Unfavorable social determinants of health and risk of mortality in adults with diabetes: findings from the National Health Interview Survey

INTRODUCTION

Understanding the role of social determinants of health as predictors of mortality in adults with diabetes may help improve health outcomes in this high-risk population. Using population-based, nationally representative data, this study investigated the cumulative effect of unfavorable social determinants on all-cause mortality in adults with diabetes.

RESEARCH DESIGN AND METHODS

We used data from the 2013-2018 National Health Interview Survey, linked to the National Death Index through 2019, for mortality ascertainment. A total of 47 individual social determinants of health were used to categorize participants in quartiles denoting increasing levels of social disadvantage. Poisson regression was used to report age-adjusted mortality rates across increasing social burden. Multivariable Cox proportional hazards models were used to assess the association between cumulative social disadvantage and all-cause mortality in adults with diabetes, adjusting for traditional risk factors.

RESULTS

The final sample comprised 182 445 adults, of whom 20 079 had diabetes. In the diabetes population, mortality rate increased from 1052.7 per 100 000 person-years in the first quartile (Q1) to 2073.1 in the fourth quartile (Q4). In multivariable models, individuals in Q4 experienced up to twofold higher mortality risk relative to those in Q1. This effect was observed similarly across gender and racial/ethnic subgroups, although with a relatively stronger association for non-Hispanic white participants compared with non-Hispanic black and Hispanic subpopulations.

CONCLUSIONS

Cumulative social disadvantage in individuals with diabetes is associated with over twofold higher risk of mortality, independent of established risk factors. Our findings call for action to screen for unfavorable social determinants and design novel interventions to mitigate the risk of mortality in this high-risk population.

Effects of inappropriate cause-of-death certification on mortality from cardiovascular disease and diabetes mellitus in Tonga

BACKGROUND

Cardiovascular disease (CVD) and diabetes mellitus are major health issues in Tonga and other Pacific countries, although mortality levels and trends are unclear. We assess the impacts of cause-of-death certification on coding of CVD and diabetes as underlying causes of death (UCoD).

METHODS

Tongan records containing cause-of-death data (2001-2018), including medical certificates of cause-of-death (MCCD), had UCoD assigned according to International Classification of Diseases 10th revision (ICD-10) coding rules. Deaths without recorded cause were included to ascertain total mortality. Diabetes and hypertension causes were reallocated from Part 1 of the MCCD (direct cause) to Part 2 (contributory cause) if potentially fatal complications were not recorded, and an alternative UCoD was assigned. Proportional mortality by cause based on the alternative UCoD were applied to total deaths then mortality rates calculated by age and sex using census/intercensal population estimates. CVD and diabetes mortality rates for unaltered and alternative UCoD were compared using Poisson regression.

RESULTS

Over 2001-18, in ages 35-59 years, alternative CVD mortality was higher than unaltered CVD mortality in men (p = 0.043) and women (p = 0.15); for 2010-18, alternative versus unaltered measures in men were 3.3/103 (95%CI: 3.0-3.7/103) versus 2.9/103 (95%CI: 2.6-3.2/103), and in women were 1.1/103 (95%CI: 0.9-1.3/103) versus 0.9/103 (95%CI: 0.8-1.1/103). Conversely, alternative diabetes mortality rates were significantly lower than the unaltered rates over 2001-18 in men (p < 0.0001) and women (p = 0.013); for 2010-18, these measures in men were 1.3/103 (95%CI: 1.1-1.5/103) versus 1.9/103 (95%CI: 1.6-2.2/103), and in women were 1.4/103 (95%CI: 1.2-1.7/103) versus 1.7/103 (95%CI: 1.5-2.0/103). Diabetes mortality rates increased significantly over 2001-18 in men (unaltered: p < 0.0001; alternative: p = 0.0007) and increased overall in women (unaltered: p = 0.0015; alternative: p = 0.014).

CONCLUSIONS

Diabetes reporting in Part 1 of the MCCD, without potentially fatal diabetes complications, has led to over-estimation of diabetes, and under-estimation of CVD, as UCoD in Tonga. This indicates the importance of controlling various modifiable risks for atherosclerotic CVD (including stroke) including hypertension, tobacco use, and saturated fat intake, besides obesity and diabetes. Accurate certification of diabetes as a direct cause of death (Part 1) or contributory factor (Part 2) is needed to ensure that valid UCoD are assigned. Examination of multiple cause-of-death data can improve understanding of the underlying causes of premature mortality to better inform health planning.

Trends in all causes and cause specific mortality attributable to ambient particulate matter pollution in China from 1990 to 2019: A secondary data analysis study

BACKGROUND

Particularly fine particulate matter (PM2.5) has become a significant public health concern in China due to its harmful effects on human health. This study aimed to examine the trends in all causes and cause specific morality burden attributable to PM2.5 pollution in China.

METHODS

We extracted data on all causes and cause specific mortality data attributable to PM2.5 exposure for the period 1990-2019 in China from the Global Burden of Disease 2019. The average annual percent change (AAPC) in age-standardized mortality rates (ASMR) and years of life lost (YLLs) due to PM2.5 exposure were calculated using the Joinpoint Regression Program. Using Pearson's correlation, we estimated association between burden trends, urban green space area, and higher education proportions.

RESULTS

During the period 1990-1999, there were increases in mortality rates for All causes (1.6%, 95% CI: 1.5% to 1.8%), Diabetes mellitus (5.2%, 95% CI: 4.9% to 5.5%), Encephalitis (3.1%, 95% CI: 2.6% to 3.5%), Ischemic heart disease (3.3%, 95% CI: 3% to 3.6%), and Tracheal, bronchus and lung cancer (5%, 95% CI: 4.7% to 5.2%). In the period 2010-2019, Diabetes mellitus still showed an increase in mortality rates, but at a lower rate with an AAPC of 1.2% (95% CI: 1% to 1.4%). Tracheal bronchus and lung cancer showed a smaller increase in this period, with an AAPC of 0.5% (95% CI: 0.3% to 0.6%). In terms of YLLs, the trends appear to be similar.

CONCLUSION

Our findings highlight increasing trends in disease burden attributable to PM2.5 in China, particularly for diabetes mellitus, tracheal, bronchus, and lung cancer.

Relationship between social development indicators and mortality due to Diabetes Mellitus in Brazil: a space-time analysis

OBJECTIVE

to identify the space-time pattern of mortality due to Diabetes Mellitus in Brazil, as well as its relationship with social development indicators.

METHOD

an ecological and time series nationwide study based on secondary data from the Unified Health System Informatics Department, with space-time analysis and inclusion of indicators in non-spatial and spatial regression models. The following was performed: overall mortality rate calculation; characterization of the sociodemographic and regional profiles of the death cases by means of descriptive and time analysis; and elaboration of thematic maps.

RESULTS

a total of 601,521 deaths related to Diabetes Mellitus were recorded in Brazil, representing a mean mortality rate of 29.5/100,000 inhabitants. The states of Rio Grande do Norte, Paraíba, Pernambuco, Alagoas and Sergipe, Rio de Janeiro, Paraná and Rio Grande do Sul presented high-high clusters. By using regression models, it was verified that the Gini index (β=11.7) and the Family Health Strategy coverage (β=3.9) were the indicators that most influenced mortality due to Diabetes Mellitus in Brazil.

CONCLUSION

in Brazil, mortality due to Diabetes presents an overall increasing trend, revealing itself as strongly associated with places that have worse social indicators.

HIGHLIGHTS

(1) The time-space pattern of mortality due to Diabetes presents an increasing trend. (2) The Northeast and South regions present high rates of mortality due to Diabetes. (3) Mortality due to Diabetes is associated with worse sociodemographic indicators. (4) A relationship is observed between income, access to health and mortality due to Diabetes.

Trends and all-cause mortality associated with multimorbidity of non-communicable diseases among adults in the United States, 1999-2018: a retrospective cohort study

OBJECTIVES

Multimorbidity of non-communicable diseases (NCDs) has brought enormous challenges to public health, becoming a major medical burden. However, the patterns, temporal trends, and all-cause mortality associated with NCD multimorbidity over time have not been well described in the United States.

METHODS

All adult participants were sourced from nationally representative data from the National Health and Nutrition Examination Survey. In total, 55,081 participants were included in trend analysis, and 38,977 participants were included in Cox regression.

RESULTS

The 5 NCDs with the largest increases over the study period were diabetes, osteoporosis, obesity, liver conditions, and cancer. The estimated prevalence of multimorbidity increased with age, especially for middle-aged participants with 5 or more NCDs; in general, the prevalence of NCD multimorbidity was higher among females than males. Participants with 5 or more NCDs were at 4.49 times the risk of all-cause mortality of participants without any diseases. Significant interactions were found between multimorbidity and age group (p for interaction <0.001), race/ethnicity (p for interaction<0.001), and educational attainment (p for interaction=0.010).

