Association of Visit-to-Visit Variability of Systolic Blood Pressure With Cardiovascular Disease and Mortality in Primary Care Chinese Patients With Type 2 Diabetes-A Retrospective Population-Based Cohort Study

Long-term statin use and risk of cancers: a target trial emulation study

BACKGROUND AND OBJECTIVES

Controversy exists regarding potential cancer risks associated with long-term statin use. This study aimed to use real-world data to investigate the association between cancer incidence and sustained statin use over a 10-year period.

METHODS

Using territory-wide public electronic medical records in Hong Kong, we emulated a sequence of nested target trials on patients who met indications for statin initiation in each calendar month from January 2009 to December 2011. Statin initiators and noninitiators were matched in a 1:1 ratio to mimic the randomization of eligible person-trials at baseline. Pooled logistic regression was applied to obtain the hazard ratios for the cancer incidence of statin initiation in intention-to-treat analysis, with the adjustment of baseline confounders and the inverse probability weighting accounting for the postbaseline confounders in per-protocol analysis.

RESULTS

Among 8,560,051 eligible person-trials, 119,715 noninitiators were matched to 119,715 initiators for analysis. Over the 10-year study period, the estimated hazard ratio of overall cancer incidence was 0.96 (0.87, 1.05), and the standardized 10-year risk difference was -0.4% (-1.3%, 0.4%) in the per-protocol analysis. For the cancer subtypes of interest (ie, breast cancer, colorectal cancer, hematological cancer, pancreatic cancer, prostate cancer, urothelial carcinoma, and lung cancer), the 10-year risk differences ranged from -0.3% to 0.2% in the per-protocol analysis. No observable risk change for cancer was found in all patient subgroups with regards to their sex, age (<70/≥70 years), Charlson Comorbidity Index (≤4/>4), and statin indication.

CONCLUSION

Statin use has no impact on cancer incidence over a 10-year follow-up period, including all cancer subtypes of interest and patient subgroups with regards to sex, age, comorbidities, and statin indications.

Associations and attributable burden between risk factors and all-cause and cause-specific mortality at different ages in patients with hypertension

It remains unclear the age-specific associations of risk factors with deaths and mortality burden attributable across age. In a territory-wide retrospective cohort, 1,012,228 adults with hypertension were identified. Comorbidities including diabetes, chronic kidney disease (CKD), cardiovascular disease (CVD), heart failure, and cancer, and risk factors including current smoking and suboptimal control of blood pressure (BP), glucose and low-density lipoprotein cholesterol were defined. Associations of comorbidities/risk factors with all-cause and cause-specific mortality across age groups (18-54, 55-64, 65-74, and ≥75 years) were assessed. Population attributable fractions were also quantified. During a median follow-up of 10.7 years, 244,268 (24.1%) patients died, with pneumonia (7.2%), cancer (5.1%), and CVD (4.2%) being the leading causes. Despite increasing deaths with age, relative risk of mortality related to comorbidities/risk factors decreased with age; similar patterns were found for cause-specific mortality. The assessed risk factors accounted for 24.0% (95% CI 22.5%, 25.4%) deaths, with highest proportion in the youngest group (33.5% [28.1%, 38.5%] in 18-54 years vs 19.4% [17.0%, 21.6%] in ≥75 years). For mortality burden, CKD was the overall leading risk factor (12.7% [12.4%, 12.9%]) with higher proportions in older patients (11.1-13.1% in ≥65 years), while diabetes was the leading risk factor in younger patients (15.9-13.5% in 18-54 years). The association of comorbidities or risk factors with mortality is stronger in younger patients with hypertension, despite lower absolute mortality in young patients than in the elderly. Leading risk factors differed across age, highlighting the importance of targeted and precise risk management.

Association of body mass index and blood pressure variability with 10-year mortality and renal disease progression in type 2 diabetes

BACKGROUND

Variability in biological parameters may be associated with adverse outcomes. The aim of the study was to determine whether variability in body mass index (BMI) and blood pressure is associated with all-cause, cardiovascular mortality and cancer mortality or with renal disease progression in subjects with type 2 diabetes.

METHODS

The diabetes database was accessed, and all the information on patient visits (consultations) carried out in the study period (1 January 2008-31 December 2019) was extracted and linked to the laboratory database and the mortality register.

RESULTS

The total number of patients included in the study population was 26,261, of whom 54.4% were male. Median (interquartile range, IQR) age was 60.2 (51.8-68.3) years. The coefficient of variability of BMI was independently associated with increased all-cause and cardiovascular, but not cancer, mortality. Glycated haemoglobin (HbA1c) was associated with increased all-cause, cardiovascular, and cancer mortality as well as with renal progression. Variability in systolic blood pressure, diastolic blood pressure, and pulse pressure was associated with increased all-cause and cardiovascular mortality in bivariate, but not in multivariate, analyses.

CONCLUSIONS

Variability in BMI was associated with increased all-cause and cardiovascular, but not cancer, mortality in a large real-world contemporary population. Our results also confirm the association of HbA1c with increased all-cause, cardiovascular, and cancer mortality as well as with renal progression.

Comparison of BP variability, cumulative BP, and BP trajectory for predicting cardiovascular events in the general population

OBJECTIVE

Systolic blood pressure variability (SBPV), cumulative systolic BP (cumSBP), and systolic blood pressure trajectory (trajSBP) are major indices describing characteristics of BP changes. The aim of this study was to compare their discrimination abilities for cardiovascular (CV) events.

METHODS

In 51698 subjects, associations were assessed using Cox regression in the overall cohort and Framingham risk score (FRS) stratified groups. Individuals with <10%, 10%-20%, and >20% 10-year CV risk were categorized into the low-, intermediate-, and high-risk group, respectively. Discrimination capabilities were evaluated using the area under curve (AUC), Harrell's C index, net reclassification index (NRI), and integrated discrimination index (IDI).

RESULTS

Within a mean follow-up of 6.83 ± 0.89 years, 2330 participants had CV events, and all three markers were significantly associated with CV events. TrajSBP provided the best additional discriminative value for CV events, with improvements of 1.54% in AUC%, 0.01 in Harrell's C, 37.52% in NRI%, and 0.59% in IDI%. CumSBP had good additional discriminative capability in the intermediate to high FRS groups, but the effect sizes were smaller than those of trajSBP. Although, SBPV improved the predictive capabilities in the low-to intermediate-risk groups, the effect sizes were much smaller than those of the other indices. Sensitivity analyses excluding patients who underwent antihypertensive therapy revealed similar patterns but higher effect sizes than in the overall population.

CONCLUSION

TrajSBP provides the best additional discrimination capabilities based on traditional risk profiles and may assist the risk stratification and individual prediction for future CV events.

Comprehensive Factors for Predicting the Complications of DiabetesMellitus: A Systematic Review

BACKGROUND

This article focuses on extracting a standard feature set for predicting the complications of diabetes mellitus by systematically reviewing the literature. It is conducted and reported by following the guidelines of PRISMA, a well-known systematic review and meta-analysis method. The research articles included in this study are extracted using the search engine "Web of Science" over eight years. The most common complications of diabetes, diabetic neuropathy, retinopathy, nephropathy, and cardiovascular diseases are considered in the study.

METHOD

The features used to predict the complications are identified and categorised by scrutinising the standards of electronic health records.

RESULT

Overall, 102 research articles have been reviewed, resulting in 59 frequent features being identified. Nineteen attributes are recognised as a standard in all four considered complications, which are age, gender, ethnicity, weight, height, BMI, smoking history, HbA1c, SBP, eGFR, DBP, HDL, LDL, total cholesterol, triglyceride, use of insulin, duration of diabetes, family history of CVD, and diabetes. The existence of a well-accepted and updated feature set for health analytics models to predict the complications of diabetes mellitus is a vital and contemporary requirement. A widely accepted feature set is beneficial for benchmarking the risk factors of complications of diabetes.

CONCLUSION

This study is a thorough literature review to provide a clear state of the art for academicians, clinicians, and other stakeholders regarding the risk factors and their importance.

