning. Secondary outcomes will include, for example, the change from baseline to 6 months in physical functioning, diabetes self-management, depressive symptoms, and cost of use of healthcare services. Analysis of covariance (ANCOVA) models will be used to analyze all outcomes, with intention-to-treat analysis using multiple imputation to address missing data. Descriptive and qualitative data from older adults, caregivers and intervention teams will be used to examine intervention implementation, site-specific adaptations, and scalability potential. DISCUSSION: An interprofessional intervention supporting self-management may be effective in improving health outcomes and client/caregiver experience and reducing service use and costs in this complex population. This pragmatic trial includes a scalability assessment which considers a range of effectiveness and implementation criteria to inform the future scale-up of the ACHRU-CPP. TRIAL REGISTRATION: Clinical Trials.gov Identifier NCT03664583 . Registration date: September 10, 2018.


Subject(s)
Diabetes Mellitus , Multiple Chronic Conditions , Aged , Aging , Cost-Benefit Analysis , Diabetes Mellitus/diagnosis , Diabetes Mellitus/therapy , Humans , Pyrazines , Quality of Life , Randomized Controlled Trials as Topic
3.
Prim Care Diabetes ; 16(1): 65-68, 2022 02.
Article in English | MEDLINE | ID: covidwho-1683495

ABSTRACT

BACKGROUND AND AIMS: While the higher prevalence of diabetes mellitus (DM) at younger age in Indonesia might contribute to the relatively higher COVID-19 mortality rate in Indonesia, there were currently no available evidence nor specific policy in terms of COVID-19 prevention and management among DM patients. We aimed to find out the association between diagnosed diabetes mellitus (DM) with COVID-19 mortality in Indonesia. METHODS: We performed a retrospective cohort study using Jakarta Province's COVID-19 epidemiological registry within the first 6 months of the pandemic. All COVID-19 confirmed patients, aged >15 years with known DM status were included. Patients were assessed for their clinical symptoms and mortality outcome based on their DM status. A multivariate Cox-regression test was performed to obtain the relative risk (RR) of COVID-19 mortality in the diagnosed DM group. RESULTS: Of 20,481 patients with COVID-19, 705 (3.4%) had DM. COVID-19 mortality rate in DM group was 21.28%, significantly higher compared to 2.77% mortality in the non-DM group [adjusted RR 1.98 (CI 95% 1.57-2.51), p < 0.001]. In addition, COVID-19 patients with DM generally developed more symptoms. CONCLUSIONS: DM is associated not only with development of more COVID-19 clinical symptoms, but also with a higher risk of COVID-19 mortality. This finding may provide a basis for future policy regarding COVID-19 prevention and management among diabetes patients in Indonesia.


Subject(s)
COVID-19 , Diabetes Mellitus , Adolescent , Diabetes Mellitus/diagnosis , Diabetes Mellitus/epidemiology , Humans , Registries , Retrospective Studies , Risk Factors , SARS-CoV-2
4.
Elife ; 112022 01 13.
Article in English | MEDLINE | ID: covidwho-1677761

ABSTRACT

Protein biomarkers have been identified across many age-related morbidities. However, characterising epigenetic influences could further inform disease predictions. Here, we leverage epigenome-wide data to study links between the DNA methylation (DNAm) signatures of the circulating proteome and incident diseases. Using data from four cohorts, we trained and tested epigenetic scores (EpiScores) for 953 plasma proteins, identifying 109 scores that explained between 1% and 58% of the variance in protein levels after adjusting for known protein quantitative trait loci (pQTL) genetic effects. By projecting these EpiScores into an independent sample (Generation Scotland; n = 9537) and relating them to incident morbidities over a follow-up of 14 years, we uncovered 137 EpiScore-disease associations. These associations were largely independent of immune cell proportions, common lifestyle and health factors, and biological aging. Notably, we found that our diabetes-associated EpiScores highlighted previous top biomarker associations from proteome-wide assessments of diabetes. These EpiScores for protein levels can therefore be a valuable resource for disease prediction and risk stratification.


Although our genetic code does not change throughout our lives, our genes can be turned on and off as a result of epigenetics. Epigenetics can track how the environment and even certain behaviors add or remove small chemical markers to the DNA that makes up the genome. The type and location of these markers may affect whether genes are active or silent, this is, whether the protein coded for by that gene is being produced or not. One common epigenetic marker is known as DNA methylation. DNA methylation has been linked to the levels of a range of proteins in our cells and the risk people have of developing chronic diseases. Blood samples can be used to determine the epigenetic markers a person has on their genome and to study the abundance of many proteins. Gadd, Hillary, McCartney, Zaghlool et al. studied the relationships between DNA methylation and the abundance of 953 different proteins in blood samples from individuals in the German KORA cohort and the Scottish Lothian Birth Cohort 1936. They then used machine learning to analyze the relationship between epigenetic markers found in people's blood and the abundance of proteins, obtaining epigenetic scores or 'EpiScores' for each protein. They found 109 proteins for which DNA methylation patterns explained between at least 1% and up to 58% of the variation in protein levels. Integrating the 'EpiScores' with 14 years of medical records for more than 9000 individuals from the Generation Scotland study revealed 137 connections between EpiScores for proteins and a future diagnosis of common adverse health outcomes. These included diabetes, stroke, depression, Alzheimer's dementia, various cancers, and inflammatory conditions such as rheumatoid arthritis and inflammatory bowel disease. Age-related chronic diseases are a growing issue worldwide and place pressure on healthcare systems. They also severely reduce quality of life for individuals over many years. This work shows how epigenetic scores based on protein levels in the blood could predict a person's risk of several of these diseases. In the case of type 2 diabetes, the EpiScore results replicated previous research linking protein levels in the blood to future diagnosis of diabetes. Protein EpiScores could therefore allow researchers to identify people with the highest risk of disease, making it possible to intervene early and prevent these people from developing chronic conditions as they age.


