scholarly journals Trends in all-cause mortality among people with diagnosed diabetes in high-income settings: a multicountry analysis of aggregate data

2022 ◽  
Author(s):  
Dianna J Magliano ◽  
Lei Chen ◽  
Bendix Carstensen ◽  
Edward W Gregg ◽  
Meda E Pavkov ◽  
...  
Keyword(s):  
Aggregate Data ◽  
High Income ◽  
All Cause Mortality ◽  
Diagnosed Diabetes

Abstract MP53: 1,5-anhydroglucitol to Identify Older Adults with Diabetes at Risk of Hospitalization and All-cause Mortality

Circulation ◽  
2018 ◽  
Vol 137 (suppl_1) ◽  
Author(s):  
Bethany Warren ◽  
Andreea Rawlings ◽  
A. Richey Sharrett ◽  
Josef Coresh ◽  
Anna Kottgen ◽  
...  
Keyword(s):  
Older Adults ◽  
At Risk ◽  
Negative Binomial ◽  
Cox Regression ◽  
Negative Binomial Regression ◽  
Glycemic Variability ◽  
Adverse Outcomes ◽  
Improve Risk Stratification ◽  
All Cause Mortality ◽  
Diagnosed Diabetes

Introduction: Older adults with diabetes have variable prognosis. There is critical need to improve risk stratification among this population to understand who is most likely to experience adverse outcomes. Low 1,5-anhydroglucitol (1,5-AG) is a biomarker of glycemic variability and has demonstrated value for identification of middle-aged adults with diabetes at risk for major clinical outcomes. Total hospitalizations are a useful summary measure of poor health outcomes. It is unknown whether 1,5-AG can identify older adults at risk for hospitalizations and all-cause mortality. Methods: We included 2,061 participants from the Atherosclerosis Risk in Communities (ARIC) Study with diagnosed diabetes who attended the 2011-2013 visit. We dichotomized 1,5-AG (≥6μg/mL; <6μg/mL) and followed participants until December 31, 2015. We examined the associations of 1,5-AG with total and diabetes-related hospitalizations using negative binomial regression and all-cause mortality using Cox regression. Results: Participants ranged in age from 67-90 years, 57% were female, 30% were black, and 17% had 1,5-AG <6μg/mL. Median HbA1c was 6.2% in those with 1,5-AG ≥6μg/mL and 7.8% in persons with 1,5-AG <6μg/mL. During a median of 3.6 years of follow-up, there were 2,813 hospitalizations (1,689 diabetes-related) and 247 deaths. Compared to 1,5-AG ≥6μg/mL, individuals with 1,5-AG <6μg/mL had a significantly higher risk of hospitalizations, diabetes-related hospitalizations, and death ( Table ). After adjustment for diabetes medication use or HbA1c, associations with hospitalizations were attenuated and non-significant, while the relationship with all-cause mortality remained. Conclusion: Among older adults with diagnosed diabetes, glycemic variability may be an important risk factor for major short-term complications.

scholarly journals Glycemic Measures and Risk of Mortality in Older Chinese: The Guangzhou Biobank Cohort Study

2019 ◽  
Vol 105 (3) ◽  
pp. e181-e190 ◽  
Author(s):  
Chao Qiang Jiang ◽  
Lin Xu ◽  
Tai Hing Lam ◽  
Ya Li Jin ◽  
Wei Sen Zhang ◽  
...  
Keyword(s):  
Cohort Study ◽  
Confidence Interval ◽  
Mortality Risk ◽  
Fasting Glucose ◽  
Tolerance Test ◽  
Hazard Ratio ◽  
Oral Glucose ◽  
Risk Of Mortality ◽  
All Cause Mortality ◽  
Diagnosed Diabetes

Abstract Context China has the largest number of people with type 2 diabetes mellitus (T2DM) in the world. Data from previous studies have suggested that up to one-fifth of individuals with diabetes would be missed without an oral glucose tolerance test (OGTT). To date, there is little information on the mortality risk of these individuals. Objective We estimated the association of different indicators of hyperglycemia with mortality in the general Chinese population. Design Prospective cohort study. Setting China. Participants A total of 17 939 participants aged 50+ years. Exposures Previously diagnosed diabetes and newly detected diabetes defined by fasting glucose (≥7.0 mmol/L), 2-hour postload glucose (≥11.1 mmol/L), or hemoglobin A1c (HbA1c, ≥6.5%). Main Outcomes Measures Deaths from all-cause, cardiovascular disease, and cancer were identified by record linkage with death registration. Results During 7.8 (SD, 1.5) years’ follow-up, 1439 deaths were recorded. Of 3706 participants with T2DM, 2126 (57%) had known T2DM, 118 (3%) were identified by isolated elevated fasting glucose, 1022 (28%) had isolated elevated postload glucose, and 440 (12%) had both elevated fasting and postload glucose. Compared with normoglycemia, the hazard ratio (95% confidence interval) of all-cause mortality was 1.71 (1.46-2.00), 0.96 (0.47-1.93), 1.43 (1.15-1.78), and 1.82 (1.35-2.45) for the 4 groups, respectively. T2DM defined by elevated HbA1c was not significantly associated with all-cause mortality (hazard ratio, 1.17; 95% confidence interval, 0.81-1.69). Conclusion Individuals with isolated higher 2-h postload glucose had a higher risk of mortality by 43% than those with normoglycemia. Underuse of OGTT leads to substantial underdetection of individuals with a higher mortality risk and lost opportunities for early intervention.