CONCLUSIONS

The prevalence of multiple NCDs significantly increased from 1999 to 2018. Those with 5 or more NCDs had the highest risk of all-cause mortality, especially among the young population. The data reported by this study could serve as a reference for additional NCD research.

Predictive value of a novel sub-item mortality risk score derived from the Norfolk Quality of Life in Diabetic Neuropathy questionnaire in Romanian participants with diabetes mellitus

AIMS

To evaluate whether the Norfolk Quality of Life in Diabetic Neuropathy (QOL-DN) questionnaire and the novel Norfolk Mortality Risk Score (NMRS), comprising Norfolk QOL-DN items, can identify 4-year mortality risk in individuals with diabetes.

METHODS

Of 21,756 adults completing Norfolk QOL-DN in 2012, two groups of surviving and deceased patients were identified in 2016: Group 1, from a county capital and Group 2, from six small cities. NMRS was calculated in Group 1 using the 2012 scores of Norfolk QOL-DN items that discriminate between deceased and surviving participants (p &lt; 0.05) and was subsequently applied to Group 2.

RESULTS

763 participants were included (Group 1: 481 [450 surviving, 31 deceased]; Group 2: 282 [218 surviving, 64 deceased]). Total Norfolk QOL-DN score was significantly higher (worse) in deceased participants than in survivors in both groups (p ≤ 0.008). Optimal cut-off for the 25-item NMRS was 11.5 in Group 1. Individuals in Groups 1 and 2 with NMRS≥ 11.5 in 2012 had a 4-year mortality risk ratio of 4.24 (95 % confidence interval [CI]: 1.65-10.84) and 2.33 (95 % CI: 1.33-4.07), respectively, corresponding to 8 and 16 additional deaths/100 persons/4 years (p = 0.001).

CONCLUSION

Norfolk QOL-DN and NMRS can identify individuals with diabetes at risk of 4-year mortality.

Age and sex-specific associations of visit-to-visit variability of glycated hemoglobin A1c with all-cause mortality in patients with diabetes

BACKGROUND

Visit-to-visit variability (VVV) of glycated hemoglobin (HbA1c) levels have been found to be associated with prognosis of diabetes. However, little is known about whether or to what extent sex and age may modify the effects of VVV.

METHODS

To investigate age- and sex-specific rates of mortality from all causes and relative hazards of mortality in association with VVV of HbA1c levels, 47,145 patients with diabetes and prescription of any antidiabetic agents >6 months were identified from outpatient visits of a tertiary medical center in northern Taiwan during 2003-2018. VVV of HbA1c was measured by quartiles of standard deviation (SD), coefficient of variation (CV), and average real variability (ARV), respectively. The study subjects were linked to Taiwan's National Death Registry to identify all-cause mortality. The person-year approach with the Poisson assumption was used to assess the all-cause mortality rates, and Cox proportional hazard regression model was used to evaluate the relative hazards of all-cause mortality concerning various levels of VVV of HbA1c.

RESULTS

The lowest all-cause mortality rate was found in either the first or second quartile of various measures for VVV of HbA1c, but the highest mortality rate was consistently observed in the fourth quartile of VVV, regardless of SD, CV, or ARV across ages and sexes. Increased hazards of overall all-cause mortality were noticed from the second to fourth quartile of VVV of HbA1c. In detailed age- and sex-stratified analyses, elevated risk of mortality was seen in the fourth quartile of those aged <50 years while in those aged >69 years, increased risk of mortality was noticed in the third and fourth quartiles of any VVV of HbA1c irrespective of sex. In those aged 50-69 years, incremental increased hazards of mortality were consistently observed in the second to fourth quartiles of VVV of HbA1c.

CONCLUSION

HbA1c variability whether it was SD, CV, or ARV could strongly predict the risks of all-cause mortality. The extent of the relationship between VVV of HbA1c and all-cause mortality in different age groups was comparable between both sexes. Given the importance of long-term glucose fluctuation, the inclusion of HbA1c variability calculated from the standardized method should be considered by clinical guideline policymakers as part of the biochemical panel in daily diabetes management.

Relation of Hemoglobin A1C Levels to Risk of Ischemic Stroke and Mortality in Patients With Diabetes Mellitus and Atrial Fibrillation

Diabetes mellitus (DM) is associated with an increased risk of complications in atrial fibrillation (AF). This study aimed to assess the incidence and risks of ischemic stroke and mortality according to baseline HbA1c levels in patients with DM and AF. We conducted a cohort study using Clalit Health Services electronic medical records. The study population included all Clalit Health Services members aged ≥25 years, with the first diagnosis of AF between January 1, 2010, and December 31, 2016, who had a diagnosis of DM. The risk of stroke and all-cause death were compared according to HbA1c levels at the time of AF diagnosis: <7.0%, between 7% and 9%, and ≥9%. A total of 44,451 patients with DM and AF were identified. The median age was 75 years (interquartile 65 to 83), and 52.5% were women. During a mean follow-up of 38 months, higher levels of HbA1c were associated with an increased risk of stroke with a dose-dependent response when compared with patients with HbA1c <7% (Adjusted hazard ratio [aHR] =1.30 [95% confidence interval 1.10 to 2.05] for levels between 7% and 9% and 1.60 (95% confidence interval 1.25 to 2.03) for HbA1c >9%, even after adjusting for CHA₂DS₂-Vasc risk factors and use of oral anticoagulants. The risk for overall mortality was significantly higher in the HBA1C >9% group (aHR = 1.17 [1.07 to 1.28]). In conclusion, in this cohort of patients with AF and DM, HbA1c levels were associated with the risk of stroke in a dose-dependent manner even after accounting for other recognized risk factors for stroke.

Trends in lifetime risk and years of potential life lost from diabetes in the United States, 1997–2018

Background

Both incidence and mortality of diagnosed diabetes have decreased over the past decade. However, the impact of these changes on key metrics of diabetes burden–lifetime risk (LR), years of potential life lost (YPLL), and years spent with diabetes–is unknown.

Methods

We used data from 653,811 adults aged ≥18 years from the National Health Interview Survey, a cross-sectional sample of the civilian non-institutionalized population in the United States. LR, YPLL, and years spent with diabetes were estimated from age 18 to 84 by survey period (1997–1999, 2000–2004, 2005–2009, 2010–2014, 2015–2018). The age-specific incidence of diagnosed diabetes and mortality were estimated using Poisson regression. A multistate difference equation accounting for competing risks was used to model each metric.

Results

LR and years spent with diabetes initially increased then decreased over the most recent time periods. LR for adults at age 20 increased from 31.7% (95% CI: 31.2–32.1%) in 1997–1999 to 40.7% (40.2–41.1%) in 2005–2009, then decreased to 32.8% (32.4–33.2%) in 2015–2018. Both LR and years spent with diabetes were markedly higher among adults of non-Hispanic Black, Hispanic, and other races compared to non-Hispanic Whites. YPLL significantly decreased over the study period, with the estimated YPLL due to diabetes for an adult aged 20 decreasing from 8.9 (8.7–9.1) in 1997–1999 to 6.2 (6.1–6.4) in 2015–2018 (p = 0.02).

Conclusion

In the United States, diabetes burden is declining, but disparities by race/ethnicity remain. LR remains high with approximately one-third of adults estimated to develop diabetes during their lifetime.

Long-term exposure to objective and perceived residential greenness and diabetes mortality: A census-based cohort study

BACKGROUND

Residing close to green spaces might reduce diabetes mellitus (DM) risk; however, evidence for diabetes mortality is limited. Moreover, individual and neighbourhood social factors may determine DM risk. Exposure to green spaces may also depend on socioeconomic position (SEP). This study examined the associations between residential greenness and diabetes-related mortality, and the role of the social environment in these associations.

METHODS

We used the 2001 Belgian census linked to mortality register data for the period 2001-2014. We included individuals aged 40-79 years old and residing in the five largest Belgian urban areas at baseline. Exposure to residential greenness was assessed with surrounding greenness using the Normalized Difference Vegetation Index (NDVI) within 500-m of residence (objective indicator), and perceived neighbourhood greenness (subjective indicator). We conducted mixed-effects Cox proportional hazards models to obtain hazard ratios (HR) for diabetes-related mortality per interquartile range (IQR) increments of residential greenness. We assessed effect modification by social factors through stratification.

