Time series of diabetes attributable mortality from 2008 to 2017

PURPOSE

Diabetes is a growing health problem. The aim of this study was to capture time trends in mortality associated with diabetes.

METHODS

The mortality database of the Veneto region (Italy) includes both the underlying causes of death, and all the diseases mentioned in the death certificate. The annual percent change (APC) in age-standardized rates from 2008 to 2017 was computed by the Joinpoint Regression Program.

RESULTS

Overall 453,972 deaths (56,074 with mention of diabetes) were observed among subjects aged ≥ 40 years. Mortality rates declined for diabetes as the underlying cause of death and from diabetes-related circulatory diseases. The latter declined especially in females - 4.4 (CI 95% - 5.3/- 3.4), while in males the APC was - 2.8 (CI 95% - 4.0/- 1.6).

CONCLUSION

We observed a significant reduction in mortality during the period 2008-2017 in diabetes either as underlying cause of death or when all mentions of diabetes in the death certificate were considered.

Prevalence and impact of diabetes in hospitalized COVID-19 patients: A systematic review and meta-analysis

BACKGROUND

Diabetes is a cardiometabolic comorbidity that may predispose COVID-19 patients to worse clinical outcomes. This study sought to determine the prevalence of diabetes in hospitalized COVID-19 patients and investigate the association of diabetes severe COVID-19, rate of acute respiratory distress syndrome (ARDS), mortality, and need for mechanical ventilation by performing a systematic review and meta-analysis.

METHODS

Individual studies were selected using a defined search strategy, including results up until July 2021 from PubMed, Embase, and Cochrane Central Register of Controlled Trials. A random-effects meta-analysis was performed to estimate the proportions and level of association of diabetes with clinical outcomes in hospitalized COVID-19 patients. Forest plots were generated to retrieve the odds ratios (OR), and the quality and risk assessment was performed for all studies included in the meta-analysis.

RESULTS

The total number of patients included in this study was 10 648, of whom 3112 had diabetes (29.23%). The overall pooled estimate of prevalence of diabetes in the meta-analysis cohort was 31% (95% CI, 0.25-0.38; z = 16.09, P < .0001). Diabetes significantly increased the odds of severe COVID-19 (OR 3.39; 95% CI, 2.14-5.37; P < .0001), ARDS (OR 2.55; 95% CI, 1.74-3.75; P = <.0001), in-hospital mortality (OR 2.44; 95% CI, 1.93-3.09; P < .0001), and mechanical ventilation (OR 3.03; 95% CI, 2.17-4.22; P < .0001).

CONCLUSIONS

Our meta-analysis demonstrates that diabetes is significantly associated with increased odds of severe COVID-19, increased ARDS rate, mortality, and need for mechanical ventilation in hospitalized patients. We also estimated an overall pooled prevalence of diabetes of 31% in hospitalized COVID-19 patients.

Prediabetes and risk of mortality, diabetes-related complications and comorbidities: umbrella review of meta-analyses of prospective studies

AIMS/HYPOTHESIS

The term prediabetes is used for individuals who have impaired glucose metabolism whose glucose or HbA_1c levels are not yet high enough to be diagnosed as diabetes. Prediabetes may already be associated with an increased risk of chronic 'diabetes-related' complications. This umbrella review aimed to provide a systematic overview of the available evidence from meta-analyses of prospective observational studies on the associations between prediabetes and incident diabetes-related complications in adults and to evaluate their strength and certainty.

METHODS

For this umbrella review, systematic reviews with meta-analyses reporting summary risk estimates for the associations between prediabetes (based on fasting or 2 h postload glucose or on HbA_1c) and incidence of diabetes-related complications, comorbidities and mortality risk were included. PubMed, Web of Science, the Cochrane Library and Epistemonikos were searched up to 17 June 2021. Summary risk estimates were recalculated using a random effects model. The certainty of evidence was evaluated by applying the GRADE tool. This study is registered with PROSPERO, CRD42020153227.

RESULTS

Ninety-five meta-analyses from 16 publications were identified. In the general population, prediabetes was associated with a 6-101% increased risk for all-cause mortality and the incidence of cardiovascular outcomes, CHD, stroke, heart failure, atrial fibrillation and chronic kidney disease, as well as total cancer, total liver cancer, hepatocellular carcinoma, breast cancer and all-cause dementia with moderate certainty of evidence. No associations between prediabetes and incident depressive symptoms and cognitive impairment were observed (with low or very low certainty of evidence). The association with all-cause mortality was stronger for prediabetes defined by impaired glucose tolerance than for prediabetes defined by HbA_1c.

CONCLUSIONS/INTERPRETATION

Prediabetes was positively associated with risk of all-cause mortality and the incidence of cardiovascular outcomes, CHD, stroke, chronic kidney disease, cancer and dementia. Further high-quality studies, particularly on HbA_1c-defined prediabetes and other relevant health outcomes (e. g. neuropathy) are required to support the evidence.

The association between trajectories of risk factors and risk of cardiovascular disease or mortality among patients with diabetes or hypertension: A systematic review

Introduction

Cardiometabolic risk factors and renal function are monitored regularly for patients with diabetes mellitus (DM)/ hypertension (HT). In addition to risk factor levels at a single time point, their trajectory (changes over time) can also be differentially related to the risk of cardiovascular diseases (CVD) and mortality. This study aimed to systematically examine the evidence regarding the association between risk factor trajectories and risk of CVD/mortality in patients with DM/HT.

Method

PubMed, MEDLINE, and Embase were searched for articles from January 1963 to April 2021. Inclusion criteria: studies that 1) analyzed trajectories of risk factors including haemoglobin A1c (HbA1c), blood pressure, estimated glomerular filtration rate (eGFR), body mass index (BMI), and blood lipids; 2) were performed in the DM/HT population and, 3) included risk of CVD/mortality as outcomes. Study quality was assessed using the Newcastle-Ottawa quality assessment scale.

Results

A total of 22,099 articles were identified. After screening by title and abstract, 22,027 articles were excluded by irrelevant outcomes, exposure, population, or type of articles. Following full-text screening, 11 articles investigating the trajectories of HbA1c (N = 7), systolic blood pressure (SBP) (N = 3), and eGFR (N = 1) were included for data extraction and analysis. No studies were identified examining the association of BMI or lipid trajectories with CVD/mortality. All included studies were of good quality based on the NOS criteria. In general, stable trajectories within optimal ranges of the risk factors (HbA1c: <7%, SBP: 120-139mmHg, eGFR: >60mL/min/1.73m²) had the lowest CVD/mortality risk compared to an increasing HbA1c trajectory (from 8% to 10%), an increasing SBP trajectory (from 120–139 to ≥140mmHg), or a decreasing eGFR trajectory (from 90 to 70mL/min/1.73m²).

Conclusion

A relatively stable and well-controlled trajectory for cardiometabolic risk factors was associated with the lowest risk of CVD/mortality. Risk factor trajectories have important clinical implications in addition to single time point measurements. More attention should be given to patients with suboptimal control and those with unstable trends of cardiometabolic risk factors.

Can Overnutrition Lead to Wasting?-The Paradox of Diabetes Mellitus in End-Stage Renal Disease Treated with Maintenance Hemodialysis

Background: The population of end-stage renal disease (ESRD) patients with diabetes mellitus (DM) may be at increased risk of protein energy wasting (PEW). The aim of the study was to investigate the impact of DM on selected indicators of PEW in the ESRD population that was undergoing maintenance hemodialysis (MHD). Methods: A total of 515 MHD patients were divided into two subgroups with and without DM. The evaluation of diet composition, Charlson Comorbidity Index (CCI), SGA, and laboratory and BIS analyses were performed. All-cause and cardiovascular mortality was recorded. Results: DM patients had lower albumin (3.93 (3.61–4.20) vs. 4.10 (3.80–4.30) g/dL, p < 0.01), total cholesterol (158 (133–196) vs. 180 (148–206) mg/dL, p < 0.01), and creatinine (6.34 (5.08–7.33) vs. 7.12 (5.70–8.51) mg/dL, p < 0.05). SGA score (12.0 (10.0–15.0) vs. 11.0 (9.0–13.0) points, p < 0.001), BMI (27.9 (24.4–31.8) vs. 25.6 (22.9–28.8) kg/m², p < 0.001), fat tissue index (15.0 (11.4–19.6) vs. 12.8 (9.6–16.0) %, p < 0.001), and overhydration (2.1 (1.2–4.1) vs. 1.8 (0.7, 2.7) L, p < 0.001) were higher in the DM group. Increased morbidity, reflected in the CCI and mortality—both all-cause and cardiovascular—were observed in DM patients. Conclusions: Hemodialysis recipients with DM experience overnutrition with a paradoxically higher predisposition to PEW, expressed by a higher SGA score and lower serum markers of nutrition. This population is also more comorbid and is at higher risk of death, including from cardiovascular causes.