Association of eGFR slope with all-cause mortality, macrovascular and microvascular outcomes in people with type 2 diabetes and early-stage chronic kidney disease

AIMS

The association of estimated glomerular filtration rate (eGFR) slope with progression of complications in people with type 2 diabetes (T2D) and early-stage chronic kidney disease (CKD) is less clear.

METHODS

We identified 115,139 T2D participants without decreased eGFR (>60 mL/min/1.73 m2) between 2008 and 2015 from the electronic database of the Hong Kong Hospital Authority. eGFR slope calculated by linear-mixed effects model using 3-year eGFR measurements was categorized into quintiles. With Quintile 3 of eGFR slope as the reference group, we used Cox proportional or cause-specific models to investigate the association between eGFR slope and all-cause mortality, macrovascular and microvascular complications, as appropriate.

RESULTS

Over a median follow-up of 7.8 years, fastest eGFR declines (Quintile 1 with median eGFR slope: -4.32 mL/min/1.73 m2/year) were associated with increased risk of all adverse outcomes (adjusted hazard ratio [aHR] 1.36 to 2.97, all P < 0.0001), compared with less steep eGFR declines (Quintile 3: -1.08 mL/min/1.73 m2/year). Substantial eGFR increases (Quintile 5: 1.34 mL/min/1.73 m2/year) were associated with decreased risk of CKD and ≥ 40 % decline in eGFR (aHR [95 % CI] 0.65 [0.63, 0.67] and 0.85 [0.82, 0.89], respectively) and higher risk of death, CVD, DR and DN (aHR [95 % CI] 1.48 [1.40, 1.56], 1.19 [1.14, 1.25], 1.07 [1.004, 1.15] and 1.62 [1.37, 1.91], respectively).

CONCLUSIONS

In a cohort of T2D people without decreased eGFR, accelerated declines and increases in eGFR were associated with all-cause mortality, macrovascular and microvascular complications, supporting the potential prognostic utility of eGFR slope in T2D people with early-stage CKD.

Age-specific associations between the number of co-morbidities, all-cause mortality and public direct medical costs in patients with type 2 diabetes: A retrospective cohort study

AIM

To evaluate the association between the number of co-morbidities, all-cause mortality and public health system expenditure in patients with type 2 diabetes (T2D) across different age groups.

MATERIALS AND METHODS

A retrospective observational study of T2D patients using electronic health records in Hong Kong was conducted. Patients were stratified by age (< 50, 50-64, 65-79, ≥ 80 years) and the number of co-morbidities (0, 1, 2, 3, ≥ 4), defined using the Charlson Comorbidity Index and prevalent chronic diseases identified in local surveys. The association between the number of co-morbidities, all-cause mortality and direct medical costs was examined using Cox proportional hazard regression and the gamma generalized linear model with log link function.

RESULTS

A total of 262 212 T2D patients with a median follow-up of 10 years were included. Hypertension and dyslipidaemia were the most common co-morbidities in all age groups. After age stratification, cardiovascular diseases dominated the top pair of co-morbidities in the older age groups (65-79 and ≥ 80 years), while inflammatory and liver disease were predominant among younger individuals. Compared with co-morbidity-free T2D patients, the hazard ratios (95% CI) of death for patients aged younger than 50 and 80 years or older with two co-morbidities were 1.31 (1.08-1.59) and 1.25 (1.15-1.36), respectively, and increased to 3.08 (2.25-4.21) and 1.98 (1.82-2.16), respectively, as the number of co-morbidities increased to four or more. Similar trends were observed for medical costs.

CONCLUSIONS

Age-specific co-morbidity patterns were observed for patients with T2D. A greater number of co-morbidities was associated with increased mortality and healthcare costs, with stronger relationships observed among younger patients.

Diabetes with poor-control HbA1c is cardiovascular disease 'risk equivalent' for mortality: UK Biobank and Hong Kong population-based cohort study

INTRODUCTION

Type 2 diabetes mellitus (T2DM) has traditionally been considered a coronary heart disease 'risk equivalent' for future mortality, but significant heterogeneity exists across people with T2DM. This study aims to determine the risk of all-cause mortality of patients with cardiovascular disease (CVD) and T2DM in UK and Hong Kong, with stratifications for hemoglobin A1 (HbA1c) concentrations, compared with those without CVD and diabetes mellitus.

RESEARCH DESIGN AND METHODS

This is a retrospective cohort study of 3 839 391 adults from Hong Kong and a prospective cohort study of 497 779 adults from the UK Biobank. Individuals were divided into seven disease groups: (1) no T2DM and CVD, (2) T2DM only with HbA1c <7%, (3) T2DM only with HbA1c 7%-7.9%, (4) T2DM only with HbA1c 8%-8.9%, (5) T2DM only with HbA1c ≥9%, (6) CVD only, and (7) T2DM and CVD. Differences in all-cause mortality between groups were examined using Cox regression.

RESULTS

After around 10 years of median follow-up, 423 818 and 19 844 deaths were identified in the Hong Kong cohort and UK Biobank, respectively. Compared with individuals without T2DM and CVD, the adjusted HR for all-cause mortality in the other six disease groups for the Hong Kong cohort was 1.25 (95% CI 1.23 to 1.27) for T2DM only with HbA1c <7%, 1.21 (95% CI 1.19 to 1.23) for T2DM only with HbA1c 7%-7.9%, 1.36 (95% CI 1.33 to 1.39) for T2DM only with HbA1c 8%-8.9%, 1.82 (95% CI 1.78 to 1.85) for T2DM only with HbA1c ≥9%, 1.37 (95% CI 1.36 to 1.38) for CVD only, and 1.83 (95% CI 1.81 to 1.85) for T2DM and CVD, and for the UK Biobank the HR was 1.45 (95% CI 1.33 to 1.58), 1.50 (95% CI 1.32 to 1.70), 1.72 (95% CI 1.43 to 2.08), 2.51 (95% CI 2.05 to 3.08), 1.67 (95% CI 1.59 to 1.75) and 2.62 (95% CI 2.42 to 2.83), respectively. This indicates that patients with T2DM had an increased risk of mortality compared with those without T2DM and CVD, and in those with HbA1c ≥9% an even higher risk than people with CVD.

CONCLUSIONS

Patients with T2DM with poor HbA1c control (8%-8.9% and ≥9%) were associated with similar and higher risk of mortality compared with patients with CVD, respectively. Optimal HbA1c, controlled for risk reduction and prevention of mortality and complications in diabetes management, remains important.

Population-Based Clinical Studies Using Routinely Collected Data in Hong Kong, China: A Systematic Review of Trends and Established Local Practices

Background: Routinely collected health data are increasingly used in clinical research. No study has systematically reviewed the temporal trends in the number of publications and analyzed different aspects of local research practices and their variations in Hong Kong, China, with a specific focus on research ethics governance and approval.

Methods: PubMed was systematically searched from its inception to March 28, 2023, for studies using routinely collected healthcare data from Hong Kong.

Results: A total of 454 studies were included. Between 2000 and 2009, 32 studies were identified. The number of publications increased from 5 to 120 between 2010 and 2022. Of the investigator-led studies using the Hospital Authority (HA)’s cross-cluster data (n = 393), 327 (83.2%) reported receiving ethics approval from a single cluster/university-based REC, whereas 50 studies (12.7%) did not report approval from a REC. For use of the HA Data Collaboration Lab, approval by a single hospital-based or University-based REC is accepted. Repeated submission of identical ethics applications to different RECs is estimated to cost HK$4.2 million yearly.

Conclusions: Most studies reported gaining approval from a single cluster REC before retrieval of cross-cluster HA data. Substantial cost savings would result if repeated review of identical ethics applications were not required.

