Impact of Being Eligible for Type 2 Diabetes Treatment on All-Cause Mortality and Cardiovascular Events: Regression Discontinuity Design Study

Opportunistic measurement of sagittal abdominal diameter with bone densitometry predicts death and cardiovascular events

Supine sagittal abdominal diameter (SAD), also known as abdominal height, has been proposed as a simple measure for assessing abdominal adiposity. We aimed to determine whether SAD from DXA performed for osteoporosis assessment predicts major adverse cardiovascular events (MACEs) using the population-based DXA registry for the Province of Manitoba, Canada. The study population comprised 72 974 individuals aged 40 yr and older with baseline DXA assessment between February 1999 and March 2018. Incident MACE (composite of all-cause mortality, acute myocardial infarction [MI], non-hemorrhagic stroke) was ascertained from linked healthcare databases. During mean 8.4 yr follow-up (611 862 person-years), 14 457 (18.8%) individuals experienced incident MACE. Risk stratification was greatest with SAD/weight ratio, with area under the curve (AUC) for MACE and its components ranging from 0.582 for acute MI to 0.620 for death (all p < .001), all significantly better than with BMI (p < .001). In multivariable-adjusted models, each SD increase in SAD/weight was associated with increased risk for MACE (hazards ratio [HR] 1.20, 95% CI 1.18-1.22), death (HR 1.22, 95% CI 1.20-1.25), acute MI (HR 1.19, 95% CI 1.14-1.24), and stroke (HR 1.17, 95% CI 1.12-1.22). A linear gradient was seen across SAD/weight quintiles (all p-trend < .001), with adjusted HR for MACE 1.61 (95% CI 1.50-1.72) for highest vs lowest quintile. Results were similar when further adjusted for BMI in non-obese and obese individuals (p-interaction for obesity = .141) and in both women and men (p-interaction for sex = .471). In conclusion, SAD measured opportunistically at the time of DXA testing is predictive of death and major cardiovascular events in individuals undergoing osteoporosis assessment.

FRAX predicts cardiovascular risk in women undergoing osteoporosis screening: the Manitoba bone mineral density registry

Osteoporosis and cardiovascular disease (CVD) are highly prevalent in older women, with increasing evidence for shared risk factors and pathogenesis. Although FRAX was developed for the assessment of fracture risk, we hypothesized that it might also provide information on CVD risk. To test the ability of the FRAX tool and FRAX-defined risk factors to predict incident CVD in women undergoing osteoporosis screening with DXA, we performed a retrospective prognostic cohort study which included women aged 50 yr or older with a baseline DXA scan in the Manitoba Bone Mineral Density Registry between March 31, 1999 and March 31, 2018. FRAX scores for major osteoporotic fracture (MOF) were calculated on all participants. Incident MOF and major adverse CV events (MACE; hospitalized acute myocardial infarction [AMI], hospitalized non-hemorrhagic cerebrovascular disease [CVA], or all-cause death) were ascertained from linkage to population-based healthcare data. The study population comprised 59 696 women (mean age 65.7 ± 9.4 yr). Over mean 8.7 yr of observation, 6021 (10.1%) had MOF, 12 277 women (20.6%) had MACE, 2274 (3.8%) had AMI, 2061 (3.5%) had CVA, and 10 253 (17.2%) died. MACE rates per 1000 person-years by FRAX risk categories low (10-yr predicted MOF <10%), moderate (10%-19.9%) and high (≥20%) were 13.5, 34.0, and 64.6, respectively. Although weaker than the association with incident MOF, increasing FRAX quintile was associated with increasing risk for MACE (all P-trend <.001), even after excluding prior CVD and adjusting for age. HR for MACE per SD increase in FRAX was 1.99 (95%CI, 1.96-2.02). All FRAX-defined risk factors (except parental hip fracture and lower BMI) were independently associated with higher non-death CV events. Although FRAX is intended for fracture risk prediction, it has predictive value for cardiovascular risk.

