Reference Systolic Blood Pressure Research Articles

Systolic Blood Pressure, Diastolic Blood Pressure and Pulse Pressure and the Risk of Subclinical Myocardial Injury: The HUNT Study.

Subclinical myocardial injury expressed as higher cardiac troponin concentrations may represent an important intermediary between hypertension and the risk of cardiovascular disease. The study aimed to assess the relative strength of associations between systolic blood pressure (BP), diastolic BP, and pulse pressure, and subclinical myocardial injury, and how change in BP variables over time associates with subclinical myocardial injury. cTnl (cardiac troponin I) was measured in 32 968 participants of the fourth wave of the population-based cohort HUNT4 (Trøndelag Health Study) without a history of cardiovascular disease. An additional longitudinal analysis included participants from HUNT4 with BP measurements from HUNT3 (n=18 681). Associations between BP variables and cTnI concentrations were assessed by linear and logistic regression analyses. The median cTnI concentration was 1.6 ng/L (25th-75th percentiles, 0.6-3.1 ng/L), median age was 52 years (39.1-65.6 years), and 57% were female subjects. Cross-sectionally, only systolic BP categories ≥130 mm Hg associated with higher cTnI concentrations, compared with a reference systolic BP of <110 mm Hg. All categories of diastolic BP and pulse pressure were positively associated with higher cTnI concentrations when diastolic BP 70 to 79 mm Hg and pulse pressure <40 mm Hg were used as references, respectively. When comparing systolic BP, diastolic BP, and pulse pressure as continuous variables, cross-sectionally, pulse pressure most strongly associated with cTnI concentrations (P for all comparisons <0.001), whereas longitudinally, change in diastolic BP was most strongly associated with cTnI concentrations (P for all comparisons <0.05). Subjects with high pulse pressure and longitudinal increase in diastolic BP are at higher risk for subclinical myocardial injury.

Blood Pressure Measurement Based on the Camera and Inertial Measurement Unit of a Smartphone: Instrument Validation Study.

Even though several mobile apps that can measure blood pressure have been developed, the data about the accuracy of these apps are limited. We assessed the accuracy of AlwaysBP (test) in blood pressure measurement compared with the standard, cuff-based, manual method of brachial blood pressure measurement (reference). AlwaysBP is a smartphone software that estimates systolic blood pressure (SBP) and diastolic blood pressure (DBP) based on pulse transit time (PTT). PTT was calculated with a finger photoplethysmogram and seismocardiogram using, respectively, the camera and inertial measurement unit sensor of a commercially available smartphone. After calculating PTT, SBP and DBP were estimated via the Bramwell-Hill and Moens-Korteweg equations. A calibration process was carried out 3 times for each participant to determine the input parameters of the equations. This study was conducted from March to August 2021 at Chungnam National University Sejong Hospital with 87 participants aged between 19 and 70 years who met specific conditions. The primary analysis aimed to evaluate the accuracy of the test method compared with the reference method for the entire study population. The secondary analysis was performed to confirm the stability of the test method for up to 4 weeks in 15 participants. At enrollment, gender, arm circumference, and blood pressure distribution were considered according to current guidelines. Among the 87 study participants, 45 (52%) individuals were male, and the average age was 35.6 (SD 10.4) years. Hypertension was diagnosed in 14 (16%) participants before this study. The mean test and reference SBPs were 120.0 (SD 18.8) and 118.7 (SD 20.2) mm Hg, respectively (difference: mean 1.2, SD 7.1 mm Hg). The absolute differences between the test and reference SBPs were <5, <10, and <15 mm Hg in 57.5% (150/261), 84.3% (220/261 ), and 94.6% (247/261) of measurements. The mean test and reference DBPs were 80.1 (SD 12.6) and 81.1 (SD 14.4) mm Hg, respectively (difference: mean -1.0, SD 6.0 mm Hg). The absolute differences between the test and reference DBPs were <5, <10, and <15 mm Hg in 75.5% (197/261), 93.9% (245/261), and 97.3% (254/261) of measurements, respectively. The secondary analysis showed that after 4 weeks, the differences between SBP and DBP were 0.1 (SD 8.8) and -2.4 (SD 7.6) mm Hg, respectively. AlwaysBP exhibited acceptable accuracy in SBP and DBP measurement compared with the standard measurement method, according to the Association for the Advancement of Medical Instrumentation/European Society of Hypertension/International Organization for Standardization protocol criteria. However, further validation studies with a specific validation protocol designed for cuffless blood pressure measuring devices are required to assess clinical accuracy. This technology can be easily applied in everyday life and may improve the general population's awareness of hypertension, thus helping to control it.

