Continuous Blood Pressure Monitoring Research Articles

#2812 Continuous blood pressure monitoring with a finger cuff is unreliable in chronic hemodialysis patients

Abstract Background and Aims Intradialytic hypotension (IDH) is the most common complication of hemodialysis (HD), which is often related to ultrafiltration. Due to the high prevalence of cardiovascular disease (CVD), compensatory mechanisms often fail. In clinical practice, BP is measured 2x/hour, while additional readings are only performed when symptoms arise. However, since IDH defined by a nadir systolic BP (SBP)<90 mmHg or <100 mmHg (depending on pre-dialysis SBP), regardless of symptoms, is most strongly associated with mortality, current BP measurement frequency may severely underestimate the true incidence of IDH. Continuous BP-monitoring may offer a solution to this issue. The Clearsight device (CSD) is a non-invasive continuous BP-monitoring system that measures arterial pressure and waveforms through a finger cuff by photoplethysmography. Yet, a compromised peripheral circulation may hamper its reliability in HD patients. This study aims to assess the agreement between intradialytic CSD-monitoring and standard oscillometric brachial arterial pressure (oBAP) assessment. Methods 40 Chronic HD patients were cross-over randomized to 4 modalities, each for 2 weeks: [standard HD (S-HD), cool HD (C-HD), low volume hemodiafiltration (LV-HDF) and high-volume HDF (HV-HDF)]. During one session of each second week, BP and heart rate (HR) were continuously recorded with the CSD (BMEYE/Edwards Lifesciences) and every 15 minutes with a brachial arterial cuff (contralateral of the fistula or graft, if applicable). Simultaneous measurements of SBP, diastolic BP (DBP) and HR were compared with descriptive statistics (mean difference [bias, BAP minus CSD], standard deviation (SD) and range) and Bland-Altman analysis. Bias was defined as the mean difference between oBAP and CSD, and 95% limits of agreement (LA) as the mean difference ±1.96 SD. Post-hoc, patients were stratified into tertiles of unexplained missing CSD-readings, to explore whether specific patient characteristics explain failed readings. Results 75% of patients was male, with a mean age 69.7 (±13.5 years) and median dialysis vintage 3.0 years (IQR 1.0-5.8). Diabetes mellitus and CVD were present in 48% and 73%, resp. Of the 2720 paired BP-measurements, 42% CSD and 6% of oBAP-readings were missing, leaving 36% of absent CSD-readings unexplained. Bland-Altman analysis, comparing oBAP and CSD-measurements, revealed a mean bias ± LA of 13.3 ± 44.5 mmHg for SBP, a mean bias ± LA of 13.3 ± 25.5 for DBP, and a mean bias ± LA of −0.03 ± 22.9 for HR. Surprisingly, the group with a high (>38%) proportion of unexplained missing CSD-values was significantly younger compared to the low (<21%) and intermediate group (21-38%) (p = 0.015), whereas no significant differences were observed with respect to dialysis vintage, diabetes mellitus or CVD. Conclusions 1) Compared to the oBAP method, finger cuff-monitoring shows poor precision and accuracy in BP-measurements, but good accuracy and poor precision in HR-readings; 2) 1/3 of readings failed for unknown reasons. Thus, CSD-monitoring is unsuitable for intradialytic hemodynamic monitoring in chronic HD patients.

