A Clinical Feature-Based Validation and Calibration for Diagnosing Hypertension and Cardiovascular Diseases: Integrative Review.: Validation and Calibration for Diagnosing Hypertension and Cardiovascular Disease - Abdulrahman, Nahla; Hamed, Abdelelah; Elfaki, Nahid; Idris, Amna; Taha, Wargaa (Zanco Journal of Medical Sciences (ZJMS), 2025)
Background and objective: Hypertension and Cardiovascular Diseases (CVD) are major global public health issues, leading to a large impact on illness and death rates. Prompt and precise identification of these diseases is essential for efficient management and avoidance of complication. This study aims to examine the significance of clinical characteristics in the diagnosis of cardiovascular diseases and hypertension. Identification and categorization of risk are crucial for prompt interventions and efficient management of these widespread and influential situations. The diagnostic techniques are based on clinical aspects, which include blood pressure measures, lipid profiles, family history, lifestyle choices, and comorbidities. Methods: The review evaluates the validation and calibration of clinical characteristics, drawing from robust data obtained through extensive cohort studies, risk prediction models, and adherence to defined criteria. It examines the role of measuring blood pressure, lipid profiles, and lifestyle habits in efficiently identifying individuals at risk of developing hypertension and CVD. Additionally, the review explores the incorporation of technology innovations, such as wearable devices, mobile apps, and artificial intelligence, in improving the diagnostic process. Results: This study shows that measuring blood pressure, lipid profiles, and lifestyle habits may efficiently detect individuals who are susceptible to develop hypertension and CVD. It is crucial to calibrate clinical characteristics in order to guarantee their precision and dependability in predicting the probability of hypertension and cardiovascular disease. This method entails enhancing risk assessment systems to include population-specific attributes and dynamic disease patterns. The incorporation of technology innovations, such as wearable devices, mobile apps, and artificial intelligence, has significantly improved the process of diagnosing clinical features, and the accuracy of predicting clinical parameters, making it easier to measure individualized risk and diagnose hypertension and cardiovascular disease at an early stage. Conclusion: Incorporating verified clinical characteristics into risk assessment tools and prediction models, together with advancements in technology, has the capacity to enhance the early identification and individualized treatment of these illnesses. Ongoing research and innovation in this sector are crucial to improve diagnostic methods and increase the accuracy of clinical feature-based diagnosis for hypertension and cardiovascular disease.