Comparative Risks of Nonsteroidal Anti-inflammatory Drugs on Cardiovascular Diseases: A Population-Based Cohort Study

Through examining the incidence of cardiovascular diseases (CVDs) among nonsteroidal anti-inflammatory drug (NSAID) users and nonusers, this study aims to compare the risks contributed by different NSAIDs in a Chinese population. The retrospective cohort including 4 298 368 adults without CVD from electronic health records between 2008 and 2017 in Hong Kong was adopted. A total of 4.5% of individuals received NSAIDs including celecoxib, etoricoxib, diclofenac, ibuprofen, indomethacin, mefenamic acid, or naproxen for ≥4 consecutive weeks at baseline. Cox regression, including NSAID use as a time-dependent covariate and adjusted with patient's characteristics, was conducted to examine the association between NSAID exposure and incident CVD. After a median follow-up of 6.9 years (30 million person-years), a total of 258 601 cases of incident CVD was recorded. NSAID use was shown to be associated with a significantly higher risk of CVD (hazard ratio [HR], 1.32 [95%CI, 1.28-1.37]) compared to non-NSAID use. Similar results in coronary heart disease (HR, 1.37 [95%CI, 1.31-1.43]), stroke (HR, 1.27 [95%CI, 1.21-1.33]), and heart failure (HR, 1.25 [95%CI, 1.16-1.34]) were obtained. Overall, similar CVD risk was observed across users of NSAIDs except for etoricoxib, which showed a higher risk (HR, 2.01 [95%CI, 1.63-2.48]). Considering that a higher CVD risk was consistently displayed among NSAID users, NSAIDs should be used cautiously, and the usage of etoricoxib in the Chinese population should be reviewed.

Incremental value of risk factor variability for cardiovascular risk prediction in individuals with type 2 diabetes: results from UK primary care electronic health records

BACKGROUND

Cardiovascular disease (CVD) risk prediction models for individuals with type 2 diabetes are important tools to guide intensification of interventions for CVD prevention. We aimed to assess the added value of incorporating risk factors variability in CVD risk prediction for people with type 2 diabetes.

METHODS

We used electronic health records (EHRs) data from 83 910 adults with type 2 diabetes but without pre-existing CVD from the UK Clinical Practice Research Datalink for 2004-2017. Using a landmark-modelling approach, we developed and validated sex-specific Cox models, incorporating conventional predictors and trajectories plus variability of systolic blood pressure (SBP), total and high-density lipoprotein (HDL) cholesterol, and glycated haemoglobin (HbA1c). Such models were compared against simpler models using single last observed values or means.

RESULTS

The standard deviations (SDs) of SBP, HDL cholesterol and HbA1c were associated with higher CVD risk (P < 0.05). Models incorporating trajectories and variability of continuous predictors demonstrated improvement in risk discrimination (C-index = 0.659, 95% CI: 0.654-0.663) as compared with using last observed values (C-index = 0.651, 95% CI: 0.646-0.656) or means (C-index = 0.650, 95% CI: 0.645-0.655). Inclusion of SDs of SBP yielded the greatest improvement in discrimination (C-index increase = 0.005, 95% CI: 0.004-0.007) in comparison to incorporating SDs of total cholesterol (C-index increase = 0.002, 95% CI: 0.000-0.003), HbA1c (C-index increase = 0.002, 95% CI: 0.000-0.003) or HDL cholesterol (C-index increase= 0.003, 95% CI: 0.002-0.005).

CONCLUSION

Incorporating variability of predictors from EHRs provides a modest improvement in CVD risk discrimination for individuals with type 2 diabetes. Given that repeat measures are readily available in EHRs especially for regularly monitored patients with diabetes, this improvement could easily be achieved.

Visit-to-visit variability of blood pressure and risk of macrovascular and microvascular complications in patients with type 2 diabetes: A Chinese primary-care cohort study

BACKGROUND

We evaluated the effects of visit-to-visit variability of systolic blood pressure (SBP) and diastolic blood pressure (DBP) on macrovascular and microvascular complications among patients with type 2 diabetes.

METHODS

A total of 11 043 patients with type 2 diabetes from primary healthcare institutions between January 2010 and June 2020 were included. The visit-to-visit blood pressure variability was calculated using three metrics: SD, coefficient of variation (CV), and average real variability (ARV), obtained over a 12-month measurement period. The associations of visit-to-visit blood pressure variability with macrovascular and microvascular complications were evaluated using multivariate-adjusted Cox proportional hazards models, and hazard ratio (HR) with 95% confidence interval (CI) were reported.

RESULTS

There were 330 macrovascular events and 542 microvascular events. Compared to those for participants with the lowest quartile of SD of SBP and DBP, increased risks were observed in patients with the highest quartile of SD of SBP and DBP for macrovascular complications (SD-SBP: HR = 1.78, 95% CI: 1.24-2.57; SD-DBP: HR = 2.20, 95% CI: 1.50-3.25) and microvascular complications (SD-SBP: HR = 1.85, 95% CI: 1.39-2.46; SD-DBP: HR = 1.82, 95% CI: 1.36-2.44). CV and ARV of SBP and DBP also had statistically significant associations with macrovascular and microvascular complications. The optimal variability of blood pressure target was SD of SBP <6.45 mm Hg and SD of DBP <4.81 mm Hg.

CONCLUSIONS

Visit-to-visit blood pressure variability may be a potential predictor for macrovascular and microvascular complications in patients with type 2 diabetes.

Joint effect of blood pressure and glycemic variation on the risk of cardiovascular morbidity and mortality in persons with type 2 diabetes

OBJECTIVE

Few studies have explored the association of visit-to-visit variation in blood pressure (BP) and glycemic factors with cardiovascular disease (CVD) morbidity and mortality. This study aimed to examine the independent and joint effect of visit-to-visit BP and glycemic variation on CVD morbidity and mortality in persons with T2DM.

METHODS

The present study consisted of two retrospective cohort studies. The Taiwan Diabetes Study was based on a database of the National Diabetes Care Management Program (DCMP) and linked with cardiovascular morbidity incidence. The Taichung Diabetes Study was based on the DCMP database of a medical center, which can be linked with the National Death Registry dataset. The outcomes were analyzed by using Cox's proportional hazard models.

RESULTS

A total of 13,280 and 10,894 persons with T2DM in Taiwan and Taichung Diabetes Study, respectively, were included. SBP-CV, FPG-CV, and HbA1c-CV were significant predictors of stroke, CVD event or death, all-cause mortality, and expanded CVD mortality, whereas DBP-CV was a significant predictor of all-cause mortality and expanded and non-expanded CVD mortality. The joint effect of SBP, FPG, and HbA1c predicted the incidence of stroke and CVD event or death with increased risks of 16 %-35 %. In addition, the joint effect of SBP, DBP, FPG, and HbA1c was associated with all-cause and expanded CVD mortality with increased risks of 29 %-81 %.

CONCLUSIONS

The joint effect of BP and glucose variation improved the prediction of cardiovascular morbidity and mortality. Moreover, simultaneous measurement of visit-to-visit BP and glycemic variation may stratify persons with cardiovascular risks and may be regarded as important therapeutic goals in the care of T2DM.

Variabilidade da Pressão Arterial em Única Visita e Risco Cardiovascular em Participantes do ELSA-Brasil

Fundamento

A variabilidade da pressão arterial (VPA) tem valor prognóstico para desfechos cardiovasculares fatais e não fatais.

Objetivos

Este estudo teve como objetivo avaliar a associação entre a VPA em uma única visita e o risco cardiovascular em participantes do Estudo Longitudinal de Saúde do Adulto (ELSA-Brasil).

Métodos

O presente estudo transversal foi conduzido com dados basais (2008-2010) de 14.357 participantes do ELSA-Brasil, sem história de doença cardiovascular. A VPA foi quantificada pelo coeficiente de variação de três medidas padronizadas da pressão arterial sistólica (PAS) realizadas com um oscilômetro. Medidas antropométricas e exames laboratoriais também foram realizados. O risco cardiovascular foi avaliado pelo estimador de risco de doença cardiovascular aterosclerótica (ASCVD), e se empregou a análise de regressão logística multivariada com nível de significância de 5%.

Resultados

Um risco cardiovascular significativamente maior foi determinado por uma VPA elevada para ambos os sexos. Uma prevalência significativamente maior de alto risco foi observada mais em homens que em mulheres em todos os quartis, com a maior diferença observada no quarto quartil de variabilidade (48,3% vs. 17,1%). Comparações entre quartis por sexo revelaram um risco significativamente mais alto para homens no terceiro (OR=1,20; IC95%: 1,02 - 1,40) e no quarto quartis OR=1,46; IC95%: 1,25 -1,71), e para mulheres no quarto quartil (OR=1,27; IC95%: 1,03 - 1,57).