Speckle Plethysmograph-Based Blood Pressure Assessment

Continuous non-invasive blood pressure (CNBP) monitoring is of the utmost importance in detecting and managing hypertension, a leading cause of death in the United States. Extensive research has delved into pioneering methods for predicting systolic and diastolic blood pressure values by leveraging pulse arrival time (PAT), the time difference between the proximal and distal signal peaks. The most widely employed pairing involves electrocardiography (ECG) and photoplethysmography (PPG). Possessing similar characteristics in terms of measuring blood flow changes, a recently investigated optical signal known as speckleplethysmography (SPG) showed its stability and high signal-to-noise ratio compared with PPG. Thus, SPG is a potential surrogate to pair with ECG for CNBP estimation. The present study aims to unlock the untapped potential of SPG as a signal for non-invasive blood pressure monitoring based on PAT. To ascertain SPG’s capabilities, eight subjects were enrolled in multiple recording sessions. A third-party device was employed for ECG and PPG measurements, while a commercial device served as the reference for arterial blood pressure (ABP). SPG measurements were obtained using a prototype smartphone-based system. Following the completion of three scenarios—sitting, walking, and running—the subjects’ signals and ABP were recorded to investigate the predictive capacity of systolic blood pressure. The collected data were processed and prepared for machine learning models, including support vector regression and decision tree regression. The models’ effectiveness was evaluated using root-mean-square error and mean absolute percentage error. In most instances, predictions utilizing PATSPG exhibited comparable or superior performance to PATPPG (i.e., SPG Rest ± 12.4 mmHg vs. PPG Rest ± 13.7 mmHg for RSME, and SPG 8% vs. PPG 9% for MAPE). Furthermore, incorporating an additional feature, namely the previous SBP value, resulted in reduced prediction errors for both signals in multiple model configurations (i.e., SPG Rest ± 12.4 mmHg to ±3.7 mmHg for RSME, and SPG Rest 8% to 3% for MAPE). These preliminary tests of SPG underscore the remarkable potential of this novel signal in PAT-based blood pressure predictions. Subsequent studies involving a larger cohort of test subjects and advancements in the SPG acquisition system hold promise for further improving the effectiveness of this newly explored signal in blood pressure monitoring.

Machine learning models reveal the critical role of nighttime systolic blood pressure in predicting functional outcome for acute ischemic stroke after endovascular thrombectomy.

Blood pressure (BP) is a key factor for the clinical outcomes of acute ischemic stroke (AIS) receiving endovascular thrombectomy (EVT). However, the effect of the circadian pattern of BP on functional outcome is unclear. This multicenter, retrospective, observational study was conducted from 2016 to 2023 at three hospitals in China (ChiCTR2300077202). A total of 407 patients who underwent endovascular thrombectomy (EVT) and continuous 24-h BP monitoring were included. Two hundred forty-one cases from Beijing Hospital were allocated to the development group, while 166 cases from Peking University Shenzhen Hospital and Hainan General Hospital were used for external validation. Postoperative systolic BP (SBP) included daytime SBP, nighttime SBP, and 24-h average SBP. Least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), Boruta were used to screen for potential features associated with functional dependence defined as 3-month modified Rankin scale (mRS) score ≥ 3. Nine algorithms were applied for model construction and evaluated using area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy. Three hundred twenty-eight of 407 (80.6%) patients achieved successful recanalization and 182 patients (44.7%) were functional independent. NIHSS at onset, modified cerebral infarction thrombolysis grade, atrial fibrillation, coronary atherosclerotic heart disease, hypertension were identified as prognostic factors by the intersection of three algorithms to construct the baseline model. Compared to daytime SBP and 24-h SBP models, the AUC of baseline + nighttime SBP showed the highest AUC in all algorithms. The XGboost model performed the best among all the algorithms. ROC results showed an AUC of 0.841 in the development set and an AUC of 0.752 in the validation set for the baseline plus nighttime SBP model, with a brier score of 0.198. This study firstly explored the association between circadian BP patterns with functional outcome for AIS. Nighttime SBP may provide more clinical information regarding the prognosis of patients with AIS after EVT.

Flexible Strain Sensors Based on an Interlayer Synergistic Effect of Nanomaterials for Continuous and Noninvasive Blood Pressure Monitoring.

The continuous, noninvasive monitoring of human blood pressure (BP) through the accurate detection of pulse waves has extremely stringent requirements on the sensitivity and stability of flexible strain sensors. In this study, a new ultrasensitive flexible strain sensor based on the interlayer synergistic effect was fabricated through drop-casting and drying silver nanowires and graphene films on polydimethylsiloxane substrates and was further successfully applied for continuous monitoring of BP. This strain sensor exhibited ultrahigh sensitivity with a maximum gauge factor of 34357.2 (∼700% sensitivity enhancement over other major sensors), satisfactory response time (∼85 ms), wide strange range (12%), and excellent stability. An interlayer fracture mechanism was proposed to elucidate the working principle of the strain sensor. The real-time BP values can be obtained by analyzing the relationship between the BP and the pulse transit time. To verify our strain sensor for real-time BP monitoring, our strain sensor was compared with a conventional electrocardiogram-photoplethysmograph method and a commercial cuff-based device and showed similar measurement results to BP values from both methods, with only minor differences of 0.693, 0.073, and 0.566 mmHg in the systolic BP, diastolic BP, and mean arterial pressure, respectively. Furthermore, the reliability of the strain sensors was validated by testing 20 human subjects for more than 50 min. This ultrasensitive strain sensor provides a new pathway for continuous and noninvasive BP monitoring.