RESULTS

From 2,309,236 individuals included at baseline, 1.2% died from DM during follow-up. Both residential greenness indicators were inversely associated with diabetes-related mortality after adjustment for individual social factors. After controlling for neighbourhood SEP, the beneficial association with surrounding greenness disappeared [HR 1.02 (95%CI:0.99,1.06)], but persisted with perceived neighbourhood greenness [HR 0.93 (95%CI:0.91,0.95)]. After stratification the inverse associations with perceived neighbourhood greenness were strongest for women, the lowest educated, and individuals residing in least deprived neighbourhoods.

CONCLUSIONS

Our findings suggest that an overall positive perception of neighbourhood green spaces reduces independently the risk of diabetes-related mortality, regardless of the neighbourhood social environment. Nevertheless, neighbourhood SEP may be a strong confounder in the associations between diabetes-related mortality and greenness indicators derived from satellite images. Perception factors not captured by objective measurements of green spaces are potentially relevant in the association with DM, especially among disadvantaged groups.

Diabetes acts on mortality in hemodialysis patients predicted by asymmetric dimethylarginine and inflammation

BACKGROUND

The mortality rate of diabetic patients on dialysis is higher than that of non-diabetic patients. Asymmetric dimethylarginine and inflammation are strong predictors of death in hemodialysis. This study aimed to evaluate asymmetric dimethylarginine and C-reactive protein interaction in predicting mortality in hemodialysis according to the presence or absence of diabetes.

METHODS

Asymmetric dimethylarginine and C-reactive protein were measured in 202 patients in maintenance hemodialysis assembled from 2011 to 2012 and followed for four years. Effect modification of C-reactive protein on the relationship between asymmetric dimethylarginine and all-cause mortality was investigated dividing the population into four categories according to the median of asymmetric dimethylarginine and C-reactive protein.

RESULTS

Asymmetric dimethylarginine and C-reactive protein levels were similar between diabetics and non-diabetics. Asymmetric dimethylarginine - median IQR μM - (1.95 1.75-2.54 versus 1.03 0.81-1.55 P=0.000) differed in non-diabetics with or without evolution to death (HR 2379 CI 1.36-3.68 P=0.000) and was similar in diabetics without or with evolution to death. Among non-diabetics, the category with higher asymmetric dimethylarginine and C-reactive protein levels exhibited the highest mortality (69.0% P=0.000). No differences in mortality were seen in diabetics. A joint effect was found between asymmetric dimethylarginine and C-reactive protein, explaining all-cause mortality (HR 15.21 CI 3.50-66.12 P=0.000).

CONCLUSIONS

Asymmetric dimethylarginine is an independent predictor of all-cause mortality in non-diabetic patients in hemodialysis. Other risk factors may overlap asymmetric dimethylarginine in people with diabetes. Inflammation dramatically increases the risk of death associated with high plasma asymmetric dimethylarginine in hemodialysis.

Excess years of life lost to COVID-19 and other causes of death by sex, neighbourhood deprivation, and region in England and Wales during 2020: A registry-based study

BACKGROUND

Deaths in the first year of the Coronavirus Disease 2019 (COVID-19) pandemic in England and Wales were unevenly distributed socioeconomically and geographically. However, the full scale of inequalities may have been underestimated to date, as most measures of excess mortality do not adequately account for varying age profiles of deaths between social groups. We measured years of life lost (YLL) attributable to the pandemic, directly or indirectly, comparing mortality across geographic and socioeconomic groups.

METHODS AND FINDINGS

We used national mortality registers in England and Wales, from 27 December 2014 until 25 December 2020, covering 3,265,937 deaths. YLLs (main outcome) were calculated using 2019 single year sex-specific life tables for England and Wales. Interrupted time-series analyses, with panel time-series models, were used to estimate expected YLL by sex, geographical region, and deprivation quintile between 7 March 2020 and 25 December 2020 by cause: direct deaths (COVID-19 and other respiratory diseases), cardiovascular disease and diabetes, cancer, and other indirect deaths (all other causes). Excess YLL during the pandemic period were calculated by subtracting observed from expected values. Additional analyses focused on excess deaths for region and deprivation strata, by age-group. Between 7 March 2020 and 25 December 2020, there were an estimated 763,550 (95% CI: 696,826 to 830,273) excess YLL in England and Wales, equivalent to a 15% (95% CI: 14 to 16) increase in YLL compared to the equivalent time period in 2019. There was a strong deprivation gradient in all-cause excess YLL, with rates per 100,000 population ranging from 916 (95% CI: 820 to 1,012) for the least deprived quintile to 1,645 (95% CI: 1,472 to 1,819) for the most deprived. The differences in excess YLL between deprivation quintiles were greatest in younger age groups; for all-cause deaths, a mean of 9.1 years per death (95% CI: 8.2 to 10.0) were lost in the least deprived quintile, compared to 10.8 (95% CI: 10.0 to 11.6) in the most deprived; for COVID-19 and other respiratory deaths, a mean of 8.9 years per death (95% CI: 8.7 to 9.1) were lost in the least deprived quintile, compared to 11.2 (95% CI: 11.0 to 11.5) in the most deprived. For all-cause mortality, estimated deaths in the most deprived compared to the most affluent areas were much higher in younger age groups, but similar for those aged 85 or over. There was marked variability in both all-cause and direct excess YLL by region, with the highest rates in the North West. Limitations include the quasi-experimental nature of the research design and the requirement for accurate and timely recording.

CONCLUSIONS

In this study, we observed strong socioeconomic and geographical health inequalities in YLL, during the first calendar year of the COVID-19 pandemic. These were in line with long-standing existing inequalities in England and Wales, with the most deprived areas reporting the largest numbers in potential YLL.

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.

Long-term glycemic variability and the risk of mortality in diabetic patients receiving peritoneal dialysis

Background

The large amount of glucose in the dialysate used in peritoneal dialysis (PD) likely affects the glycemic control. The aim of this study was to investigate the association between HbA1c variability, as a measure of long-term glycemic variability, and the risk of all-cause mortality in diabetic patients with PD.

Methods

325 patients with diabetes and ESRD were followed (2008–2018) in the Swedish Renal Registry. Patients were separated in seven groups according to level of HbA1c variability. The group with the lowest variability was denoted the reference. The ratio of the standard deviation (SD) to the mean of HbA1c, HbA1c (SD)/HbA1c (mean), i.e. the coefficient of variation (CV), was defined as HbA1c variability. Hazard ratios (HR) and 95% confidence intervals (CI) were examined using Cox regression analyses.

Results

During follow-up, 170 (52%) deaths occurred. The highest mortality was among patients with the second highest HbA1c variability, CV≥2.83 [n = 44 of which 68% patients died]. In the multivariate analyses where lowest HbA1c variability (CV≤0.51) was used as the reference group, HbA1c CV 2.83–4.60 (HR 3.15, 95% CI 1.78–5.55; p<0.001) and CV> 4.6 (HR 2.48, 95% CI 1.21–5.11; p = 0.014) were associated with increased risk of death.

Conclusion

The high risk of all-cause mortality in patients with diabetes and PD increased significantly with elevated HbA1c variability, as measure of long-term glycemic control. This indicates that stable glycemia is associated with an improvement of survival; whereas more severe glycemic fluctuations, possibly caused by radical changes in dialysis regimes or peritonitis, are associated with a higher risk of mortality in diabetic patients with PD.

Current forecast of COVID-19 in Mexico: A Bayesian and machine learning approaches

The COVID-19 pandemic has been widely spread and affected millions of people and caused hundreds of deaths worldwide, especially in patients with comorbilities and COVID-19. This manuscript aims to present models to predict, firstly, the number of coronavirus cases and secondly, the hospital care demand and mortality based on COVID-19 patients who have been diagnosed with other diseases. For the first part, I present a projection of the spread of coronavirus in Mexico, which is based on a contact tracing model using Bayesian inference. I investigate the health profile of individuals diagnosed with coronavirus to predict their type of patient care (inpatient or outpatient) and survival. Specifically, I analyze the comorbidity associated with coronavirus using Machine Learning. I have implemented two classifiers: I use the first classifier to predict the type of care procedure that a person diagnosed with coronavirus presenting chronic diseases will obtain (i.e. outpatient or hospitalised), in this way I estimate the hospital care demand; I use the second classifier to predict the survival or mortality of the patient (i.e. survived or deceased). I present two techniques to deal with these kinds of unbalanced datasets related to outpatient/hospitalised and survived/deceased cases (which occur in general for these types of coronavirus datasets) to obtain a better performance for the classification.

Trends in Diabetes Mortality in Urban and Rural China, 1987-2019: A Joinpoint Regression Analysis

Purpose

Diabetes mellitus is emerging as an epidemic worldwide, and the incidence and prevalence of diabetes have drastically changed in China over the past 30 years, but data on its mortality rate are scarce. This study aimed to analyze the time trends of mortality rates among patients with diabetes in the rural and urban population in China between 1987 and 2019.