Racial differences in all-cause mortality and future complications among people with diabetes: a systematic review and meta-analysis of data from more than 2.4 million individuals

AIMS/HYPOTHESIS

The aim of this work was to quantify racial/ethnic differences in risk for future diabetic complications and all-cause mortality by performing a meta-analysis of prospective studies.

METHODS

A systematic search in PubMed and EMBASE was performed from inception to May 2021. Prospective cohort studies that reported HRs and associated 95% CIs of diabetes complications and all-cause mortality among racial/ethnic groups, with White people as the reference group, were included. Study characteristics and HR estimates were extracted from each study. Estimates were pooled using random-effects inverse-variance model with the Hartung-Knapp-Sidik-Jonkman variance estimator.

RESULTS

A total of 23 studies were included, comprising 2,416,516 individuals diagnosed with diabetes (White 59.3%, Black 11.2%, Asian 1.3%, Hispanic-American 2.4%, Native American 0.2%, East Asian 1.9%, South Asian 0.8%, Pacific Islander 2.3%, Māori 2.4% and others 18.2%). Compared with White individuals with diabetes, individuals of Māori ethnicity were at higher risk for all-cause mortality (HR 1.88 [95% CI 1.61, 2.21]; I² = 7.1%), Hispanic-American individuals had a significantly lower risk for CVD (HR 0.66 [95% CI 0.53, 0.81]; I² = 0%) and Black individuals had higher risk for end-stage renal disease (HR 1.54 [95% CI 1.05, 2.24]; I² = 95.4%). No significant higher risk for diabetes complications was found in other racial/ethnic groups relative to White people.

CONCLUSIONS/INTERPRETATION

Racial/ethnic differences exist in the risk for future diabetic complications and all-cause mortality. Our results support the use of such categories for international diabetes clinical guideline recommendations until better predictors become available. Efforts to identify high-risk groups and to better control cardiovascular risk factors across ethnically diverse populations are therefore needed.

REGISTRATION

PROSPERO registration ID CRD42021239274.

COVID-19 associated mucormycosis: A Descriptive Multisite Study from India

BACKGROUND AND AIMS

Mucormycosis is an invasive fungal infection and carries a significant morbidity and mortality. A number of cases of mucormycosis have been reported in association with COVID-19. In this study, a consortium of clinicians from various parts of India studied clinical profile of COVID-19 associated mucormycosis (CAM) and this analysis is presented here.

METHODS

Investigators from multiple sites in India were involved in this study. Clinical details included the treatment and severity of COVID-19, associated morbidities, as well as the diagnosis, treatment and prognosis of mucormycosis. These data were collected using google spreadsheet at one centre. Descriptive analysis was done.

RESULTS

There were 115 patients with CAM. Importantly, all patients had received corticosteroids. Diabetes was present in 85.2% of patients and 13.9% of patients had newly detected diabetes. The most common site of involvement was rhino-orbital. Mortality occurred in 25 (21.7%) patients. On logistic regression analysis, CT scan-based score for severity of lung involvement was associated with mortality.

CONCLUSION

Universal administration of corticosteroids in our patients is notable. A large majority of patients had diabetes, while mortality was seen in ∼1/5th of patients, lower as compared to recently published data.

Predictors of mortality among patients with type 2 diabetes in Jordan

BACKGROUND

Diabetes Mellitus (DM) is a common metabolic disease associated with increased risk of mortality.

OBJECTIVE

The aim of this study was to examine predictors of mortality among patients with type 2 diabetes in the north of Jordan.

METHODS

Electronic data files for diabetes patients admitted between the period of 2014-2018 at a tertiary center in the north of Jordan were reviewed. Patient's characteristics, clinical and laboratory data, use of medications and mortality rate were collected.

RESULTS

Mean age of patients (n = 957) was 60.99 ± 0.37 (mean ± sem). Most of patients had multiple risk factors and underlying cardiovascular diseases (CVDs). Mortality rate was 10.1%. Univariate predictors of mortality included age, chronic kidney disease (CKD), acute kidney injury, hypertension, heart failure (HF), coronary artery disease, venous thromboembolism (VTE), stroke, atrial fibrillation (AF), and chronic obstructive pulmonary disease (COPD). As the number of CVDs increases, mortality rate also increases (Odd ratio 2.0, p < 0.0001). Use of insulin, aspirin, ACEi/ARBS, beta blockers, and diuretics were also associated with mortality. Fasting glucose and percentage of glycated hemoglobin were not associated with mortality. By multivariable logistic regression analysis adjusting for confounders and collinearity; age, HF, AF, COPD, VTE, and CKD were associated with mortality.

CONCLUSION

Key risk factors of mortality are CVDs and CKD indicating that the primary step of management should focus on optimizing risk factors to prevent diabetes complications and death.

Does diabetes mellitus mitigate the gender gap in COVID-19 mortality?

In this SARS-COV2-pandemic, diabetes mellitus (DM) soon emerged as one of the most prominent risk factors for a severe course of corona virus disease-2019 (COVID-19) and increased mortality due to hyperglycemia/insulin resistance, obesity, inflammation, altered immune status, and cardiovascular complications. In general, men are at a higher risk of severe or fatal COVID-19 disease irrespective of age, region and despite comparable infection rates in both sexes. In COVID-19, there is also a male predominance among hospitalized patients with diabetes, however, overall, data among patients with diabetes are ambiguous so far. Of note, similar to cardiovascular complications, women with type 2 diabetes (DM2) appear to lose their biological female advantage resulting in comparable death rates to those of men. The complex interplay of biological and behavioral factors, which may put men at greater risk of a severe or fatal course of COVID-19, and gender-related psychosocial factors, which may cause disadvantage to women concerning the infection rates, might explain why sex-disaggregated data among infected patients with diabetes are conflicting. Better knowledge on biological factors leading to functionally different immune responses and of gender-sensitive sociocultural determinants of COVID-19 infection rates may help to optimize prevention and management in the high-risk groups of men and women with diabetes.

Improvement of glycemic control in type 2 diabetes: A systematic review and meta-analysis of randomized controlled trials

AIM

Different guidelines provide similar, but not identical, therapeutic targets for HbA1c in type 2 diabetes. These targets can also depend from the different pharmacological strategies adopted for intensifying glycemic control.

DATA SYNTHESIS

This meta-analysis includes randomized trials adopting any pharmacological regimen for intensifying glycemic control in T2DM (versus standard of care/placebo), with a trial duration ≥2 years and a between-group HbA1c difference≥0.5%. The primary outcome was to assess the effects of the improvement of glycemic control on major cardiovascular events (MACE), ocular and renal complications, and severe hypoglycemia. Mantel-Haenszel odds ratios (MH-OR) with 95% Confidence Intervals were calculated for all the outcomes considered. We included 13 trials fulfilling the inclusion criteria. The improvement of glycemic control was associated with a lower risk of MACE (MH-OR:0.89 [95%CI 0.85-0.94]) and renal adverse events (MH-OR 0.73 [0.65-0.82]), but not all-cause mortality (MH-OR 0.95 [0.88-1.01]) and ocular adverse complications (MH-OR 0.94 [0.72-1.22]). For glucose-lowering drugs inducing hypoglycemia, a protective effect on the risk of microvascular complications, but not of MACE and all-cause mortality, was observed only for HbA1c ≤ 48 mmol/mol, but with higher risk of severe hypoglycaemia (MH-OR 2.72 [1.79-4.13]). Drugs not inducing hypoglycaemia were associated with a reduction of MACE, renal adverse events, and all-cause mortality, for HbA1c< 7% (no data for lower targets).

CONCLUSIONS

The present meta-analysis show that the improvement of glycemic control with drugs not inducing hypoglycemia is associated with a reduction in the risk of long-term chronic vascular and renal complications, and all-cause mortality.

The triumvirate: why hypertension, obesity, and diabetes are risk factors for adverse effects in patients with COVID-19

The outbreak of coronavirus disease 2019 (COVID-19) caused by a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a pandemic. The cellular receptor for SARS-CoV-2 entry is the angiotensin-converting enzyme 2, a membrane-bound homolog of angiotensin-converting enzyme. Henceforth, this has brought the attention of the scientific community to study the interaction between COVID-19 and the renin-angiotensin system (RAS), as well as RAS inhibitors. However, these inhibitors are commonly used to treat hypertension, chronic kidney disorder, and diabetes. Obesity is a known risk factor for heart disease, diabetes, and hypertension, whereas diabetes and hypertension may be indirectly related to each other through the effects of obesity. Furthermore, people with hypertension, obesity, diabetes, and other related complications like cardiovascular and kidney diseases have a higher risk of severe COVID-19 infection than the general population and usually exhibit poor prognosis. This severity could be due to systemic inflammation and compromised immune response and RAS associated with these comorbid conditions. Therefore, there is an urgent need to develop evidence-based treatment methods that do not affect the severity of COVID-19 infection and effectively manage these chronic diseases in people with COVID-19.