Dirichlet process mixture models for regression discontinuity designs

The regression discontinuity design is a quasi-experimental design that estimates the causal effect of a treatment when its assignment is defined by a threshold for a continuous variable. The regression discontinuity design assumes that subjects with measurements within a bandwidth around the threshold belong to a common population, so that the threshold can be seen as a randomising device assigning treatment to those falling just above the threshold and withholding it from those who fall below. Bandwidth selection represents a compelling decision for the regression discontinuity design analysis as results may be highly sensitive to its choice. A few methods to select the optimal bandwidth, mainly from the econometric literature, have been proposed. However, their use in practice is limited. We propose a methodology that, tackling the problem from an applied point of view, considers units' exchangeability, that is, their similarity with respect to measured covariates, as the main criteria to select subjects for the analysis, irrespectively of their distance from the threshold. We cluster the sample using a Dirichlet process mixture model to identify balanced and homogeneous clusters. Our proposal exploits the posterior similarity matrix, which contains the pairwise probabilities that two observations are allocated to the same cluster in the Markov chain Monte Carlo sample. Thus we include in the regression discontinuity design analysis only those clusters for which we have stronger evidence of exchangeability. We illustrate the validity of our methodology with both a simulated experiment and a motivating example on the effect of statins on cholesterol levels.

Changes in type 2 diabetes incidence and mortality associated with introduction of HbA1c as diagnostic option: A Danish 24-year population-based study

Background

In 2011, the World Health Organization began recommending glycated haemoglobin (HbA_1c) as a measure for diagnosing type 2 diabetes (T2D). This initiative may have changed basic T2D epidemiology. Consequently, we examined time changes in T2D incidence and mortality during 1995-2018.

Methods

In this population-based cohort study, we included 415,553 individuals with incident T2D. We calculated annual age-standardized incidence rates of T2D. We examined HbA_1c testing and used Poisson-regression to investigate all-cause mortality among the T2D patients and a matched comparison cohort from the general population over successive 3-year periods.

Findings

From 1995 to the 2012 introduction of HbA_1c testing as a diagnostic option in Denmark, the annual standardized incidence rate (SIR) of T2D doubled, from 193 to 396 per 100,000 persons (4.1% increase annually). From 2012 onwards, the T2D incidence declined by 36%, reaching 253 per 100,000 persons in 2018 (5.7% decrease annually). This was driven by fewer patients starting treatment with an HbA_1c measurement of <6·5% or without prior HbA_1c testing. Mortality per 1,000 person-years following a T2D diagnosis decreased by 44% between 1995-1997 and 2010-2012, from 69 deaths to 38 deaths (adjusted mortality rate ratio: 0·55 (95% CI: 0·54-0·56)). After the low level during 2010-2012, mortality increased again by 27% to 48 per 1,000 person-years (95% CI: 46-50) by 2016-2018.

Interpretation

Our findings suggest that introducing HbA_1c as a diagnostic option may have changed basic T2D epidemiology by leaving patients undiagnosed, that previously would have been diagnosed and treated.

Funding

Aarhus University funded the study and had no further involvement.

Major adverse cardiovascular event definitions used in observational analysis of administrative databases: a systematic review

Background

Major adverse cardiovascular events (MACE) are increasingly used as composite outcomes in randomized controlled trials (RCTs) and observational studies. However, it is unclear how observational studies most commonly define MACE in the literature when using administrative data.

Methods

We identified peer-reviewed articles published in MEDLINE and EMBASE between January 1, 2010 to October 9, 2020. Studies utilizing administrative data to assess the MACE composite outcome using International Classification of Diseases 9th or 10th Revision diagnosis codes were included. Reviews, abstracts, and studies not providing outcome code definitions were excluded. Data extracted included data source, timeframe, MACE components, code definitions, code positions, and outcome validation.

Results

A total of 920 articles were screened, 412 were retained for full-text review, and 58 were included. Only 8.6% (n = 5/58) matched the traditional three-point MACE RCT definition of acute myocardial infarction (AMI), stroke, or cardiovascular death. None matched four-point (+unstable angina) or five-point MACE (+unstable angina and heart failure). The most common MACE components were: AMI and stroke, 15.5% (n = 9/58); AMI, stroke, and all-cause death, 13.8% (n = 8/58); and AMI, stroke and cardiovascular death 8.6% (n = 5/58). Further, 67% (n = 39/58) did not validate outcomes or cite validation studies. Additionally, 70.7% (n = 41/58) did not report code positions of endpoints, 20.7% (n = 12/58) used the primary position, and 8.6% (n = 5/58) used any position.

