Registry of the Egyptian specialized hypertension clinics: patient risk profiles and geographical differences.
Amr El FaramawyGhada YoussefWafaa El AroussyDalia El RemisyHeba El DeebAmr Abdel AalM Mohsen IbrahimPublished in: Journal of human hypertension (2019)
Data regarding the prevalence and characteristics of cardiovascular (CV) risk factors among Egyptian hypertensive patients are limited. Nationwide Specialized Hypertension Clinics (SHCs) were initiated for screening, investigating, and treating hypertensive patients. This study aimed to determine the clinical characteristics and the CV risk profile of hypertensive Egyptians attending SHCs. Data from 4701 hypertensive patients were collected from the SHCs of nine university hospitals representing the different geographical regions of Egypt. Data collection started in October 2014 and ended in September 2017. Data included blood pressure (BP) measurements, clinical data, socio-demographic characteristics, anthropometric measurements, and cardiovascular risk profiles. The patients' mean age was 51.8 ± 11.5 years, 58.7% were older than 50 years, and 58.5% were females. The mean office systolic and diastolic BP values were 145.2 ± 22.4 and 88.7 ± 12.9 mmHg, respectively. Regarding CV risk factors, 58.6% were obese, 23.4% were smokers, and 25.1% had diabetes mellitus. Obesity was more prevalent in females than males (65.7% vs. 53.0%, p < 0.001, respectively), while dyslipidaemia and smoking were significantly more common in male patients. The highest levels of BP and the highest global risk were observed in the inhabitants of the Delta region, despite their younger age. In conclusion, this study revealed a high prevalence of modifiable CV risk factors among a cohort of Egyptian hypertensive patients attending SHCs. The pattern of the risk factors across the different geographic regions may be attributed to rapid urbanization. Governmental and community-based approaches are needed for better control of hypertension and its associated CV risk factors.
Keyphrases
- blood pressure
- hypertensive patients
- risk factors
- heart rate
- electronic health record
- end stage renal disease
- big data
- ejection fraction
- chronic kidney disease
- primary care
- type diabetes
- prognostic factors
- weight loss
- metabolic syndrome
- palliative care
- blood glucose
- adipose tissue
- left ventricular
- machine learning
- physical activity
- smoking cessation
- data analysis
- heart failure
- insulin resistance
- patient reported outcomes
- bariatric surgery
- deep learning
- tertiary care
- quantum dots
- weight gain
- middle aged