Reply to Hungerford, S.; Bart, N. Blood-Pressure-Monitoring Smartphone Applications: Ushering in a New Era of Wearable Cardiac Devices? Comment on “Vischer et al. Comparability of a Blood-Pressure-Monitoring Smartphone Application with Conventional Measurements—A Pilot Study. <i>Diagnostics</i> 2022, <i>12</i>, 749”

We would like to thank Drs. Hungerford and Bart for their kind comment [...

A model for early failure prediction of blood pressure measurement devices in a stepped validation approach

Abstract Blood pressure monitoring (BPM) devices have to be validated according to strict international validation protocols. Each protocol requests a specific number of participants to be included. All protocols use vast amounts of resources, as three people have to be present for every measurement, making trials costly, especially when the manufacturer has no intention to execute a validation study, reflected in the low share of validated in the commercially available BPM devices. The aim of our study was to develop criteria, which could detect low accuracy devices that could not pass a validation protocol early in the course of the validation process. The 2010 European Society of Hypertension International Protocol (ESH‐IP) and the Universal Standard for Validation of BPM devices (AAMI/ESH/ISO) were scrutinized for criteria which can be used for preclusion of passing. Based on this, we developed a fail model. We found that a BPM device cannot pass the ESH‐IP protocol, if there are ≥27, 13, or 4 single measurements differing more than 5, 10, or 15 mmHg, respectively, from the reference. For the AAMI/ESH/ISO protocol, we developed a model, which calculates best‐case standard deviations (SDs) to detect SDs which would prevent the passing of the protocol before its completion, making a stepwise validation process possible. In conclusion, we found that our model is able to predict failure of low‐accuracy BPM devices early during a validation protocol if used in a stepwise‐approach. This can be useful to keep costs of validation studies low and to enable investigator‐initiated trials

Prevalence and Characterisation of Severe Left Ventricular Hypertrophy Diagnosed by Echocardiography in Hypertensive Patients

Background: Arterial hypertension (AHT) is the leading preventable cause of death worldwide. Left ventricular hypertrophy (LVH) is one of the most important prognostic markers in hypertension and a predictor for mortality. The goals of this study were to examine the prevalence of LVH detected by echocardiography in patients with AHT and to describe patients with severe LVH. Methods: This is a retrospective monocentric study including patients treated at a tertiary hypertension clinic. Echocardiographic data were taken from written reports from our hospital’s echocardiography laboratories. We compared patients with severe LVH (septum thickness ≥ 15 mm) with patients with normal left ventricular (LV) geometry and with patients with concentric or eccentric hypertrophy regarding age, gender, comorbidities, medication, duration of hypertension, blood pressure (BP) and ECG changes at time of echocardiography. Results: Twenty-nine patients (7.3%) out of four hundred patients showed severe LVH and one hundred and eighty-nine (47.3%) a normal geometry. In comparison to patients with normal geometry, patients with severe LVH were more likely to be male, older, and with more uncontrolled BP, especially regarding asleep values, multi-drug antihypertensive treatment and comorbidities. In comparison to patients with concentric or eccentric hypertrophy, patients with severe LVH had a significantly higher diastolic BP in the 24 h mean, awake and asleep values. A positive Sokolow-Lyon index did not predict LVH. However, patients with severe LVH were more likely to have T-wave-inversions V4–V6 in at least one lead. Conclusions: More than half of the patients with AHT have an abnormal geometry in our study (52.5%) and 7.3% a severe LVH. Patients with severe LVH have more often an uncontrolled AHT than patients with a normal LV geometry, despite more antihypertensive treatment. The Sokolow-Lyon index seems to be insufficient to detect LVH

How should we measure blood pressure? Implications of the fourth blood pressure measurement in office blood pressure