Subject(s)
Cardiovascular Diseases/diagnosis , DNA Methylation/genetics , Diabetes Mellitus/diagnosis , Epigenomics/methods , Neoplasms/diagnosis , Proteome/genetics , Adolescent , Adult , Aged , Aged, 80 and over , Aging , Biomarkers , Epigenesis, Genetic , Female , Humans , Life Style , Male , Middle Aged , Risk Factors , Scotland , Young Adult
5.
J Diabetes Complications ; 36(4): 108145, 2022 04.
Article in English | MEDLINE | ID: covidwho-1665158

ABSTRACT

AIMS: High rates of newly diagnosed diabetes mellitus (NDDM) have been reported in association with coronavirus disease-2019 (COVID-19). Factors associated with NDDM and long-term glycemic outcomes are not known. METHODS: Retrospective review of individuals admitted with COVID-19 and diabetes mellitus (DM; based on labs, diagnoses, outpatient insulin use, or severe inpatient hyperglycemia) between March and September 2020, with follow-up through July 2021. RESULTS: Of 1902 individuals admitted with COVID-19, 594 (31.2%) had DM; 77 (13.0%) of these had NDDM. Compared to pre-existing DM, NDDM was more common in younger patients and less common in those of non-Hispanic White race/ethnicity. Glycemic parameters were lower and inflammatory markers higher in patients with NDDM. In adjusted models, NDDM was associated with lower insulin requirements, longer length of stay, and intensive care unit admission but not death. Of 64 survivors with NDDM, 36 (56.3%) continued to have DM, 26 (40.6%) regressed to normoglycemia or pre-diabetes, and 2 were unable to be classified at a median follow-up of 323 days. CONCLUSIONS: Diabetes diagnosed at COVID-19 presentation is associated with lower glucose but higher inflammatory markers and ICU admission, suggesting stress hyperglycemia as a major physiologic mechanism. Approximately half of such individuals experience regression of DM.


Subject(s)
COVID-19 , Diabetes Mellitus , Hyperglycemia , Blood Glucose , COVID-19/complications , COVID-19/diagnosis , COVID-19/epidemiology , Diabetes Mellitus/diagnosis , Diabetes Mellitus/epidemiology , Diabetes Mellitus/therapy , Humans , Hyperglycemia/diagnosis , Hyperglycemia/epidemiology , Phenotype , Retrospective Studies
6.
MMWR Morb Mortal Wkly Rep ; 71(2): 59-65, 2022 Jan 14.
Article in English | MEDLINE | ID: covidwho-1622894

ABSTRACT

The COVID-19 pandemic has disproportionately affected people with diabetes, who are at increased risk of severe COVID-19.* Increases in the number of type 1 diabetes diagnoses (1,2) and increased frequency and severity of diabetic ketoacidosis (DKA) at the time of diabetes diagnosis (3) have been reported in European pediatric populations during the COVID-19 pandemic. In adults, diabetes might be a long-term consequence of SARS-CoV-2 infection (4-7). To evaluate the risk for any new diabetes diagnosis (type 1, type 2, or other diabetes) >30 days† after acute infection with SARS-CoV-2 (the virus that causes COVID-19), CDC estimated diabetes incidence among patients aged <18 years (patients) with diagnosed COVID-19 from retrospective cohorts constructed using IQVIA health care claims data from March 1, 2020, through February 26, 2021, and compared it with incidence among patients matched by age and sex 1) who did not receive a COVID-19 diagnosis during the pandemic, or 2) who received a prepandemic non-COVID-19 acute respiratory infection (ARI) diagnosis. Analyses were replicated using a second data source (HealthVerity; March 1, 2020-June 28, 2021) that included patients who had any health care encounter possibly related to COVID-19. Among these patients, diabetes incidence was significantly higher among those with COVID-19 than among those 1) without COVID-19 in both databases (IQVIA: hazard ratio [HR] = 2.66, 95% CI = 1.98-3.56; HealthVerity: HR = 1.31, 95% CI = 1.20-1.44) and 2) with non-COVID-19 ARI in the prepandemic period (IQVIA, HR = 2.16, 95% CI = 1.64-2.86). The observed increased risk for diabetes among persons aged <18 years who had COVID-19 highlights the importance of COVID-19 prevention strategies, including vaccination, for all eligible persons in this age group,§ in addition to chronic disease prevention and management. The mechanism of how SARS-CoV-2 might lead to incident diabetes is likely complex and could differ by type 1 and type 2 diabetes. Monitoring for long-term consequences, including signs of new diabetes, following SARS-CoV-2 infection is important in this age group.