Methods

The research data come from China's annual report on national health statistics and the Chinese Health Statistics Yearbook. Age-standardized mortality rates were calculated by using the direct method based on the World Standard Population from the WHO. Joinpoint regression analysis was employed to estimate the annual percent change and average annual percentage changes of mortality rates of diabetes mellitus.

Results

An overall trend for increment in diabetes mortality was observed. The crude mortality rates and age-standardized mortality rates of diabetes for urban and rural residents in China showed a significant increasing trend between 1987 and 2019. Mortality due to diabetes in urban areas has been higher than in rural areas for 30 years. However, due to the rapid increase of rural diabetes mortality in the past decade, the gap between the two gradually narrowed. The age-standardized mortality rates of diabetes increased by about 38.5% in urban areas and 254.9% in rural areas over the whole study period. In addition, the age-standardized mortality rate of females with diabetes was higher than that of males, but this pattern began to change in urban areas in 2012. Finally, the age-standardized mortality rates in the elderly population in China are higher with a faster growth rate, especially in rural areas.

Conclusion

The mortality rate of diabetes is on the rise in China. The rapid growth of the mortality rate of diabetes in rural areas leads to the reduction of the urban-rural gap. Male mortality rates in urban areas have surpassed those of women. At the same time, the mortality rate of diabetes showed obvious elder-group orientation. As China's population ages, the burden of death and disability caused by diabetes and its complications will continue to increase. These results indicate that diabetes has become a significant public health problem in China. Such an effect increases the demand for strategies aimed at the prevention and treatment of diabetes mellitus. In addition to the prevention and intervention of diabetes in high-risk groups, it is also necessary to establish diabetes screening networks to identify patients with mild symptoms. Early detection and timely intervention can effectively reduce the incidence and mortality of diabetes.

COVID-19-Induced New-Onset Diabetes: Trends and Technologies

The coronavirus disease 2019 (COVID-19) global pandemic continues to spread worldwide with approximately 216 million confirmed cases and 4.49 million deaths to date. Intensive efforts are ongoing to combat this disease by suppressing viral transmission, understanding its pathogenesis, developing vaccination strategies, and identifying effective therapeutic targets. Individuals with preexisting diabetes also show higher incidence of COVID-19 illness and poorer prognosis upon infection. Likewise, an increased frequency of diabetes onset and diabetes complications has been reported in patients following COVID-19 diagnosis. COVID-19 may elevate the risk of hyperglycemia and other complications in patients with and without prior diabetes history. It is unclear whether the virus induces type 1 or type 2 diabetes or instead causes a novel atypical form of diabetes. Moreover, it remains unknown if recovering COVID-19 patients exhibit a higher risk of developing new-onset diabetes or its complications going forward. The aim of this review is to summarize what is currently known about the epidemiology and mechanisms of this bidirectional relationship between COVID-19 and diabetes. We highlight major challenges that hinder the study of COVID-19-induced new-onset of diabetes and propose a potential framework for overcoming these obstacles. We also review state-of-the-art wearables and microsampling technologies that can further study diabetes management and progression in new-onset diabetes cases. We conclude by outlining current research initiatives investigating the bidirectional relationship between COVID-19 and diabetes, some with emphasis on wearable technology.

Effect of glycemic gap upon mortality in critically ill patients with diabetes

AIMS/INTRODUCTION

Hyperglycemia, hypoglycemia, and blood glucose fluctuation are associated with the outcome in critically ill patients, but the target of blood glucose control is debatable especially in patients with diabetes regarding the status of blood glucose control before admission to ICU. This study aimed to investigate the association between the glycemic gap which is calculated as the mean blood glucose level during the first 7 days after admission to ICU minus the A1C-derived average glucose and the outcome of critically ill patients with diabetes.

METHOD

This study was undertaken in two intensive care units (ICUs) with a total of 30 beds. Patients with diabetes who were expected to stay for more than 24 h were enrolled, the HbA1c was tested within 3 days after admission and converted to the A1C-derived average glucose (ADAG) by the equation: ADAG = [(HbA1c * 28.7) - 46.7 ] * 18-1 , arterial blood glucose measurements were four per day routinely during the first 7 days after admission, the APACHE II score within the first 24 h, the mean blood glucose level (MGL), standard deviation (SD), and coefficient of variation (CV) during the first 7 days were calculated for each person, the GAPadm and GAPmean were calculated as the admission blood glucose and MGL minus the ADAG, respectively, the incidence of moderate hypoglycemia (MH) and severe hypoglycemia (SH), the total dosage of glucocorticoids and average daily dosage of insulin within 7 days, the duration of renal replacement therapy (RRT), ventilator-free hours, and non-ICU stay days within 28 days were also collected. The enrolled patients were divided into a survival group and a nonsurvival group according to survival or not at 28 days and 1 year after admission, and the relationship between parameters derived from blood glucose and mortality in the enrolled critically ill patients was explored.

RESULTS

Five hundred and two patients were enrolled and divided into a survival group (n = 310) and a nonsurvival group (n = 192). It was shown that the two groups had a comparable level of HbA1c, the nonsurvivors had a greater APACHE II, MGL, SD, CV, GAPadm , GAPmean , and a higher incidence of hypoglycemia. A lesser duration of ventilator-free, non-ICU stay, and a longer duration of RRT were recorded in the nonsurvival group, who received a lower carbohydrate intake, a higher daily dosage of insulin and glucocorticoid. GAPmean had the greatest predictive power with an AUC of 0.820 (95%CI: 0.781-0.850), the cut-off value was 3.60 mmol/L (sensitivity 78.2% and specificity 77.3%). Patients with a low GAPmean tended to survive longer than the high GAPmean group 1 year after admission.

CONCLUSIONS

Glycemic GAP between the mean level of blood glucose within the first 7 days after admission to ICU and the A1C-derived average glucose was independently associated with a 28 day mortality of critically ill patients with diabetes, the predictive power extended to 1 year. The incidence of hypoglycemia was associated with mortality either.

Biodegradable Polymer DES (Ultimaster) vs. Magnesium Bioresorbable Scaffold (BRS Magmaris) in Diabetic Population with NSTE-ACS: A One-Year Clinical Outcome of Two Sirolimus-Eluting Stents

BACKGROUND

Cardiovascular disease (CVD) with significant involvement of coronary artery disease (CAD) remains a major cause of death and disability among the diabetic population. Although percutaneous coronary intervention (PCI) continues to evolve, type 2 diabetes mellitus (T2DM) is a well-established marker of poor clinical prognosis after PCI, which is mainly attributed to the rapid progression of atherosclerosis requiring recurrent revascularizations. Hence, the use of bioresorbable materials could provide some solution to this problem. Material and Methods. The study was divided into two arms. For the first one, we qualified 169 patients with NSTE-ACS treated with PCI who received the drug-eluting stent (DES) coated with a biodegradable polymer Ultimaster (Terumo, Tokyo, Japan). The second arm was composed of 193 patients with ACS who underwent PCI with a magnesium bioresorbable scaffold Magmaris (Biotronik, Berlin, Germany). Both arms were divided into two subsequent groups: the T2DM (59 and 72) and the non-DM (110 and 121, respectively). The primary outcomes were cardiovascular death, myocardial infarction, and in-stent thrombosis. The main secondary outcomes included target lesion failure (TLF) and were recorded at a 1-year-follow-up.

RESULTS

There were no significant differences between the diabetic and nondiabetic populations in primary endpoints or main secondary endpoints (TLF, scaffold restenosis, death from any reason, and other cardiovascular events) either in the Ultimaster or Magmaris group. At a 1-year-follow-up, the primary endpoint in the DM t.2 population was recorded in 2.7% Ultimaster vs. 5.1% Magmaris, respectively. At the same time, the TLF occurred in the diabetic group in 4.1% Magmaris and 3.3% in the Ultimaster arm, respectively.

CONCLUSION

Both, Ultimaster and Magmaris revealed relative safety and efficiency at a one-year follow-up in the diabetic population in ACS settings. The observed rates of TLF were low, which combined with a lack of in-stent thrombosis suggests that both investigated devices might be an interesting therapeutic option for diabetics with ACS. Nevertheless, further large randomized clinical trials are needed to confirm fully our results.

Diabetes Mellitus and COVID-19: Review Article

BACKGROUND AND AIMS

We aim to cover most of the current evidence on the mutual effect of diabetes & COVID-19 infection on each other and the management of the COVID-19 patients with diabetes.

METHODS

We utilized databases to review the current evidence related to diabetes mellitus and COVID-19.