Abstract According to the European Hypertension Guidelines regarding office blood pressure measurements (OBPMs), the mean between second/third or third/fourth OBPM should be taken if the first two readings differ by ≤10 or >10 mmHg, respectively. Our aim was to explore the value of the fourth OBPM and determine whether a simplified OBPM procedure is feasible without loss of quality. In this cross‐sectional study, four standard OBPMs were taken. The mean of the second/third OBPM (S2S3/D2D3) and third/fourth OBPM (S3S4/D3D4) for systolic/diastolic values was calculated. Correlation, agreement, and differences regarding BP classification were explored for the entire cohort and subsets with a difference between the first/second OBPM (S1S2/D1D2) ≤10 and >10 mmHg. Overall (n = 802) and for the subsets with an S1S2 (n = 596) and D1D2 (n = 742) difference ≤10 mmHg, S3S4/D3D4 was in median 0.5 mmHg lower than S2S3/D2D3, respectively (p 10 mmHg, S3S4/D3D4 differed numerically from S2S3/D2D3, respectively (p > .1 for all). Overall and for all subsets with an S1S2/D1D2 difference ≤10/>10 mmHg, less subjects were numerically classified as hypertensive with S3S4/D3D4 than with S2S3/D2D3 (p > .04), but BP reclassification occurred in both directions in 1.0%‐10.0%, depending on the cohort. In conclusion, the third/fourth OBPM results in lower BP values than the second/third measurement, regardless of the difference between first/second OBPM, whereby BP reclassifications occurred in both directions. Therefore, the cutoff of >10 versus ≤10mmHg difference between first/second OBPM to implement a fourth BPM harbors the risk of distorted results. We therefore recommend using the second/third BPM for standardized OBPM. Trial registration: Registered on clinicaltrials.gov (NCT02552030)

Risk stratification for 1-year mortality in acute heart failure

BACKGROUND: Simple tools for risk stratification of patients with acute heart failure (AHF) are an unmet clinical need, particularly regarding long-term mortality. METHODS: We prospectively enrolled 610 consecutive patients presenting to the emergency department with AHF. The diagnosis of AHF was adjudicated by two independent cardiologists. The classification and regression tree (CART) analysis was used to develop a simple risk algorithm. This was internally validated by cross-validation. RESULTS: One-year follow-up was complete in all patients (100%). A total of 201 patients (33%) died within 360 days. The CART analysis identified blood urea nitrogen (BUN) and age as the best single predictors of 1-year mortality and patients were categorised to three risk groups: high risk group (BUN /= 86 years) and low risk group (BUN >/= 27.5 mg/dl). The Kaplan-Meier curves showed a significant increase in mortality in the high risk group compared with the lower risk groups (log-rank test p >0.001). The hazard ratio regarding 1-year mortality between patients identified as low and high risk was 2.0 (95% confidence interval, 1.7-2.4), with statistically significant differences between all risk groups (p >0.001). The likelihood-based 95%-confidence set for the age- and the urea-threshold is contained in the rectangular set defined by 25 mg/dl >/= urea threshold >/=30.6 mg/dl and 76 years >/= age threshold >/=96 years. CONCLUSION: These results suggest that AHF patients at low, intermediate and high risk for death within 360 days can be easily identified using patient's demographics and laboratory data obtained at presentation. Application of this simple risk stratification algorithm may help to improve the management of these patients

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

BackgroundBlood 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.DesignIn 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).ResultsWe 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).ConclusionBased 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

Effect of Cuff Inflation on Blood Pressure, Arousals, Sleep Efficiency, and Desaturations: Sub-Analysis of the VAST Pilot Study

The influence of cuff inflations on night-time measurements during 24 h ambulatory blood pressure (BP) measurements is unknown. We investigated the potential effect of cuff inflations on sleep parameters using measurements taken simultaneously with a cuffless device using pulse-transit-time (PTT). On the first day of measurement, standard cuff-based 24 h BP and cuffless measurements were simultaneously performed on the right and left arms (CUFF/PTT-D). In this experiment, 1–2 days after the first measurement, the cuffless device was worn alone (PTT-D). Only data from the cuffless device were analyzed. The following mean sleep parameters were analyzed: mean systolic and diastolic BP, arousals, sleep efficiency, total arousals, arousal per hour, and desaturations. In total, 21 individuals were prospectively enrolled. The mean (SD) age was 47 (±15) years, and 57% were female. The mean systolic asleep BP during CUFF/PTT-D and during PTT-D were 131 (±21) and 131 (±26) mmHg, respectively. The mean diastolic asleep BP values during CUFF/PTT-D and during PTT-D were 80 (±14) and 84 (±14) mmHg, respectively (p = 0.860, p = 0.100, respectively). Systolic and diastolic asleep mean difference was 0.1 (±18.0) and −3.6 (±9.8) mmHg, respectively. There were significantly more total arousals during PTT-D (p = 0.042). There were no significant differences seen in sleep efficiency (p = 0.339) or desaturations (p = 0.896) between the two measurement periods. We could not show any significant impact from cuff inflations during sleep, as documented by PTT-D measurements