Subject(s)
COVID-19/complications , Diabetes Mellitus/diagnosis , Diabetes Mellitus/epidemiology , Diabetic Ketoacidosis/diagnosis , Diabetic Ketoacidosis/epidemiology , SARS-CoV-2 , Adolescent , Child , Child, Preschool , Cohort Studies , Databases, Factual , Female , Humans , Incidence , Infant , Male , Retrospective Studies , Risk , United States/epidemiology
8.
Sci Rep ; 11(1): 24436, 2021 12 24.
Article in English | MEDLINE | ID: covidwho-1585781

ABSTRACT

Patients diagnosed with diabetes mellitus (DM) who are infected with severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) belong to the most vulnerable patient subgroups. Emerging data has shown increased risks of severe infections, increased in ICU admissions, longer durations of admission, and increased mortality among coronavirus disease 2019 (COVID-19) patients with diabetes. We performed a subgroup analysis comparing the outcomes of patients diagnosed with DM (n = 2191) versus patients without DM (n = 8690) on our data from our study based on a nationwide, comparative, retrospective, cohort study among adult, hospitalized COVID-19 patients involving 37 hospital sites from around the Philippines. We determined distribution differences between two independent samples using Mann-Whitney U and t tests. Data on the time to onset of mortality, respiratory failure, intensive care unit (ICU) admission were used to build Kaplan-Meier curves and to compute for hazard ratios (HR). The odds ratios (OR) for longer ventilator dependence, longer ICU stay, and longer hospital stays were computed via multivariate logistic regression. Adjusted hazard ratios (aHR) and ORs (aOR) with 95% CI were calculated. We included a total of 10,881 patients with confirmed COVID-19 infection (2191 have DM while 8690 did not have DM). The median age of the DM cohort was 61, with a female to male ratio of 1:1.25 and more than 50% of the DM population were above 60 years old. The aOR for mortality was significantly higher among those in the DM group by 1.46 (95% CI 1.28-1.68; p < 0.001) as compared to the non-DM group. Similarly, the aOR for respiratory failure was also significantly higher among those in the DM group by 1.67 (95% CI 1.46-1.90). The aOR for developing severe COVID-19 at nadir was significantly higher among those in the DM group by 1.85 (95% CI 1.65-2.07; p < 0.001). The aOR for ICU admission was significantly higher among those in the DM group by 1.80 (95% CI 1.59-2.05) than those in the non-DM group. DM patients had significantly longer duration of ventilator dependence (aOR 1.33, 95% CI 1.08-1.64; p = 0.008) and longer hospital admission (aOR 1.13, 95% CI 1.01-1.26; p = 0.027). The presence of DM among COVID-19 patients significantly increased the risk of mortality, respiratory failure, duration of ventilator dependence, severe/critical COVID-19, ICU admission, and length of hospital stay.


Subject(s)
COVID-19/pathology , Diabetes Mellitus/diagnosis , Adolescent , Adult , Aged , COVID-19/complications , COVID-19/mortality , COVID-19/virology , Diabetes Mellitus/pathology , Female , Hospital Mortality , Humans , Length of Stay , Male , Middle Aged , Odds Ratio , Philippines , Proportional Hazards Models , Respiratory Insufficiency/etiology , Retrospective Studies , Risk Factors , SARS-CoV-2/isolation & purification , Severity of Illness Index , Ventilators, Mechanical , Young Adult
9.
PLoS One ; 16(11): e0260389, 2021.
Article in English | MEDLINE | ID: covidwho-1533422

ABSTRACT

BACKGROUND: In recent non-pandemic periods, tuberculosis (TB) has been the leading killer worldwide from a single infectious disease. Patients with DM are three times more likely to develop active TB and poor treatment outcomes. Single glycemic measurements at TB diagnosis may inaccurately diagnose or mischaracterize DM severity. Data are limited regarding glycemic dynamics from TB diagnosis through treatment. METHODS: Prospective study of glycemia dynamics in response to TB treatment measured glycosylated haemoglobin (HbA1c) in patients presenting to TB screening centres in Bangladesh to determine the prevalence and risk factors of hyperglycemia before and at TB treatment completion. RESULTS: 429 adults with active TB disease were enrolled and divided into groups based on history of DM and initial HbA1c range: normoglycemia, prediabetes, and DM. DM was diagnosed in 37%. At treatment completion,14(6%) patients from the normoglycemia and prediabetes groups had HbA1c>6.5%, thus increasing the prevalence of DM to 39%. The number needed to screen to diagnose one new case of DM at TB diagnosis was 5.7 and 16 at treatment completion in the groups without DM. Weight gain>5% at treatment completion significantly increased the risk of hyperglycemia in the groups without DM at TB diagnosis (95% CI 1.23-26.04, p<0.05). CONCLUSION: HbA1c testing prior to and at TB treatment completion found a high prevalence of prediabetes and DM, including a proportion found at treatment completion and commonly in people with a higher percentage of weight gain. Further longitudinal research is needed to understand the effects of TB disease and treatment on insulin resistance and DM complications.


Subject(s)
Diabetes Mellitus/diagnosis , Hyperglycemia/diagnosis , Prediabetic State/diagnosis , Tuberculosis/complications , Adolescent , Adult , Bangladesh/epidemiology , Diabetes Mellitus/blood , Diabetes Mellitus/epidemiology , Disease Management , Female , Glycated Hemoglobin A/analysis , Humans , Hyperglycemia/blood , Hyperglycemia/epidemiology , Male , Middle Aged , Prediabetic State/blood , Prediabetic State/epidemiology , Prospective Studies , Risk Factors , Tuberculosis/diagnosis , Tuberculosis/therapy , Young Adult
10.
Prim Care Diabetes ; 16(1): 65-68, 2022 02.
Article in English | MEDLINE | ID: covidwho-1510177