Advancing cuffless blood pressure estimation: A PPG-based multi-task learning model for enhanced feature extraction and fusion

Cuffless continuous blood pressure (BP) monitoring is essential for personalized health management. Although existing cuffless BP estimation applies advanced machine learning techniques and integrates PPG signals, it is deficient in feature extraction and fusion. In addition, it is inefficient to train the model separately for different tasks. In this study, an advanced multi-domain and local–global feature parallel multi-task learning network (MDLG-MTLNet) is introduced. The MDLG-MTLNet was designed with three key aspects: first, temporal and multi-scale spatial features were extracted from PPG signals and their derivatives via a multi-scale spatial and temporal feature block; interaction of features from different domains was facilitated by the introduction of a local–global attention module that captured and efficiently fused local–global information; and lastly, intrinsic correlation between systolic (SBP) and diastolic blood pressure (DBP) was taken into account via a multi-task learning network to improve the overall performance of the model. On the MIMIC-II dataset, the MAEs of MDLG-MTLNet for DBP, SBP, and MBP were 2.64 mmHg, 1.57 mmHg, and 2.02 mmHg, respectively. These errors were superior to those of the existing methods, meeting the AAMI criteria, and earning an A grade according to the BHS protocol. The experimental results confirm the effectiveness of our proposed model in feature extraction and fusion.

Toll-like Receptor 4 Promotes Salt-Sensitivity in Dahl SS Rats: An Investigation into the Mechanism

Renal inflammation accompanies hypertension and renal damage in Dahl Salt-Sensitive (SS) rats fed a high salt diet (HS, Dyets AIN-76A 4.0% NaCl). Previous studies demonstrated that toll-like receptor 4 (TLR4), a component of innate immune activation, is upregulated in macrophages infiltrating the kidneys of Dahl SS rats fed high salt. Preliminary studies in our laboratory indicated that mean arterial pressure (MAP) (SS: 162.5 ± 4.9 vs. SSTLR4−/−: 147.1 ± 3.5 mmHg, p<0.0001, n=10/group) and albuminuria (321.3 ± 62.7 vs. 170.6 ± 27.1 mg/day, p<0.05, n=10/group) were significantly reduced in male Dahl SS TLR4 knockout rats (SSTLR4−/−) compared to male SS after three weeks of HS. Furthermore, peritoneal macrophages isolated from SSTLR4−/− produce significantly less IL-1β compared to SS macrophages upon stimulation with lipopolysaccharide (LPS) . Since TLR4 is widely expressed in many tissues, we examined the specific effects of TLR4 deletion in immune cells via a total body irradiation/bone marrow transfer approach. The present study tested the hypothesis that TLR4 deletion specifically in hematopoietic cells would attenuate male Dahl SS hypertension and renal damage. At 6 weeks of age, Dahl SS male recipients were irradiated (11Gy) then received either SS or SSTLR4−/− bone marrow transplantation via tail vein injection (~15-20 million cells). Following recovery, rats (maintained on a low salt chow (LS, Dyets AIN-76A 0.4% NaCl)) underwent telemeter implantation at approximately 8 weeks of age for continuous monitoring of blood pressure. Animals were switched to HS following recovery and baseline blood pressure recordings. Urine samples were collected once during the LS period and weekly throughout a 3-week HS challenge. Upon euthanasia, kidneys were flushed and harvested for analysis. MAP was not found to be different between groups during the LS baseline period (SS: 113.4 ± 1.6 vs. SSTLR4−/−: 116.5 ± 2.3 mmHg, n=5-6/group), and our preliminary data also revealed that MAP was not different between groups throughout the high salt challenge (HS day 20: 136.4 ± 10.5 vs 144.8 ± 9.2). Urinary albumin excretion was also not found to be different between rats receiving either SS or TLR4−/− bone marrow transfer (165.2 ± 38.5 vs. 247.9 ± 58.7 mg/day, n=7/group). Furthermore, assessment of BUN at the conclusion of the experiment revealed no differences (33.0 ± 6.1 vs. 29.3 ± 3.2 mg/dL, n=7/group). Immune cells were isolated from the blood and kidneys of these animals and characterized by flow cytometric analysis. There was no difference in the number of circulating leukocytes or lymphocytes (2.1x106 vs. 2.3x106 CD45+ cells per mL blood, n=6-7/group) indicating comparable reconstitution of immune cells in both groups. We also found no difference in renal infiltrating leukocytes or lymphocytes (3.1 x106 vs. 3.2x106 CD45+ cells per kidney, n=7/group). Together, these data contrast the effects of whole-body TLR4 knockout and suggest that TLR4 in hematopoietic cells may not be responsible for promoting Dahl SS hypertension and renal damage in males. Further studies are needed to assess the inflammatory status of immune cells from these animals as well as alternative TLR4-expressing cell types responsible for promoting disease. 23PRE1020121, HL161231, HL166458. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Non-invasive pulse arrival time as a surrogate for oscillometric systolic blood pressure changes during non-pharmacological intervention

