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Introduction: Hypertension and dyslipidaemia are major risk factors for cardiovascular diseases, and achieving treatment goals mitigates such risks. This study determined demographic and medication-related factors associated with blood pressure (BP) goal attainment in patients with concomitant hypertension and dyslipidaemia. Methods: This paper consisted of a sub-analysis of the Lipid HEALTH study, a questionnaire survey focusing on adult Asian patients with both dyslipidaemia and hypertension. Intervieweradministered questionnaire was used to obtain information on demographic and clinical information. Laboratory and prescription data was retrieved from electronic health records. BP goals were defined by international guidelines. Data was audited and analysed, followed by logistic regression analysis to identify factors determining BP goal attainment. Results: The complete data of 851 included patients were analysed; 49.7% of them attained their BP goals. 37% were on monotherapy, 57.6% on two or more BP-lowering medications, and 5.5% had no pharmacologic treatment. Among those on pharmacotherapy, 51.2% failed to achieve BP goals. Calcium channel blockers were the most frequently prescribed medications. Attainment of BP goals was significantly associated who had no type 2 diabetes mellitus (DM) (OR 2.27; 95% CI 1.61-3.13); attained low-density lipoprotein cholesterol (LDL-C) goal (OR 2.02; 95% CI 1.45-.81); were solely on dietary control (OR 2.19; 95% CI 1.09-4.39); and received monotherapy (OR 1.71; 95% CI 1.18-2.48). Conclusion: BP treatment goals were attained by half of the patients with dyslipidaemia and hypertension, and half of those on pharmacotherapy. Type 2 DM and LDL-C control were significantly associated with BP goal attainment.

BACKGROUND: Coronary artery disease (CAD) risk prediction tools are useful decision supports. Their clinical impact has not been evaluated amongst Asians in primary care. OBJECTIVE: We aimed to develop and validate a diagnostic prediction model for CAD in Southeast Asians by comparing it against three existing tools. DESIGN: We prospectively recruited patients presenting to primary care for chest pain between July 2013 and December 2016. CAD was diagnosed at tertiary institution and adjudicated. A logistic regression model was built, with validation by resampling. We validated the Duke Clinical Score (DCS), CAD Consortium Score (CCS), and Marburg Heart Score (MHS). MAIN MEASURES: Discrimination and calibration quantify model performance, while net reclassification improvement and net benefit provide clinical insights. KEY RESULTS: CAD prevalence was 9.5% (158 of 1658 patients). Our model included age, gender, type 2 diabetes mellitus, hypertension, smoking, chest pain type, neck radiation, Q waves, and ST-T changes. The C-statistic was 0.808 (95% CI 0.776-0.840) and 0.815 (95% CI 0.782-0.847), for model without and with ECG respectively. C-statistics for DCS, CCS-basic, CCS-clinical, and MHS were 0.795 (95% CI 0.759-0.831), 0.756 (95% CI 0.717-0.794), 0.787 (95% CI 0.752-0.823), and 0.661 (95% CI 0.621-0.701). Our model (with ECG) correctly reclassified 100% of patients when compared with DCS and CCS-clinical respectively. At 5% threshold probability, the net benefit for our model (with ECG) was 0.063. The net benefit for DCS, CCS-basic, and CCS-clinical was 0.056, 0.060, and 0.065. CONCLUSIONS: PRECISE (Predictive Risk scorE for CAD In Southeast Asians with chEst pain) performs well and demonstrates utility as a clinical decision support for diagnosing CAD among Southeast Asians.