ABSTRACT

BACKGROUND AND AIMS: While the higher prevalence of diabetes mellitus (DM) at younger age in Indonesia might contribute to the relatively higher COVID-19 mortality rate in Indonesia, there were currently no available evidence nor specific policy in terms of COVID-19 prevention and management among DM patients. We aimed to find out the association between diagnosed diabetes mellitus (DM) with COVID-19 mortality in Indonesia. METHODS: We performed a retrospective cohort study using Jakarta Province's COVID-19 epidemiological registry within the first 6 months of the pandemic. All COVID-19 confirmed patients, aged >15 years with known DM status were included. Patients were assessed for their clinical symptoms and mortality outcome based on their DM status. A multivariate Cox-regression test was performed to obtain the relative risk (RR) of COVID-19 mortality in the diagnosed DM group. RESULTS: Of 20,481 patients with COVID-19, 705 (3.4%) had DM. COVID-19 mortality rate in DM group was 21.28%, significantly higher compared to 2.77% mortality in the non-DM group [adjusted RR 1.98 (CI 95% 1.57-2.51), p < 0.001]. In addition, COVID-19 patients with DM generally developed more symptoms. CONCLUSIONS: DM is associated not only with development of more COVID-19 clinical symptoms, but also with a higher risk of COVID-19 mortality. This finding may provide a basis for future policy regarding COVID-19 prevention and management among diabetes patients in Indonesia.


Subject(s)
COVID-19 , Diabetes Mellitus , Adolescent , Diabetes Mellitus/diagnosis , Diabetes Mellitus/epidemiology , Humans , Registries , Retrospective Studies , Risk Factors , SARS-CoV-2
11.
Prim Care Diabetes ; 16(1): 57-64, 2022 02.
Article in English | MEDLINE | ID: covidwho-1487917

ABSTRACT

AIMS: The purpose of this study was to examine whether pandemic exposure impacted unmet social and diabetes needs, self-care behaviors, and diabetes outcomes in a sample with diabetes and poor glycemic control. METHODS: This was a cross-sectional analysis of participants with diabetes and poor glycemic control in an ongoing trial (n = 353). We compared the prevalence of unmet needs, self-care behaviors, and diabetes outcomes in successive cohorts of enrollees surveyed pre-pandemic (prior to March 11, 2020, n = 182), in the early stages of the pandemic (May-September, 2020, n = 75), and later (September 2020-January 2021, n = 96) stratified by income and gender. Adjusted multivariable regression models were used to examine trends. RESULTS: More participants with low income reported food insecurity (70% vs. 83%, p < 0.05) and needs related to access to blood glucose supplies (19% vs. 67%, p < 0.05) during the pandemic compared to pre-pandemic levels. In adjusted models among people with low incomes, the odds of housing insecurity increased among participants during the early pandemic months compared with participants pre-pandemic (OR 20.2 [95% CI 2.8-145.2], p < 0.01). A1c levels were better among participants later in the pandemic than those pre-pandemic (ß = -1.1 [95% CI -1.8 to -0.4], p < 0.01), but systolic blood pressure control was substantially worse (ß = 11.5 [95% CI 4.2-18.8, p < 0.001). CONCLUSION: Adults with low-incomes and diabetes were most impacted by the pandemic. A1c may not fully capture challenges that people with diabetes are facing to manage their condition; systolic blood pressures may have worsened and problems with self-care may forebode longer-term challenges in diabetes control.


Subject(s)
COVID-19 , Diabetes Mellitus , Adult , Cross-Sectional Studies , Diabetes Mellitus/diagnosis , Diabetes Mellitus/epidemiology , Diabetes Mellitus/therapy , Glycemic Control , Humans , Pandemics , SARS-CoV-2 , Self Care
12.
Mol Med ; 27(1): 129, 2021 10 18.
Article in English | MEDLINE | ID: covidwho-1477255

ABSTRACT

BACKGROUND: Host inflammation contributes to determine whether SARS-CoV-2 infection causes mild or life-threatening disease. Tools are needed for early risk assessment. METHODS: We studied in 111 COVID-19 patients prospectively followed at a single reference Hospital fifty-three potential biomarkers including alarmins, cytokines, adipocytokines and growth factors, humoral innate immune and neuroendocrine molecules and regulators of iron metabolism. Biomarkers at hospital admission together with age, degree of hypoxia, neutrophil to lymphocyte ratio (NLR), lactate dehydrogenase (LDH), C-reactive protein (CRP) and creatinine were analysed within a data-driven approach to classify patients with respect to survival and ICU outcomes. Classification and regression tree (CART) models were used to identify prognostic biomarkers. RESULTS: Among the fifty-three potential biomarkers, the classification tree analysis selected CXCL10 at hospital admission, in combination with NLR and time from onset, as the best predictor of ICU transfer (AUC [95% CI] = 0.8374 [0.6233-0.8435]), while it was selected alone to predict death (AUC [95% CI] = 0.7334 [0.7547-0.9201]). CXCL10 concentration abated in COVID-19 survivors after healing and discharge from the hospital. CONCLUSIONS: CXCL10 results from a data-driven analysis, that accounts for presence of confounding factors, as the most robust predictive biomarker of patient outcome in COVID-19.