Background. Non-invasive continuous blood pressure (BP) monitoring is of longstanding interest in various cardiovascular scenarios. In this context, pulse arrival time (PAT), i.e., a surrogate parameter for systolic BP (change), became very popular recently, especially in the context of cuffless BP measurement and dedicated lifestyle interventions. Nevertheless, there is also understandable doubt on its reliability in uncontrolled and mobile settings. Objective. The aim of this work is therefore the investigation whether PAT follows oscillometric systolic BP readings during moderate interventions by physical or mental activity using a medical grade handheld device for non-invasive PAT assessment. Approach. A study was conducted featuring an experimental group performing a physical and a mental task, and a control group. Oscillometric BP and PAT were assessed at baseline and after each intervention. Interventions were selected randomly but then performed sequentially in a counterbalanced order. Multivariate analyses of variance were used to test within-subject and between-subject effects for the dependent variables, followed by univariate analyses for post-hoc testing. Furthermore, correlation analysis was performed to assess the association of intervention effects between BP and PAT. Main results. The study included 51 subjects (31 females). Multivariate analysis of variances showed that effects in BP, heart rate, PAT and pulse wave parameters were consistent and significantly different between experimental and control groups. After physical activity, heart rate and systolic BP increased significantly whereas PAT decreased significantly. Mental activity leads to a decrease in systolic BP at stable heart rate. Pulse wave parameters follow accordingly by an increase of PAT and mainly unchanged pulse wave analysis features due to constant heart rate. Finally, also the control group behaviour was accurately registered by the PAT method compared to oscillometric cuff. Correlation analyses revealed significant negative associations between changes of systolic BP and changes of PAT from baseline to the physical task (−0.33 [−0.63, 0.01], p < 0.048), and from physical to mental task (−0.51 [−0.77, −0.14], p = 0.001), but not for baseline to mental task (−0.12 [−0,43,0,20], p = 0.50) in the experimental group. Significance. PAT and the used digital, handheld device proved to register changes in BP and heart rate reliably compared to oscillometric measurements during intervention. Therefore, it might add benefit to future mobile health solutions to support BP management by tracking relative, not absolute, BP changes during non-pharmacological interventions.

Orthostatic hypotension in Parkinson's disease: Sit-to-stand vs. supine-to-stand protocol and clinical correlates

BackgroundScreening for orthostatic hypotension (OH) is integral in Parkinson's disease (PD) management, yet evidence-based guidelines on best practice methods for diagnosing OH in PD are lacking. MethodsWe investigated the frequency and correlates of OH, symptomatic OH, and neurogenic OH, in a large consecutively recruited PD cohort (n = 318), and compared the diagnostic performance of the sit-to-stand vs. the supine-to-stand blood pressure (BP) test. We evaluated the utility of continuous BP monitoring and tilt table testing in patients with postural symptoms or falls who were undetected to have OH with clinic-based BP measurements. Disease severity, fluid intake, orthostatic and overactive bladder symptoms, falls, comorbidities and medication history were evaluated. ResultsPatients’ mean age was 66.1 ± 9.5years, with mean disease duration 7.8 ± 5.5years. OH frequency was 35.8 % based on the supine-to-stand test. OH in PD was significantly associated with older age, lower body mass index, longer disease duration, worse motor, cognitive and overactive bladder symptoms and functional disabilities, falls, and lower fluid intake. A similar profile was seen with asymptomatic OH. Three quarters of OH were neurogenic, with the majority also having supine hypertension. The sit-to-stand test had a sensitivity of only 0.39. One quarter of patients were additionally diagnosed with OH during continuous BP monitoring. ConclusionsThe sit-to-stand test substantially underdiagnoses OH in PD, with the important practice implication that supine-to-stand measurements may be preferred. Screening for OH is warranted even in asymptomatic patients. Adequate fluid intake, treatment of urinary dysfunction and falls prevention are important strategies in managing PD patients with OH.