Conclusão

Análises de dados basais de participantes do ELSA-Brasil revelaram que a variabilidade da pressão arterial se associou com risco cardiovascular aumentado, especialmente nos homens.

Visit-to-visit variability in albuminuria predicts renal function deterioration in patients with type 2 diabetes

Aims/Introduction

We aimed to study the predictive ability of visit‐to‐visit variability in albuminuria for changes in renal function in patients with type 2 diabetes mellitus.

Materials and Methods

The cohort study was carried out in a single medical center. In the model development cohort of 1008 subjects, we developed the albuminuria variability score (AVS) to evaluate the visit‐to‐visit variability in albuminuria, which was the percentage of the number of changes in the urine albumin : creatinine ratio ≥3.39 mg/mmol among all visit‐to‐visit urine albumin : creatinine ratio differences within an individual. Multivariate logistic regression was applied to predict the influence of AVS levels on the occurrence of study end‐points. In another independent validation cohort of 310 participants, survival analysis was carried out to evaluate the ability of AVS in predicting the study end‐point.

Results

In the model development cohort, a higher AVS was associated with higher adjusted odds of having a declined or rapidly declined estimated glomerular filtration rate (eGFR) trajectory (1.84, 95% confidence interval 1.23–2.76 and 5.70, 95% confidence interval 2.28–14.25, respectively), a resultant eGFR <60 mL/min/1.73 m² (2.61, 95% confidence interval 1.63–4.16) and a >40% decline in eGFR from baseline (6.44, 95% confidence interval 2.15–19.26). In the validation cohort, a higher AVS independently predicted a 5‐year decrease of >40% in eGFR to <60 mL/min/1.73 m² (adjusted hazard ratio 3.33, 95% confidence interval 1.10–10.05). Integrated discrimination index and concordance statistics showed that AVS significantly improved the predictive ability of the models.

Conclusions

Visit‐to‐visit variability in albuminuria can independently predict long‐term renal function deterioration in patients with type 2 diabetes mellitus. Further investigations are warranted to elucidate the potential clinical applications.

Blood pressure variability in individuals with diabetes mellitus: a scoping review

ABSTRACT Objectives: to map methods and devices used to assess very short-, short-, medium-, and long-term pressure variability in adults with type 1 or 2 diabetes mellitus. Methods: scoping review conducted in January and February 2021 in MEDLINE, Web of Science, CINAHL, LILACS, PubMed, and Embase databases. Studies conducted within the last ten years analyzing pressure variability in adult and older patients with diabetes mellitus type 1 or 2 were included. Studies that used discontinued devices were excluded. Results: the sample was composed of 25 articles published since 2017, with the majority developed in Japan (n=11); with the predominance of the oscillometric method (n=22); the most used devices were from the Omron® brand (n=14); the most detected type was long-term variability (n=10). Conclusions: we observed the increasing application of the oscillometric method for pressure variability analysis with various brands and models of automatic devices.

Impact of Visit-to-Visit Triglyceride-Glucose Index Variability on the Risk of Cardiovascular Disease in the Elderly

BACKGROUND

The aging population is increasingly susceptible to cardiovascular disease (CVD). Visit-to-visit variability in glucose and lipid levels both contributed to CVD risk independent of their mean values. However, whether variability in the triglyceride-glucose (TyG) index is a risk factor for CVD remains unknown. Research Design and Methods. In this retrospective study of electronic health records, 27,520 participants aged over 60 years were enrolled. The visit-to-visit variability of TyG index was calculated from annual health examination data and defined as average real variability (ARV), standard deviation (SD), or the coefficient of variability (CV). CVD events were identified from the chronic disease registry or follow-up database and included myocardial infarction, angina, coronary, and stroke. Multivariate Cox regression was used to examine the correlation between TyG variability and incident CVD.

RESULTS

Over a median follow-up of 6.2 years, there were 2,178 CVD events. When participants were divided into four quartiles according to their TyG variability, after adjusting for established CVD risk factors, subjects in the top quartile had (HR = 1.18, 95% CI 1.05-1.34, P=0.005) significantly higher CVD risk than those in the bottom quartile. The association remained significant in overweight individuals or those without diabetes (P < 0.005 and P < 0.01, respectively).

CONCLUSIONS

High variability in TyG was significantly associated with elevated CVD risk in the elderly, independent of average TyG and other risk factors. Close monitoring variability in TyG might be informative to identify old individuals at high risk of CVD.

Age-Specific Associations of Usual Blood Pressure Variability With Cardiovascular Disease and Mortality: 10-Year Diabetes Mellitus Cohort Study

Background

The detrimental effects of increased variability in systolic blood pressure (SBP) on cardiovascular disease (CVD) and mortality risk in patients with diabetes mellitus remains unclear. This study evaluated age‐specific association of usual SBP visit‐to‐visit variability with CVD and mortality in patients with type 2 diabetes mellitus.

Methods and Results

A retrospective cohort study investigated 155 982 patients with diabetes mellitus aged 45 to 84 years without CVD at baseline (2008–2010). Usual SBP variability was estimated using SBP SD obtained from a mixed‐effects model. Age‐specific associations (45–54, 55–64, 65–74, 75–84 years) between usual SBP variability, CVD, and mortality risk were assessed by Cox regression adjusted for patient characteristics. After a median follow‐up of 9.7 years, 49 816 events (including 34 039 CVD events and 29 211 mortalities) were identified. Elevated SBP variability was independently, positively, and log‐linearly associated with higher CVD and mortality risk among all age groups, with no evidence of any threshold effects. The excess CVD and mortality risk per 5 mm Hg increase in SBP variability within the 45 to 54 age group is >3 times higher than the 70 to 79 age group (hazard ratio, 1.66; 95% CI, 1.49–1.85 versus hazard ratio, 1.19; 95% CI, 1.15–1.23). The significant associations remained consistent among all subgroups. Patients with younger age had a higher association of SBP variability with event outcomes.

Conclusions

The findings suggest that SBP visit‐to‐visit variability was strongly associated with CVD and mortality with no evidence of a threshold effect in a population with diabetes mellitus. As well as controlling overall blood pressure levels, SBP visit‐to‐visit variability should be monitored and evaluated in routine practice, in particular for younger patients.

Long-Term Variability of Blood Pressure, Cardiovascular Outcomes, and Mortality: The Look AHEAD Study

BACKGROUND

We evaluated the associations of visit-to-visit blood pressure (BP) variability with incident cardiovascular disease (CVD) and deaths in adults with type 2 diabetes.

METHODS

We analyzed 4,152 participants in Look AHEAD (Action for Health in Diabetes) free of CVD events and deaths during the first 36 months of follow-up. Variability of systolic BP (SBP) and diastolic BP (DBP) across 4 annual visits was assessed using the intraindividual SD, variation independent of the mean, and coefficient of variation. Cox regression was used to generate the adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for CVD (myocardial infarction [MI], stroke, or CVD-related deaths) and mortality.

RESULTS

Over a median of 6.6 years, there were 220 MIs, 105 stroke cases, 62 CVD-related deaths, and 236 deaths. After adjustment for confounders including average BP, the aHRs for the highest (vs. lowest) tertile of SD of SBP were 1.98 (95% CI 1.01-3.92), 1.25 (95% CI 0.90-1.72), 1.26 (95% CI 0.96-1.64), 1.05 (95% CI 0.75-1.46), and 1.64 (95% CI 0.99-2.72) for CVD mortality, all-cause mortality, CVD, MI, and stroke, respectively. The equivalent aHRs for SD of DBP were 1.84 (95% CI 0.98-3.48), 1.43 (95% CI 1.03-1.98), 1.19 (95% CI 0.91-1.56), 1.14 (95% CI 0.82-1.58), and 0.97 (95% CI 0.58-1.60), respectively.

CONCLUSIONS

In a large sample of individuals with type 2 diabetes, a greater variability in SBP was associated with higher cardiovascular mortality and CVD events; a higher variability in DBP was linked to increased overall and cardiovascular mortality.