Subject(s)
COVID-19/diagnosis , Chemokine CXCL10/blood , Coronary Artery Disease/diagnosis , Diabetes Mellitus/diagnosis , Hypertension/diagnosis , Biomarkers/blood , C-Reactive Protein/metabolism , COVID-19/blood , COVID-19/immunology , COVID-19/mortality , Comorbidity , Coronary Artery Disease/blood , Coronary Artery Disease/immunology , Coronary Artery Disease/mortality , Creatine/blood , Diabetes Mellitus/blood , Diabetes Mellitus/immunology , Diabetes Mellitus/mortality , Female , Hospitalization , Humans , Hypertension/blood , Hypertension/immunology , Hypertension/mortality , Immunity, Humoral , Immunity, Innate , Inflammation , Intensive Care Units , L-Lactate Dehydrogenase/blood , Leukocyte Count , Lymphocytes/immunology , Lymphocytes/pathology , Male , Middle Aged , Neutrophils/immunology , Neutrophils/pathology , Prognosis , Prospective Studies , Retrospective Studies , SARS-CoV-2 , Severity of Illness Index , Survival Analysis
13.
Front Endocrinol (Lausanne) ; 12: 727419, 2021.
Article in English | MEDLINE | ID: covidwho-1444039

ABSTRACT

Background: Blood parameters, such as neutrophil-to-lymphocyte ratio, have been identified as reliable inflammatory markers with diagnostic and predictive value for the coronavirus disease 2019 (COVID-19). However, novel hematological parameters derived from high-density lipoprotein-cholesterol (HDL-C) have rarely been studied as indicators for the risk of poor outcomes in patients with severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) infection. Here, we aimed to assess the prognostic value of these novel biomarkers in COVID-19 patients and the diabetes subgroup. Methods: We conducted a multicenter retrospective cohort study involving all hospitalized patients with COVID-19 from January to March 2020 in five hospitals in Wuhan, China. Demographics, clinical and laboratory findings, and outcomes were recorded. Neutrophil to HDL-C ratio (NHR), monocyte to HDL-C ratio (MHR), lymphocyte to HDL-C ratio (LHR), and platelet to HDL-C ratio (PHR) were investigated and compared in both the overall population and the subgroup with diabetes. The associations between blood parameters at admission with primary composite end-point events (including mechanical ventilation, admission to the intensive care unit, or death) were analyzed using Cox proportional hazards regression models. Receiver operating characteristic curves were used to compare the utility of different blood parameters. Results: Of 440 patients with COVID-19, 67 (15.2%) were critically ill. On admission, HDL-C concentration was decreased while NHR was high in patients with critical compared with non-critical COVID-19, and were independently associated with poor outcome as continuous variables in the overall population (HR: 0.213, 95% CI 0.090-0.507; HR: 1.066, 95% CI 1.030-1.103, respectively) after adjusting for confounding factors. Additionally, when HDL-C and NHR were examined as categorical variables, the HRs and 95% CIs for tertile 3 vs. tertile 1 were 0.280 (0.128-0.612) and 4.458 (1.817-10.938), respectively. Similar results were observed in the diabetes subgroup. ROC curves showed that the NHR had good performance in predicting worse outcomes. The cutoff point of the NHR was 5.50. However, the data in our present study could not confirm the possible predictive effect of LHR, MHR, and PHR on COVID-19 severity. Conclusion: Lower HDL-C concentrations and higher NHR at admission were observed in patients with critical COVID-19 than in those with noncritical COVID-19, and were significantly associated with a poor prognosis in COVID-19 patients as well as in the diabetes subgroup.


Subject(s)
COVID-19/blood , Cholesterol, HDL/blood , Diabetes Mellitus/blood , Aged , Biomarkers/blood , COVID-19/diagnosis , COVID-19/mortality , China , Diabetes Mellitus/diagnosis , Diabetes Mellitus/mortality , Female , Humans , Kaplan-Meier Estimate , Leukocytes/cytology , Male , Middle Aged , Prognosis , ROC Curve , Retrospective Studies , Severity of Illness Index
14.
Front Endocrinol (Lausanne) ; 12: 688071, 2021.
Article in English | MEDLINE | ID: covidwho-1399132

ABSTRACT

Coronavirus disease 19 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection continues to scale and threaten human health and public safety. It is essential to identify those risk factors that lead to a poor prognosis of the disease. A predisposing host genetic background could be one of these factors that explain the interindividual variability to COVID-19 severity. Thus, we have studied whether the rs4341 and rs4343 polymorphisms of the angiotensin converting enzyme (ACE) gene, key regulator of the renin-aldosterone-angiotensin system (RAAS), could explain the different outcomes of 128 COVID-19 patients with diverse degree of severity (33 asymptomatic or mildly symptomatic, 66 hospitalized in the general ward, and 29 admitted to the ICU). We found that G allele of rs4341 and rs4343 was associated with severe COVID-19 in hypertensive patients, independently of gender (p<0.05). G-carrier genotypes of both polymorphisms were also associated with higher mortality (p< 0.05) and higher severity of COVID-19 in dyslipidemic (p<0.05) and type 2 diabetic patients (p< 0.01). The association of G alleles with disease severity was adjusted for age, sex, BMI and number of comorbidities, suggesting that both the metabolic comorbidities and the G allele act synergistically on COVID-19 outcome. Although we did not find a direct association between serum ACE levels and COVID-19 severity, we found higher levels of ACE in the serum of patients with the GG genotype of rs4341 and rs4343 (p<0.05), what could explain the higher susceptibility to develop severe forms of the disease in patients with the GG genotype, in addition to hypertension and dyslipidemia. In conclusion, our preliminary study suggests that the G-containing genotypes of rs4341 and rs4343 confer an additional risk of adverse COVID-19 prognosis. Thus, rs4341 and rs4343 polymorphisms of ACE could be predictive markers of severity of COVID-19 in those patients with hypertension, dyslipidemia or diabetes. The knowledge of these genetic data could contribute to precision management of SARS-CoV-2 infected patients when admitted to hospital.