Hierarchical Piezoelectric Composites for Noninvasive Continuous Cardiovascular Monitoring.

Continuous monitoring of blood pressure (BP) and multiparametric analysis of cardiac functions are crucial for the early diagnosis and therapy of cardiovascular diseases. However, existing monitoring approaches often suffer from bulky and intrusive apparatus, cumbersome testing procedures, and challenging data processing, hampering their applications in continuous monitoring. Here, a heterogeneously hierarchical piezoelectric composite is introduced for wearable continuous BP and cardiac function monitoring, overcoming the rigidity of ceramic and the insensitivity of polymer. By optimizing the hierarchical structure and components of the composite, the developed piezoelectric sensor delivers impressive performances, ensuring continuous and accurate monitoring of BP at Grade A level. Furthermore, the hemodynamic parameters are extracted from the detected signals, such as local pulse wave velocity, cardiac output, and stroke volume, all of which are in alignment with clinical results. Finally, the all-day tracking of cardiac function parameters validates the reliability and stability of the developed sensor, highlighting its potential for personalized healthcare systems, particularly in early diagnosis and timely intervention of cardiovascular disease.

A Direct Assessment of Noninvasive Continuous Blood Pressure Monitoring in the Emergency Department and Intensive Care Unit

IntroductionNoninvasive continuous blood pressure monitoring has the potential to improve patient treatment in the hospital setting. Such noninvasive devices can be applied earlier in the treatment process to empower nurses and clinicians to react more quickly to patient deterioration with the added benefit of eliminating the risks associated with invasive monitoring. However, emerging technologies must be capable of reproducing current clinical measures for medical decision making. MethodsThis study aimed to determine the usability and willingness of nurses to implement a noninvasive continuous blood pressure monitoring device. The secondary aim directly compared the systolic blood pressure, diastolic blood pressure, and mean arterial pressure values recorded by the device (VitalStream; CareTaker Medical LLC, Charlottesville, VA) with the “gold standard” brachial cuff and arterial line measures recorded in the emergency department and intensive care unit settings. ResultsVitalStream was similarly received by nurses in the emergency department and intensive care setting, but ultimately had greater promotion from emergency nurses. Despite some statistical similarity between measurement methodologies, all direct comparisons were found to not meet the Association for the Advancement of Medical Instrumentation 2008 and Association for the Advancement of Medical Instrumentation / European Society of Hypertension / International Organization for Standardization 2019 consensus statement criteria for acceptable blood pressure measure differences between the VitalStream and “gold standard” clinical measures. In all instances, the standard deviation of the Bland-Altman bias exceeded 8 mm Hg with less than 85% of paired differences falling within 10 mm Hg of the “gold standard.” DiscussionTaken together, the tested device requires additional postprocessing for medical decision making in trauma or emergent care.

STP: Self-supervised transfer learning based on transformer for noninvasive blood pressure estimation using photoplethysmography

Non-invasive blood pressure (BP) monitoring plays a crucial role in cardiovascular disease prevention, but traditional cuff-based methods lack continuous monitoring capability. Photoplethysmography (PPG) offers a promising alternative by capturing blood volume changes optically. The challenge of effectively capturing fine-grained discriminative features of BP using limited paired signals persists, despite the benefits offered by deep models trained on extensive data. The objective of this study is to create a Transformer framework for continuous monitoring of noninvasive BP through self-supervised transfer learning and BP pattern adaptation. We developed a data preprocessing strategy that integrates eleven physiological signal transformations to perform unsupervised pseudo-labels for PPG signals. Then, we developed a self-supervised learning network based on the Transformer architecture to extract robust signal representations from transformed PPGs during the pretraining phase. Furthermore, we designed a transfer learning approach that incorporates BP pattern adaptation to derive discriminative features for accurate estimation of BP values. The proposed STP model was evaluated on multi-source datasets containing 1,213 subjects based on a subject-wise paradigm. The clinical standard was met with estimation errors of 0.85 ± 4.21 mmHg and 0.49 ± 2.76 mmHg for systolic BP and diastolic BP, respectively. These results indicate that the STP model performs competitively in terms of BP estimation when compared to current state-of-the-art approaches. Our study presents a novel STP approach for continuous monitoring of noninvasive BP using PPG signals. By integrating BP pattern adaptation, our approach achieves a competitive performance in estimating BP values, demonstrating its potential for clinical applications.

