Implementing Automated Office Blood Pressure Measurement

Current apparent treatment-resistant hypertension in patients undergoing peritoneal dialysis: A multi-center cross-sectional study

Apparent treatment‐resistant hypertension (aTRH) is the most commonly used term to report resistant hypertension (RH) and is considered as a common problem in dialysis population. However, few reports have focused on peritoneal dialysis (PD) hypertensive patients. The authors conducted a multi‐center cross‐sectional study involving 1789 PD patients from nine centers in Guangdong, China. The prevalence of aTRH was estimated by home blood pressure (BP) monitoring. Evaluating drug adherence through Eight‐item Morisky Medication Adherence Scale (MMAS‐8) and pill counting was performed to assess RH in one PD center. Related factors of aTRH were analyzed using logistic regression analysis. The prevalence of aTRH in PD patients was estimated at 42.2% (755 out of 1789 hypertensive patients) based on home BP. Of those, 91.4% patients were classified as uncontrolled RH, 2.0% as controlled RH, and 6.6% as refractory hypertension. The prevalence of RH was 40.6% and 41.9% among those with medium/high adherence based on the MMAS‐8 scores and the pill counting rate, respectively. PD patients who were younger, with higher body mass index, with lower serum albumin and poorer dialysis adequacy were significantly associated with higher aTRH incident. In conclusion, the present study demonstrates a high prevalence of aTRH in PD population, which occurs in about two in five treated hypertensive patients. Nutritional status and dialysis adequacy might tightly associate with aTRH.

Direct comparison of the reproducibility of in-office and self-measured home blood pressures

OBJECTIVE

The aim was to compare short-term and long-term reproducibilities of in-office unattended blood pressure (BP), namely automated office blood pressure (AOBP), conventionally measured attended office BP, and self-measured home BP.

METHODS

A multicentre, clinical study was conducted in Japan, and 287 Japanese outpatients on antihypertensive drug medication were followed-up for 1 year.

RESULTS

The intensity of drug treatment was sustained consistently throughout the study period (defined daily doses, 1.62-1.68; P = 0.12). The mean SBP differences between baseline and 1 month later, as well as baseline and 1 year later, were less than 1.5 mmHg, whereas the standard deviations of the differences for home, AOBP, and attended office measurements for the 1-year interval were 7.7, 14.5, and 15.3 mmHg, respectively. The coefficients of variation were significantly smaller for home BP than for AOBP among all patients at both 1-month and 1-year intervals (P < 0.0001). In the 1-month interval, partial correlation coefficients of home BP (r, 0.73/0.88 for systolic/diastolic measures) were significantly higher than of conventional BP (r, 0.47/0.69). However, the correlations converged to the modest level regardless of BP information (r, 0.49-0.54/0.63-0.73) when the 1-year interval was assessed. Results were confirmatory when patients on the same drug regimen (n = 167) were analysed.

CONCLUSION

A higher reproducibility of home BP was demonstrated compared with in-office BP, including AOBP. However, the modest correlations for the 1-year interval support the importance of regular assessment of BP, regardless of in-office or home measurements for treatment of hypertension.

Heart Failure Events in a Clinical Trial on Arterial Hypertension: New Insights Into the SPRINT Trial

[Figure: see text].

Accuracy of abbreviated protocols for unattended automated office blood pressure measurements, a retrospective study

Background

Blood pressure measurement (BPM) is one of the most often performed procedures in clinical practice, but especially office BPM is prone to errors. Unattended automated office BPM (AOBPM) is somewhat standardised and observer-independent, but time and space consuming. We aimed to assess whether an AOBPM protocol can be abbreviated without losing accuracy.

Design

In our retrospective single centre study, we used all AOBPM (AOBPM protocol of the SPRINT study), collected over 14 months. Three sequential BPM (after 5 minutes of rest, spaced 2 minutes) were automatically recorded with the patient alone in a quiet room resulting in three systolic and diastolic values. We compared the mean of all three (RefProt) with the mean of the first two (ShortProtA) and the single first BPM (ShortProtB).

Results

We analysed 413 AOBPM sets from 210 patients. Mean age was 52±16 years. Mean values for RefProt were 128.3/81.3 mmHg, for ShortProtA 128.4/81.4 mmHg, for ShortProtB 128.8/81.4 mmHg. Mean difference and limits of agreement for RefProt vs. ShortProtA and ShortProtB were -0.1±4.2/-0.1±2.8 mmHg and -0.5±8.1/-0.1±5.3 mmHg, respectively. With ShortProtA, 83% of systolic and 92% of diastolic measurements were within 2 mmHg from RefProt (67/82% for ShortProtB). ShortProtA or ShortProtB led to no significant hypertensive reclassifications in comparison to RefProt (p-values 0.774/1.000/1.000/0.556).

Conclusion

Based on our results differences between the RefProt and ShortProtA are minimal and within acceptable limits of agreement. Therefore, the automated procedure may be shorted from 3 to 2 measurements, but a single measurement is insufficient.

Human Errors in Automated Office Blood Pressure Measurement: Still Room for Improvement

In this review of the literature and commentary, we examine the literature on automated blood pressure (BP) measurements in the office and clinic. Our purpose is to revisit issues as to the pros and cons of automated BP measurement published in Hypertension in June 2020 and to identify areas needing additional research. Despite initial reservations about automated BP, it is here to stay. A number of experts suggest that human error will be reduced when we move from the more complex skills required by aneroid sphygmomanometer measurement to the fewer skills and steps required by automated BP measurement. Our review indicates there is still need for reduction in errors in automated BP assessment, for example, retraining programs and monitoring of assessment procedures. We need more research on the following questions: (1) which classes of health care providers are least likely to measure BP accurately, usually by ignoring necessary steps; (2) how accurate is BP assessment by affiliated health care providers for example the dental office, the optometrist; and (3) why do some dedicated and well-informed health care professionals fail to follow simple directions for automated BP measurement? We offer additional solutions for improving automated BP assessment in the office and clinic.