Systolic blood pressure, chronic obstructive pulmonary disease and cardiovascular risk

ObjectiveIn individuals with complex underlying health problems, the association between systolic blood pressure (SBP) and cardiovascular disease is less well recognised. The association between SBP and risk of cardiovascular events...

Systolic blood pressure estimation using ECG and PPG in patients undergoing surgery

Background and ObjectivesIn a significant portion of surgeries, blood pressure (BP) is often measured non-invasively in an intermittent manner. This practice has a risk of missing clinically relevant BP changes between two adjacent intermittent BP measurements. This study proposes a method to non-invasively estimate systolic blood pressure (SBP) with high accuracy in patients undergoing surgery. MethodsContinuous arterial BP, electrocardiography (ECG), and photoplethysmography (PPG) signals were acquired from 29 patients undergoing surgery. After extracting 9 features from the PPG and ECG signals, we dynamically selected features upon each intermittent measurement (every 10 min) of SBP based on feature robustness and the principle of correlation-based feature selection. Finally, multiple linear regression models were built to combine these features to estimate SBP every 30 s. ResultsCompared to the reference SBP, the proposed method achieved a mean of difference at 0.08 mmHg, a standard deviation of difference at 7.97 mmHg, and a correlation coefficient at 0.89 (p < 0.001). ConclusionsThis study demonstrates the feasibility of non-invasively estimating SBP every 30 s with high accuracy during surgery by using ECG, PPG, and intermittent SBP measurements every 10 min, which meets the standard of the Association for the Advancement of Medical Instrumentation. The proposed method has the potential to enhance BP monitoring in the operating room, improving patient outcomes and experiences.

Novel Cuffless Blood Pressure Estimation Method Using a Bayesian Hierarchical Model.

Continuous blood pressure (BP) monitoring is important for the prevention and early diagnosis of cardiovascular diseases. Cuffless BP estimation using pulse arrival time (PAT) via a mathematical model which enables continuous BP measurement has recently become a popular research topic. In this study, simultaneous biomedical signals from ten healthy subjects were acquired by electrocardiogram (ECG) and photoplethysmogram (PPG) sensors and the continuous reference BP data were collected by a cuff-based Finometer PRO BP monitor. A hierarchical model was applied to estimate the parameters of a nonlinear model which in turn is used to estimate systolic blood pressure (SBP) using PAT with few calibration measurements. The mean absolute difference (MAD) between the estimated SBP and reference SBP is 4.35±1.43 mmHg using the proposed hierarchical model with three calibration measurements and is 4.36±1.17 mmHg with a single calibration measurement.

A minimally-occlusive cuff method utilizing ultrasound vascular imaging for stress-free blood pressure measurement

