Why the study?
Does cardiothoracic ratio on chest radiographs predict hypertensive heart disease in adults with systemic hypertension?
Does cardiothoracic ratio on chest radiographs predict hypertensive heart disease in adults with systemic hypertension?
Cardiothoracic ratio on chest radiographs is significantly higher in hypertensive patients and can serve as a simple, accessible predictor for hypertensive heart disease.
May aid detection of hypertensive heart disease where echocardiography is unavailable; leaves open prospective validation against imaging standards.
Background: Systemic hypertension is a worldwide epidemic and often called a silent killer. It is the commonest cardiovascular disease among Africans, and an acknowledged potential risk factor for the development of cardiovascular diseases such as stroke, hypertensive heart disease, hypertensive heart failure, and end organ damage of the brain, eyes, and kidneys. Hypertensive heart disease results in high cardiothoracic ratio (CTR), which is evident on a chest radiograph. This study was aimed at using CTR on chest radiographs to predict the occurrence of hypertensive heart disease among hypertensive adults in Zaria.Patients and Methods: The study was carried out in the Department of Radiology, Ahmadu Bello University Teaching Hospital, Zaria, Nigeria, using static conventional x-ray machine. Consecutive 305 hypertensive patients and equal number of normal individuals, age and sex matched (as controls), were recruited. The chest radiographs of the participants were taken according to standard technique, and required measurements such as CTR and aortic arch width were taken and documented.Results: The mean CTR for the hypertensive patients and controls were 0.52 ± 0.07 and 0.45 ± 0.04, respectively. There was significant relationship between CTR and hypertensive heart disease. Other variables such as blood pressure, age, and sex also correlated significantly with CTR.Conclusion: The CTR showed positive relationship with blood pressure and hypertensive heart disease and it could, therefore, be used to predict the occurrence of these conditions.
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Aiyekomogbon et al. (2017) studied this question.
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