RESULTS

We discussed the most recent evidence of diabetes milieus and COVID-19 regarding risk factors, management, complications, and telemedicine.

CONCLUSION

Diabetes mellitus is associated with a significant risk of complications, extended hospital stays, and mortality in COVID-19 infected patients.

Mortality and Clinical Outcomes among Patients with COVID-19 and Diabetes

Background Diabetes mellitus (DM) is a decisive risk factor for severe illness in coronavirus disease 2019 (COVID-19). India is home to a large number of people with DM, and many of them were infected with COVID-19. It is critical to understand the impact of DM on mortality and other clinical outcomes of COVID-19 infection from this region. Aims The primary objective of our study was to analyze the mortality rate in people with DM infected with COVID-19. The secondary objectives were to assess the effect of various comorbidities on mortality and study the impact of DM on other clinical outcomes. Methods This is a retrospective study of COVID-19 infected patients admitted to a tertiary care hospital in north India in the early phase of the pandemic. Results Of the 1211 cases admitted, 19 were excluded because of incomplete data, and 1192 cases were finally considered for analysis. DM constituted 26.8% of total patients. The overall mortality rate was 6.1%, and the rate was 10.7% in the presence of diabetes (p < 0.01, OR 2.55). In univariate analysis, increased age, chronic kidney disease (CKD), coronary artery disease (CAD), stroke, and cancer were associated with mortality. On multiple logistic regression, the independent predictors of mortality were CAD, CKD, and cancer. Breathlessness and low SpO₂ at presentation, extensive involvement in CXR, and elevated ANC/ALC ratio were also significantly associated with mortality. Conclusions The presence of comorbidities such as DM, hypertension, CAD, CKD, and cancer strongly predict the risk of mortality in COVID-19 infection. Early triaging and aggressive therapy of patients with these comorbidities can optimize clinical outcomes.

Association of tooth loss with morbidity and mortality by diabetes status in older adults: a systematic review

OBJECTIVE

This systematic review assesses the association of tooth loss (TL), as the exposure, with morbidity and mortality by diabetes mellitus (DM) status, as the outcome, in older adults.

BACKGROUND

Individuals with DM have higher prevalence of severe TL and increased risk of developing morbidities and mortality. No systematic review has evaluated the association between TL with morbidity and mortality by DM status.

MATERIAL AND METHODS

Comprehensive searches used multiple publication databases containing reports published between 01/01/2000 and 04/21/2021. Two authors independently evaluated included studies for quality and risk of bias using the Critical Appraisal Skills Programme (CASP) checklist for cohort and Center for Evidence-Based Medicine (CEBM) critical appraisal sheet for cross-sectional studies, while a third author arbitrated decisions to resolve disagreements.

RESULTS

Thirteen studies met the inclusion criteria: eight cross-sectional and five cohort. Qualitative review of the included studies indicated TL is associated with increased incidence and prevalence of DM. TL is also associated with DM-related morbidities including greater prevalence of heart disease, diabetic retinopathy, metabolic syndrome; poorer health-related quality of life; poorer survival of participants with chronic kidney disease; and increased medical expenditure. Overall, the quality of the evidence reviewed was medium, as per the Oxford Centre for Evidence-Based Medicine 2011 Levels of Evidence.

CONCLUSIONS/PRACTICAL IMPLICATIONS

This review found significant associations of TL with prevalence and incidence of DM and adverse DM-related outcomes. An interprofessional team-care approach that includes an oral health component could benefit the prevention and management of DM.

Mortality risk factors of COVID-19 infection in kidney transplantation recipients: a systematic review and meta-analysis of cohorts and clinical registries

Kidney transplantation recipients (KTR) with coronavirus disease 2019 (COVID-19) are at higher risk of death than general population. However, mortality risk factors in KTR are still not clearly identified. Our objective was to systematically analyze published evidence for risk factors associated with mortality in COVID-19 KTR. Electronic databases were searched for eligible studies on 1 August 2021. All prospective and retrospective studies of COVID-19 in KTR were considered eligible without language restriction. Since data in case reports and series could potentially be subsets of larger studies, only studies with ≥ 50 patients were included. Random-effects model meta-analysis was used to calculate weighted mean difference (WMD) and pooled odds ratio (OR) of factors associated with mortality. From a total 1,137 articles retrieved, 13 were included in the systematic review and meta-analysis comprising 4,440 KTR. Compared with survivors, non-survivors were significantly older (WMD 10.5 years, 95% CI 9.3-11.8). KTR of deceased donor were at higher risk of death (OR 1.73, 95% CI 1.10-2.74). Comorbidities including diabetes mellitus, cardiovascular disease, and active cancer significantly increased mortality risk. KTR with dyspnea (OR 5.68, 95% CI 2.11-15.33) and pneumonia (OR 10.64, 95% CI 3.37-33.55) at presentation were at higher mortality risk, while diarrhea decreased the risk (OR 0.61, 95% CI 0.47-0.78). Acute kidney injury was associated with mortality (OR 3.24, 95% CI 1.36-7.70). Inflammatory markers were significantly higher in the non-survivors, including C-reactive protein, procalcitonin, and interleukine-6. A number of COVID-19 mortality risk factors were identified from KTR patient characteristics, presenting symptoms, and laboratory investigations. KTR with these risk factors should receive more intensive monitoring and early therapeutic interventions to optimize health outcomes.

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.

Clinical outcomes in patients infected with different SARS-CoV-2 variants at one hospital during three phases of the COVID-19 epidemic in Marseille, France

Objectives

To compare the demographics, clinical characteristics and severity of patients infected with nine different SARS-CoV-2 variants, during three phases of the COVID-19 epidemic in Marseille.

Methods

A single centre retrospective cohort study was conducted in 1760 patients infected with SARS-CoV-2 of Nextstrain clades 20A, 20B, and 20C (first phase, February–May 2020), Pangolin lineages B.1.177 (we named Marseille-2) and B.1.160 (Marseille-4) variants (second phase, June–December 2020), and B.1.1.7 (alpha), B.1.351 (beta), P.1 (gamma) and A.27 (Marseille-501) variants (third phase, January 2021-today). Outcomes were the occurrence of clinical failures, including hospitalisation, transfer to the intensive-care unit, and death.

Results

During each phase, no major differences were observed with regards to age and gender distribution, the prevalence of chronic diseases, and clinical symptoms between variants circulating in a given phase. The B.1.177 and B.1.160 variants were associated with more severe outcomes. Infections occurring during the second phase were associated with a higher rate of death as compared to infections during the first and third phases. Patients in the second phase were more likely to be hospitalised than those in the third phase. Patients infected during the third phase were more frequently obese than others.

Conclusion:

A large cohort study is recommended to evaluate the transmissibility and to better characterise the clinical severity of emerging variants.

Institutional mortality rate and cause of death at health facilities in Ghana between 2014 and 2018

BACKGROUND

The epidemiological transition, touted as occurring in Ghana, requires research that tracks the changing patterns of diseases in order to capture the trend and improve healthcare delivery. This study examines national trends in mortality rate and cause of death at health facilities in Ghana between 2014 and 2018.

METHODS

Institutional mortality data and cause of death from 2014-2018 were sourced from the Ghana Health Service's District Health Information Management System. The latter collates healthcare service data routinely from government and non-governmental health institutions in Ghana yearly. The institutional mortality rate was estimated using guidelines from the Ghana Health Service. Percent change in mortality was examined for 2014 and 2018. In addition, cause of death data were available for 2017 and 2018. The World Health Organisation's 11th International Classification for Diseases (ICD-11) was used to group the cause of death.

RESULTS

Institutional mortality decreased by 7% nationally over the study period. However, four out of ten regions (Greater Accra, Volta, Upper East, and Upper West) recorded increases in institutional mortality. The Upper East (17%) and Volta regions (13%) recorded the highest increase. Chronic non-communicable diseases (NCDs) were the leading cause of death in 2017 (25%) and 2018 (20%). This was followed by certain infectious and parasitic diseases (15% for both years) and respiratory infections (10% in 2017 and 13% in 2018). Among the NCDs, hypertension was the leading cause of death with 2,243 and 2,472 cases in 2017 and 2018. Other (non-ischemic) heart diseases and diabetes were the second and third leading NCDs. Septicaemia, tuberculosis and pneumonia were the predominant infectious diseases. Regional variations existed in the cause of death. NCDs showed more urban-region bias while infectious diseases presented more rural-region bias.

CONCLUSIONS

This study examined national trends in mortality rate and cause of death at health facilities in Ghana. Ghana recorded a decrease in institutional mortality throughout the study. NCDs and infections were the leading causes of death, giving a double-burden of diseases. There is a need to enhance efforts towards healthcare and health promotion programmes for NCDs and infectious diseases at facility and community levels as outlined in the 2020 National Health Policy of Ghana.

