Is cardiovascular risk reduction therapy effective in South Asian, Chinese and other patients with diabetes? A population-based cohort study from Canada

Ethnic differences in the association between age at diagnosis of diabetes and the risk of cardiovascular complications: a population-based cohort study

BACKGROUND

We examined ethnic differences in the association between age at diagnosis of diabetes and the risk of cardiovascular complications.

METHODS

We conducted a population-based cohort study in Ontario, Canada among individuals with diabetes and matched individuals without diabetes (2002-18). We fit Cox proportional hazards models to determine the associations of age at diagnosis and ethnicity (Chinese, South Asian, general population) with cardiovascular complications. We tested for an interaction between age at diagnosis and ethnicity.

RESULTS

There were 453,433 individuals with diabetes (49.7% women) and 453,433 matches. There was a significant interaction between age at diagnosis and ethnicity (P < 0.0001). Young-onset diabetes (age at diagnosis < 40) was associated with higher cardiovascular risk [hazard ratios: Chinese 4.25 (3.05-5.91), South Asian: 3.82 (3.19-4.57), General: 3.46 (3.26-3.66)] than usual-onset diabetes [age at diagnosis ≥ 40 years; Chinese: 2.22 (2.04-2.66), South Asian: 2.43 (2.22-2.66), General: 1.83 (1.81-1.86)] versus ethnicity-matched individuals. Among those with young-onset diabetes, Chinese ethnicity was associated with lower overall cardiovascular [0.44 (0.32-0.61)] but similar stroke risks versus the general population; while South Asian ethnicity was associated with lower overall cardiovascular [0.75 (0.64-0.89)] but similar coronary artery disease risks versus the general population. In usual-onset diabetes, Chinese ethnicity was associated with lower cardiovascular risk [0.44 (0.42-0.46)], while South Asian ethnicity was associated with lower cardiovascular [0.90 (0.86-0.95)] and higher coronary artery disease [1.08 (1.01-1.15)] risks versus the general population.

CONCLUSIONS

There are important ethnic differences in the association between age at diagnosis and risk of cardiovascular complications.

Association between Chinese or South Asian ethnicity and end-of-life care in Ontario, Canada

BACKGROUND

Ethnicity may be associated with important aspects of end-of-life care, such as what treatments are received, access to palliative care and where people die. However, most studies have focused on end-of-life care of white, Hispanic and black patients. We sought to compare end-of-life care delivered to people of Chinese and South Asian ethnicity with that delivered to others from the general population, in Ontario, Canada.

METHODS

In this population-based cohort study, we included all people who died in Ontario, Canada, between Apr. 1, 2004, and Mar. 31, 2015. People were identified as having Chinese or South Asian ethnicity on the basis of a validated surname algorithm. We used modified Poisson regression analyses to assess location of death and care received in the last 6 months of life.

RESULTS

We analyzed 967 339 decedents, including 18 959 (2.0%) of Chinese and 11 406 (1.2%) of South Asian ethnicity. Chinese (13.6%) and South Asian (18.5%) decedents were more likely than decedents from the general population (10.1%) to die in the intensive care unit (ICU). The adjusted relative risk of dying in intensive care was 1.21 (95% confidence interval [CI] 1.15 to 1.27) for Chinese and 1.25 (95% CI 1.20 to 1.30) for South Asian decedents. In their last 6 months of life, decedents of Chinese and South Asian ethnicity experienced significantly more ICU admission, hospital admission, mechanical ventilation, dialysis, percutaneous feeding tube placement, tracheostomy and cardiopulmonary resuscitation than the general population.

INTERPRETATION

Decedents of Chinese and South Asian ethnicity in Ontario were more likely than decedents from the general population to receive aggressive care and to die in an ICU. These findings may be due to communication difficulties between patients and clinicians, differences in preferences about end-of-life care or differences in access to palliative care services.

Development and validation of algorithms to classify type 1 and 2 diabetes according to age at diagnosis using electronic health records

BACKGROUND

Validated algorithms to classify type 1 and 2 diabetes (T1D, T2D) are mostly limited to white pediatric populations. We conducted a large study in Hong Kong among children and adults with diabetes to develop and validate algorithms using electronic health records (EHRs) to classify diabetes type against clinical assessment as the reference standard, and to evaluate performance by age at diagnosis.

METHODS

We included all people with diabetes (age at diagnosis 1.5-100 years during 2002-15) in the Hong Kong Diabetes Register and randomized them to derivation and validation cohorts. We developed candidate algorithms to identify diabetes types using encounter codes, prescriptions, and combinations of these criteria ("combination algorithms"). We identified 3 algorithms with the highest sensitivity, positive predictive value (PPV), and kappa coefficient, and evaluated performance by age at diagnosis in the validation cohort.