Subject(s)
COVID-19/genetics , Diabetes Mellitus/genetics , Dyslipidemias/genetics , Genetic Variation/genetics , Hypertension/genetics , Peptidyl-Dipeptidase A/genetics , Adult , Aged , Aged, 80 and over , COVID-19/diagnosis , COVID-19/epidemiology , Diabetes Mellitus/diagnosis , Diabetes Mellitus/epidemiology , Dyslipidemias/diagnosis , Dyslipidemias/epidemiology , Female , Hospitalization/trends , Humans , Hypertension/diagnosis , Hypertension/epidemiology , Male , Middle Aged , Pilot Projects , Risk Factors , Severity of Illness Index , Spain/epidemiology
15.
Eur J Endocrinol ; 185(2): 299-311, 2021 Jul 05.
Article in English | MEDLINE | ID: covidwho-1398974

ABSTRACT

OBJECTIVE: Male sex is one of the determinants of severe coronavirus diseas-e-2019 (COVID-19). We aimed to characterize sex differences in severe outcomes in adults with diabetes hospitalized for COVID-19. METHODS: We performed a sex-stratified analysis of clinical and biological features and outcomes (i.e. invasive mechanical ventilation (IMV), death, intensive care unit (ICU) admission and home discharge at day 7 (D7) or day 28 (D28)) in 2380 patients with diabetes hospitalized for COVID-19 and included in the nationwide CORONADO observational study (NCT04324736). RESULTS: The study population was predominantly male (63.5%). After multiple adjustments, female sex was negatively associated with the primary outcome (IMV and/or death, OR: 0.66 (0.49-0.88)), death (OR: 0.49 (0.30-0.79)) and ICU admission (OR: 0.57 (0.43-0.77)) at D7 but only with ICU admission (OR: 0.58 (0.43-0.77)) at D28. Older age and a history of microvascular complications were predictors of death at D28 in both sexes, while chronic obstructive pulmonary disease (COPD) was predictive of death in women only. At admission, C-reactive protein (CRP), aspartate amino transferase (AST) and estimated glomerular filtration rate (eGFR), according to the CKD-EPI formula predicted death in both sexes. Lymphocytopenia was an independent predictor of death in women only, while thrombocytopenia and elevated plasma glucose concentration were predictors of death in men only. CONCLUSIONS: In patients with diabetes admitted for COVID-19, female sex was associated with lower incidence of early severe outcomes, but did not influence the overall in-hospital mortality, suggesting that diabetes mitigates the female protection from COVID-19 severity. Sex-associated biological determinants may be useful to optimize COVID-19 prevention and management in women and men.


Subject(s)
COVID-19/diagnosis , COVID-19/epidemiology , Diabetes Mellitus/diagnosis , Diabetes Mellitus/epidemiology , Sex Characteristics , Aged , Aged, 80 and over , COVID-19/complications , COVID-19/therapy , Diabetes Complications/diagnosis , Diabetes Complications/epidemiology , Female , France/epidemiology , Hospital Mortality , Hospitalization/statistics & numerical data , Humans , Incidence , Inpatients , Intensive Care Units/statistics & numerical data , Male , Middle Aged , Prognosis , Respiration, Artificial/statistics & numerical data , Retrospective Studies , Risk Factors , SARS-CoV-2/physiology , Severity of Illness Index
16.
Rev Med Virol ; 31(6): e2288, 2021 11.
Article in English | MEDLINE | ID: covidwho-1384306

ABSTRACT

SARS Coronavirus-2 is one of the most widespread viruses globally during the 21st century, whose severity and ability to cause severe pneumonia and death vary. We performed a comprehensive systematic review of all studies that met our standardised criteria and then extracted data on the age, symptoms, and different treatments of Covid-19 patients and the prognosis of this disease during follow-up. Cases in this study were divided according to severity and death status and meta-analysed separately using raw mean and single proportion methods. We included 171 complete studies including 62,909 confirmed cases of Covid-19, of which 148 studies were meta-analysed. Symptoms clearly emerged in an escalating manner from mild-moderate symptoms, pneumonia, severe-critical to the group of non-survivors. Hypertension (Pooled proportion (PP): 0.48 [95% Confident interval (CI): 0.35-0.61]), diabetes (PP: 0.23 [95% CI: 0.16-0.33]) and smoking (PP: 0.12 [95% CI: 0.03-0.38]) were highest regarding pre-infection comorbidities in the non-survivor group. While acute respiratory distress syndrome (PP: 0.49 [95% CI: 0.29-0.78]), (PP: 0.63 [95% CI: 0.34-0.97]) remained one of the most common complications in the severe and death group respectively. Bilateral ground-glass opacification (PP: 0.68 [95% CI: 0.59-0.75]) was the most visible radiological image. The mortality rates estimated (PP: 0.11 [95% CI: 0.06-0.19]), (PP: 0.03 [95% CI: 0.01-0.05]), and (PP: 0.01 [95% CI: 0-0.3]) in severe-critical, pneumonia and mild-moderate groups respectively. This study can serve as a high evidence guideline for different clinical presentations of Covid-19, graded from mild to severe, and for special forms like pneumonia and death groups.