Impact of insulin therapy on the mortality of acute heart failure patients with diabetes mellitus

BACKGROUND

Patients with diabetes mellitus (DM) have a higher prevalence of heart failure (HF) than those without it. Approximately 40 % of HF patients have DM and they tend to have poorer outcomes than those without DM. This study evaluated the impact of insulin therapy on mortality among acute HF patients.

METHODS

A total of 1740 patients from the Korean Acute Heart Failure registry with DM were included in this study. The risk of all-cause mortality according to insulin therapy was assessed using the Cox proportional hazard models with inverse probability of treatment weighting to balance the clinical characteristics (pretreatment covariates) between the groups.

RESULTS

DM patients had been treated with either oral hypoglycemic agents (OHAs) alone (n = 620), insulin alone (n = 682), or insulin combined with OHAs (n = 438). The insulin alone group was associated with an increased mortality risk compared with the OHA alone group (HR = 1.41, 95 % CI 1.21-1.66]). Insulin therapy combined with OHAs also showed an increased mortality risk (HR = 1.29, 95 % CI 1.14-1.46) compared with the OHA alone group. Insulin therapy was consistently associated with increased mortality risk, regardless of the left ventricular ejection fraction (LVEF) or HF etiology. A significant increase in mortality was observed in patients with good glycemic control (HbA1c < 7.0 %) receiving insulin, whereas there was no significant association in patients with poor glycemic control (HbA1c ≥ 7.0%).

CONCLUSIONS

Insulin therapy was found to be associated with increased mortality compared to OHAs. The insulin therapy was harmful especially in patients with low HbA1c levels which may suggest the necessity of specific management strategies and blood sugar targets when using insulin in patients with HF.

Effect of a patient-centered hypertension delivery strategy on all-cause mortality: Secondary analysis of SEARCH, a community-randomized trial in rural Kenya and Uganda

BACKGROUND

Hypertension treatment reduces morbidity and mortality yet has not been broadly implemented in many low-resource settings, including sub-Saharan Africa (SSA). We hypothesized that a patient-centered integrated chronic disease model that included hypertension treatment and leveraged the HIV care system would reduce mortality among adults with uncontrolled hypertension in rural Kenya and Uganda.

METHODS AND FINDINGS

This is a secondary analysis of the SEARCH trial (NCT:01864603), in which 32 communities underwent baseline population-based multidisease testing, including hypertension screening, and were randomized to standard country-guided treatment or to a patient-centered integrated chronic care model including treatment for hypertension, diabetes, and HIV. Patient-centered care included on-site introduction to clinic staff at screening, nursing triage to expedite visits, reduced visit frequency, flexible clinic hours, and a welcoming clinic environment. The analytic population included nonpregnant adults (≥18 years) with baseline uncontrolled hypertension (blood pressure ≥140/90 mm Hg). The primary outcome was 3-year all-cause mortality with comprehensive population-level assessment. Secondary outcomes included hypertension control assessed at a population level at year 3 (defined per country guidelines as at least 1 blood pressure measure <140/90 mm Hg on 3 repeated measures). Between-arm comparisons used cluster-level targeted maximum likelihood estimation. Among 86,078 adults screened at study baseline (June 2013 to July 2014), 10,928 (13%) had uncontrolled hypertension. Median age was 53 years (25th to 75th percentile 40 to 66); 6,058 (55%) were female; 677 (6%) were HIV infected; and 477 (4%) had diabetes mellitus. Overall, 174 participants (3.2%) in the intervention group and 225 participants (4.1%) in the control group died during 3 years of follow-up (adjusted relative risk (aRR) 0.79, 95% confidence interval (CI) 0.64 to 0.97, p = 0.028). Among those with baseline grade 3 hypertension (≥180/110 mm Hg), 22 (4.9%) in the intervention group and 42 (7.9%) in the control group died during 3 years of follow-up (aRR 0.62, 95% CI 0.39 to 0.97, p = 0.038). Estimated population-level hypertension control at year 3 was 53% in intervention and 44% in control communities (aRR 1.22, 95% CI 1.12 to 1.33, p < 0.001). Study limitations include inability to identify specific causes of death and control conditions that exceeded current standard hypertension care.

CONCLUSIONS

In this cluster randomized comparison where both arms received population-level hypertension screening, implementation of a patient-centered hypertension care model was associated with a 21% reduction in all-cause mortality and a 22% improvement in hypertension control compared to standard care among adults with baseline uncontrolled hypertension. Patient-centered chronic care programs for HIV can be leveraged to reduce the overall burden of cardiovascular mortality in SSA.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01864603.

Detrimental effect of diabetes and hypertension on the severity and mortality of COVID-19 infection: A multi-center case-control study from India

AIMS

This study aims to find a quantitative association between the presence of co-existing diabetes mellitus (DM) and/or hypertension (HTN) with COVID-19 infection severity and mortality.

METHODS

A total of 813 patients with a positive COVID-19 were included. A case-control design was used to dissect the association between DM and HTN with COVID-19 severity and mortality.

RESULTS

According to MOHFW guidelines, 535 (65.7%) patients had mild, 160 (19.7%) patients had moderate, and 118 (14.5%) patients had severe disease outcomes including mortality in 52 patients. Age, Neutrophil%, and Diabetes status were significantly associated with severe COVID-19 infection. After adjusting for age, patients with diabetes were 2.46 times more likely to have severe disease (Chi-squared = 18.89, p-value<0.0001) and 2.11 times more likely to have a fatal outcome (Chi-squared = 6.04, p-value = 0.014). However, we did not find evidence for Hypertension modifying the COVID-19 outcomes in Diabetic patients.

CONCLUSION

COVID-19 severity and mortality both were significantly associated with the status of DM and its risk may not be modified by the presence of HTN.

Clinical characteristics and prognostic implications of diabetes and myocardial injury in patients admitted to the emergency room

BACKGROUND

This study aimed to investigate the clinical features and prognosis of diabetes and myocardial injury in patients admitted to the emergency department.

METHODS

We analyzed the clinical data of all consecutive patients admitted to the emergency department during the years 2012 and 2013 with at least 1 cardiac Troponin I (cTnI Ultra Siemens, Advia Centaur) determination, and were classified according to the status of diabetes mellitus (DM) and myocardial injury (MI). Clinical events were evaluated in a 4-year follow-up.

RESULTS

A total of 3622 patients were classified according to the presence of DM (n = 924 (25.55%)) and MI (n = 1049 (28.96%)). The proportion of MI in patients with DM was 40% and 25% in patients without DM. Mortality during follow-up was 10.9% in non-DM patients without MI, 21.3% in DM patients without MI, 40.1% in non-DM patients with MI, and 52.8% in DM patients with MI. A competitive risk model was used to obtain the Hazard Ratio (HR) for readmission for myocardial infarction or heart failure. There was a similar proportion of readmission for myocardial infarction and heart failure at a four-year follow-up in patients with DM or MI, which was much higher when DM was associated with MI, with respect to patients without DM or MI. The HR (95% Coefficient Interval) for myocardial infarction in the DM without MI, non-DM with MI, and DM with MI groups with respect to the non-DM without MI group was 2511 (1592-3960), 2682 (1739-4138), and 5036 (3221-7876), respectively. The HR (95% CI) for the risk of readmission for heart failure in the DM without MI, non-DM with MI, and DM with MI groups with respect to the non-DM without MI group was 2663 (1825-3886), 2562 (1753-3744) and 4292 (2936-6274), respectively.

CONCLUSIONS

The association of DM and MI in patients treated in an Emergency Service identifies patients at very high risk of mortality and cardiovascular events.

Impact of diabetes mellitus on in-hospital mortality in adult patients with COVID-19: a systematic review and meta-analysis

BACKGROUND

The novel coronavirus disease 2019 (COVID-19) has spread worldwide since the beginning of 2020, placing the heavy burden on the health systems all over the world. The population that particularly has been affected by the pandemic is the group of patients suffering from diabetes mellitus. Having taken the public health in considerations, we have decided to perform a systematic review and meta-analysis of diabetes mellitus on in-hospital mortality in patients with COVID-19.

METHODS

A systematic literature review (MEDLINE, EMBASE, Web of Science, Scopus, Cochrane) including all published clinical trials or observational studies published till December 10, 2020, was performed using following terms "diabetes mellitus" OR "diabetes" OR "DM" AND "survival" OR "mortality" AND "SARS-CoV-2" OR "COVID-19".