Abstract Objective Occlusive cuff inflation in ambulatory blood pressure (BP) monitoring disturbs the daily life of the user, and affects efficacy of monitoring. To overcome this limitation, we have developed a novel minimally-occlusive cuff method for stress-free measurement of BP. This study aimed to experimentally evaluate the reliability of this method, and improve the precision of this method by implementing a machine learning algorithm. Methods In this method, a thin-plate-type ultrasound probe (Size: 5.6mm-thickness × 28mm × 26mm; weight: 10g) is placed between the cuff and the skin, and used to measure the ultrasonic dimension of the artery (Figure 1). The cuff pressure (Pc), arterial dimension at systole (Ds) and diastole (Dd), systolic BP (SBP) and diastolic BP (DBP) during cuff inflation are theoretically related by the following equations, SBP-Pc = P0·Exp[α·Ds] DBP-Pc = P0·Exp[α·Dd] Where P0 and α are constants, and α indicates arterial stiffness. Since multiple sets of the two equations can be defined over multiple cardiac beats while measuring Pc, Ds and Dd during mild cuff inflation (Pc is controlled less than 50 mmHg, Figure 1), it is possible to estimate SBP (SBPe) and DBP (DBPe) as solutions of the equations. In 6 anesthetized dogs, we attached the cuff and the probe to the right thigh to get SBPe and DBPe, which were one-time calibrated in each animal against reference SBP and DBP measured by using an intra-arterial catheter. We also determined the pulse arrival time (PAT), which is a commonly employed parameter in cuff-less BP monitoring. In all the dogs, BP was changed extensively by infusing noradrenaline or sodium nitroprusside. Results DBPe correlated tightly with DBP with a coefficient of determination (R2) of 0.85±0.08, and predicted DBP with error of 3.9±7.9 mmHg after one-time calibration (Figure 2). PAT correlated poorly with DBP (R2=0.49±0.17), and predicted DBP less accurately than this method. SBPe correlated well with SBP (R2=0.78±0.08) (Figure 3). However, even after one-time calibration, difference between SBPe and SBP was 2.6±18.9 mmHg, which was not acceptable. To improve the precision in SBP prediction, we used supervised machine learning approach with use of a support vector algorithm (Python, Scikit-learn), which regressed feature variables (SBPe, DBPe, Ds, Dd heart rate, and PAT) against teacher signal (reference SBP). The support vector algorithm, once trained, predicted SBP with acceptable accuracy with error of 0.7±6.9 mmHg (Figure 3). Conclusions This method reliably tracks BP changes without occlusive cuff inflation. Once calibrated, this method measures DBP accurately. With the aid of machine learning, precision in SBP prediction was greatly improved to an acceptable level. This method with machine learning approach has potential for stress-free BP measurement in ambulatory BP monitoring. Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): Japan Society for the Promotion of Science

MobiEye: turning your smartphones into a ubiquitous unobtrusive vital sign monitoring system

Recent advances in mobile and wearable technologies have stimulated significantly growing demands for more affordable, user-friendly, pervasive healthcare solutions that can be adopted by the public to proactively manage their health conditions and alleviate the burdens of hospitalization. This study seeks to propose a personalized ubiquitous health monitoring system that can unobtrusively monitor individuals’ vital signs, anywhere at any time. The proposed MobiEye framework makes use of the regular camera available on any smartphones or tablets to record various most important physiological signals without the need for acquiring extra specialized medical devices or attaching any sensor to the body. Through recording the reflected light intensities corresponding to the subtle blood flow changes with blood volume pulses, the proposed technique accurately extracts blood volume pulses from the facial videos recorded in real-world scenarios with the designed protocol. Experiments show that the proposed system achieved $$96 \, \% \,$$ accuracy on average (with the standard deviations of $$\pm 1.2$$ ) for the heart rate estimation and higher correlations between the pulse transit time and the reference systolic blood pressure $$(mean \, r = 0.89,\, SE= 0.05)$$ .

Optimal systolic blood pressure in noncritically ill patients with acute kidney injury: A retrospective cohort study

BackgroundFew data showed the optimal blood pressure (BP) in noncritically ill patients with acute kidney injury (AKI) relative to mortality or severe AKI. We therefore sought to analyze the data that exist for the ideal target range for BP in noncritically ill patients with AKI.MethodsWe performed a retrospective cohort study involving 1,612 hospitalized patients who were diagnosed with AKI using the Kidney Disease: Improving Global Outcomes definition based on serum creatinine measurements for a period of 1 year. The average systolic BP (SBP) was categorized into 10-mmHg increments (within 48 hours after the development of AKI). The primary outcome was a composite of severe AKI or 90-day mortality.ResultsThe composite outcome rate in patients was 18.7% (302/1,612). The relationship between BP and the composite outcome followed a U-shaped curve, with an increased event rate observed at both low and high BP values. The average SBP after AKI predicted the composite outcome after adjusting for baseline variables (reference SBP: 120–129 mmHg; < 100 mmHg: hazard ratio [HR] 1.84, P = 0.015; 100–109 mmHg: HR 1.56, P = 0.038; 110–119 mmHg: HR 1.15, P = 0.483; 130–139 mmHg: HR 1.51, P = 0.045; ≥ 140 mmHg: HR 1.73, P = 0.005).ConclusionAmong noncritically ill patients with AKI, a U-shaped curve association was observed between the average SBP within 48 hours after AKI and the composite primary outcome of this study, with the lowest event rate for SBP ranging from approximately 110 to 129 mmHg.