Risk phenotypes of diabetes and association with COVID-19 severity and death: a living systematic review and meta-analysis

AIMS/HYPOTHESIS

Diabetes has been identified as a risk factor for poor prognosis of coronavirus disease-2019 (COVID-19). The aim of this study is to identify high-risk phenotypes of diabetes associated with COVID-19 severity and death.

METHODS

This is the first edition of a living systematic review and meta-analysis on observational studies investigating phenotypes in individuals with diabetes and COVID-19-related death and severity. Four different databases were searched up to 10 October 2020. We used a random effects meta-analysis to calculate summary relative risks (SRR) with 95% CI. The certainty of evidence was evaluated by the GRADE tool.

RESULTS

A total of 22 articles, including 17,687 individuals, met our inclusion criteria. For COVID-19-related death among individuals with diabetes and COVID-19, there was high to moderate certainty of evidence for associations (SRR [95% CI]) between male sex (1.28 [1.02, 1.61], n = 10 studies), older age (>65 years: 3.49 [1.82, 6.69], n = 6 studies), pre-existing comorbidities (cardiovascular disease: 1.56 [1.09, 2.24], n = 8 studies; chronic kidney disease: 1.93 [1.28, 2.90], n = 6 studies; chronic obstructive pulmonary disease: 1.40 [1.21, 1.62], n = 5 studies), diabetes treatment (insulin use: 1.75 [1.01, 3.03], n = 5 studies; metformin use: 0.50 [0.28, 0.90], n = 4 studies) and blood glucose at admission (≥11 mmol/l: 8.60 [2.25, 32.83], n = 2 studies). Similar, but generally weaker and less precise associations were observed between risk phenotypes of diabetes and severity of COVID-19.

CONCLUSIONS/INTERPRETATION

Individuals with a more severe course of diabetes have a poorer prognosis of COVID-19 compared with individuals with a milder course of disease. To further strengthen the evidence, more studies on this topic that account for potential confounders are warranted.

REGISTRATION

PROSPERO registration ID CRD42020193692.

Could Exogenous Insulin Ameliorate the Metabolic Dysfunction Induced by Glucocorticoids and COVID-19?

The finding that high-dose dexamethasone improves survival in those requiring critical care due to COVID-19 will mean much greater usage of glucocorticoids in the subsequent waves of coronavirus infection. Furthermore, the consistent finding of adverse outcomes from COVID-19 in individuals with obesity, hypertension and diabetes has focussed attention on the metabolic dysfunction that may arise with critical illness. The SARS coronavirus itself may promote relative insulin deficiency, ketogenesis and hyperglycaemia in susceptible individuals. In conjunction with prolonged critical care, these components will promote a catabolic state. Insulin infusion is the mainstay of therapy for treatment of hyperglycaemia in acute illness but what is the effect of insulin on the admixture of glucocorticoids and COVID-19? This article reviews the evidence for the effect of insulin on clinical outcomes and intermediary metabolism in critical illness.

Glycemic and lipid variability for predicting complications and mortality in diabetes mellitus using machine learning

INTRODUCTION

Recent studies have reported that HbA1c and lipid variability is useful for risk stratification in diabetes mellitus. The present study evaluated the predictive value of the baseline, subsequent mean of at least three measurements and variability of HbA1c and lipids for adverse outcomes.

METHODS

This retrospective cohort study consists of type 1 and type 2 diabetic patients who were prescribed insulin at outpatient clinics of Hong Kong public hospitals, from 1st January to 31st December 2009. Standard deviation (SD) and coefficient of variation were used to measure the variability of HbA1c, total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglyceride. The primary outcome is all-cause mortality. Secondary outcomes were diabetes-related complications.

RESULT

The study consists of 25,186 patients (mean age = 63.0, interquartile range [IQR] of age = 15.1 years, male = 50%). HbA1c and lipid value and variability were significant predictors of all-cause mortality. Higher HbA1c and lipid variability measures were associated with increased risks of neurological, ophthalmological and renal complications, as well as incident dementia, osteoporosis, peripheral vascular disease, ischemic heart disease, atrial fibrillation and heart failure (p <  0.05). Significant association was found between hypoglycemic frequency (p <  0.0001), HbA1c (p <  0.0001) and lipid variability against baseline neutrophil-lymphocyte ratio (NLR).

CONCLUSION

Raised variability in HbA1c and lipid parameters are associated with an elevated risk in both diabetic complications and all-cause mortality. The association between hypoglycemic frequency, baseline NLR, and both HbA1c and lipid variability implicate a role for inflammation in mediating adverse outcomes in diabetes, but this should be explored further in future studies.

The doubled burden of diabetic bone disease: hip fracture and post-hip fracture mortality

OBJECTIVE

Patients with diabetes have an increased risk of osteoporosis and shorter life expectancy. Hip fracture (HF) is the most serious consequence of osteoporosis and is associated with increased mortality risk. We aimed to assess the association of antidiabetic medications with HF and the post-hip fracture mortality risk among diabetic patients ≥50 years.

DESIGN

In this nationwide case-control study 53 992 HF cases and 112 144 age-, sex- and region-matched non-hip fracture controls were analyzed. A cohort of hip-fractured diabetic patients were followed-up for an all-cause mortality.

METHODS

We defined three groups of diabetic patients based on a prescription of antidiabetic medications: group 1 treated with insulin monotherapy (G1DM), group 2 (G2DM) treated with blood glucose-lowering drugs (BGLD) only, group 3 on a combined BGLD and insulin therapy (G3DM). We applied logistic regression and Cox regression.

RESULTS

We identified 2757 G1DM patients, 15 310 G2DM patients, 3775 G3DM patients and 144 294 patients without any antidiabetic treatment. All three groups of diabetic patients had increased odds of HF compared to controls. G1DM patients aged 50-64 years (aOR: 4.80, 95% CI: 3.22-7.17) and G3DM patients (aOR: 1.39, 95% CI: 1.02-1.88) showed the highest HF odds, whereas G2DM patients had 18% decrease in HF odds than their non-diabetic controls (aOR: 0.82, 95% CI: 0.69-0.99). All diabetic patients had increased post-hip fracture mortality risk compared to non-diabetic controls. The highest mortality hazard was observed in G1DM patients, being greater for women than men (HR: 1.71, 95% CI: 1.55-1.89 and HR: 1.44, 95% CI: 1.27-1.64, respectively).

CONCLUSIONS

Antidiabetic medications increase the probability of HF. Diabetic patients, who sustained HF have a higher mortality risk than non-diabetic patients.

Colchicine and mortality in patients with coronavirus disease 2019 (COVID-19) pneumonia: A systematic review, meta-analysis, and meta-regression

Objective

This systematic review, with meta-analysis and meta-regression aims to evaluate the effect of colchicine administration on mortality in patients with coronavirus disease 2019 (COVID-19) and factors affecting the association.

Methods

A systematic literature search using the PubMed, Scopus, and Embase databases were performed from inception of databases up until 3 March 2021. We included studies that fulfill all of the following criteria: 1) observational studies or randomized controlled trials (RCTs) that report COVID-19 patients, 2) reporting colchicine use, and 3) mortality within 30 days. There was no restriction on the age, inpatients or outpatients setting, and severity of diseases. The intervention was colchicine administration during treatment for COVID-19. The control was receiving placebo or standard of care. The outcome was mortality and the pooled effect estimate was reported as odds ratio (OR). Random-effects restricted maximum likelihood meta-regression was performed to evaluate factors affecting the pooled effect estimate.

Results

Eight studies comprising of 5530 patients were included in this systematic review and meta-analysis. There were three RCTs and five observational studies. Pooled analysis showed that colchicine was associated with lower mortality in patients with COVID-19 (OR 0.47 [0.31, 0.72], p = 0.001; I²: 30.9, p = 0.181). Meta-regression analysis showed that the association between colchicine and mortality was reduced by increasing age (OR 0.92 [0.85, 1.00], p = 0.05), but not gender (reference: male, p = 0.999), diabetes (p = 0.376), hypertension (p = 0.133), and CAD (p = 0.354).

Conclusion

This meta-analysis indicates that colchicine may reduce mortality in patients with COVID-19. Meta-regression analysis showed that the benefit was reduced as age increases.

PROSPERO: CRD42021240609.

Predictors of hospital discharge and mortality in patients with diabetes and COVID-19: updated results from the nationwide CORONADO study

AIMS/HYPOTHESIS

This is an update of the results from the previous report of the CORONADO (Coronavirus SARS-CoV-2 and Diabetes Outcomes) study, which aims to describe the outcomes and prognostic factors in patients with diabetes hospitalised for coronavirus disease-2019 (COVID-19).

METHODS

The CORONADO initiative is a French nationwide multicentre study of patients with diabetes hospitalised for COVID-19 with a 28-day follow-up. The patients were screened after hospital admission from 10 March to 10 April 2020. We mainly focused on hospital discharge and death within 28 days.