RESULTS

Nineteen studies were included out of the 7327 initially identified studies. Mortality of DM patients vs non-DM patients was 21.3 versus 6.1%, respectively (OR = 2.39; 95%CI: 1.65, 3.64; P < 0.001), while severe disease in DM and non-DM group varied and amounted to 34.8% versus 22.8% (OR = 1.43; 95%CI: 0.82, 2.50; P = 0.20). In the DM group, the complications were observed far more often when compared with non-DM group, both in acute respiratory distress (31.4 vs. 17.2%; OR = 2.38; 95%CI:1.80, 3.13; P < 0.001), acute cardiac injury (22.0% vs. 12.8%; OR = 2.59; 95%CI: 1.81, 3.73; P < 0.001), and acute kidney injury (19.1 vs. 10.2%; OR = 1.97; 95%CI: 1.36, 2.85; P < 0.001).

CONCLUSIONS

Based on the findings, we shall conclude that diabetes is an independent risk factor of the severity of COVID-19 in-hospital settings; therefore, patients with diabetes shall aim to reduce the exposure to the potential infection of COVID-19.

High Fibrosis-4 Index Is Related with Worse Clinical Outcome in Patients with Coronavirus Disease 2019 and Diabetes Mellitus: A Multicenter Observational Study

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.

The sex-related discrepancy in laboratory parameters of severe COVID-19 patients with diabetes: A retrospective cohort study

AIM

This study aimed at providing evidence to consider sex differences in interpretations of laboratory parameters of severe COVID-19 patients with diabetes.

METHODS

For 118 diabetic patients, laboratory measurements and clinical outcomes were compared between males and females. This study also compared inflammatory ratios obtained from combinations of six inflammatory markers between the two groups. The risk factors for mortality were identified through logistic regression.

RESULTS

Males were 54 (45.8%) and females were 64 (54.2%). Males showed a significant increase in ALT (P = 0.003), CRP (P = 0.03), mean platelet volume (MPV)-to-lymphocyte ratio (P = 0.001), and C-reactive protein-to-albumin ratio (P = 0.044), whereas females had a significant increase in lymphocytes (P < 0.005) and MPV (P = 0.01). In all participants, multivariate analysis illustrated that older age, male sex, increased serum total bilirubin, and decreased PO2 were significant independent predictors of mortality (P < 0.05).

CONCLUSION

In severe COVID-19 patients with diabetes, there were significant sex differences in many laboratory characteristics with a higher risk of mortality among males.

Morbidity and mortality outcomes of COVID-19 patients with and without hypertension in Lagos, Nigeria: a retrospective cohort study

BACKGROUND

The current pandemic of coronavirus disease (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has shown epidemiological and clinical characteristics that appear worsened in hypertensive patients. The morbidity and mortality of the disease among hypertensive patients in Africa have yet to be well described.

METHODS

In this retrospective cohort study all confirmed COVID-19 adult patients (≥18 years of age) in Lagos between February 27 to July 62,020 were included. Demographic, clinical and outcome data were extracted from electronic medical records of patients admitted at the COVID-19 isolation centers in Lagos. Outcomes included dying, being discharged after recovery or being evacuated/transferred. Descriptive statistics considered proportions, means and medians. The Chi-square and Fisher's exact tests were used in determining associations between variables. Kaplan-Meier survival analysis and Cox regression were performed to quantify the risk of worse outcomes among hypertensives with COVID-19 and adjust for confounders. P-value ≤0.05 was considered statistically significant.

RESULTS

A total of 2075 adults with COVID-19 were included in this study. The prevalence of hypertension, the most common comorbidity, was 17.8% followed by diabetes (7.2%) and asthma (2.0%). Overall mortality was 4.2% while mortality among the hypertensives was 13.7%. Severe symptoms and mortality were significantly higher among the hypertensives and survival rates were significantly lowered by the presence of additional comorbidity to 50% from 91% for those with hypertension alone and from 98% for all other patients (P < 0.001). After adjustment for confounders (age and sex), severe COVID-19and death were higher for hypertensives {severe/critical illness: HR = 2.41, P = 0.001, 95%CI = 1.4-4.0, death: HR = 2.30, P = 0.001, 95%CI = 1.2-4.6, for those with hypertension only} {severe/critical illness: HR = 3.76, P = 0.001, 95%CI = 2.1-6.4, death: crude HR = 6.63, P = 0.001, 95%CI = 3.4-1.6, for those with additional comorbidities}. Hypertension posed an increased risk of severe morbidity (approx. 4-fold) and death (approx. 7-fold) from COVID-19 in the presence of multiple comorbidities.

CONCLUSION

The potential morbidity and mortality risks of hypertension especially with other comorbidities in COVID-19 could help direct efforts towards prevention and prognostication. This provides the rationale for improving preventive caution for people with hypertension and other comorbidities and prioritizing them for future antiviral interventions.

Admission hyperglycemia as an independent predictor of long-term prognosis in acute myocardial infarction patients without diabetes: A retrospective study

AIMS/INTRODUCTION

The predictive value of admission hyperglycemia in the long-term prognosis of acute myocardial infarction patients is still controversial. We aimed to investigate this value based on the diabetes status.

MATERIALS AND METHODS

We carried out a multicenter, retrospective study of 1,288 acute myocardial infarction patients enrolled in 11 hospitals between March 2014 and June 2019 in Chengdu, China. The patients were classified into those with diabetes and those without diabetes, each was further divided into: hyperglycemia and non-hyperglycemia subgroups, according to the optimal cut-off value of the blood glucose to predict all-cause mortality during follow up. The end-points were all-cause death and major adverse cardiovascular and cerebrovascular events, including all-cause death, non-fatal myocardial infarction, vessel revascularization and non-fatal stroke.

RESULTS

In the follow-up period of 15 months, we observed 210 (16.3%), 6 (0.5%), 57 (4.4%) and 34 (2.6%) cases of death, non-fatal myocardial infarction, revascularization and non-fatal stroke, respectively. The optimal cut-off values of admission blood glucose for patients with diabetes and patients without diabetes to predict all-cause mortality during follow up were 14.80 and 6.77 mmol/L, respectively. We divided patients with diabetes (n = 331) into hyperglycemia (n = 92) and non-hyperglycemia (n = 239), and patients without diabetes (n = 897) into hyperglycemia (n = 425) and non-hyperglycemia (n = 472). The cumulative rates of all-cause death and major adverse cardiovascular and cerebrovascular events among the patients in each hyperglycemia group was higher than that in the corresponding non-hyperglycemia group (P < 0.001). In patients without diabetes, admission hyperglycemia was an independent predictor of all-cause mortality and major adverse cardiovascular and cerebrovascular events.

CONCLUSION

Admission hyperglycemia was an independent predictor for long-term prognosis in acute myocardial infarction patients without diabetes.

Risk factors for COVID-19 hospitalisation and death in people living with diabetes: A virtual cohort study from the Western Cape Province, South Africa

BACKGROUND

COVID-19 outcomes and risk factors, including comorbidities and medication regimens, in people living with diabetes (PLWD) are poorly defined for low- and middle-income countries.

METHODS

The Provincial Health Data Centre (Western Cape, South Africa) is a health information exchange collating patient-level routine health data for approximately 4 million public sector health care seekers. Data from COVID-19 patients diagnosed between March and July 2020, including PLWD, were analysed to describe risk factors, including dispensed diabetes medications and comorbidities, and their association with COVID-19 outcomes in this population.

FINDINGS

There were 64,476 COVID-19 patients diagnosed. Of 9305 PLWD, 44.9% were hospitalised, 4.0% admitted to ICU, 0.6% received ventilation and 15.4% died. In contrast, proportions of COVID-19 patients without diabetes were: 12.2% hospitalised, 1.0% admitted, 0.1% ventilated and 4.6% died. PLWD were significantly more likely to be admitted (OR:3.73, 95 %CI: 3.53, 3.94) and to die (OR:3.01, 95 %CI: 2.76,3.28). Significant hospitalised risk factors included HIV infection, chronic kidney disease, current TB, male sex and increasing age. Significant risk factors for mortality were CKD, male sex, HIV infection, previous TB and increasing age. Pre-infection use of insulin was associated with a significant increased risk for hospitalisation (OR:1·39, 95 %CI:1·24,1·57) and mortality (OR1·49, 95 %CI:1·27; 1·74) and metformin was associated with a reduced risk for hospitalisation (OR:0·62,95 %CI:0·55, 0·71) and mortality (OR 0·77, 95 %CI:0·64; 0·92).

INTERPRETATION

Using routine health data from this large virtual cohort, we have described the association of infectious and noncommunicable comorbidities as well as pre-infection diabetes medications with COVID-19 outcomes in PLWD in the Western Cape, South Africa.