Subject(s)
COVID-19/pathology , Cough/pathology , Dyspnea/pathology , Fatigue/pathology , Fever/pathology , SARS-CoV-2/pathogenicity , Antiviral Agents/therapeutic use , COVID-19/drug therapy , COVID-19/mortality , COVID-19/virology , Comorbidity , Cough/drug therapy , Cough/mortality , Cough/virology , Diabetes Mellitus/diagnosis , Diabetes Mellitus/physiopathology , Dyspnea/drug therapy , Dyspnea/mortality , Dyspnea/virology , Fatigue/drug therapy , Fatigue/mortality , Fatigue/virology , Fever/drug therapy , Fever/mortality , Fever/virology , Humans , Hypertension/diagnosis , Hypertension/physiopathology , Immunologic Factors/therapeutic use , Prognosis , Respiratory Distress Syndrome/diagnosis , Respiratory Distress Syndrome/physiopathology , Severity of Illness Index , Smoking/physiopathology , Survival Analysis
17.
Expert Rev Proteomics ; 18(8): 707-717, 2021 08.
Article in English | MEDLINE | ID: covidwho-1380972

ABSTRACT

INTRODUCTION: Active matrix metalloproteinase (aMMP)-8 utilized in point-of-care testing (POCT) is regarded as a potential biomarker for periodontal and peri-implant diseases. Various host and microbial factors eventually influence the expression, degranulation, levels and activation of aMMP-8. The type of oral fluids (saliva, mouthrinse, gingival crevicular, and peri-implant sulcular fluids [GCF/PISF], respectively) affect the analysis. AREAS COVERED: With this background, we aimed to review here the recent studies on practical, inexpensive, noninvasive and quantitative mouthrinse and GCF/PISF chair-side POCT lateral flow aMMP-8 immunoassays (PerioSafe and ImplantSafe/ORALyzer) and how they help to detect, predict, monitor the course, treatment and prevention of periodontitis and peri-implantitis. The correlations of aMMP-8 POCT to other independent and catalytic activity assays of MMP-8 are also addressed. EXPERT OPINION: The mouthrinse aMMP-8 POCT can also detect prediabetes/diabetes and tissue destructive oral side-effects due to the head and neck cancers' radiotherapy. Chlorhexidine and doxycycline can inhibit collagenolytic human neutrophil and GCF aMMP-8. Furthermore, by a set of case-series we demonstrate the potential of mouthrinse aMMP-8 POCT to real-time/online detect periodontitis as a potential risk disease for coronavirus disease 2019 (COVID-19). The clinical interdisciplinary utilization of aMMP-8 POCT requires additional oral, medical, and interdisciplinary studies.


Subject(s)
COVID-19/enzymology , Matrix Metalloproteinase 8/metabolism , Pandemics , SARS-CoV-2 , Biomarkers/analysis , Biomarkers/metabolism , COVID-19/complications , COVID-19/drug therapy , Diabetes Mellitus/diagnosis , Diabetes Mellitus/enzymology , Doxycycline/therapeutic use , Humans , Immunoassay/methods , Matrix Metalloproteinase 8/analysis , Mouthwashes , Oral Hygiene , Peri-Implantitis/diagnosis , Peri-Implantitis/enzymology , Periodontitis/complications , Periodontitis/diagnosis , Periodontitis/enzymology , Point-of-Care Testing , Radiotherapy/adverse effects , Risk Factors
18.
Endocrinol Metab (Seoul) ; 36(4): 800-809, 2021 08.
Article in English | MEDLINE | ID: covidwho-1367944

ABSTRACT

BACKGROUND: Based on recent evidence on the importance of the presence of diabetes mellitus (DM) and fibrosis-4 (FIB-4) index in coronavirus disease 2019 (COVID-19) mortality, we analyzed whether these factors could additively predict such mortality. METHODS: This multicenter observational study included 1,019 adult inpatients admitted to university hospitals in Daegu. The demographic and laboratory findings, mortality, prevalence of severe disease, and duration of quarantine were compared between patients with and without DM and/or a high FIB-4 index. The mortality risk and corresponding hazard ratio (HR) were analyzed using the Kaplan-Meier method and Cox proportional hazard models. RESULTS: The patients with DM (n=217) exhibited significantly higher FIB-4 index and mortality compared to those without DM. Although DM (HR, 2.66; 95% confidence interval [CI], 1.63 to 4.33) and a high FIB-4 index (HR, 4.20; 95% CI, 2.21 to 7.99) were separately identified as risk factors for COVID-19 mortality, the patients with both DM and high FIB-4 index had a significantly higher mortality (HR, 9.54; 95% CI, 4.11 to 22.15). Higher FIB-4 indices were associated with higher mortality regardless of DM. A high FIB-4 index with DM was more significantly associated with a severe clinical course with mortality (odds ratio, 11.24; 95% CI, 5.90 to 21.41) than a low FIB-4 index without DM, followed by a high FIB-4 index alone and DM alone. The duration of quarantine and hospital stay also tended to be longer in those with both DM and high FIB-4 index. CONCLUSION: Both DM and high FIB-4 index are independent and additive risk factors for COVID-19 mortality.