RESULTS

We included 2796 participants: 63.7% men, mean age 69.7 ± 13.2 years, median BMI (25th-75th percentile) 28.4 (25.0-32.4) kg/m². Microvascular and macrovascular diabetic complications were found in 44.2% and 38.6% of participants, respectively. Within 28 days, 1404 (50.2%; 95% CI 48.3%, 52.1%) were discharged from hospital with a median duration of hospital stay of 9 (5-14) days, while 577 participants died (20.6%; 95% CI 19.2%, 22.2%). In multivariable models, younger age, routine metformin therapy and longer symptom duration on admission were positively associated with discharge. History of microvascular complications, anticoagulant routine therapy, dyspnoea on admission, and higher aspartate aminotransferase, white cell count and C-reactive protein levels were associated with a reduced chance of discharge. Factors associated with death within 28 days mirrored those associated with discharge, and also included routine treatment by insulin and statin as deleterious factors.

CONCLUSIONS/INTERPRETATION

In patients with diabetes hospitalised for COVID-19, we established prognostic factors for hospital discharge and death that could help clinicians in this pandemic period.

TRIAL REGISTRATION

Clinicaltrials.gov identifier: NCT04324736.

Association of diabetes type and chronic diabetes complications with early exit from the labour force: register-based study of people with diabetes in Finland

AIMS/HYPOTHESIS

Diabetes and diabetes complications are a cause of substantial morbidity, resulting in early exits from the labour force and lost productivity. The aim of this study was to examine differences in early exits between people with type 1 and 2 diabetes and to assess the role of chronic diabetes complications on early exit. We also estimated the economic burden of lost productivity due to early exits.

METHODS

People of working age (age 17-64) with diabetes in 1998-2011 in Finland were detected using national registers (N_{type 1} = 45,756, N_{type 2} = 299,931). For the open cohort, data on pensions and deaths, healthcare usage, medications and basic demographics were collected from the registers. The outcome of the study was early exit from the labour force defined as pension other than old age pension beginning before age 65, or death before age 65. We analysed the early exit outcome and its risk factors using the Kaplan-Meier method and extended Cox regression models. We fitted linear regression models to investigate the risk factors of lost working years and productivity costs among people with early exit.

RESULTS

The difference in median age at early exit from the labour force between type 1 (54.0) and type 2 (58.3) diabetes groups was 4.3 years. The risk of early exit among people with type 1 diabetes increased faster after age 40 compared with people with type 2 diabetes. Each of the diabetes complications was associated with an increase in the hazard of early exit regardless of diabetes type compared with people without the complication, with eye-related complications as an exception. Diabetes complications partly but not completely explained the difference between diabetes types. The mean lost working years was 6.0 years greater in the type 1 diabetes group than in the type 2 diabetes group among people with early exit. Mean productivity costs of people with type 1 diabetes and early exit were found to be 1.4-fold greater compared with people with type 2 diabetes. The total productivity costs of incidences of early exits in the type 2 diabetes group were notably higher compared with the type 1 group during the time period (€14,400 million, €2800 million).

CONCLUSIONS/INTERPRETATION

We found a marked difference in the patterns of risk of early exit between people with type 1 and type 2 diabetes. The difference was largest close to statutory retirement age. On average, exits in the type 1 diabetes group occurred at an earlier age and resulted in higher mean lost working years and mean productivity costs. The potential of prevention, timely diagnosis and management of diabetes is substantial in terms of avoiding reductions in individual well-being and productivity.

Trends in predominant causes of death in individuals with and without diabetes in England from 2001 to 2018: an epidemiological analysis of linked primary care records

BACKGROUND

The prevalence of diabetes has increased in the UK and other high-income countries alongside a substantial decline in cardiovascular mortality. Yet data are scarce on how these trends have changed the causes of death in people with diabetes who have traditionally died primarily of vascular causes. We estimated how all-cause mortality and cause-specific mortality in people with diabetes have changed over time, how the composition of the mortality burden has changed, and how this composition compared with that of the non-diabetes population.

METHODS

In this epidemiological analysis of primary care records, we identified 313 907 individuals with diabetes in the Clinical Practice Research Datalink, a well described primary care database, between 2001 to 2018, and linked these data to UK Office for National Statistics mortality data. We assembled serial cross sections with longitudinal follow-up to generate a mixed prevalence and incidence study population of patients with diabetes. We used discretised Poisson regression models to estimate annual death rates for deaths from all causes and 12 specific causes for men and women with diabetes. We also identified age-matched and sex matched (1:1) individuals without diabetes from the same dataset and estimated mortality rates in this group.

FINDINGS

Between Jan 1, 2001, and Oct 31, 2018, total mortality declined by 32% in men and 31% in women with diagnosed diabetes. Death rates declined from 40·7 deaths per 1000 person-years to 27·8 deaths per 1000 person-years in men and from 42·7 deaths per 1000 person-years to 29·5 deaths per 1000 person-years in women with diagnosed diabetes. We found similar declines in individuals without diabetes, hence the gap in mortality between those with and without diabetes was maintained over the study period. Cause-specific death rates declined in ten of the 12 cause groups, with exceptions in dementia and liver disease, which increased in both populations. The large decline in vascular disease death rates led to a transition from vascular causes to cancers as the leading contributor to death rates in individuals with diagnosed diabetes and to the gap in death rates between those with and without diabetes.

INTERPRETATION

The decline in vascular death rates has been accompanied by a diversification of causes in individuals with diagnosed diabetes and a transition from vascular diseases to cancers as the leading contributor to diabetes-related death. Clinical and preventative approaches must reflect this trend to reduce the excess mortality risk in individuals with diabetes.

FUNDING

Wellcome Trust.

Sodium Intake and Incidence of Diabetes Complications in Elderly Patients with Type 2 Diabetes-Analysis of Data from the Japanese Elderly Diabetes Intervention Study (J-EDIT)

This study investigates the associations between sodium intake and diabetes complications in a nationwide cohort of elderly Japanese patients with type 2 diabetes aged 65–85. Data from 912 individuals regarding their dietary intake at baseline is analyzed and assessed by the Food Frequency Questionnaire based on food groups. Primary outcomes are times to diabetic retinopathy, overt nephropathy, cardiovascular disease (CVD), and all-cause mortality during six years. We find that mean sodium intake in quartiles ranges from 2.5 g to 5.9 g/day. After adjustment for confounders, no significant associations are observed between sodium intake quartiles and incidence of diabetes complications and mortality, except for a significant trend for an increased risk of diabetic retinopathy (p = 0.039). Among patients whose vegetable intake was less than the average of 268.7 g, hazard ratios (HRs) for diabetic retinopathy in patients in the second, third, and fourth quartiles of sodium intake compared with the first quartile were 0.87 (95% CI, 0.31–2.41), 2.61 (1.00–6.83), and 3.70 (1.37–10.02), respectively. Findings indicate that high sodium intake under conditions of low vegetable intake is associated with an elevated incidence of diabetic retinopathy in elderly patients with type 2 diabetes.

Diabetes increases the mortality of patients with COVID-19: a meta-analysis

AIMS

Nowadays, the ongoing pandemic of COVID-19 caused by the novel coronavirus Syndrome-Coronavirus-2 (SARS-CoV-2) is an emerging, rapidly evolving situation. Complications such as hypertension, diabetes, COPD, cardiovascular disease, and cerebrovascular disease are major risk factors for patients with COVID-19.

METHODS

No meta-analysis has explored if or not diabetes related to mortality of patients with COVID-19. Therefore, this meta-analysis first aims to explore the possible clinical mortality between diabetes and COVID-19, analyze if diabetes patients infected with SARS-CoV-2 are exposed to the worst clinical prognostic risk, and to evaluate the reliability of the evidence.

RESULTS

Our results showed a close relationship between diabetes and mortality of COVID-19, with a pooled OR of 1.75 (95% CI 1.31-2.36; P = 0.0002). The pooled data were calculated with the fixed effects model (FEM) as no heterogeneity appeared in the studies. Sensitivity analysis showed that after omitting any single study or converting a random effect model to FEM, the main results still held.

CONCLUSIONS

Our meta-analysis showed that diabetes increases the mortality of patients with COVID-19. These results indicated the disturbance of blood glucose in the COVID-19 patients. More importantly, this meta-analysis grades the reliability of evidence for further basic and clinical research into the diabetes dysfunction in COVID-19 patients.

Predictions of diabetes complications and mortality using hba1c variability: a 10-year observational cohort study

INTRODUCTION

Emerging evidence suggests that HbA1c variability, in addition to HbA1c itself, can be used as a predictor for mortality. The present study aims to examine the predictive power of mean HbA1c and HbA1c variability measures for diabetic complications as well as mortality.