Blood pressure characteristics in patients with acute basilar artery occlusion undergoing endovascular thrombectomy

Acute basilar artery occlusion (BAO) is a rare but potentially life-threatening neurological condition. While endovascular therapy (EVT) has been shown to improve outcome, there is limited knowledge about prognostic factors beyond early recanalization. We studied whether blood pressure (BP) exceeds or falls below suggested thresholds during intervention and whether these changes are associated with complications and outcome. BP measurements mostly with one-minute intervals were available in 39 patients. An individual systolic blood pressure (SBP) reference value was defined as the median of the first five intra-procedural measurements. Half of the patients (51.3%) received drugs for BP augmentation and two a BP lowering drug (5.1%). Thrombolysis in cerebral infarction grade 2b and 3 (TICI) was achieved in 29 (74.4%) and 23 patients (58.9%) had good outcome at three months. We observed a continuous intra-procedural increase of median SBP (+11%) and mean arterial pressure (MAP, +10%, both p < 0.001), and a unique temporal pattern of intermittent peaks and troughs. Successful recanalization was more common in patients whose intra-procedural duration with SBP under 140 mmHg was shorter (p = 0.009). Patients with isolated tip of basilar artery (TBA) occlusion had significantly more BP excursion of 20% below the reference SBP and required more frequent use of sympathomimetic drugs compared to vertebrobasilar occlusion (p = 0.008 and p = 0.041, respectively). Brain hemorrhage was more prevalent in patients who experienced SBP excursions at least 20% above the individual reference value (p = 0.038) and a longer duration of time spent with SBP above 180 mmHg (p = 0.029). Patients with higher pre-procedural mean SBP had a greater chance of a good outcome (p = 0.03). This study using high resolution BP monitoring suggests a relationship between intra-procedural BP characteristics and recanalization, hemorrhagic complications and outcome in patients receiving EVT for acute posterior circulation cerebrovascular syndromes. Differences with regard to BP regulation during recanalization therapy for vertebrobasilar and TBA occlusion deserves further attention.

Continuous non-invasive determination of nocturnal blood pressure variation using photoplethysmographic pulse wave signals: comparison of pulse propagation time, pulse transit time and RR-interval

Objective: Cardiovascular diseases are the leading cause of death, whereas nocturnal ambulatory blood pressure (BP) is the most potent predictor for cardiovascular risk. The volume clamp and pulse transit time (PTT) are common methods for continuous non-invasive BP measurement, but have drawbacks during unsupervised ambulatory use and undisturbed sleep. The pulse propagation time (PPT), defined as the time between pulse wave systolic peak and diastolic peak, provides valid information about the pressure pulse waveform. However, the use of PPT for nocturnal BP variation determination and whether such variation is affected by BP or heart rate (i.e. RR-interval or RRI) has not been investigated. Approach: To assess whether the PPT method is suitable for ubiquitous nocturnal BP monitoring, we compared systolic blood pressure (SBP) estimates derived from PPT, PTT, and RRI signals with parallel recorded BP measurements. The RRI-derived SBP signals were used as a baseline for testing a potential heart rate dependency. This work provides an overview of BP measurements, presents the developed real-time signal analysis, and describes the performance assessment. The signal analysis was validated with data records from 42 subjects acquired from an ergometry and sleep laboratory in equal parts. Main results: The algorithms applied to the ergometry laboratory database achieved a correlation coefficient between reference SBP and estimated SBPPPT of 0.89 (p < 0.001) with bias 0.1 mmHg and limits of agreement (LoA) −29.8 to 30.0 mmHg, SBPPTT of 0.97 (p < 0.001) with bias 0.0 mmHg and LoA −15.2 to 15.3 mmHg, and SBPRRI of 0.96 (p < 0.001) with bias 0.0 mmHg and LoA −19.5 to 19.5 mmHg. For the sleep laboratory database, the correlation coefficient was 0.95 (p < 0.001) with bias 0.2 mmHg and LoA −18.3 to 18.8 mmHg for SBPPPT, 0.88 (p < 0.001) with bias 0.0 mmHg and LoA −25.0 to 24.9 mmHg for SBPPTT, and 0.88 (p < 0.001) with bias of 0.1 mmHg and LoA −23.6 to 23.7 mmHg for SBPRRI. A heart rate dependency of PPT or PTT could not be found. The analysis of variance shows no significant differences between the reference SBP values and the estimated values for either the ergometry (F(3, 627) = 2.27, p = 0.08) or the sleep laboratory (F(3, 327) = 2.28, p = 0.08). Significance: In conclusion, the PPT method seems to be an interesting alternative for continuous determination of SBP during simplified cardiovascular monitoring and sleep screening compared to more expensive devices based on volume clamp or PTT methods.