Subject(s)
COVID-19/diagnosis , COVID-19/mortality , Diabetes Mellitus/diagnosis , Diabetes Mellitus/mortality , Liver Cirrhosis/diagnosis , Liver Cirrhosis/mortality , Adult , Aged , COVID-19/therapy , Diabetes Mellitus/therapy , Female , Humans , Liver Cirrhosis/therapy , Male , Middle Aged , Retrospective Studies , Risk Factors , Treatment Outcome
19.
Cell Metab ; 33(8): 1565-1576.e5, 2021 08 03.
Article in English | MEDLINE | ID: covidwho-1343160

ABSTRACT

Emerging evidence points toward an intricate relationship between the pandemic of coronavirus disease 2019 (COVID-19) and diabetes. While preexisting diabetes is associated with severe COVID-19, it is unclear whether COVID-19 severity is a cause or consequence of diabetes. To mechanistically link COVID-19 to diabetes, we tested whether insulin-producing pancreatic ß cells can be infected by SARS-CoV-2 and cause ß cell depletion. We found that the SARS-CoV-2 receptor, ACE2, and related entry factors (TMPRSS2, NRP1, and TRFC) are expressed in ß cells, with selectively high expression of NRP1. We discovered that SARS-CoV-2 infects human pancreatic ß cells in patients who succumbed to COVID-19 and selectively infects human islet ß cells in vitro. We demonstrated that SARS-CoV-2 infection attenuates pancreatic insulin levels and secretion and induces ß cell apoptosis, each rescued by NRP1 inhibition. Phosphoproteomic pathway analysis of infected islets indicates apoptotic ß cell signaling, similar to that observed in type 1 diabetes (T1D). In summary, our study shows SARS-CoV-2 can directly induce ß cell killing.


Subject(s)
COVID-19/virology , Diabetes Mellitus/virology , Insulin-Secreting Cells/virology , Neuropilin-1/metabolism , Receptors, Virus/metabolism , SARS-CoV-2/pathogenicity , Virus Internalization , A549 Cells , Adult , Aged , Aged, 80 and over , Angiotensin-Converting Enzyme 2/metabolism , Antigens, CD/metabolism , Apoptosis , Apoptosis Regulatory Proteins/metabolism , COVID-19/complications , COVID-19/diagnosis , Case-Control Studies , Diabetes Mellitus/diagnosis , Diabetes Mellitus/metabolism , Female , Host-Pathogen Interactions , Humans , Insulin/metabolism , Insulin-Secreting Cells/metabolism , Male , Middle Aged , Receptors, Transferrin/metabolism , SARS-CoV-2/metabolism , Serine Endopeptidases/metabolism , Spike Glycoprotein, Coronavirus/metabolism
20.
Metabolism ; 123: 154845, 2021 10.
Article in English | MEDLINE | ID: covidwho-1340768

ABSTRACT

PURPOSE: Individuals with diabetes/stress hyperglycemia carry an increased risk for adverse clinical outcome in case of SARS-CoV-2 infection. The purpose of this study was to evaluate whether this risk is, at least in part, modulated by an increase of thromboembolic complications. METHODS: We prospectively followed 180 hospitalized patients with confirmed COVID-19 pneumonia admitted to the Internal Medicine Units of San Raffaele Hospital. Data from 11 out of 180 patients were considered incomplete and excluded from the analysis. We analysed inflammation, tissue damage biomarkers, hemostatic parameters, thrombotic events (TEs) and clinical outcome according to the presence of diabetes/stress hyperglycemia. RESULTS: Among 169 patients, 51 (30.2%) had diabetes/stress hyperglycemia. Diabetes/stress hyperglycemia and fasting blood glucose (FBG) were associated with increased inflammation and tissue damage circulating markers, higher D-dimer levels, increased prothrombin time and lower antithrombin III activity. Forty-eight venous and 10 arterial TEs were identified in 49 (29%) patients. Diabetes/stress hyperglycemia (HR 2.71, p = 0.001), fasting blood glucose (HR 4.32, p < 0.001) and glucose variability (HR 1.6, p < 0.009) were all associated with an increased risk of thromboembolic complication. TEs significantly increased the risk for an adverse clinical outcome only in the presence of diabetes/stress hyperglycemia (HR 3.05, p = 0.010) or fasting blood glucose ≥7 mmol/L (HR 3.07, p = 0.015). CONCLUSIONS: Thromboembolism risk is higher among patients with diabetes/stress hyperglycemia and COVID-19 pneumonia and is associated to poor clinical outcome. In case of SARS-Cov-2 infection patients with diabetes/stress hyperglycemia could be considered for a more intensive prophylactic anticoagulation regimen.


Subject(s)
COVID-19/epidemiology , Diabetes Mellitus/epidemiology , Hyperglycemia/epidemiology , Thromboembolism/etiology , Aged , Aged, 80 and over , COVID-19/complications , COVID-19/diagnosis , COVID-19/therapy , Diabetes Complications/diagnosis , Diabetes Complications/epidemiology , Diabetes Complications/therapy , Diabetes Mellitus/blood , Diabetes Mellitus/diagnosis , Diabetes Mellitus/therapy , Female , Follow-Up Studies , Hospitalization/statistics & numerical data , Humans , Hyperglycemia/diagnosis , Hyperglycemia/etiology , Hyperglycemia/therapy , Inflammation/complications , Inflammation/diagnosis , Inflammation/epidemiology , Inflammation/therapy , Italy/epidemiology , Male , Middle Aged , Mortality , Prognosis , Risk Factors , Stress, Psychological/complications , Stress, Psychological/diagnosis , Stress, Psychological/epidemiology , Thromboembolism/diagnosis , Thromboembolism/epidemiology , Treatment Outcome
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