METHODS

The retrospective observational study analyzed diabetic patients who were prescribed insulin at outpatient clinics of the Prince of Wales Hospital and Shatin Hospital, Hong Kong, from 1 January to 31 December, 2009. Standard deviation (SD), root mean square (RMS), and coefficient of variation were used as measures of HbA1c variability. The primary outcomes were all-cause and cardiovascular mortality. Secondary outcomes were diabetes-related complications.

RESULTS

The study cohort consists of 3424 patients, including 3137 patients with at least three HbA1c measurements. The low mean HbA1c subgroup had significantly shorter time-to-death for all-cause mortality (P < 0.001) but not cardiovascular mortality (P = 0.920). The high Hba1c subgroup showed shorter time-to-death for all-cause (P < 0.001) and cardiovascular mortality (P < 0.001). Mean Hba1c and Hba1c variability predicted all-cause as well as cardiovascular-specific mortality. In terms of secondary outcomes, mean HbA1c and HbA1c variability significantly predicted diabetic ketoacidosis/hyperosmolar hyperglycemic state/diabetic coma, neurological, ophthalmological, and renal complications. A significant association between dichotomized HbA1c variability and hypoglycemia frequency was found (P < 0.0001).

CONCLUSION

High HbA1c variability is associated with increased risk of all-cause and cardiovascular mortality, as well as diabetic complications. The association between hypoglycemic frequency, HbA1c variability, and mortality suggests that intermittent hypoglycemia resulting in poorer outcomes in diabetic patients.

Characteristics, comorbidities and survival analysis of young adults hospitalized with COVID-19 in New York City

This study reviewed 395 young adults, 18–35 year-old, admitted for COVID-19 to one of the eleven hospitals in New York City public health system. Demographics, comorbidities, clinical course, outcomes and characteristics linked to hospitalization were analyzed including temporal survival analysis. Fifty-seven percent of patients had a least one major comorbidity. Mortality without comorbidity was in 3.8% patients. Further investigation of admission features and medical history was conducted. Comorbidities associated with mortality were diabetes (n = 54 deceased/73 diagnosed,74% tested POS;98.2% with diabetic history deceased; Wilcoxon p (Wp) = .044), hypertension (14/44,32% POS, 25.5%; Wp = 0.030), renal (6/16, 37.5% POS,11%; Wp = 0.000), and cardiac (6/21, 28.6% POS,11%; Wp = 0.015). Kaplan survival plots were statistically significant for these four indicators. Data suggested glucose >215 or hemoglobin A1c >9.5 for young adults on admission was associated with increased mortality. Clinically documented respiratory distress on admission was statistically significant outcome related to mortality (X² = 236.6842, df = 1, p < .0001). Overall, 28.9% required supportive oxygen beyond nasal cannula. Nasal cannula oxygen alone was required for 71.1%, who all lived. Non-invasive ventilation was required for 7.8%, and invasive mechanical ventilation 21.0% (in which 7.3% lived, 13.7% died). Temporal survival analysis demonstrated statistically significant response for Time to Death <10 days (X² = 18.508, df = 1, p = .000); risk lessened considerably for 21 day cut off (X² = 3.464, df = 1, p = .063), followed by 31 or more days of hospitalization (X² = 2.212, df = 1, p = .137).

Are the Different Diabetes Subgroups Correlated With All-Cause, Cancer-Related, and Cardiovascular-Related Mortality?

CONTEXT

Numerous studies have shown that cardiovascular disease (CVD) represents the most important cause of mortality among people with diabetes mellitus (DM). However, no studies have evaluated the risk of CVD-related mortality among different DM subgroups.

OBJECTIVE

We aimed to examine all-cause, CVD-related, and cancer-related mortality for different DM subgroups.

DESIGN, SETTING, PATIENTS, AND INTERVENTIONS

We included participants (age ≥ 20 years) from the National Health and Nutrition Examination Survey III (NHANES III) data set. We evaluated the risks of all-cause and cause-specific (CVD and cancer) mortality among 5 previously defined diabetes subgroups: severe autoimmune diabetes (SAID), severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD), and mild age-related diabetes (MARD).

PRIMARY OUTCOME MEASURE

The hazard ratios (HRs) for all-cause and cause-specific (CVD and cancer) mortality were measured for each of the 5 DM subgroups. We also evaluated the odds ratios (ORs) for retinopathy and nephropathy in each subgroup.

RESULTS

A total of 712 adults were enrolled and the median follow-up time was 12.71 years (range, 0.25-18.08 years). The number of deaths in the 5 subgroups (SAID, SIDD, SIRD, MOD, and MARD) were 50, 75, 64, 7, and 18, respectively, and the number of CVD-related deaths in the 5 subgroups was 29, 30, 26, 2, and 11, respectively. Compared to the MOD subgroup, the adjusted HRs and 95% CIs of CVD-related mortality for the SAID, SIDD, SIRD, and MARD subgroups were 3.23 (95% CI, 0.77-13.61), 2.87 (95% CI, 0.68-12.06), 2.23 (95% CI, 0.53-9.50), and 4.75 (95% CI, 1.05-21.59), respectively (the HR for the MARD subgroup had a P value of .04). In addition, compared to the MARD subgroup, the adjusted ORs and 95% CIs for retinopathy in the SAID and SIDD groups were 2.38 (95% CI, 1.13-5.01, P = .02) and 3.34 (95% CI, 1.17-6.88, P = .001), respectively. The ORs for nephropathy were nonsignificant.

CONCLUSIONS

Our study of patients from the NHANES III data set indicated that among the different DM subgroups, the MARD subgroup tended to have a higher CVD-related mortality than the MOD subgroup. The all-cause and cancer-related mortality rates were similar across the different diabetes subgroups. In addition, compared to the MARD subgroup, the SAID and SIDD subgroups had a higher retinopathy risk, but there was no difference in nephropathy among the subgroups.

A statistical predictive model consistent within a 5-year follow-up period for patients with acute heart failure

BACKGROUND

Acute heart failure (AHF) is a major and rapidly growing health problem responsible for millions of hospitalizations annually. Due to a high proportion of in-hospital mortality and postdischarge rehospitalization and mortality, a prompt strategy for risk stratification and subsequently tailored therapy is desirable to help improve clinical outcomes. The AHEAD (A: atrial fibrillation; H: hemoglobin; E: elderly; A: abnormal renal parameters; D: diabetes mellitus) and AHEAD-U (A: atrial fibrillation; H: hemoglobin; E: elderly; A: abnormal renal parameters; D: diabetes mellitus, U: uric acid) are popular prognostic scoring systems. However, only a specific follow-up period is considered in these systems, and whether their predictive capability is still accurate in a significantly shorter or longer follow-up period is not known.

METHODS

In this research, we adapted extensive statistical approaches based on the Cox model to explore consistent risk factors in various follow-up durations. Results showed that six factors, namely, hemoglobin level, age, sodium level, blood urea nitrogen level, atrial fibrillation, and high-density lipoprotein level could be used to establish a new prognostic model, which was referred to as HANBAH. For a simple clinical application, the HANBAH scoring system, with scores from 0 to 6, was developed using several statistical models.

RESULTS

Based on an evaluation using the conventional statistical approaches, such as the Akaike information criterion, concordance statistic, and Cox area under the curve, the HANBAH scoring system consistently outperformed other strategies in predicting short- and long-term mortality. Notably, an independent replication study also revealed similar results. In addition, a modern machine learning technique using the support vector machine confirmed its superior performance.

CONCLUSION

The use of the HANBAH scoring system, which is a clinically friendly tool, was proposed, and its efficacy in predicting the mortality rates of patients with AHF regardless of the follow-up duration was independently validated.

Relevance of SARS-CoV-2 related factors ACE2 and TMPRSS2 expressions in gastrointestinal tissue with pathogenesis of digestive symptoms, diabetes-associated mortality, and disease recurrence in COVID-19 patients

COVID-19 is caused by a new strain of coronavirus called SARS-coronavirus-2 (SARS-CoV-2), which is a positive sense single strand RNA virus. In humans, it binds to angiotensin converting enzyme 2 (ACE2) with the help a structural protein on its surface called the S-spike. Further, cleavage of the viral spike protein (S) by the proteases like transmembrane serine protease 2 (TMPRSS2) or Cathepsin L (CTSL) is essential to effectuate host cell membrane fusion and virus infectivity. COVID-19 poses intriguing issues with imperative relevance to clinicians. The pathogenesis of GI symptoms, diabetes-associated mortality, and disease recurrence in COVID-19 are of particular relevance because they cannot be sufficiently explained from the existing knowledge of the viral diseases. Tissue specific variations of SARS-CoV-2 cell entry related receptors expression in healthy individuals can help in understanding the pathophysiological basis the aforementioned collection of symptoms. ACE2 mediated dysregulation of sodium dependent glucose transporter (SGLT1 or SLC5A1) in the intestinal epithelium also links it to the pathogenesis of diabetes mellitus which can be a possible reason for the associated mortality in COVID-19 patients with diabetes. High expression of ACE2 in mucosal cells of the intestine and GB make these organs potential sites for the virus entry and replication. Continued replication of the virus at these ACE2 enriched sites may be a basis for the disease recurrence reported in some, thought to be cured, patients. Based on the human tissue specific distribution of SARS-CoV-2 cell entry factors ACE2 and TMPRSS2 and other supportive evidence from the literature, we hypothesize that SARS-CoV-2 host cell entry receptor-ACE2 based mechanism in GI tissue may be involved in COVID-19 (i) in the pathogenesis of digestive symptoms, (ii) in increased diabetic complications, (iii) in disease recurrence.