FUNDING

This research was funded in part, by the Wellcome Trust 203135/Z/16/Z, through support of NT. For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. The Wellcome Centre for Infectious Diseases Research in Africa is supported by core funding from the Wellcome Trust [203135/Z/16/Z]. NT receives funding from the CIDRI-Africa Wellcome Trust grant (203135/Z/16/Z), and NT and TT receive funding from the NIH H3ABioNET award (U24HG006941). NT receives funding from the UKRI/MRC (MC_PC_MR/T037733/1).

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.

Prevalence and impact of comorbidities on disease prognosis among patients with COVID-19 in Bangladesh: A nationwide study amid the second wave

BACKGROUND

Socio-demographics and comorbidities are involved in determining the severity and fatality in patients with COVID-19 suggested by studies in various countries, but study in Bangladesh is insufficient.

AIMS

We designed the study to evaluate the association of sociodemographic and comorbidities with the prognosis of adverse health outcomes in patients with COVID-19 in Bangladesh.

METHODS

A multivariate retrospective cohort study was conducted on data from 966 RT-PCR positive patients from eight divisions during December 13, 2020, to February 13, 2021. Variables included sociodemographic, comorbidities, symptoms, Charlson comorbidity index (CCI) and access to health facilities. Major outcome was fatality. Secondary outcomes included hospitalization, duration of hospital stay, requirement of mechanical ventilation and severity.

RESULTS

Male (65.8%, 636 of 966) was predominant and mean age was 39.8 ± 12.6 years. Fever (79%), dry cough (55%), and loss of test/smell (51%) were frequent and 74% patients had >3 symptoms. Fatality was recorded in 10.5% patients. Comorbidities were found in 44% patients. Hypertension (21.5%) diabetes (14.6%), and cardiovascular diseases (11.3%) were most prevalent. Age >60 years (OR: 4.83, 95% CI: 2.45-6.49), and CCI >3 (OR: 5.48, 95% CI: 3.95-7.24) were predictors of hospitalizations. CCI >4 (aOR: 3.41, 95% CI: 2.57-6.09) was predictor of severity. Age >60 years (aOR: 3.77, 95% CI: 1.07-6.34), >3 symptoms (aOR: 2.14, 95% CI: 0.97-4.91) and CCI >3 vs. CCI <3 (aOR: 5.23, 95% CI: 3.77-8.09) were independently associated with fatality.

CONCLUSIONS

Increased age, >3 symptoms, increasing comorbidities, higher CCI were associated with increased hospitalization, severity and fatality in patients with COVID-19.

Predictors of COVID-19 related death in diabetes patients: A case-control study in Iran

BACKGROUND

Identifying the predictors of COVID-19 related death in diabetes patients can assist physicians for detecting risk factors related to the worse outcome in these patients. In this study we investigated the predictors of the death in patients with diabetes compared with non-diabetic COVID-19 patients.

METHODS

In the present case-control study, the case group were diabetic patients with COVID-19 and the control group included Non-diabetic COVID-19 patients. The data source regarding the demographic characteristics, clinical symptoms, laboratory, and radiological findings on admission as well as the complications, treatment, and outcomes during hospitalization were gathered from their medical record through two trained nurses. Adjusted and unadjusted odds ratios (OR) estimate were calculated using the simple and multiple logistic regression through backward model.

RESULTS

The mean (SD) age of the case group was higher than that of the control group; [65.24 (12.40) years vs. 59.35 (17.34) years, respectively (P < 0.001)]. Results of the adjusted logistic regression model showed that, advanced age (+60 year) (OR = 5.13, P = 0.006), addiction (OR = 5.26, P = 0.033), high level of Blood urea nitrogen (OR = 5.85, P < 0.001), and high level of Alkaline Phosphatase (OR = 3.38, P = 0.012) in diabetic patients were significantly associated with increase the odds of death in COVID-19 patients.

CONCLUSION

We found that in COVID-19 patients with diabetes; advanced age, addiction, high level of BUN and Alp and in non-diabetic COVID-19 patients advanced age, dyspnea, high level of BUN and SGOT were associated with increase risk of death in these patients.

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.

Can the in-hospital mortality gap between STEMI patients with and without diabetes mellitus be reduced? The cardio-renal hypothesis

BACKGROUND AND AIMS

Diabetes mellitus (DM) is a frequent comorbidity in ST-elevation-myocardial infarction (STEMI) patients and carries a higher risk of in-hospital mortality. We recently demonstrated that the higher in-hospital mortality of STEMI patients with DM, when compared to that of patients without DM, is mainly associated with their more frequent cardiac and renal dysfunction. These exploratory results prompted us to hypothesize that this higher risk in DM patients is mediated by their lower cardio-renal functional reserve.

METHODS AND RESULTS

We included 5152 STEMI patients treated with primary angioplasty. By using an advanced statistical methodology (path analysis), able to clarify the putative causal paths between variables of interest, we reported that the higher in-hospital mortality of STEMI patients with DM is possibly caused by its adverse impact on cardio-renal function.

CONCLUSION

This statistical approach allows to reinforce the well-known notion that DM is associated with an increased in-hospital mortality risk in STEMI and sheds lights on the causal relationship among DM, cardio-renal dysfunction, and higher in-hospital mortality. Whether the mortality gap between DM and non-DM patients with STEMI can be reduced by pharmacological strategies combining cardio-renal protective effects is an intriguing question that deserves an answer in the future.

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.

Trends in the effects of pre-transplant diabetes on mortality and cardiovascular events after kidney transplantation

AIMS/INTRODUCTION

It is not clear whether survival in kidney transplant recipients with pre-transplant diabetes has improved over the past decades. We compared the rates of mortality and major adverse cardiovascular events (MACE) after renal transplantation in patients with and without pre-transplant diabetes. Furthermore, we investigated whether transplant era and recipient age affected the association between diabetes status and adverse events.

MATERIALS AND METHODS

This retrospective cohort study included 691 patients who underwent renal transplantation between 1994 and 2016 at a single tertiary center. We compared the incidences of post-transplant mortality and four-point MACE in patients with and without pre-transplant diabetes using Kaplan-Meier analysis and the Cox proportional hazard model, and assessed the interactions between diabetes status and transplant era and recipient age.

RESULTS

Of 691 kidney recipients, 143 (20.7%) had pre-transplant diabetes. The mean follow-up duration was 94.5 months. Kaplan-Meier analysis showed that patients with pre-transplant diabetes had higher incidences of post-transplant mortality and four-point MACE compared with those without pre-transplant diabetes (log-rank test, P < 0.001 for both). After adjusting for potential confounding factors, pre-transplant diabetes was associated with an increased risk of post-transplant mortality and four-point MACE (hazard ratio 1.90, 95% confidence interval 1.05-3.44, P = 0.034; and hazard ratio 1.75; 95% confidence interval 1.02-3.00, P = 0.043, respectively). The associations between pre-transplant diabetes status and all-cause mortality and four-point MACE were not affected by transplant era or recipient age.

CONCLUSIONS

Pre-transplant diabetes remains a significant risk factor for mortality and four-point MACE in kidney transplant recipients.

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.

Copeptin and stress-induced hyperglycemia in critically ill patients: A prospective study

Objectives

Copeptin, an equimolar indicator of serum antidiuretic hormone levels, has been associated with higher mortality in critically ill patients and with the development of diabetes in the general population. The aim of the present study was to investigate the association of copeptin levels with glycemic parameters in critically ill patients and to compare the time-course of copeptin in survivors and non-survivors.

Design

Prospective cohort study.

Patients

From June to October 2019, critically ill patients were prospectively enrolled and followed for 90 days.

Measurements

Plasma copeptin levels were determined at intensive care unit (ICU) admission (copeptin T1), 24 h (copeptin T2), and 48 h (copeptin T3) after study entry. Blood glucose and glycated hemoglobin levels were measured. ICU, in-hospital, and 90-day mortality, and length of stay in the ICU and hospital were evaluated.

Results

104 patients were included. No significant correlation was detected between copeptin levels and blood glucose (r = -0.17, p = 0.09), HbA1c (r = 0.01, p = 0.9), glycemic gap (r = -0.16, p = 0.11), and stress hyperglycemia ratio (r = -0.14, p = 0.16). Copeptin T3 levels were significantly higher in survivors than in non-survivors at hospital discharge (561 [370–856] vs 300 [231–693] pg/mL, p = 0.015) and at 90 days (571 [380–884] vs 300 [232–698] pg/mL, p = 0.03).

Conclusions

No significant correlations were found between copeptin levels and glycemic parameters, suggesting that copeptin is not a relevant factor in the induction of hyperglycemia during critical illness. Copeptin levels at ICU day 3 were higher in survivors than in non-survivors.