IPhone App Compared with Standard RR Measurement - The iPARR Trial

The possibility to use built-in smartphone-cameras for photoplethysmographic (PPG) recording of pulse waves lead to the release of numerous BP health apps, that claim to measure BP based on PPG signals. Even though these apps are highly popular, there is still not a single clinically validated PPG based BP smartphone app so far. We tested a new algorithm designed to estimate systolic blood pressure (SBP) based on PPG signals recorded by a smartphone camera. The study was designed based on the European Society of Hypertension International Protocol revision 2010 (ESH-IP 2010. Each individual received seven sequential BP measurements, starting with the reference device - an automated oscillometric cuff device - followed by the PPG recording at the patients' index finger. Between September 2015 and April 2016 a total 1036 subjects were recruited of which 965 could be included for final analysis. Mean (±SD) error between test and reference device was -0.41 (±16.52) mm Hg. Only 38.1% of all 2895 BP comparisons reached a delta within ±5 mm Hg, while 29.3% reached a delta larger than 15 mm Hg. Bland-Altman plot showed an overestimation of smartphone SBP in comparison to reference SBP in low range and an underestimation in high SBP range. According to the ESH-IP 2010 the algorithm failed validation for SBP measurement and was not commercialized. These findings emphasize that all health apps should be validated according to common guidelines before market release as under- and/or overestimation of BP is potentially exposing persons at health risk in short and long term. Clinical Trial Number: ClinicalTrials.gov, number NCT02552030, (https://clinicaltrials.gov/ct2/show/NCT02552030) Funding Statement: This study was supported by the Department of Clinical Research of the University Hospital of Basel and supported with hardware, services and 0.5FTE salary for a study nurse by Preventicus®. Declaration of Interests: Jens Eckstein, Marcus Dorr, Ralf Birkemeyer and Stefan Weber hold 0.5% virtual shares of Preventicus®. None of the remaining authors has a conflict of interest to disclose regarding this work. Ethics Approval Statement: The study was approved by the local ethics committee (EKNZ 2015-287) and registered with ClinicalTrials.gov. All individuals gave written informed consent before study inclusion. The study was monitored by the Clinical Trial Unit in Basel.

Systolic blood pressure estimation using PPG and ECG during physical exercise

In this work, a model to estimate systolic blood pressure (SBP) using photoplethysmography (PPG) and electrocardiography (ECG) is proposed. Data from 19 subjects doing a 40 min exercise was analyzed. Reference SBP was measured at the finger based on the volume-clamp principle. PPG signals were measured at the finger and forehead. After an initialization process for each subject at rest, the model estimated SBP every 30 s for the whole period of exercise. In order to build this model, 18 features were extracted from PPG signals by means of its waveform, first derivative, second derivative, and frequency spectrum. In addition, pulse arrival time (PAT) was derived as a feature from the combination of PPG and ECG. After evaluating four regression models, we chose multiple linear regression (MLR) to combine all derived features to estimate SBP. The contribution of each feature was quantified using its normalized weight in the MLR. To evaluate the performance of the model, we used a leave-one-subject-out cross validation. With the aim of exploring the potential of the model, we investigated the influences of the inclusion of PAT, regression models, measurement sites (finger and forehead), and posture change (lying, sitting, and standing). The results show that the inclusion of PAT reduced the standard deviation (SD) of the difference from 14.07 to 13.52 mmHg. There was no significant difference in the estimation performance between the model using finger- and forehead-derived PPG signals. Separate models are necessary for different postures. The optimized model using finger-derived PPG signals during physical exercise had a performance with a mean difference of 0.43 mmHg, an SD of difference of 13.52 mmHg, and median correlation coefficients of 0.86. Furthermore, we identified two groups of features that contributed more to SBP estimation compared to other features. One group consists of our proposed features depicting beat morphology. The other comprises existing features depicting the dicrotic notch. The present work demonstrates promising results of the SBP estimation model during physical exercise.