Variability of risk factors and diabetes complications

Several studies suggest that, together with glucose variability, the variability of other risk factors, as blood pressure, plasma lipids, heart rate, body weight, and serum uric acid, might play a role in the development of diabetes complications. Moreover, the variability of each risk factor, when contemporarily present, may have additive effects. However, the question is whether variability is causal or a marker. Evidence shows that the quality of care and the attainment of the target impact on the variability of all risk factors. On the other hand, for some of them causality may be considered. Although specific studies are still lacking, it should be useful checking the variability of a risk factor, together with its magnitude out of the normal range, in clinical practice. This can lead to an improvement of the quality of care, which, in turn, could further hesitate in an improvement of risk factors variability.

Visit-to-visit variability of clinical risk markers in relation to long-term complications in type 1 diabetes

BACKGROUND

Clinical characteristics such as HbA_1c , systolic blood pressure (SBP), albuminuria and estimated glomerular filtration rate (eGFR) are important when treating type 1 diabetes. We investigated the variability in these measures as risk markers for micro- and macrovascular complications.

METHODS

This prospective study included 1062 individuals with type 1 diabetes. Visit-to-visit variability of HbA_1c , SBP, albuminuria and eGFR was calculated as the SD of the residuals in individual linear regression models using all available measures in a specified period of 3 years (VV). Endpoints included were as follows: cardiovascular events (CVE) defined as myocardial infarction, non-fatal stroke, or coronary or peripheral arterial intervention; end-stage kidney disease (ESKD) defined as eGFR <15 ml/min/1.73 m² , chronic dialysis or kidney transplantation; eGFR decline ≥30%; and mortality. Adjustment included age, sex, cholesterol, HbA_1c , SBP, body mass index, smoking, albuminuria, eGFR, and mean, intercept, slope of respective exposure variables and regression models.

RESULTS

SBP VV was significantly associated with CVE (adjusted hazard ratio per 50% increase, (CI 95%); p: 1.21 [1.05-1.39]; p = 0.008), ESKD (1.51 [1.16-1.96]; p = 0.002) and mortality (1.25 [1.09-1.44]; p = 0.002). HbA_1c VV was significantly associated with mortality (1.51 [1.30-1.75]; p < 0.001); albuminuria VV with eGFR decline (1.14 [1.08-1.20]; p = 0.024) and ESKD (1.14 [1.02-1.27]; p < 0.001), but neither CVE nor mortality. Adjusted eGFR VV was not associated with endpoints.

CONCLUSION

In type 1 diabetes, higher variability of basic clinical risk markers adds important risk stratification information for the development of micro- and macrovascular complications.

Predictive value of visit-to-visit blood pressure variability for cardiovascular events in patients with coronary artery disease with and without diabetes mellitus

Background

High blood pressure is a major risk factor for cardiovascular disease. Visit-to-visit blood pressure variability (BPV) has recently been shown to predict cardiovascular outcomes. We investigated the predictive value of BPV for major adverse cardiovascular events (MACE) among patients with coronary artery disease (CAD), with and without type 2 diabetes mellitus (T2DM).

Methods

Patients with stable CAD were enrolled and monitored for new MACE. Visit-to-visit BPV was defined as the coefficient of variation (CV) of systolic and diastolic BP across clinic visits. Multivariable logistic regression analysis was performed to evaluate the association of BPV with MACE. Area under the receiver operating characteristic curve (AUC) was used to assess its predictive ability.

Results

Among 1140 Chinese patients with stable CAD, 192 (17%) experienced a new MACE. In multivariable analyses, the risk of MACE was significantly associated with CV of systolic BP (odds ratio [OR] for highest versus lowest quartile, 3.30; 95% CI 1.97–5.54), and diastolic BP (OR for highest versus lowest quartile, 2.39; 95% CI 1.39–4.11), after adjustment for variables of the risk factor model (age, gender, T2DM, hypertension, antihypertensive agents, number of BP measurements) and mean BP. The risk factor model had an AUC of 0.70 for prediction of MACE. Adding systolic/diastolic CV into the risk factor model with mean BP significantly increased the AUC to 0.73/0.72 (P = 0.002/0.007). In subgroup analyses, higher CV of systolic BP remained significantly associated with an increased risk for MACE in patients with and without T2DM, whereas the association of CV of diastolic BP with MACE was observed only in those without T2DM.

Conclusions

Visit-to-visit variability of systolic BP and of diastolic BP was an independent predictor of new MACE and provided incremental prognostic value beyond mean BP and conventional risk factors in patients with stable CAD. The association of BPV in CAD patients without T2DM with subsequent risk for MACE was stronger than in those with T2DM.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-021-01280-z.

Prediction models and nomograms for 10-year risk of end-stage renal disease in Chinese type 2 diabetes mellitus patients in primary care

AIMS

To develop and validate 10-year risk prediction models, nomograms and charts for end-stage renal disease (ESRD) in Chinese patients with type 2 diabetes mellitus (T2DM) in primary care, in order to guide individualized treatment.

MATERIALS AND METHODS

This was a 10-year population-based observational cohort study. A total of 141 516 Chinese T2DM patients without history of cardiovascular disease or ESRD who were managed in public primary care clinics in 2008 were included and followed up until December 2017. Two-thirds of these patients were randomly selected to develop sex-specific ESRD risk prediction models using Cox regressions. The validity and accuracy of the models were tested on the remaining third of patients using Harrell's C-index. We selected variables based on their clinical and statistical importance to construct the nomograms and charts.

RESULTS

The median follow-up period was 9.75 years. The cumulative incidence of ESRD was 6.0% (men: 6.1%, women: 5.9%). Age, diabetes duration, systolic blood pressure (SBP), SBP variability, diastolic blood pressure, triglycerides, glycated haemoglobin (HbA1c), HbA1c variability, urine albumin to creatinine ratio (UACR), and estimated glomerular filtration rate (eGFR) were significant predictors for both sexes. Smoking and total cholesterol to HDL cholesterol ratio were additional significant predictors for men and women, respectively. The models showed Harrell's C-statistics of 0.889/0.889 (women/men). Age, eGFR, UACR, SBP and HbA1c were selected for both sexes to develop nomograms and charts.

CONCLUSIONS

Using routinely available variables, the 10-year ESRD risk of Chinese T2DM patients in primary care can be predicted with approximately 90% accuracy. We have developed different tools to facilitate routine ESRD risk prediction in primary care, so that individualized care can be provided to prevent or delay ESRD in T2DM patients.

Association of visit-to-visit variability of systolic blood pressure with cardiovascular disease, chronic kidney disease and mortality in patients with hypertension

OBJECTIVE

This study aimed to evaluate the association between visit-to-visit variability of systolic blood pressure (SBP) and cardiovascular disease, chronic kidney disease, and mortality among hypertensive patients.

METHODS

A population-based cohort included 225 759 Chinese hypertensive adults without diabetes, cardiovascular disease, and chronic kidney disease during 2011-2012. SBP variability was determined based on standard deviations of SBP over the previous 5 years before baseline. Cox regressions adjusted with patients' baseline characteristics, mean, and temporal trend of SBP was applied to the associations between variability and incident cardiovascular disease, chronic kidney disease and all-cause mortality.

RESULTS

In all, 25 714 patients with cardiovascular disease, 27 603 with chronic kidney disease, and 16 778 deaths have occurred during the median follow-up of 70.5 months (1.2 million person-years). SBP variability was continuously and positively associated with higher cardiovascular disease, chronic kidney disease and mortality risk among hypertensive patients without evidence of a threshold. Each 10-mmHg increase in SD of SBP was associated with 35% [hazard ratio 1.35, 95% confidence interval (CI) 1.30-1.39], 39% (HR 1.39, 95% CI 1.35-1.43), and 40% (HR 1.40, 95% CI 1.34-1.45) higher risk of cardiovascular disease, chronic kidney disease and mortality, respectively. HRs were attenuated with increased age, mean SBP, and Charlson index, and decreased temporal trend of systolic blood pressure, but it remained significant and consistent in most of the different subgroups.

CONCLUSIONS

Findings suggested that SBP variability is a significant prognostic value, in addition to baseline or mean of SBP for the risk of cardiovascular disease and mortality.

Population segmentation of type 2 diabetes mellitus patients and its clinical applications - a scoping review

Background

Population segmentation permits the division of a heterogeneous population into relatively homogenous subgroups. This scoping review aims to summarize the clinical applications of data driven and expert driven population segmentation among Type 2 diabetes mellitus (T2DM) patients.