Conclusions

Components of MACE endpoints and diagnostic codes used varied widely across observational studies. Variability in the MACE definitions used and information reported across observational studies prohibit the comparison, replication, and aggregation of findings. Studies should transparently report the administrative codes used and code positions, as well as utilize validated outcome definitions when possible.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-021-01440-5.

Time trends in the incidence of clinically diagnosed type 2 diabetes and pre-diabetes in the UK 2009-2018: a retrospective cohort study

INTRODUCTION

To describe recent trends in the incidence of clinically diagnosed type 2 diabetes and pre-diabetes in people seen in UK general practice.

RESEARCH DESIGN AND METHODS

A retrospective cohort study using IQVIA Medical Research Data looking at people newly diagnosed with type 2 diabetes and pre-diabetes through primary care registers in the UK between 1 January 2009 and 31 December 2018.

RESULTS

A cohort of 426 717 people were clinically diagnosed with type 2 diabetes and 418 656 people met the criteria for a diagnosis of pre-diabetes in that time period. The incidence of clinically diagnosed type 2 diabetes per 1000 person years at risk (PYAR) in men decreased from a peak of 5.06 per 1000 PYAR (95% CI 4.97 to 5.15) in 2013 to 3.56 per 1000 PYAR (95% CI 3.46 to 3.66) by 2018. For women, the incidence of clinically diagnosed type 2 diabetes per 1000 PYAR decreased from 4.45 (95% CI 4.37 to 4.54) in 2013 to 2.85 (2.76 to 2.93) in 2018. The incidence rate of pre-diabetes tripled by the end of the same study period in men and women.

CONCLUSIONS

Between 2009 and 2018, the incidence rate of new clinical diagnoses of type 2 diabetes recorded in a UK primary care database decreased by a third from its peak in 2013-2014, while the incidence of pre-diabetes has tripled. The implications of this on timely treatment, complication rates and mortality need further longer term exploration.

Secondary Impact of Social Media via Text Message Screening for Type 2 Diabetes Risk in Kuwait: Survey Study

BACKGROUND

Type 2 diabetes mellitus (T2DM) is an international problem of alarming epidemic proportions. T2DM can develop due to multiple factors, and it usually begins with prediabetes. Fortunately, this disease can be prevented by following a healthy lifestyle. However, many health care systems fail to properly educate the public on disease prevention and to offer support in embracing behavioral interventions to prevent diabetes. SMS messaging has been combined with cost-effective ways to reach out to the population at risk for medical comorbidities. To our knowledge, the use of nationwide SMS messaging in the Middle East as a screening tool to identify individuals who might be at risk of developing T2DM has not been reported in the literature.

OBJECTIVE

The primary aim of this study was to assess the feasibility of conducting a series of SMS messaging campaigns directed at random smartphone users in Kuwait for the detection and prevention of T2DM. It was predicted that 1% of those receiving the text message would find it relevant and participate in the study. The secondary aim of this study was to assess the incidence of participation of those who were forwarded the initial text message by family members and friends.

METHODS

In this study, 5 separate text message screening campaigns were launched inviting recipients to answer 6 questions to determine the risk of developing T2DM. If subjects agreed to participate, a link to the prediabetes screening test devised by the Centers for Disease Control and Prevention was automatically transmitted to their mobile devices. Those identified as high risk were invited to participate in a diabetes prevention program.

RESULTS

A total of 180,000 SMSs were sent to approximately 6% of the adult population in Kuwait. Of these, 0.14% (260/180,000) of the individuals who received the SMS agreed to participate, of whom 58.8% (153/260) completed the screening. Surprisingly, additional surveys were completed by 367 individuals who were invited via circulated SMS messages forwarded by family members and friends. Altogether, 23.3% (121/520) qualified and agreed to participate in a diabetes prevention program. The majority of those who chose to participate in the prevention program were overweight, aged 45-65 years, and reported being less physically active than those who chose not to participate (χ²₂=42.1, P<.001).

CONCLUSIONS

Although health care screening via text messaging was found to have limited effectiveness by itself, it exhibited increased reach through shared second-party social media messaging. Despite the fact a subpopulation at possible risk of developing T2DM could be reached via text messaging, most responders were informed about the screening campaign by family and friends. Future research should be designed to tap into the benefits of social media use in health risk campaigns.