RESULTS

There were 10,196 (T1D n = 60, T2D n = 10,136) and 5101 (T1D n = 43, T2D n = 5058) people in the derivation and validation cohorts (mean age at diagnosis 22.7, 55.9 years; 53.3, 43.9% female; for T1D and T2D respectively). Algorithms using codes or prescriptions classified T1D well for age at diagnosis < 20 years, but sensitivity and PPV dropped for older ages at diagnosis. Combination algorithms maximized sensitivity or PPV, but not both. The "high sensitivity for type 1" algorithm (ratio of type 1 to type 2 codes ≥ 4, or at least 1 insulin prescription within 90 days) had a sensitivity of 95.3% (95% confidence interval 84.2-99.4%; PPV 12.8%, 9.3-16.9%), while the "high PPV for type 1" algorithm (ratio of type 1 to type 2 codes ≥ 4, and multiple daily injections with no other glucose-lowering medication prescription) had a PPV of 100.0% (79.4-100.0%; sensitivity 37.2%, 23.0-53.3%), and the "optimized" algorithm (ratio of type 1 to type 2 codes ≥ 4, and at least 1 insulin prescription within 90 days) had a sensitivity of 65.1% (49.1-79.0%) and PPV of 75.7% (58.8-88.2%) across all ages. Accuracy of T2D classification was high for all algorithms.

CONCLUSIONS

Our validated set of algorithms accurately classifies T1D and T2D using EHRs for Hong Kong residents enrolled in a diabetes register. The choice of algorithm should be tailored to the unique requirements of each study question.

Prediction of fatal and non-fatal cardiovascular events in young and middle-aged healthy workers: The IberScore model

AIMS

Our primary objective was to improve risk assessment for fatal and non-fatal cardiovascular events in a working population, mostly young and healthy.

METHODS

We conducted a prospective cohort study to derive a survival model to predict fatal and non-fatal 10-year cardiovascular risk. We recruited 992,523 workers, free of diagnosed cardiovascular disease at entry, over six years, from 2004-2009. We divided the sample into two independent cohorts: a derivation one (626,515 workers; from 2004-2006) and a temporal validation one (366,008 workers; over 2007-2009). Then, we followed both cohorts over 10 years and registered all fatal and non-fatal cardiovascular events. We built a new risk calculator using an estimation of cardiovascular biological age as a predictor and named it IberScore. There were remarkable differences between this new model and Systematic Coronary Risk Evaluation (SCORE) (in both the specification and the equation).

RESULTS

Over the 10-year follow-up, we found 3762 first cardiovascular events (6‰) in the derivation cohort. Most of them (80.3%) were non-fatal ischaemic events. If we had been able to use our model at the beginning of the study, we had classified in the 'high-risk' or 'very high-risk' groups 82% of those who suffered a cardiovascular event during the follow-up. All the post-estimation tests showed superior performance (true positive rate: 81.8% vs 11.8%), higher discrimination power and better clinical utility (standardised net benefit: 58% vs 13%) for IberScore when compared to SCORE.

CONCLUSION

Risk assessment of fatal and non-fatal cardiovascular events in young and healthy workers was improved when compared to the previously used model (SCORE). The latter was not reliable to predict cardiovascular risk in our sample. The new model showed superior clinical utility and provided four useful measures for risk assessment. We gained valuable insight into cardiovascular ageing and its predictors.

Could Intensive Blood Pressure Control Really Reduce Diabetic Retinopathy Outcomes? Evidence from Meta-Analysis and Trial Sequential Analysis from Randomized Controlled Trials

INTRODUCTION

To explore the accumulated evidence concerning the effect of intensive blood pressure control on the incidence and progression of diabetic retinopathy (DR), proliferative diabetic retinopathy (PDR) and macular edema (ME).

METHODS

A number of electronic databases were searched including PubMed, EMBASE, CINAHL, Cochrane Library, conferences and proceedings. Randomized controlled trials comparing intensive blood pressure targets with conventional blood pressure targets in patients with type 2 diabetes were included. The definition of intensive versus conventional blood pressure targets was from the pertinent original studies. Meta-analyses and trial sequential analyses of randomized trials were analyzed in STATA.

RESULTS

Eight trials randomizing 6989 patients were assessed and reviewed in full text; 3749 vs. 3240 were in each arm (intensive vs. conventional). All trials had a low risk of bias. Intensive blood pressure control supported a 17% reduction in the incidence of DR (relative risk 0.83, 95% confidence interval 0.72-0.95). Trial sequential analyses confirmed that sufficient evidence indicated a relative risk reduction above 17% for the incidence of DR when intensive blood pressure control was targeted. Heterogeneity was absent (I² = 0%; P = 0.56). No statistically significant effect was found for intensive blood pressure targeting on the progress of DR (relative risk 0.94, 95% confidence interval 0.81-1.08). TSA showed that insufficient evidence had been found, although the Z value line appeared to have a tendency of approaching the futility boundaries. There were also no statistically significant effects on the incidence of PDR and ME (TSA-adjusted CI 0.84-1.12).

CONCLUSION

Intensive blood pressure control reduced the relative risk of incidence of DR by 17%. The available data were insufficient to prove or refute a relative risk reduction for the progression of DR or incidence of PDR and ME at a magnitude of 15%.