YIA 01-05 OPTIMAL BLOOD PRESSURE FOR MORTALITY IN PATIENT WITH AKI; WHAT AND WHEN?

Objective: Blood pressure (BP) is an important target for kidney injury, but few data showed optimal BP in patients with acute kidney injury (AKI) relative to mortality. Design and Method: We performed a retrospective cohort study of 2304 patients who had their creatinine levels measured (≥ 1 measurement) during admission for a period of 1 year (January 1, 2013 through December 31, 2013) at tertiary hospital and were diagnosed with AKI by Kidney Disease Improving Global Outcomes (KDIGO) definition based on serum creatinine criteria. Average BP (systolic [SBP] and diastolic [DBP]) was categorized into 10-mmHg increments (at early period of admission within 48hr and at 48hr after development of AKI). Results: The overall 90-day and 1-year mortality for patients were 17.6 % (405/2304) and 29.0% (669/2304). The relationship between BP (SBP and DBP) followed a J-shaped curve association with increased 90-day and 1-year mortality at low BP value in univariable analysis (SBP <120 mmHg and DBP <60 mmHg at admission and after AKI) (Figure1). However, SBP at 48hr after AKI was only a predictor for 90-day mortality after adjustment for baseline variables (reference systolic BP ≥ 140 mmHg, <100 mmHg, Hazard ratio [HR] 4.528, P <0.001; 100–110 mmHg, HR 2.177, P = 0.005; 110–120 mmHg, HR 1.764, P = 0.033; 120–130 mmHg, HR 1.415, P = 0.215; 130–140 mmHg, HR 1.656, P = 0.088). This trend also remained in the relationship between average SBP after AKI and 1-year mortality. Conclusions: After AKI, a J-shaped curve association existed between SBP at 48hr after AKI and 90-day/1-year mortality, which suggests that too low of a pressure (especially <120 mmHg) may be dangerous. SBP after AKI was only a predictor for mortality rather than SBP/DBP at admission or DBP after AKI.

Optimizing non-invasive blood pressure estimation using pulse transit time.

Continuous blood pressure (BP) monitoring during exercise is an important means to ensure exercise safety, particularly in seniors and individuals with various comorbidities. Use of automated BP monitors is limited during exercise. Pulse transit time (PTT) has been suggested for non-invasive BP monitoring however its implementation into clinical practice was hampered by lack of non-expensive practical solutions. The goal of this project was to introduce and to test a practical low-cost solution for using PTT to estimate BP during exercise. Our approach was based on obtaining 3 calibration points during different levels of exertion for each subject and utilizing the resulting individualized BP estimation equitation for patient-specific monitoring of BP during home-based exercise. Evaluation of the proposed approach showed that the mean difference between reference systolic BP (SBP) and estimated systolic BP was 0.0 mmHg. The optimal way to calculate PTT has been established by comparison of three main characteristic points used to derive PTT.

Relationship Between Blood Pressure Values, Depressive Symptoms, and Cardiovascular Outcomes in Patients With Cardiometabolic Disease.

The authors studied the joint effect of blood pressure (BP) and depression on the risk of major adverse cardiovascular outcome in patients with existing cardiometabolic disease. A cohort of 35,537 patients with coronary heart disease, diabetes, or stroke underwent depression screening and BP measurement recorded concurrently. The authors used Cox's proportional hazards to calculate risk of major adverse cardiovascular event (MACE; myocardial infarction/heart failure/stroke or cardiovascular death) over 4 years associated with baseline BP and depression. A total of 11% (3939) had experienced a MACE within 4 years. Patients with very high systolic BP (160–240 mm Hg; hazard ratio, 1.28) and depression (hazard ratio, 1.22) at baseline had significantly higher adjusted risk. Depression had a significant interaction with systolic BP in risk prediction (P=.03). Patients with a combination of high systolic BP and depression at baseline had 83% higher adjusted risk of MACE, as compared with patients with reference systolic BP without depression. Patients with cardiometabolic disease and comorbid depression may benefit from closer monitoring of systolic BP.