Diabetes mellitus increases the risk of hospital mortality in patients with Covid-19: Systematic review with meta-analysis

BACKGROUND

The mortality rate associated with Covid-19 varies considerably among studies and determinants of this variability are not well characterized.

METHODS

A systematic review of peer-reviewed literature published through March 31, 2020 was performed to estimate the mortality rate among hospitalized patients in China with a confirmed diagnosis of Covid-19. Hospital mortality rates were estimated using an inverse variance-weighted random-effects meta-analysis model. Funnel plot symmetry was evaluated for small-study effects, a one-study removed sensitivity analysis assessed the influence of individual studies on the pooled mortality rate, and metaregression assessed the association of potential confounding variables with mortality rates.

RESULTS

The review included 16 observational studies involving 1832 hospitalized patients with a diagnosis of Covid-19. The surveillance period among studies ranged from December 16, 2019 to February 23, 2020. The median patient age was 53 years and 53% were males. A total of 38.5% of patients presented with at least 1 comorbidity, most commonly hypertension (24.0%), cardiac disease (15.1%), and diabetes mellitus (14.4%). Fever and cough, reported in 84.8% and 61.7% of patients respectively, were the most common patient symptoms. The pooled mortality rate was 9.9% (95% confidence interval 6.1% to 14.5%). Funnel plot asymmetry was not observed and the meta-analysis results were not substantially influenced by any single study since the pooled mortality rate ranged from 8.9% to 11.1% following iterative removal of one study at a time. Substantial heterogeneity in the mortality rate was identified among studies (I = 87%; P < .001). In a metaregression that included demographics, patient risk factors, and presenting symptoms, only a higher prevalence of diabetes mellitus was associated with a higher mortality rate (P = .03).

CONCLUSIONS

In a meta-analysis of hospitalized patients in China with a diagnosis of Covid-19, the mortality rate was 9.9% and a higher diabetes mellitus prevalence was independently associated with a worse prognosis. The independent influence of diabetes mellitus with Covid-19 mortality should be viewed as hypothesis-generating and warrants further study.

Prevalence of co-morbidities and their association with mortality in patients with COVID-19: A systematic review and meta-analysis

AIM

To estimate the prevalence of both cardiometabolic and other co-morbidities in patients with COVID-19, and to estimate the increased risk of severity of disease and mortality in people with co-morbidities.

MATERIALS AND METHODS

Medline, Scopus and the World Health Organization website were searched for global research on COVID-19 conducted from January 2019 up to 23 April 2020. Study inclusion was restricted to English language publications, original articles that reported the prevalence of co-morbidities in individuals with COVID-19, and case series including more than 10 patients. Eighteen studies were selected for inclusion. Data were analysed using random effects meta-analysis models.

RESULTS

Eighteen studies with a total of 14 558 individuals were identified. The pooled prevalence for co-morbidities in patients with COVID-19 disease was 22.9% (95% CI: 15.8 to 29.9) for hypertension, 11.5% (9.7 to 13.4) for diabetes, and 9.7% (6.8 to 12.6) for cardiovascular disease (CVD). For chronic obstructive pulmonary disease (COPD), chronic kidney disease (CKD), cerebrovascular disease and cancer, the pooled prevalences were all less than 4%. With the exception of cerebrovascular disease, all the other co-morbidities presented a significantly increased risk for having severe COVID-19. In addition, the risk of mortality was significantly increased in individuals with CVD, COPD, CKD, cerebrovascular disease and cancer.

CONCLUSIONS

In individuals with COVID-19, the presence of co-morbidities (both cardiometabolic and other) is associated with a higher risk of severe COVID-19 and mortality. These findings have important implications for public health with regard to risk stratification and future planning.

Elevated depressive symptoms and risk of all-cause and cardiovascular mortality among adults with and without diabetes: The REasons for Geographic And Racial Differences in Stroke (REGARDS) study

AIMS

To examine the association of elevated depressive symptoms with all-cause and cardiovascular disease (CVD) mortality and determine whether these associations differ for those with and without diabetes.

METHODS

We included 22,807 black and white men and women aged 45-98 years at baseline (2003-2007) from the REasons for Geographic And Racial Differences in Stroke (REGARDS) Study. Elevated depressive symptoms were defined as a score ≥ 4 on the 4-item Centers for Epidemiologic Studies of Depression Scale. Participants were classified as having diabetes, prediabetes, or no prediabetes/diabetes based on glucose levels and diabetes medication use. All-cause mortality events were available through 2018 and adjudicated CVD mortality events were available through 2015.

RESULTS

During follow-up, there were 5383 all-cause deaths, of which 1585 were adjudicated CVD deaths. The mean survival time was lower for participants with elevated depressive symptoms than those without elevated depressive symptoms for those with diabetes, prediabetes, and no prediabetes/diabetes. In multivariable adjusted models, elevated depressive symptoms increased the risk of all-cause mortality for those with diabetes (HR = 1.15; 95% CI = 1.00-1.32), prediabetes (HR = 1.56; 95% CI = 1.28-1.91), and neither prediabetes/diabetes (HR = 1.34; 95% CI = 1.19-1.50) (p for interaction = 0.0342). Findings were similar for CVD mortality.

CONCLUSION

Elevated depressive symptoms increased the risk of all-cause and CVD mortality among individuals with and without diabetes, with a stronger magnitude of association observed among those with prediabetes. This underscores the need for assessing depressive symptoms across the glycemic spectrum, including those with prediabetes.

Influence of diabetes mellitus on the severity and fatality of SARS-CoV-2 (COVID-19) infection

AIM

To evaluate the influence of diabetes on the severity and fatality of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection.

MATERIALS AND METHODS

The medical records of 66 hospitalized coronavirus disease 2019 (COVID-19) patients were collected and classified into non-severe (mild/moderate cases) and severe (severe/critical cases) groups. Logistic regression analysis was used to estimate the risk of severe COVID-19 (severe/critical infection). In addition, a meta-analysis including published studies reported the impact of diabetes on the severity and fatality of COVID-19. The current study was conducted using fixed effects models.

RESULTS

There were 22 diabetes and 44 non-diabetes cases among the 66 hospitalized COVID-19 patients. Seven patients with diabetes (31.82%) were diagnosed as severe COVID-19 cases, which was significantly higher than that in the non-diabetes group (4/44, 9.09%, P = .033). After adjustment for age and gender, diabetes was significantly associated with COVID-19 severity (OR: 5.29, 95% CI: 1.07-26.02). A meta-analysis further confirmed the positive association between diabetes and COVID-19 severity (pooled OR = 2.58, 95% CI: 1.93-3.45). Moreover, the patients with diabetes infected with SARS-CoV-2 had a 2.95-fold higher risk of fatality compared with those patients without diabetes (95% CI: 1.93-4.53).

CONCLUSIONS

Our findings provide new evidence that diabetes is associated with a higher risk of severity and fatality of COVID-19. Therefore, intensive monitoring and antidiabetic therapy should be considered in patients with diabetes with SARS-CoV-2 infection.

NT-proBNP by Itself Predicts Death and Cardiovascular Events in High-Risk Patients With Type 2 Diabetes Mellitus

Background NT-proBNP (N-terminal pro-B-type natriuretic peptide) improves the discriminatory ability of risk-prediction models in type 2 diabetes mellitus (T2DM) but is not yet used in clinical practice. We assessed the discriminatory strength of NT-proBNP by itself for death and cardiovascular events in high-risk patients with T2DM. Methods and Results Cox proportional hazards were used to create a base model formed by 20 variables. The discriminatory ability of the base model was compared with that of NT-proBNP alone and with NT-proBNP added, using C-statistics. We studied 5509 patients (with complete data) of 8561 patients with T2DM and cardiovascular and/or chronic kidney disease who were enrolled in the ALTITUDE (Aliskiren in Type 2 Diabetes Using Cardiorenal Endpoints) trial. During a median 2.6-year follow-up period, 469 patients died and 768 had a cardiovascular composite outcome (cardiovascular death, resuscitated cardiac arrest, nonfatal myocardial infarction, stroke, or heart failure hospitalization). NT-proBNP alone was as discriminatory as the base model for predicting death (C-statistic, 0.745 versus 0.744, P=0.95) and the cardiovascular composite outcome (C-statistic, 0.723 versus 0.731, P=0.37). When NT-proBNP was added, it increased the predictive ability of the base model for death (C-statistic, 0.779 versus 0.744, P<0.001) and for cardiovascular composite outcome (C-statistic, 0.763 versus 0.731, P<0.001). Conclusions In high-risk patients with T2DM, NT-proBNP by itself demonstrated discriminatory ability similar to a multivariable model in predicting both death and cardiovascular events and should be considered for risk stratification. Registration URL: https://www.clini​caltr​ials.gov; Unique identifier: NCT00549757.