Abstract P129: Biomarkers of Hyperglycemia With All-cause Mortality in Older Adults With and Without Diagnosed Diabetes

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Mary R Rooney ◽  
Olive Tang ◽  
James S Pankow ◽  
Elizabeth Selvin
Keyword(s):  
Older Adults ◽  
Cox Regression ◽  
Glycated Albumin ◽  
Cohort Analysis ◽  
Undiagnosed Diabetes ◽  
Atherosclerosis Risk In Communities ◽  
All Cause Mortality ◽  
Before And After ◽  
Diagnosed Diabetes ◽  
Glycemic Markers

Introduction: HbA1c is central to diagnosis and management of diabetes. However, our understanding of the associations of HbA1c with clinical outcomes is based primarily on studies of middle-aged adults. Objective: To characterize the associations between HbA1c and mortality among older adults with and without diabetes. We compared the HbA1c-mortality associations with those for alternative glycemic markers (fructosamine and glycated albumin). Methods: We conducted a prospective cohort analysis of 6370 participants (32% with diagnosed diabetes, mean age 76, 59% female, 23% black) in the Atherosclerosis Risk in Communities (ARIC) Study, baseline visit 5 (2011-13). We used Cox regression models to examine the association of each glycemic biomarker (modeled as a linear spline) with all-cause mortality through 2017, stratified by diagnosed diabetes. Model discrimination was tested using c-statistics. Results: There were 1022 deaths over 6 years of follow-up. In persons with diabetes, there was a J-shaped association between HbA1c and mortality ( Figure ). Associations were largely similar for fructosamine and glycated albumin. Among persons without diabetes, HbA1c was not strongly associated with mortality, but confidence intervals were wide for HbA1c <5.0% and ≥6.5% (undiagnosed diabetes); whereas, higher levels of fructosamine and glycated albumin were associated with an elevated mortality risk. Associations were similar before and after adjustment for cardiovascular risk factors. The addition of individual glycemic markers to the models modestly improved discrimination in both persons with and without diabetes. C-statistics were similar when the glycemic markers were added individually to the diabetes-stratified models (Figure). Conclusions: Among older adults, HbA1c and other glycemic markers tend to have similar associations with mortality. HbA1c, fructosamine, and glycated albumin, including low levels, may reflect common markers of risk in older adults, particularly in those with diabetes.

scholarly journals Distinctive role of income in the all-cause mortality among working age migrants and the settled population in Finland: A follow-up study from 2001 to 2014

2017 ◽  
Vol 46 (2) ◽  
pp. 214-220 ◽  
Author(s):  
Kishan Patel ◽  
Anne Kouvonen ◽  
Aki Koskinen ◽  
Lauri Kokkinen ◽  
Michael Donnelly ◽  
...  
Keyword(s):  
Mortality Risk ◽  
Low Income ◽  
Income Level ◽  
Cox Proportional Hazards ◽  
High Income ◽  
Mortality Data ◽  
Majority Population ◽  
All Cause Mortality ◽  
Working Age ◽  
Migrant Groups

Background: Although income level may play a significant part in mortality among migrants, previous research has not focused on the relationship between income, migration and mortality risk. The aim of this register study was to compare all-cause mortality by income level between different migrant groups and the majority settled population of Finland. Methods: A random sample was drawn of 1,058,391 working age people (age range 18–64 years; 50.4% men) living in Finland in 2000 and linked to mortality data from 2001 to 2014. The data were obtained from Statistics Finland. Cox proportional hazards models were used to investigate the association between region of origin and all-cause mortality in low- and high-income groups. Results: The risk for all-cause mortality was significantly lower among migrants than among the settled majority population (hazards ratio (HR) 0.57; 95% confidence interval (CI) 0.53–0.62). After adjustment for age, sex, marital status, employment status and personal income, the risk of mortality was significantly reduced for low-income migrants compared with the settled majority population with a low income level (HR 0.46; 95% CI 0.42–0.50) and for high-income migrants compared with the high-income settled majority (HR 0.81; 95% CI 0.69–0.95). Results comparing individual high-income migrant groups and the settled population were not significant. Low-income migrants from Africa, the Middle East and Asia had the lowest mortality risk of any migrant group studied (HR 0.32; 95% CI 0.27–0.39). Conclusions: Particularly low-income migrants seem to display a survival advantage compared with the corresponding income group in the settled majority population. Downward social mobility, differences in health-related lifestyles and the healthy migrant effect may explain this phenomenon.