Methods

The literature search was conducted in Medline®, Embase®, Scopus® and PsycInfo®. Articles which utilized expert-based or data-driven population segmentation methodologies for evaluation of outcomes among T2DM patients were included. Population segmentation variables were grouped into five domains (socio-demographic, diabetes related, non-diabetes medical related, psychiatric / psychological and health system related variables). A framework for PopulAtion Segmentation Study design for T2DM patients (PASS-T2DM) was proposed.

Results

Of 155,124 articles screened, 148 articles were included. Expert driven population segmentation approach was most commonly used, of which judgemental splitting was the main strategy employed (n = 111, 75.0%). Cluster based analyses (n = 37, 25.0%) was the main data driven population segmentation strategies utilized. Socio-demographic (n = 66, 44.6%), diabetes related (n = 54, 36.5%) and non-diabetes medical related (n = 18, 12.2%) were the most used domains. Specifically, patients’ race, age, Hba1c related parameters and depression / anxiety related variables were most frequently used. Health grouping/profiling (n = 71, 48%), assessment of diabetes related complications (n = 57, 38.5%) and non-diabetes metabolic derangements (n = 42, 28.4%) were the most frequent population segmentation objectives of the studies.

Conclusions

Population segmentation has a wide range of clinical applications for evaluating clinical outcomes among T2DM patients. More studies are required to identify the optimal set of population segmentation framework for T2DM patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-021-01209-w.

Prognostic importance of long-term SBP variability in high-risk hypertension

OBJECTIVE

In addition to high blood pressure variability (BPV), low BPV was associated with adverse cardiovascular prognosis in selected high-risk patients. We explored this issue in the Systolic Blood Pressure Intervention Trial (SPRINT) using a nonlinear approach with BPV as a continuous variable.

METHODS

Long-term systolic BPV (SBPV) (coefficient of variation, CoV %) was calculated on quarterly visits until a fatal/nonfatal cardiovascular event or all-cause mortality, excluding titration period and patients with missing visits. We used Cox proportional hazard models with penalized smoothing splines to shape the risk of outcomes against the continuum of SBPV (independent variable). Adjusted hazard ratios (aHR, 95% CI) were calculated using the reference range derived from the nonlinear model. Sensitivity analysis based on propensity score matching (PSM) was performed.

RESULTS

The association of SBPV with fatal/nonfatal cardiovascular events was J-shaped, whereas that with all-cause mortality was linear. After multivariate adjustment, however, the only significant associations remained that of low SBPV (CoV <5%) with cardiovascular events (hazard ratio 1.85, 95% CI 1.24-2.75, P = 0.003), and of high SBPV (CoV >10%) with the composite of cardiovascular events and all-cause mortality (hazard ratio 1.35, 95% CI 1.02-1.80; P = 0.037). Low SBPV was associated with ischemic heart disease (hazard ratio 2.76, 95% CI 1.55-4.91; P < 0.001). There was a significant U-shaped association of SBPV with cardiovascular events in the PSM cohort.

CONCLUSION

Nonlinear modeling indicates that low and high long-term SBPV have prognostic relevance in high-risk hypertensive individuals from SPRINT. Randomized trials are needed to test these findings and their potential therapeutic implications.

Greater variability in lipid measurements associated with cardiovascular disease and mortality: A 10-year diabetes cohort study

AIM

To examine the associations between variability in lipids and the risk of cardiovascular disease (CVD) and mortality in patients with type 2 diabetes based on low-density lipoprotein-cholesterol (LDL-C), the total cholesterol (TC) to high-density lipoprotein-cholesterol (HDL-C) ratio and triglycerides (TG).

MATERIALS AND METHODS

A retrospective cohort study included 125 047 primary care patients with type 2 diabetes aged 45-84 years without CVD during 2008-2012. The variability of LDL-C, TC to HDL-C and TG was determined using the standard deviation of variables in a mixed effects model to minimize regression dilution bias. The associations between variability in lipids and CVD and mortality risk were assessed by Cox regression. Subgroup analyses based on patients' baseline characteristics were also conducted.

RESULTS

A total of 19 913 CVD events and 15 329 mortalities were recorded after a median follow-up period of 77.5 months (0.8 million person-years), suggesting a positive linear relationship between variability in lipids and the risk of CVD and mortality. Each unit increase in the variability of LDL-C (mmol/L), the TC to HDL-C ratio and TG (mmol/L) was associated with a 27% (HR: 1.27 [95% CI: 1.20-1.34]), 31% (HR:1.31 [95% CI: 1.25-1.38]) and 9% (HR: 1.09 [95% CI: 1.04-1.15]) increase in the risk of composite endpoint of CVD and mortality, respectively. Age-specific effects were also found when comparing LDL-C variability, with patients aged 45-54 years (HR: 1.70 [95% CI: 1.42-2.02]) exhibiting a 53% increased risk for the composite endpoints than those aged 75-84 years (HR: 1.11 [95% CI: 1.01-1.23]). Similar age effects were observed for both the TC to HDL-C ratio and TG variability. Significant associations remained consistent among most of the subgroups.

CONCLUSIONS

Variability in respective lipids are significant factors in predicting CVD and mortality in primary care patients with type 2 diabetes, with the strongest effects related to LDL-C and the TC to HDL-C ratio and most significant in the younger age group of patients aged 45-54 years. Further study is warranted to confirm these findings.

Prediction models for the risk of cardiovascular diseases in Chinese patients with type 2 diabetes mellitus: a systematic review

OBJECTIVES

Diabetes mellitus (DM) is a serious public health issue worldwide, and DM patients have higher risk of cardiovascular diseases (CVDs), which is the leading cause of DM-related deaths. China has the largest DM population, yet a robust model to predict CVDs in Chinese DM patients is still lacking. This systematic review is carried out to summarize existing models and identify potentially important predictors for CVDs in Chinese DM patients.

STUDY DESIGN

Systematic review.

METHODS

Medline and Embase were searched for data from April 1st, 2011 to May 31st, 2018. A study was eligible if it developed CVD (defined as total CVD or any major cardiovascular component) risk prediction models or explored potential predictors of CVD specifically for Chinese people with type 2 DM. Standardized forms were utilized to extract information, appraise applicability, risk of bias, and availabilities.

RESULTS

Five models and 29 studies focusing on potential predictors were identified. Models for a primary care setting, or to predict total CVD, are rare. A number of common predictors (e.g. age, sex, diabetes duration, smoking status, glycated hemoglobin (HbA1c), blood pressure, lipid profile, and treatment modalities) were observed in existing models, in which urine albumin:creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR) are highly recommended for the Chinese population. Variability of blood pressure (BP) and HbA1c should be included in prediction model development as novel factors. Meanwhile, interactions between age, sex, and risk factors should also be considered.

CONCLUSIONS

A 10-year prediction model for CVD risk in Chinese type 2 DM patients is lacking and urgently needed. There is insufficient evidence to support the inclusion of other novel predictors in CVDs risk prediction functions for routine clinical use.

Age-specific associations of glycated haemoglobin variability with cardiovascular disease and mortality in patients with type 2 diabetes mellitus: A 10- year cohort study

AIMS

To investigate the associations of increased variability in glycated haemoglobin (HbA1c) with cardiovascular disease (CVD) and mortality risk in patients with diabetes.

MATERIALS AND METHODS

This prospective cohort study included 147 811 patients aged 45 to 84 years with type 2 diabetes mellitus, without CVD and with at least three HbA1c values recorded before baseline in the period 2008 to 2010. HbA1c variability was evaluated using a mixed effects model to reduce regression dilution bias. Age-specific associations (45- 54, 55- 64, 65- 74 and 75- 84 years) between HbA1c variability and risk of CVD and mortality were assessed by Cox regression, adjusted for patient characteristics and usual HbA1c.