Study of hospitalization and mortality in Korean diabetic patients using the diabetes complications severity index

BACKGROUND

The prevalence of type 2 diabetes mellitus (T2DM) is expected to increase from 7.7% in 2017 to 8.4% in 2045 worldwide. Diabetes complications contribute to morbidity and mortality. To evaluate whether the diabetes complications severity index (DCSI) was associated with increased risks of mortality and hospitalization.

METHODS

A retrospective cohort study was conducted using the National Health Insurance Database (NHID) sample cohort of 1,102,047 patients (2002-2015) in Korea. Diabetes complications were evaluated at 2 years after the initial diagnosis and during the subsequent follow-up period (mean duration 6.56 ± 2.81 years). The type and severity of complications were evaluated on the basis of the International Classification of Disease Ninth (ICD-9) codes used in DCSI with 7 categories and 55 subcategories of complications. The Cox proportional hazard and Poisson regression models were used to evaluate the mortality and hospitalization rates. The incidence and relative risk of diabetes complications as well as the risk of mortality and hospitalization were the main outcome measures.

RESULTS

A total of 27,871 patients were finally included and grouped by the number of complications present at 2 years. Four hundred ninety patients (5.37%) died without complications, 659 (7.31%) died with one complication and 1153 (11.85%) died with two or more complications. As DCSI at index date increased, the risk of additional new diabetes complications increased by 26% [relative risk (RR) 1.26, 95% CI 1.25-1.27]. The risks of mortality and hospitalization were linearly related to DCSI [hazard ratio 1.13 (95% CI 1.11-1.16), relative risk 1.04 (95% CI 1.03-1.06)].

CONCLUSIONS

Patients with higher incidence and severity of diabetes complications have increased risks of mortality and hospitalization.

Possible differential benefits of edetate disodium in post-myocardial infarction patients with diabetes treated with different hypoglycemic strategies in the Trial to Assess Chelation Therapy (TACT)

BACKGROUND

The NIH-funded Trial to Assess Chelation Therapy (TACT) randomized 1708 stable patients age ≥50 who were ≥6 months post myocardial infarction to 40 infusions of an edetate disodium-based regimen or placebo. In 633 patients with diabetes, edetate disodium significantly reduced the primary composite endpoint of mortality, recurrent myocardial infarction, stroke, coronary revascularization, or hospitalization for angina (hazard ratio [HR] 0.59, 95% confidence interval [CI] 0.44-0.79, p < 0.001). The principal secondary endpoint of a composite of cardiovascular death, myocardial infarction, or stroke was also reduced (HR 0.60, 95% CI 0.39-0.91, p = 0.017). It is unknown if the treatment effect differs by diabetes therapy.

METHODS

We grouped the subset of 633 patients with diabetes according to glucose-lowering therapy at time of randomization. The log-rank test was used to compare active therapy versus placebo. All treatment comparisons were performed using 2-sided significance tests at the significance level of 0.05 and were as randomized. Relative risks were expressed as HR with associated 95% CI, calculated using the Cox proportional hazards model.

RESULTS

There were 162 (25.7%) patients treated with insulin; 301 (47.5%) with oral hypoglycemics only; and 170 (26.8%) receiving no pharmacologic treatment for diabetes. Patients on insulin reached the primary endpoint more frequently than patients on no pharmacologic treatment [61 (38%) vs 49 (29%) (HR 1.56, 95% CI 1.07-2.27, p = 0.022)] or oral hypoglycemics [61 (38%) vs 87 (29%) (HR 1.46, 1.05-2.03, p = 0.024)]. The primary endpoint occurred less frequently with edetate disodium based therapy versus placebo in patients on insulin [19 (26%) vs 42 (48%) (HR 0.42, 95% CI 0.25-0.74, log-rank p = 0.002)], marginally in patients on oral hypoglycemics [38 (25%) vs 49 (34%) (HR 0.66, 95% CI 0.43-1.01, log-rank p = 0.041)], and no significant difference in patients not treated with a pharmacologic therapy [23 (25%) vs 26 (34%) (HR 0.69, 95% CI 0.39-1.20, log-rank p = 0.225)]. The interaction between randomized intravenous treatment and type of diabetes therapy was not statistically significant (p = 0.203).

CONCLUSIONS

Edetate disodium treatment in stable, post-myocardial infarction patients with diabetes suggests that patients on insulin therapy at baseline may accrue the greatest benefit.

CLINICAL TRIAL REGISTRATION

clinicaltrials.gov identifier: http://clinicaltrials.gov/ct2/show/NCT00044213?term=TACT&rank=7 identifier Trial to Assess Chelation Therapy (TACT), NCT00044213.

Baseline characteristics and risk factors for short-term outcomes in 132 COVID-19 patients with diabetes in Wuhan China: A retrospective study

AIMS

To investigate the clinical characteristics, laboratory findings and high- resolution CT (HRCT) features and to explore the risk factors for in-hospital death and complications of coronavirus disease 2019 (COVID-19) patients with diabetes.

METHODS

From Dec 31, 2019, to Apr 5, 2020, a total of 132 laboratory-confirmed COVID-19 patients with diabetes from two hospitals were retrospectively included in our study. Clinical, laboratory and chest CT data were analyzed and compared between the two groups with an admission glucose level of ≤11 mmol/L (group 1) and >11 mmol/L (group 2). Logistic regression analyses were used to identify the risk factors associated with in-hospital death and complications.

RESULTS

Of 132 patients, 15 died in hospital and 113 were discharged. Patients in group 2 were more likely to require intensive care unit care (21.4% vs. 9.2%), to develop acute respiratory distress syndrome (ARDS) (23.2% vs. 9.2%) and acute cardiac injury (12.5% vs. 1.3%), and had a higher death rate (19.6% vs. 5.3%) than group 1. In the multivariable analysis, patients with admission glucose of >11 mmol/l had an increased risk of death (OR: 7.629, 95%CI: 1.391-37.984) and in-hospital complications (OR: 3.232, 95%CI: 1.393-7.498). Admission d-dimer of ≥1.5 μg/mL (OR: 6.645, 95%CI: 1.212-36.444) and HRCT score of ≥10 (OR: 7.792, 95%CI: 2.195-28.958) were associated with increased odds of in-hospital death and complications, respectively.

CONCLUSIONS

In COVID-19 patients with diabetes, poorly-controlled blood glucose (>11 mmol/L) may be associated with poor outcomes. Admission hyperglycemia, elevated d-dimer and high HRCT score are potential risk factors for adverse outcomes and death.

Comorbid diabetes and the risk of disease severity or death among 8807 COVID-19 patients in China: A meta-analysis

AIMS

Diabetes mellitus has been reported to be one of the most prevalent comorbidity in patients with Coronavirus Disease 2019 (COVID-19). We aimed to assess the association of comorbid diabetes with COVID-19 severity or mortality in China.

METHODS

We performed a systematic literature search from six electronic databases on diabetes and COVID-19. The outcome of interest was disease severity or mortality. Heterogeneity among the studies was assessed by the Cochran Q test and the I² statistic. A random effects model was applied to calculate the pooled risk ratio (RR) with 95% confidence interval (CI).

RESULTS

Nine studies from different provinces/cities were identified according to the predefined inclusion and exclusion criteria. There were a total of 1070 patients with diabetes, out of the 8807 COVID-19 cases. The majority of the cases were derived from Hubei Province. A low degree of heterogeneity in the risk estimates was observed in the included studies. Meta-analysis showed that there was a significant association of preexisting diabetes with disease severity or death. The pooled RR was 2.96 (95% CI: 2.31-3.79; p < 0.001). Sensitivity analysis demonstrated no significant changes in the pooled estimates.

CONCLUSIONS

Comorbid diabetes was associated with an increased risk of disease severity or death in Chinese COVID-19 patients.

Predicting 5- and 10-Year Mortality Risk in Older Adults With Diabetes

OBJECTIVE

Several diabetes clinical practice guidelines suggest that treatment goals may be modified in older adults on the basis of comorbidities, complications, and life expectancy. The long-term benefits of treatment intensification may not outweigh short-term risks for patients with limited life expectancy. Because of the uncertainty of determining life expectancy for individual patients, we sought to develop and validate prognostic indices for mortality in older adults with diabetes.