Blood pressure trends following birth in infants born under 25 weeks’ gestational age: a retrospective cohort study

ObjectiveThe aim of our study was to describe postnatal blood pressure (BP) trends and evaluate relevant dynamics and outcomes for a subgroup of extremely preterm (EPT) infants.DesignRetrospective observational cohort study.SettingPatients...

Evaluation of a novel cuffless photoplethysmography-based wristband for measuring blood pressure according to the regulatory standards.

Elevated blood pressure (BP) is a key risk factor in cardiovascular diseases. However, obtaining reliable and reproducible BP remains a challenge. This study, therefore, aimed to evaluate a novel cuffless wristband, based on photoplethysmography (PPG), for continuous BP monitoring. Predictions by a PPG-guided algorithm were compared to arterial BP measurements (in the sub-clavian artery), obtained during cardiac catheterization. Eligible patients were included and screened based on AAMI/European Society of Hypertension (ESH)/ISO Universal Standard requirements. The machine learning-based BP algorithm required three cuff-based initialization measurements in combination with ∼100 features (signal-derived and patient demographic-based). Ninety-seven patients and 420 samples were included. Mean age, weight, and height were 67.1 years (SD 11.1), 83.4 kg (SD 16.1), and 174 cm (SD 10), respectively. Systolic BP was ≤100 mmHg in 48 samples (11%) and ≥160 mmHg in 106 samples (25%). Diastolic BP was ≤70 mmHg in 222 samples (53%) and ≥85 mmHg in 99 samples (24%). The algorithm showed mean errors of ±3.7 mmHg (SD 4.4 mmHg) and ±2.5 mmHg (SD 3.7 mmHg) for systolic and diastolic BP, respectively. Similar results were observed across all genders and skin colours (Fitzpatrick I-VI). This study provides initial evidence for the accuracy of a PPG-based BP algorithm in combination with a cuffless wristband across a range of BP distributions. This research complies with the AAMI/ESH/ISO Universal Standard, however, further research is required to evaluate the algorithms performance in light of the remaining European Society of Hypertension recommendations. www.clinicaltrials.gov, NCT05566886.

Continuous vs intermittent Non-Invasive blood pressure MONitoring in preventing postoperative organ failure (niMON): study protocol for an open-label, multicenter randomized trial

BackgroundBlood pressure has become one of the most important vital signs to monitor in the perioperative setting. Recently, the Italian Society of Anesthesia Analgesia Resuscitation and Intensive Care (SIAARTI) recommended, with low level of evidence, continuous monitoring of blood pressure during the intraoperative period. Continuous monitoring allows for early detection of hypotension, which may potentially lead to a timely treatment. Whether the ability to detect more hypotension events by continuous noninvasive blood pressure (C-NiBP) monitoring can improve patient outcomes is still unclear. Here, we report the rationale, study design, and statistical analysis plan of the niMON trial, which aims to evaluate the effect of intraoperative C-NiBP compared with intermittent (I-NiBP) monitoring on postoperative myocardial and renal injury.MethodsThe niMon trial is an investigator-initiated, multicenter, international, open-label, parallel-group, randomized clinical trial. Eligible patients will be randomized in a 1:1 ratio to receive C-NiBP or I-NiBP as an intraoperative monitoring strategy. The proportion of patients who develop myocardial injury in the first postoperative week is the primary outcome; the secondary outcomes are the proportions of patients who develop postoperative AKI, in-hospital mortality rate, and 30 and 90 postoperative days events. A sample size of 1265 patients will provide a power of 80% to detect a 4% absolute reduction in the rate of the primary outcome.ConclusionsThe niMON data will provide evidence to guide the choice of the most appropriate intraoperative blood pressure monitoring strategy.Clinical trial registrationClinical Trial Registration: NCT05496322, registered on the 5th of August 2023.

