Correlation Between Ambulatory Blood Pressure Monitoring and Office Blood Pressure Measurement in Patients with Hypertension: A Community Study.

BACKGROUND: The current gold standard for blood pressure (BP) measurements is based on office BP measurements (OBPMs) by a sphygmomanometer or a digital device. Ambulatory BP measurement (ABPM) is a noninvasive method for continuous monitoring of BP over a period during routine activities of the patient. Thus, ABPM offers multiple BP readings during the patients' daily routine as compared to the single reading by OBPM at rest. A good correlation exists between mean 24-hour BP readings and the prediction of cardiovascular events. The present multicenter observational study was aimed to assess the correlation between ABPM and OBPM in patients with newly diagnosed, controlled, or uncontrolled hypertension in the community setting. Our hypothesis was to test if ABPM provides any further value in those hypertensive patients in whom the office blood pressure levels are controlled. A supplementary hypothesis was whether obtaining ABPM in patients with newly diagnosed or uncontrolled hypertension yields any value over and beyond OBPM. Another objective was to find out the applicability of ABPM in the community setting where the medical care is provided by primary care family physicians and not by specialists. MATERIALS AND METHODS: Materials and Methods A total of 1000 patients were analysed for this study. Those with controlled hypertension were assigned to Group A, and those with newly diagnosed/untreated hypertension comprised Group B. Group A was followed up during Visit 2 and Group B was followed up during Visit 2 and either Visit 3 or Visit 4 to assess the BP measurements by ABPM and OBPM. RESULTS: The correlation between ABPM and OBPM showed minimal variation in the BP readings of Group A subjects at Visit 2. A variation in BP readings was observed in Group B at Visit 2. Furthermore, the correlation was established between ABPM and OBPM noted for Group B subjects during Visit 3, and minimal variation was noted during Visit 4. CONCLUSIONS: Conclusions A good correlation was observed between ABPM and OBPM during both visits in patients in Groups A and B. However, a notable variation was noted in the diastolic BP readings. Thus, large-scale clinical studies are required to detect the prevalence of hypertension, masked hypertension, and dipping patterns associated with hypertension and other related medical co-morbidities.

Risk factors predisposing to acute stroke in India: a prospective study.

BACKGROUND: Stroke is an important neurological disorder with significant morbidity and mortality. In India, the risk factors for stroke (obesity, diabetes mellitus, alcoholism, hypertension, and sedentary lifestyle) are mounting with economic growth and increasing the disease burden. OBJECTIVE: To assess the severity and risk factors of stroke in India and identify any new predisposing factors. METHODS: A multicentric (six tertiary care hospitals across India) prospective observational study (from September 2016 to July 2017) was conducted on 526 stroke patients, presenting within the first 24 h to examine the risk factors for ischemic and hemorrhagic strokes. Severity was determined using the National Institutes of Health Stroke Scale (NIHSS). RESULTS: Predominantly male (72.3%), 75% of the sample was >50 years old, with a mean body mass index (BMI) of 25.8 ±â€Š4.3 kg/m2 and 14.6% obese patients. Hypertension and diabetes mellitus were the commonest comorbidities, followed by a history of ischemic heart disease and familial history of stroke. 20.5% of patients had mild strokes, 57.4% had moderate, 8.4% experienced moderate-severe strokes, whereas 7.2% had severe strokes. Regarding the admission diagnoses, 56.8% were ischemic, 18.6% were hemorrhagic, 1.1% had a transient ischemic attack, 6.6% suffered recurrent strokes, and 17% were other forms. CONCLUSION: The foremost risk factors for stroke in India, hypertension and diabetes, need to be controlled and treated like other global high-risk populations for stroke prevention. The NIHSS scores highlight the relationship between risk factors and stroke severity.