An armband wearable device for overnight and cuff-less blood pressure measurement.

24-h blood pressure (BP) has significant prognostic value for cardiovascular risk screening, but the present BP devices are mainly cuff-based, which are unsuitable for long-term BP measurement, especially during nighttime. In this paper, we developed an armband wearable pulse transit time (PTT) system for 24-h cuff-less BP measurement and evaluated it in an unattended out-of-laboratory setting. Ten healthy young subjects participated in this ambulatory study, where PTT was measured at 30-min interval by this wearable system and the reference BP was measured by a standard oscillometric ambulatory BP monitor. Due to the misalignment of BP and PTT on their recording time caused by the different measurement principles of the two BP devices, a new estimation method has been proposed: transients in PTT were removed from the raw data by defined criteria, and then evenly interpolated, low-pass filtered, and resampled to synchronize at the time when BP was recorded. The results show that with the proposed method, the correlation between PTT and systolic BP (SBP) during nighttime with dynamic range of 21.8 ± 14.2mmHg has improved from -0.50 ± 0.24 to -0.62 ± 0.20 , and the difference between the estimated and reference SBP has improved from 0.7 ± 10.7 to 2.8 ± 8.2mmHg with root mean square error reduced from 10.7 to 8.7mmHg. In addition, the correlation between a very low frequency component of SBP and PTT obtained from the proposed method during nighttime is -0.80 ± 0.10 and the difference is 2.4 ± 5.7mmHg for a dynamic BP range of 13.5 ± 8.0mmHg. It is therefore concluded from this study that the proposed wearable system has great potential to be used for overnight SBP monitoring, especially to measure the averaged SBP over a long period.

The association between systolic blood pressure on arrival at hospital and outcome in adults surviving from out-of-hospital cardiac arrests of presumed cardiac aetiology

BackgroundThe optimal blood pressure target following successful resuscitation from out-of-hospital cardiac arrest (OHCA) is uncertain. This study aimed to explore the association between level of systolic blood pressure (SBP) on arrival at hospital and survival to hospital discharge. MethodsWe analysed eligible OHCAs occurring between January 2003 and December 2011 from the Victorian Ambulance Cardiac Arrest Register (VACAR). Inclusion criteria were: adults (≥18 years), presumed cardiac aetiology, not paramedic witnessed, and ROSC at hospital arrival. Multivariate logistic regression models were performed by initial rhythm (shockable/non-shockable) to examine the relationship between SBP at hospital arrival in 10mmHg increments and survival to hospital discharge. Models were adjusted for known predictors of survival, including duration of arrest. ResultsOf 3620 eligible cases, 14% were hypotensive (SBP<90mmHg) on hospital arrival (10% shockable and 19% non-shockable). For patients in shockable rhythms, discharge survival was maximal at 120–129mmHg (54%), and in the adjusted model (≥120mmHg as reference) SBP decrements below 90mmHg were associated with lower survival: 80–89mmHg AOR=0.49 (95% CI: 0.24–0.95); <80mmHg AOR=0.24 (95% CI: 0.10–0.61); unrecordable AOR=0.10 (95% CI: 0.04–0.30). In patients found in non-shockable rhythms, SBP was not significant associated with discharge survival (AOR=1.01, 95% CI: 0.89–1.15). ConclusionsIn an EMS system using intravenous adrenaline and fluids to maintain post-resuscitation SBP at 120mmHg, hypotension on hospital arrival was relatively uncommon. However, in presumed cardiac OHCA patients with an initial shockable rhythm, SBPs below 90mmHg was associated with significant lower odds of survival to hospital discharge. This level of hypotension may indicate patients who require more aggressive post-resuscitation blood pressure management.