scholarly journals COVID-19 and all-cause-mortality; differential trends between countries and selected states of India

2021 ◽  
Author(s):  
Jaideep C Menon ◽  
P Suseela Rakesh ◽  
Omesh K Bharti ◽  
Kaushik Mishra ◽  
Basanta K Swain ◽  
...  
Keyword(s):  
Quantitative Data ◽  
Case Fatality ◽  
Himachal Pradesh ◽  
High Income ◽  
Data Monitoring ◽  
Specific Data ◽  
All Cause Mortality ◽  
Mortality Differential ◽  
Context Specific ◽  
The Uk

Abstract Background: By 22nd January 2021, the SARS-CoV-2 virus had infected over 98 million and 10.6 million individuals globally and in India, with 1.7 million and 153, 067 deaths, respectively1. Case Fatality rates (CFR) due to COVID 19 have varied significantly between countries. In order to understand the true impact of the pandemic, we should report coronavirus (COVID-19) mortality in the context of all-cause and non-COVID-19 mortality, and compare with previous years. The consequences of the pandemic have been, and will be, different in different settings within and across countries.Objectives: To compare the all-cause mortality in the year 2020 with previous years in three selected states of India correlate it to the burden of COVID19 and compare all-cause mortality between three states of India to four high income countries.We also compared the number of cases, deaths, CFR, prevalence of NCDs per million and the proportion of population > age 65 in India to four high income countries (HIC)- the UK, US, Spain and Italy.Methods: We provide quantitative data in three states across India (Himachal Pradesh, Kerala and Odisha) and compare with high-income countries to illustrate the importance of context-specific data monitoring and public health responses.Results: There was a 1.9% increase in deaths, with 2.8% decrease in births in 2020, compared to 2019 in Himachal Pradesh, 13.3 and 9.2% decrease in Kerala and 16.7% and 21.4% decrease in Odisha.Conclusion: There was a direct correlation of all cause mortality to CFR on comparison between three states of India and despite the enormous burden of COVID19 in India all-cause mortality was lower compared to previous years in addition to the CFR due to COVID 19 being lower than in selected HICs.

OP91 Individual Participant Data Meta-Analysis Of Exercise Rehabilitation In Heart Failure

2018 ◽  
Vol 34 (S1) ◽  
pp. 33-34
Author(s):  
Oriana Ciani ◽  
Sarah Walker ◽  
Fiona Warren ◽  
Neil Smart ◽  
Massimo Piepoli ◽  
...  
Keyword(s):  
Heart Failure ◽  
Systematic Review ◽  
Meta Analysis ◽  
Aggregate Data ◽  
Controlled Trials ◽  
Individual Participant Data ◽  
Exercise Rehabilitation ◽  
Randomized Controlled ◽  
All Cause Mortality ◽  
Individual Participant

Introduction:Traditional meta-analyses synthesize aggregate data obtained from study publications or study authors, such as a treatment effect estimate and its associated uncertainty. An increasingly important approach is the meta-analysis of individual participant data (IPD) where the raw individual-level data are obtained for each study and used for synthesis. This study compares and discusses results from an IPD meta-analysis vs standard meta-analysis of randomized controlled trials of exercise cardiac rehabilitation in chronic heart failure (CHF).Methods:Based on a previous systematic review, the Exercise Training Meta-Analysis of Trials for Chronic Heart Failure (ExTraMATCH II) identified and collected IPD from randomized controlled trials (RCTs) that compared exercise rehabilitation with a non-exercise control with a minimum follow-up of six months. For this abstract, the outcome of interest was all-cause mortality. Original IPD were checked for consistency and compiled in a master dataset. Standard meta-analytic models were used for aggregate data whilst two-stage and one-stage approaches, accounting for the clustering of participants within studies, were planned for statistical analyses of IPD.Results:Overall thirty-three RCTs were included in the original systematic review, whereas within the ExTraMatch II project, IPD on all-cause mortality were obtained from seventeen RCTs of approximately 3,700 patients. From aggregate data there was no significant difference in pooled mortality (relative risk 0.92, 95% confidence interval 0.67 to 1.26). IPD analysis revealed 701 events across exercise and control groups. Our ongoing IPD analyses will allow us to examine how patients’ characteristics (e.g. age, New York Heart Association functional class, ejection fraction) modify treatment benefit.Conclusions:Given the limitations of current trial level meta-analysis evidence in CHF, access to individual data from several RCTs offers a timely and important opportunity to revisit the question of which CHF patient subgroups benefit most from exercise-based rehabilitation.

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