Noninvasive Blood Pressure Monitoring via a Flexible and Wearable Piezoresistive Sensor.

In the present global context, continuous blood pressure (BP) monitoring is paramount in addressing the global mortality rates attributed to hypertension. Achieving precise insights into the human cardiovascular system necessitates accurate measurement of BP, and the accuracy depends on the faithful recording of oscillations or pulsations. This task ultimately depends on the caliber of the pressure sensor embedded in the BP device. In this context, we have fabricated a flexible resistive pressure sensor based on reduced graphene oxide (rGO) and a polydimethylsiloxane (PDMS) sponge that is highly flexible and sensitive. The designed device operates effectively with a minimal bias voltage of 500 mV, at which point it showed its maximum relative change in current, reaching approximately 25%. Additionally, the sensing device showed a notable change in resistance values, exhibiting almost 100% change in resistance when subjected to a pressure of 400 mmHg and high sensitivity of 0.27 mmHg-1. After promising outcomes were obtained during static pressure measurement, the sensor was used for BP monitoring in humans. The sensor accurately traced the oscillometric waveform (OMW) for distinct systolic blood pressure (SBP) and diastolic blood pressure (DBP) combinations to cover a range of medical situations, including hypotension, standard or normal, and hypertension. The values of SBP, DBP, and MAP were derived from the sensor's output using the MAA technique, and the errors in these values concerning the simulator and the traditional BP monitor follow the universal AAMI/ESH/ISO protocols. Bland-Altman (B&A) correlation and scatter plots were used to compare the sensor's results and further validate the proposed sensor. The sensor showed the mean and standard deviation error in the SBP, DBP, and MBP of -0.2 ± 5.9, -0.5 ± 7, and -0.9 ± 4.7 mmHg when compared with the noninvasive blood pressure (NIBP) simulator. The pulse rate (PR) was also calculated from the same OMW for the specified value of 80 beats per minute (bpm) given by the simulator and reported a mean PR value of ∼81 bpm, close to the reference value. The findings show that the flexible resistive sensing device can accurately measure BP and replace the existing sensors of BP devices.

Abstract WP145: Quantifying Blood Pressure Variability Within the First Hour Following Endovascular Therapy

Background: Blood pressure variability (BPV) during the first 24 hours following endovascular therapy is associated with poor functional outcome. However, to be a viable treatment target, BPV needs to be recognized very quickly after large vessel recanalization. Hypothesis: We hypothesized that high frequency arterial line data will facilitate BPV quantification within 1 hour of large vessel recanalization, which will correlate with 24-hour BPV. Methods: This single-center retrospective cohort included acute stroke patients who underwent endovascular therapy during 2022 for large vessel occlusion. Eligible patients had an invasive radial artery catheter for continuous blood pressure monitoring during and after endovascular therapy. Systolic and diastolic blood pressure were recorded at 1Hz. For both systolic and diastolic, BPV was calculated over one hour and 24 hours following endovascular therapy using four techniques: (1) standard deviation, (2) coefficient of variation, (3) successive variation, and (4) average real variation. Correlation between the two time windows was evaluated for each BPV metric. Results: Of 198 patients who underwent EVT during the study time frame, 108 had the required arterial line data. BPV metrics calculated based on systolic blood pressure were at least moderated correlated between the 1-hour and 24-hour window. When calculated based on diastolic blood pressure, BPV metrics were strongly correlated between the 1-hour and 24-hour window ( Table ). Conclusions: With high frequency arterial line data, BPV, in particular diastolic variability can be reliably assessed within the first hour following large vessel recanalization. Given the previously observed relationship between BPV and functional outcome, future study is needed to explore the possibility of leveraging BPV as a treatment target during post-endovascular supportive care.