Prognostic Role of Ambulatory Blood Pressure Measurement in Patients With Nondialysis Chronic Kidney Disease

Ambulatory blood pressure (BP) measurement allows a better risk stratification in essential hypertension compared with office blood pressure measurement, but its prognostic role in nondialysis chronic kidney disease has been poorly investigated. The prognostic role of daytime and nighttime systolic BP (SBP) and diastolic BP (DBP) in comparison with office measurements was evaluated in 436 consecutive patients with chronic kidney disease. Primary end points were time to renal death (end-stage renal disease or death) and time to fatal and nonfatal cardiovascular events. Quintiles of BP were used to classify patients. The mean (SD) age of the patients was 65.1(13.6) years, and the glomerular filtration rate was 42.9(19.7) mL/min/1.73 m(2); 41.7% of the participants were women, 36.5% had diabetes, and 30.5% had cardiovascular disease. Office-measured SBP/DBP values were 146(19)/82(12) mm Hg; daytime SBP/DBP was 131 (17)/75 (11) mm Hg, and nighttime SBP/DBP was 122(20)/66(10) mm Hg. During follow-up (median, 4.2 years), 155 and 103 patients reached the renal and cardiovascular end points, respectively. Compared with a daytime SBP of 126 to 135 mm Hg, patients with an SBP of 136 to 146 mm Hg and those with an SBP higher than 146 mm Hg had an increased adjusted risk of the cardiovascular end point (hazard ratio [HR], 2.23; 95% confidence interval [CI], 1.13-4.41 and 3.07; 1.54-6.09) and renal death (1.72; 1.02-2.89 and 1.85; 1.11-3.08). Nighttime SBPs of 125 to 137 mm Hg and higher than 137 mm Hg also increased the risk of the cardiovascular end point (HR, 2.52; 95% CI, 1.11-5.71 and 4.00; 1.77-9.02) and renal end point (1.87; 1.03-3.43 and 2.54; 1.41-4.57) with respect to the reference SBP value of 106-114 mm Hg. Office measurement of BP did not predict the risk of the renal or cardiovascular end point. Patients who were nondippers and those who were reverse dippers had a greater risk of both end points. In chronic kidney disease, ambulatory BP measurement and, in particular, nighttime BP measurement, allows more accurate prediction of renal and cardiovascular risk; office measurement of BP does not predict any outcome.

Systolic blood pressure at end-expiration measured by the automated systolic pressure variation monitor is equivalent to systolic blood pressure during apnea.

It is necessary to define a reference systolic arterial blood pressure (RP) to calculate delta-Up (dUp) and delta-Down (dDown) for systolic pressure variation. Most studies define the reference pressure as the average systolic blood pressure during a short period of apnea. We describe an automated systolic pressure variation monitor that measures airway pressure and defines the reference pressure as the systolic blood pressure at end-expiration. The present study compares the reference systolic blood pressure measured at end-expiration by the automated systolic pressure variation monitor and the reference systolic blood pressure measured during apnea to test whether the end-expiration value is an adequate substitute for the value during apnea. After obtaining informed consent, 108 sets of measurements of systolic pressure variation (SPV) were made in 20 intubated, mechanically-ventilated, anesthetized patients by the automated SPV monitor and during apnea. Measurements were taken during periods of hemodynamic stability defined as three consecutive end-expiratory systolic blood pressures within four mmHg of each other. The three systolic pressures at end-expiration were averaged (RPmonitor). Immediately following these measurements, the ventilator was turned off and the systolic blood pressure was measured at 6, 8, 10 and 12 seconds of apnea. The reference pressure during apnea (RPapnea) was defined as the average of the systolic blood pressure at 8, 10 and 12 seconds of apnea. For each measurement set, RPmonitor and the systolic blood pressure at 6 seconds of apnea (SBP6) were compared to RPapnea using Bland-Altman analysis. Bland-Altman analysis for the difference between SBP6 and RPapnea yielded a small bias of -0.3 mmHg with standard deviation of 1.3, indicating that the systolic pressure tends to continue to increase slightly after 6 seconds of apnea. Results were similar for the difference between RPmonitor and RPapnea (-0.2 +/- 3.1 mmHg). dUp and dDown are calculated using the reference pressure. RPmonitor is an average of 0.2 mm Hg less than RPapnea, thus dUp calculated by the automated SPV monitor is an avenge of 0.2 mm Hg greater than dUp measured by the reference pressure during apnea and dDown is 0.2 mm Hg less. Since the bias of -0.2 mmHg is clinically insignificant, there is acceptable agreement between the reference pressure obtained during apnea and that obtained by the automated SPV monitor at end-expiration. The mean difference between RPmonitor and RPapnea is explained by the continued rise in systolic pressure during the period of apnea as demonstrated by the difference between SBP6 and RPapnea.