RESULTS

After a median follow-up of 7.4 years(1.02 million person-years), an overall incidence of 40 785 events including CVD (incidence 27  793) and all-cause mortalities (incidence 23 175) were identified. Positive log-linear associations between HbA1c variability and CVD and mortality were identified in all age groups. The hazard ratios (HRs) for the composite of CVD and all-cause mortality showed that age was inversely associated with HbA1c variability, with a 28% higher risk per 1% increase in HbA1c variability in the age group 45 to 54 years (all composite outcomes: HR 1.28, 95% confidence interval [CI] 1.21, 1.35), whereas only a 14% higher risk in the 75- 84 age group (all composite outcomes: HR 1.14, 95% CI 1.11, 1.17). Subgroup analysis showed the risk in patients with usual HbA1c <53mmol/mol was about eight times higher than in those with usual HbA1c ≥64mmol/mol.

CONCLUSIONS

HbA1c variability was strongly related to CVD and mortality in patients with diabetes across all age groups. Whilst pursuing optimal HbA1c targets, attention should be given to patients with high HbA1c variability, especially younger patients with good HbA1c control.

Prognostic importance of visit-to-visit blood pressure variability for micro- and macrovascular outcomes in patients with type 2 diabetes: The Rio de Janeiro Type 2 Diabetes Cohort Study

BACKGROUND

The prognostic importance of an increased visit-to-visit blood pressure variability (BP-VVV) for the future development of micro- and macrovascular complications in type 2 diabetes has been scarcely investigated and is largely unsettled. We aimed to evaluate it in a prospective long-term follow-up study with 632 individuals with type 2 diabetes.

METHODS

BP-VVV parameters (systolic and diastolic standard deviations [SD] and variation coefficients) were measured during the first 24-months. Multivariate Cox analysis, adjusted for risk factors and mean BP levels, examined the associations between BP-VVV and the occurrence of microvascular (retinopathy, microalbuminuria, renal function deterioration, peripheral neuropathy) and macrovascular complications (total cardiovascular events [CVEs], major adverse CVEs [MACE] and cardiovascular and all-cause mortality). Improvement in risk discrimination was assessed by the C-statistic and integrated discrimination improvement (IDI) index.

RESULTS

Over a median follow-up of 11.3 years, 162 patients had a CVE (132 MACE), and 212 patients died (95 from cardiovascular diseases); 153 newly-developed or worsened diabetic retinopathy, 193 achieved the renal composite outcome (121 newly-developed microalbuminuria and 95 deteriorated renal function), and 171 newly-developed or worsened peripheral neuropathy. Systolic BP-VVV was an independent predictor of MACE (hazard ratio: 1.25, 95% CI 1.03-1.51 for a 1-SD increase in 24-month SD), but not of total CVEs, cardiovascular and all-cause mortality, and of any microvascular outcome. However, no BP-VVV parameter significantly improved cardiovascular risk discrimination (increase in C-statistic 0.001, relative IDI 0.9%).

CONCLUSIONS

Systolic BP-VVV was an independent predictor of MACE, but it did not improve cardiovascular risk stratification. The goal of anti-hypertensive treatment in patients with type 2 diabetes shall remain in controlling mean BP levels, not on decreasing their visit-to-visit variability.

Effect of mean HbA1c on the association of HbA1c variability and all-cause mortality in patients with type 2 diabetes

AIM

To evaluate the effect of mean HbA1c on the correlation between HbA1c variability and all-cause mortality, and the risks associated with different levels of HbA1c and glycaemic control status in patients with type 2 diabetes.

MATERIALS AND METHODS

Patients with type 2 diabetes and at least three HbA1c measurements within 12-24 months were included. HbA1c variability score, coefficient of variation (CV) and standard deviation (SD) were used to evaluate variability. A variability score of 50 was set as a cutoff to define low and high variability.

RESULTS

A total of 4216 patients were included, of whom 1196 died during the observation period (11.1 ± 3.2 years). All-cause mortality increased with HbA1c variability score and the quartiles of HbA1c CV and SD. The strength of this association was attenuated after adjustment for mean HbA1c, and the risks associated with HbA1c variability and glycaemic control status were similar. The highest associated risk was observed with an HbA1c variability score of >50 and mean HbA1c of ≥7.5%. Mortality risk was significantly higher with a mean HbA1c of ≤6.0% and >8.5% and of ≤6.0% and >8.0% for low and high HbA1c variability, respectively.

CONCLUSIONS

Mean HbA1c contributed to the correlation between HbA1c variability and all-cause mortality. The risks associated with HbA1c variability and glycaemic control status were similar. The relationship between mean HbA1c and mortality presented a J-shaped distribution for both low and high HbA1c variability.

Factors Associated with Visit-to-Visit Variability of Blood Pressure Measured as Part of Routine Clinical Care among Patients Attending Cardiology Outpatient Department of a Tertiary Care Centre in Northern Sri Lanka

Visit-to-visit variability (VVV) is a relatively new concept in the hypertensive arena. Data regarding VVV are lacking in our region, and factors associated with VVV are rarely examined in previous studies. This study was conducted among 406 patients attended to the cardiology outpatient department of Teaching Hospital, Jaffna, Sri Lanka, in 2018 to assess the long-term variability of blood pressure (BP) by reviewing last six consecutive BP readings from the records retrospectively. Data regarding sociodemographic variables and behavioural factors such as medication adherence, physical activity, smoking, alcohol consumption, and relevant comorbidities were taken through an interviewer-administered questionnaire. Data were analysed by using SPSS version 25 and VVV of systolic blood pressure (SBP) matrix expressed as mean of SD and association were examined with various factors and VVV of SBP. SBP showed high VVV among the participants as expressed by mean of SD which was 13.06 ± 5.64. When comparing mean SD among the categories of different variables, female sex (P=0.023) and comorbidities such as diabetes mellitus (DM) (P=0.013), chronic kidney disease (CKD) (P=0.007), and risk of developing obstructive sleep apnoea (OSA) (P=0.04) showed significant variation. Medication adherence to prescribed hypertensive medication was a major issue even though significant association was not found with high VVV (P=0.536). The SD of SBP was then classified into high and low VVV groups by means of a cutoff point at the 50th percentile. Bivariate analysis by using Chi-squared test revealed comorbidities such as DM, CKD, and physical activity (P=0.044) were significantly associated with high VVV. Further multivariate regression analysis revealed that comorbidities such as DM and CKD have 1.561 times and 5.999 times more risk to show high variability, respectively. In conclusion, we recommend simple practical measures to achieve sustainable BP control among hypertensive patients with DM and CKD to minimize the VVV and improve their cardiovascular outcome.

Association between blood pressure variability, cardiovascular disease and mortality in type 2 diabetes: A systematic review and meta-analysis

AIM

To investigate the associations of blood pressure variability (BPV), expressed as long-term (visit-to-visit) and short-term (ambulatory blood pressure monitoring [ABPM] and home blood pressure monitoring [HBPM]) and all-cause mortality, major adverse cardiovascular events (MACEs), extended MACEs, microvascular complications (MiCs) and hypertension-mediated organ damage (HMOD) in adult patients with type 2 diabetes.

MATERIALS AND METHODS

PubMed, Medline, Embase, Cinahl, Web of Science, ClinicalTrials.gov and grey literature databases were searched for studies including patients with type 2 diabetes, at least one variable of BPV (visit-to-visit, HBPM, ABPM) and evaluation of the incidence of at least one of the following outcomes: all-cause mortality, MACEs, extended MACEs and/or MiCs and/or HMOD. The extracted information was analyzed using random effects meta-analysis and meta-regression.

RESULTS

Data from a total of 377 305 patients were analyzed. Systolic blood pressure (SBP) variability was associated with a significantly increased risk of all-cause mortality (HR 1.12, 95% CI 1.04-1.21), MACEs (HR 1.01, 95% CI 1.04-1.17), extended MACEs (HR 1.07, 95% CI 1.03-1.11) and MiCs (HR 1. 12, 95% CI 1.01-1.24), while diastolic blood pressure was not. Associations were mainly driven from studies on long-term SBP variability. Qualitative analysis showed that BPV was associated with the presence of HMOD expressed as carotid intima-media thickness, pulse wave velocity and left ventricular hypertrophy. Results were independent of mean blood pressure, glycaemic control and serum creatinine levels.

CONCLUSIONS

Our results suggest that BPV might provide additional information rather than mean blood pressure on the risk of cardiovascular disease in patients with type 2 diabetes.

