Cardiovascular risk in newly diagnosed patients with type 2 diabetes mellitus: a nationwide, facility-based, cross-sectional study in Bangladesh

IF 1.9 Q3 PERIPHERAL VASCULAR DISEASE
A.B.M. Kamrul-Hasan , Muhammad Shah Alam , Marufa Mustari , Mohammad Abdul Hannan , Emran Ur Rashid Chowdhury , Sumon Rahman Chowdhury , Md. Abu Jar Gaffar , Swapan Kumar Singha , Choman Abdullah Mohana , Ershad Mondal , Md. Shahinur Rahman , Mohammad Motiur Rahman , Sourav Sarker , Md. Azizul Hoque , Md. Rashedul Islam , Md. Abdul Bari Robel , Shahryar Ahmad , Ahmed Ifrad Bin Raunak , Nur-A-Musabber , Md. Mostofa Kaisar , Shahjada Selim
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引用次数: 0

Abstract

Aims

Evidence on cardiovascular (CV) risk stratification in Bangladeshi patients with type 2 diabetes mellitus (T2DM) who are asymptomatic for cardiovascular disease (CVD) is limited. This study aimed to assess the 10-year CV risk in newly diagnosed patients with T2DM.

Methods

In 2023, a cross-sectional study was carried out at endocrinology clinics in tertiary hospitals throughout Bangladesh, involving newly diagnosed patients with T2DM aged 25 to 84 who had no prior history of CVD and were asymptomatic for the condition. CV risk was assessed and classified using QRISK3.

Results

1617 newly diagnosed patients with T2DM (age 44.92 ± 11.84 years, male 49.5 %) were analyzed. Their median QRISK3 score was 11.0 %, with 46.5 % at low, 25.7 % at moderate, and 27.8 % at high 10-year CV risk, respectively. The QRISK3 score increased with age for both men and women, with men consistently scoring higher than women in every age group. Among the age groups 25–39, 40–64, and 65–84, the percentages of patients with high 10-year CV risk were 3.3 %, 34.0 %, and 94.5 %, respectively. The median relative risk (RR) of CVD was 4.3. RR decreased with age for both sexes, and men had a lower RR than women across all age groups. A sleep duration of 6–9 h was associated with a lower 10-year CV risk.

Conclusions

Many newly diagnosed Bangladeshi patients with T2DM have substantial CV risk. QRISK3 can assist clinicians in predicting 10-year CV risk and choosing appropriate treatments to prevent CVD.
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