Smart Patch for Non-Invasive Blood Pressure Monitoring in Epileptic Seizure Patients via the Sole

Epileptic seizures can cause sudden blood pressure changes, requiring continuous monitoring. However, traditional blood pressure monitoring methods are often invasive and uncomfortable for the patient. In addition, it is difficult to measure blood pressure during seizures. This research aims to design a non-invasive, comfortable device to monitor blood pressure during epileptic seizures continuously. Photoplethysmography (PPG) signals from the sole of the patient's foot were used to extract blood pressure data. A smart patch was designed to be worn comfortably on foot for continuous monitoring during seizures. The results show that the average systolic and diastolic blood pressure errors were 2.838 and 4.494 mmHg during epileptic seizures, respectively. These blood pressure changes could be related to the onset of seizures, suggesting that the device and methodology could be combined with other measures to analyze and predict seizure activity. This research offers a non-invasive and comfortable solution for continuous blood pressure monitoring during seizures, which may affect seizure prediction and management.

Blood Pressure Estimation from Photoplythmography Using Hybrid Scattering–LSTM Networks

One of the most significant indicators of heart and cardiovascular health is blood pressure (BP). Blood pressure (BP) has gained great attention in the last decade. Uncontrolled high blood pressure increases the risk of serious health problems, including heart attack and stroke. Recently, machine/deep learning has been leveraged for learning a BP from photoplethysmography (PPG) signals. Hence, continuous BP monitoring can be introduced, based on simple wearable contact sensors or even remotely sensed from a proper camera away from the clinical setup. However, the available training dataset imposes many limitations besides the other difficulties related to the PPG time series as high-dimensional data. This work presents beat-by-beat continuous PPG-based BP monitoring while accounting for the aforementioned limitations. For a better exploration of beats’ features, we propose to use wavelet scattering transform as a better descriptive domain to cope with the limitation of the training dataset and to help the deep learning network accurately learn the relationship between the morphological shapes of PPG beats and the BP. A long short-term memory (LSTM) network is utilized to demonstrate the superiority of the wavelet scattering transform over other domains. The learning scenarios are carried out on a beat basis where the input corresponding PPG beat is used for predicting BP in two scenarios; (1) Beat-by-beat arterial blood pressure (ABP) estimation, and (2) Beat-by-beat estimation of the systolic and diastolic blood pressure values. Different transformations are used to extract the features of the PPG beats in different domains including time, discrete cosine transform (DCT), discrete wavelet transform (DWT), and wavelet scattering transform (WST) domains. The simulation results show that using the WST domain outperforms the other domains in the sense of root mean square error (RMSE) and mean absolute error (MAE) for both of the suggested two scenarios.

The Drug Effectiveness and Side Effects of Remdesivir in Neonatal COVID-19: A Case Series Study

: Due to the novelty of COVID-19, no definite treatment has yet been found for this infectious disease, especially in neonates and early infants. Although most of the neonates affected by this virus have a mild or silent course of the disease, in the severe form, there is no approved antiviral drug. This study was done to evaluate the safety and efficacy of Remdesivir as the known effective antiviral drug in both adults and children’s populations. In this case series study, we present our experience of the administration of Remdesivir in the treatment of 15 infants with severe neonatal COVID-19, with severe respiratory distress, admitted to our neonatal intensive care unit. We prescribed the drug with a 2 to 3-hour infusion of a loading dose of 5 mg/kg on day 1, followed by 2.5 mg/kg/day 4 days later, concomitant with continuous cardiac monitoring and blood pressure monitoring every 15 minutes. Fortunately, no side effects were reported either during or after the administration of the drug. Long-term patient follows up, for 10 months after birth, did not reveal any particular complications. It seems that the use of Remdesivir to treat severe forms of neonatal and early infancy COVID-19 is safe and effective.

Ambient health sensing on passive surfaces using metamaterials.

Ambient sensors can continuously and unobtrusively monitor a person's health and well-being in everyday settings. Among various sensing modalities, wireless radio-frequency sensors offer exceptional sensitivity, immunity to lighting conditions, and privacy advantages. However, existing wireless sensors are susceptible to environmental interference and unable to capture detailed information from multiple body sites. Here, we present a technique to transform passive surfaces in the environment into highly sensitive and localized health sensors using metamaterials. Leveraging textiles' ubiquity, we engineer metamaterial textiles that mediate near-field interactions between wireless signals and the body for contactless and interference-free sensing. We demonstrate that passive surfaces functionalized by these metamaterials can provide hours-long cardiopulmonary monitoring with accuracy comparable to gold standards. We also show the potential of distributed sensors and machine learning for continuous blood pressure monitoring. Our approach enables passive environmental surfaces to be harnessed for ambient sensing and digital health applications.