Association of Visit-to-Visit Variability of Blood Pressure with Cardiovascular Disease among Type 2 Diabetes Mellitus Patients: A Cohort Study

BACKGROUND

Increasing evidence has shown that visit-to-visit variability (VVV) of blood pressure (BP) is associated with an increased risk of cardiovascular disease (CVD). The objective of this study was to evaluate the impact of VVV of systolic blood pressure (SBP) and diastolic blood pressure (DBP) on the risk of CVD among patients with type 2 diabetes mellitus (T2DM) in China.

METHODS

We conducted a retrospective cohort study of 10,163 T2DM patients who were not previously diagnosed with CVD from January 2008 to December 2012 in Ningbo, China. The VVV of BP was calculated using five metrics, including standard deviation (SD), coefficient of variation (CV), variation independent of mean, average real variability, and successive variability (SV) of measurements, obtained over a 24-month measurement period. Hazard ratios and 95% confidence intervals (CIs) were estimated by Cox proportional hazards regression models for the associations of variability in BP with risk of CVD.

RESULTS

A total of 894 CVD events were observed during a median follow-up of 49.5 months. The hazard ratio in the highest quintile of SD of SBP was 1.24 (95% CI, 1.01 to 1.52) compared with patients in the lowest quintile. The association between higher VVV of DBP and risk of CVD was not consistent across different metrics and sensitivity analyses.

CONCLUSION

Higher VVV of SBP was associated with an increased risk of CVD, irrespective of the mean SBP level. Future studies are needed to confirm these findings.

Ten-year risk prediction models of complications and mortality of Chinese patients with diabetes mellitus in primary care in Hong Kong: a study protocol

INTRODUCTION

Diabetes mellitus (DM) is a major disease burden worldwide because it is associated with disabling and lethal complications. DM complication risk assessment and stratification is key to cost-effective management and tertiary prevention for patients with diabetes in primary care. Existing risk prediction functions were found to be inaccurate in Chinese patients with diabetes in primary care. This study aims to develop 10-year risk prediction models for total cardiovascular diseases (CVD) and all-cause mortality among Chinese patients with DM in primary care.

METHODS AND ANALYSIS

A 10-year cohort study on a population-based primary care cohort of Chinese patients with diabetes, who were receiving care in the Hospital Authority General Outpatient Clinic on or before 1 January 2008, were identified from the clinical management system database of the Hospital Authority. All patients with complete baseline risk factors will be included and followed from 1 January 2008 to 31 December 2017 for the development and validation of prediction models. The analyses will be carried out separately for men and women. Two-thirds of subjects will be randomly selected as the training sample for model development. Cox regressions will be used to develop 10-year risk prediction models of total CVD and all-cause mortality. The validity of models will be tested on the remaining one-third of subjects by Harrell's C-statistics and calibration plot. Risk prediction models for diabetic complications specific to Chinese patients in primary care will enable accurate risk stratification, prioritisation of resources and more cost-effective interventions for patients with DM in primary care.

ETHICS AND DISSEMINATION

The study was approved by the Institutional Review Board of the University of Hong Kong-the Hospital Authority Hong Kong West Cluster (reference number: UW 15-258).

TRIAL REGISTRATION NUMBER

NCT03299010; Pre-results.

Peak lung function during young adulthood and future long-term blood pressure variability: The Coronary Artery Risk Development in Young Adults (CARDIA) study

BACKGROUND AND AIMS

Long-term blood pressure variability (BPV) is associated with cardiovascular events independent of mean blood pressure (BP); however, little is known about its predictors.

METHODS

Using data from the CARDIA study, we investigated the association between peak lung-function and long-term BPV in 2917 individuals (mean age 24.8 years, 45.3% males, 58.6% whites) who were not taking antihypertensive medications. Lung-function was measured using forced vital capacity (FVC) and forced expiratory volume in 1-s (FEV1) at years 0, 2, 5, 10 and 20 and the maximum score attained was considered as peak lung-function. Variability independent of the mean (VIM) and coefficient of variation (CV) of BP were calculated to quantify BPV since achieving peak lung-function across 9 visits over 30 years.

RESULTS

In a multivariate linear regression models, individuals in the 2nd (-0.64 mmHg; 95% CI: -1.06, -0.19), 3rd (-0.96; -1.47, -0.45), and 4th (-0.85: -1.53, -0.17) quartiles of FVC had lower VIM of systolic BP than the those in quartile 1 (p-trend = 0.005). CV of systolic BP was also lower by -0.58 (-0.98, -0.19), -0.92 (-1.42, -0.43), and -0.74 (-1.40, -0.08) percentage points, in the three progressively higher quartiles of FVC compared to quartile 1 (p-trend = 0.008). Similar findings were observed when the outcome was diastolic BPV. There was no association of FEV1 and FEV1-to-FVC ratio with BPV.

CONCLUSIONS

These findings suggest that smaller lung volume or restrictive lung disease during young adulthood, which result in lower peak FVC, may independently increase the risk of higher long-term BPV during middle adulthood.

Prognostic impact of systolic blood pressure variability in people with diabetes

Objective

Blood pressure variability (BPV) has been associated with risk of cardiovascular events in observational studies, independently of mean BP levels. In states with higher autonomic imbalance, such as in diabetes, the importance of BP variability may theoretically be even greater. We aimed to investigate the incremental value of BPV for prediction of cardiovascular and all-cause mortality in patients with type 2 diabetes.

Methods

We identified 9,855 patients without pre-existing cardiovascular disease who did not change BP-lowering treatment during the observation period from a Swedish primary health care cohort of patients with type 2 diabetes. BPV was summarized as the standard deviation (SD), coefficient of variation (CV), or variation independent of mean (VIM). Patients were followed for a median of 4 years and associations with cardiovascular and all-cause mortality were investigated using Cox proportional hazards models.

Results

BPV was not associated with cardiovascular specific or all-cause mortality in the total sample. In patients who were not on BP-lowering drugs during the observation period (n = 2,949), variability measures were associated with all-cause mortality: hazard ratios were 1.05, 1.04 and 1.05 for 50% increases in SD, CV and VIM, respectively, adjusted for Framingham risk score risk factors, including mean BP. However, the addition of the variability measures in this subgroup only led to very minimal improvement in discrimination, indicating they may have limited clinical usefulness (change in C-statistic ranged from 0.000–0.003 in all models).

Conclusions

Although BPV was independently associated with all-cause mortality in diabetes patients in primary care who did not have pre-existing cardiovascular disease or BP-lowering drugs, it may be of minimal clinical usefulness above and beyond that of other routinely measured predictors, including mean BP.

Visit-to-visit HbA1c variability and systolic blood pressure (SBP) variability are significantly and additively associated with mortality in individuals with type 1 diabetes: An observational study

AIM

To investigate the relationship between variability in both visit-to-visit HbA1c and SBP and mortality in individuals with type 1 diabetes.

METHODS

The Scottish Care Information (SCI) Diabetes dataset was used to identify 5952 individuals with type 1 diabetes for inclusion in this observational study. The SCI-Diabetes dataset allowed access to blood pressure values, HbA1c readings, demographic information and mortality rates for all study participants. Participants were dichotomized to above and below median values for both HbA1c coefficient of variation (CV) and SBP CV, thus dividing participants into 4 cohorts for survival analysis. Survival analysis was carried out over 1430 days. A Cox proportional hazard model was used to allow comparison of mortality between the 4 cohorts.

RESULTS

Of the 5952 patients, death occurred in 416. CV for both HbA1c and SBP were significantly associated with mortality. The median values for HbA1c CV and SBP CV were 8.0 and 8.1, respectively. The hazard ratio for high HbA1c CV only (P = .0015) was 1.78 ± 0.36. The hazard ratio for high SBP CV only (P = .0018) was 1.69 ± 0.33. The hazard ratio for both high HbA1c CV and high SBP CV (P < .00001) was 2.37 ± 0.32.

CONCLUSIONS

Our findings demonstrate that variability of both HbA1c and SBP is significantly and additively associated with mortality in individuals with type 1 diabetes. The variability of these parameters might be useful for risk stratification and is a potential target for future interventional studies.