RESEARCH DESIGN AND METHODS

We used a prevalence sample of veterans with diabetes who were aged ≥65 years on 1 January 2006 (N = 275,190). Administrative data were queried for potential predictors that included patient demographics, comorbidities, procedure codes, laboratory values and anthropomorphic measurements, medication history, and previous health service utilization. Logistic least absolute shrinkage and selection operator regressions were used to identify variables independently associated with mortality. The resulting odds ratios were then weighted to create prognostic indices of mortality over 5 and 10 years.

RESULTS

Thirty-seven predictors of mortality were identified: 4 demographic variables, prescriptions for insulin or sulfonylureas or blood pressure medications, 6 biomarkers, previous outpatient and inpatient utilization, and 22 comorbidities/procedures. The prognostic indices showed good discrimination, with C-statistics of 0.74 and 0.76 for 5- and 10-year mortality, respectively. The indices also demonstrated excellent agreement between observed outcome and predictions, with calibration slopes of 1.01 for both 5- and 10-year mortality.

CONCLUSIONS

Prognostic indices obtained from administrative data can predict 5- and 10-year mortality in older adults with diabetes. Such a tool may enable clinicians and patients to develop individualized treatment goals that balance risks and benefits of treatment intensification.

The circulating ANGPTL8 levels show differences among novel subgroups of adult patients with diabetes and are associated with mortality in the subsequent 5 years

ANGPTL8, an important regulator of glucose and lipid metabolism, is associated with diabetes, but the role of ANGPTL8 in the outcomes of novel subgroups of diabetes remains unclear. To assess the circulating ANGPTL8 levels in novel subgroups of diabetes and their association with health outcomes, we performed a data-driven cluster analysis (k-means) of patients with newly diagnosed diabetes (741 patients enrolled from 2011 through 2016) from the Risk Evaluation of Cancers in Chinese Diabetic Individuals: a longitudinal (REACTION) study. The primary outcomes were mortality from all causes and cardiovascular diseases (CVD), and the secondary outcome was any cardiovascular event. Comparisons among groups were performed using the Kruskal-Wallis test, and the correlations between variables were assessed using the Pearson correlation test. Logistic regression was used to detect associations between the risk of outcomes and the ANGPTL8 levels. We identified four replicable clusters of patients with diabetes that exhibited significantly different patient characteristics and risks of all-cause mortality. The serum ANGPTL8 levels in the cluster of mild age-related diabetes (MARD), severe insulin-resistant diabetes (SIRD), and severe insulin-deficient diabetes (SIDD) were significantly higher than those in the mild obesity-related diabetes (MOD) cluster (685.01 ± 24.50 vs. 533.5 ± 18.39, p < 0.001; 649.69 ± 55.83 vs. 533.5 ± 18.39, = 0.040; 643.29 ± 30.89 vs. 533.5 ± 18.39, p = 0.001). High circulating ANGPTL8 levels were more highly associated with a greater hazard of all-cause mortality (quartile 4 vs 1: risk ratio [RR] 3.23, 95% CI 1.13-9.22; per unit increase in the Z score: RR 1.53, 95% CI 1.17-2.01) than low circulating ANGPTL8 levels. In conclusion, this 5-year follow-up REACTION study revealed that the circulating ANGPTL8 levels show differences among novel subgroups of adult patients with diabetes and are associated with all-cause mortality in the subsequent 5 years.

Diabetes as a risk factor for greater COVID-19 severity and in-hospital death: A meta-analysis of observational studies

AIMS

To estimate the prevalence of established diabetes and its association with the clinical severity and in-hospital mortality associated with COVID-19.

DATA SYNTHESIS

We systematically searched PubMed, Scopus and Web of Science, from 1st January 2020 to 15th May 2020, for observational studies of patients admitted to hospital with COVID-19. Meta-analysis was performed using random-effects modeling. A total of 83 eligible studies with 78,874 hospitalized patients with laboratory-confirmed COVID-19 were included. The pooled prevalence of established diabetes was 14.34% (95% CI 12.62-16.06%). However, the prevalence of diabetes was higher in non-Asian vs. Asian countries (23.34% [95% CI 16.40-30.28] vs. 11.06% [95% CI 9.73-12.39]), and in patients aged ≥60 years vs. those aged <60 years (23.30% [95% CI 19.65-26.94] vs. 8.79% [95% CI 7.56-10.02]). Pre-existing diabetes was associated with an approximate twofold higher risk of having severe/critical COVID-19 illness (n = 22 studies; random-effects odds ratio 2.10, 95% CI 1.71-2.57; I2 = 41.5%) and ~threefold increased risk of in-hospital mortality (n = 15 studies; random-effects odds ratio 2.68, 95% CI 2.09-3.44; I2 = 46.7%). Funnel plots and Egger's tests did not reveal any significant publication bias.

CONCLUSIONS

Pre-existing diabetes is significantly associated with greater risk of severe/critical illness and in-hospital mortality in patients admitted to hospital with COVID-19.

Trends and predictors in all-cause and cause-specific mortality in diabetic and reference populations during 21 years of follow-up

BACKGROUND

Patients with diabetes mellitus (DM) have a markedly higher overall mortality from coronary heart disease (CHD), as well as many other causes of death like cancer. Since diabetes is a multisystem disease, this fact together with the increased lifespan among individuals with diabetes may also lead to the emergence of other diabetes-related complications and ultimately to diversification of the causes of death.

METHODS

The study population of this observational historic cohort study consisted of subjects with DM, who had purchased for at least one insulin prescription and/or one oral antidiabetic between January 1, 1997 and December 31, 2010 (N=199 354), and a reference population matched by age, sex and hospital district (N=199 354). Follow-up was continued until December 31, 2017. All-cause and cause-specific mortality (cancer, CHD and stroke) was analysed with Poisson and Cox's regression. Associations between baseline medications and mortality were analysed using LASSO (Least Absolute Shrinkage and Selection Operator) models.

RESULTS

The mortality rates were significantly elevated among the patients with DM. However, the relative risk of all-cause mortality between the DM and reference populations tended to converge during the follow-up. The lowering trend was most apparent in CHD mortality. The difference between DM and reference populations in stroke mortality vanished with a later entrance to the follow-up period. There were a few differences between DM and no-DM groups with respect to how baseline medications were associated with mortality.

CONCLUSIONS

The gap between the mortality of patients with diabetes compared to subjects who are non-diabetic diminished markedly during the 21-year period. This was driven primarily by the reduced CHD mortality.

Assessment of risk, severity, mortality, glycemic control and antidiabetic agents in patients with diabetes and COVID-19: A narrative review

AIMS

Rising prevalence of non-communicable diseases world-wide has made diabetes an important comorbidity in patients with coronavirus disease-19 (COVID-19). We sought to review the risk, severity and mortality in COVID-19 and its relation to the glycemic control, and role of anti-diabetic agents in patients with diabetes.

METHODS

A Boolean search was made in PubMed, MedRxiv and Google Scholar database until May 10, 2020 and full articles with supplementary appendix were retrieved using the specific key words related to the topic.

RESULTS

There is a high prevalence of diabetes in patients with COVID-19. Patients with diabetes had a significantly more severe variety of COVID-19 and increased mortality, compared to the groups without diabetes. Moreover, poor glycemic control is associated with a significantly higher severe COVID-19 and increased mortality, compared to the well-controlled glycemic groups. No data currently available for or against any anti-diabetic agents in COVID-19.

CONCLUSIONS

Diabetes, in particular poorly-controlled group is associated with a significantly higher risk of severe COVID-19 and mortality. This calls for an optimal glycemic control and an increased emphasis on future preventative therapies including the vaccination programs for these groups in addition to the traditional risk prevention such as social distancing and self-isolation.

Combination of four clinical indicators predicts the severe/critical symptom of patients infected COVID-19

BACKGROUND

Despite the death rate of COVID-19 is less than 3%, the fatality rate of severe/critical cases is high, according to World Health Organization (WHO). Thus, screening the severe/critical cases before symptom occurs effectively saves medical resources.

METHODS AND MATERIALS

In this study, all 336 cases of patients infected COVID-19 in Shanghai to March 12th, were retrospectively enrolled, and divided in to training and test datasets. In addition, 220 clinical and laboratory observations/records were also collected. Clinical indicators were associated with severe/critical symptoms were identified and a model for severe/critical symptom prediction was developed.

RESULTS

Totally, 36 clinical indicators significantly associated with severe/critical symptom were identified. The clinical indicators are mainly thyroxine, immune related cells and products. Support Vector Machine (SVM) and optimized combination of age, GSH, CD3 ratio and total protein has a good performance in discriminating the mild and severe/critical cases. The area under receiving operating curve (AUROC) reached 0.9996 and 0.9757 in the training and testing dataset, respectively. When the using cut-off value as 0.0667, the recall rate was 93.33 % and 100 % in the training and testing datasets, separately. Cox multivariate regression and survival analyses revealed that the model significantly discriminated the severe/critical cases and used the information of the selected clinical indicators.

CONCLUSION

The model was robust and effective in predicting the severe/critical COVID cases.