Toward Automation of the Supine Pressor Test for Preeclampsia

Preeclampsia leads to increased risk of morbidity and mortality for both mother and fetus. Most previous studies have largely neglected mechanical compression of the left renal vein by the gravid uterus as a potential mechanism. In this study, we first used a murine model to investigate the pathophysiology of left renal vein constriction. The results indicate that prolonged renal vein stenosis after 14 days can cause renal necrosis and an increase in blood pressure (BP) of roughly 30 mmHg. The second part of this study aimed to automate a diagnostic tool, known as the supine pressor test (SPT), to enable pregnant women to assess their preeclampsia development risk. A positive SPT has been previously defined as an increase of at least 20 mmHg in diastolic BP when switching between left lateral recumbent and supine positions. The results from this study established a baseline BP increase between the two body positions in nonpregnant women and demonstrated the feasibility of an autonomous SPT in pregnant women. Our results demonstrate that there is a baseline increase in BP of roughly 10-14 mmHg and that pregnant women can autonomously perform the SPT. Overall, this work in both rodents and humans suggests that (1) stenosis of the left renal vein in mice leads to elevation in BP and acute renal failure, (2) nonpregnant women experience a baseline increase in BP when they shift from left lateral recumbent to supine position, and (3) the SPT can be automated and used autonomously

A review of machine learning techniques in photoplethysmography for the non-invasive cuff-less measurement of blood pressure

Hypertension or high blood pressure is a leading cause of death throughout the world and a critical factor for increasing the risk of serious diseases, including cardiovascular diseases such as stroke and heart failure. Blood pressure is a primary vital sign that must be monitored regularly for the early detection, prevention and treatment of cardiovascular diseases. Traditional blood pressure measurement techniques are either invasive or cuff-based, which are impractical, intermittent, and uncomfortable for patients. Over the past few decades, several indirect approaches using photoplethysmogram (PPG) have been investigated, namely, pulse transit time, pulse wave velocity, pulse arrival time and pulse wave analysis, in an effort to utilise PPG for estimating blood pressure. Recent advancements in signal processing techniques, including machine learning and artificial intelligence, have also opened up exciting new horizons for PPG-based cuff less and continuous monitoring of blood pressure. Such a device will have a significant and transformative impact in monitoring patients’ vital signs, especially those at risk of cardiovascular disease. This paper provides a comprehensive review for non-invasive cuff-less blood pressure estimation using the PPG approach along with their challenges and limitations

A Survey on Blood Pressure Measurement Technologies: Addressing Potential Sources of Bias

Regular blood pressure (BP) monitoring in clinical and ambulatory settings plays a crucial role in the prevention, diagnosis, treatment, and management of cardiovascular diseases. Recently, the widespread adoption of ambulatory BP measurement devices has been driven predominantly by the increased prevalence of hypertension and its associated risks and clinical conditions. Recent guidelines advocate for regular BP monitoring as part of regular clinical visits or even at home. This increased utilization of BP measurement technologies has brought up significant concerns, regarding the accuracy of reported BP values across settings. In this survey, focusing mainly on cuff-based BP monitoring technologies, we highlight how BP measurements can demonstrate substantial biases and variances due to factors such as measurement and device errors, demographics, and body habitus. With these inherent biases, the development of a new generation of cuff-based BP devices which use artificial-intelligence (AI) has significant potential. We present future avenues where AI-assisted technologies can leverage the extensive clinical literature on BP-related studies together with the large collections of BP records available in electronic health records. These resources can be combined with machine learning approaches, including deep learning and Bayesian inference, to remove BP measurement biases and to provide individualized BP-related cardiovascular risk indexes

Non-invasive vascular assessment using photoplethysmography

Photoplethysmography (PPG) has become widely accepted as a valuable clinical tool for performing non-invasive biomedical monitoring. The dominant clinical application of PPG has been pulse oximetry, which uses spectral analysis of the peripheral blood supply to establish haemoglobin saturation. PPG has also found success in screening for venous dysfunction, though to a limited degree. Arterial Disease (AD) is a condition where blood flow in the arteries of the body is reduced,a condition known as ischaernia. Ischaernia can result in pain in the affected areas, such as chest pain for an ischearnic heart, but does not always produce symptoms. The most common form of AD is arteriosclerosis, which affects around 5% of the population over 50 years old. Arteriosclerosis, more commonly known as 'hardening of the arteries' is a condition that results in a gradual thickening, hardening and loss of elasticity in the walls of the arteries, reducing overall blood flow. This thesis investigates the possibility of employing PPG to perform vascular assessment, specifically arterial assessment, in two ways. PPG based perfusion monitoring may allow identification of ischaernia in the periphery. To further investigate this premise, prospective experimental trials are performed, firstly to assess the viability of PPG based perfusion monitoring and culminating in the development of a more objective method for determining ABPI using PPG based vascular assessment. A complex interaction between the heart and the connective vasculature, detected at the measuring site, generates the PPG signal. The haemodynamic properties of the vasculature will affect the shape of the PPG waveform, characterising the PPG signal with the properties of the intermediary vasculature. This thesis investigates the feasibility of deriving quantitative vascular parameters from the PPG signal. A quantitative approach allows direct identification of pathology, simplifying vascular assessment. Both forward and inverse models are developed in order to investigate this topic. Application of the models in prospective experimental trials with both normal subjects and subjects suffering PVD have shown encouraging results. It is concluded that the PPG signal contains information on the connective vasculature of the subject. PPG may be used to perform vascular assessment using either perfusion based techniques, where the magnitude of the PPG signal is of interest, or by directly assessing the connective vasculature using PPG, where the shape of the PPG signal is of interest. it is argued that PPG perfusion based techniques for performing the ABPI diagnosis protocol can offer greater sensitivity to the onset of PAD, compared to more conventional methods. It is speculated that the PPG based ABPI diagnosis protocol could provide enhanced PAD diagnosis, detecting the onset of the disease and allowing a treatmenpt lan to be formed soonert han was possible previously. The determination of quantitative vascular parameters using PPG shape could allow direct vascular diagnosis, reducing subjectivity due to interpretation. The prospective trials investigating PPG shape analysis concentrated on PVD diagnosis, but it is speculated that quantitative PPG shaped based vascular assessment could be a powerful tool in the diagnosis of many vascular based pathological conditions

Retinal micro-vascular and aortic macro-vascular changes in postmenopausal women with primary hyperparathyroidism

Aim of the study was to evaluate the micro and macro-vascular changes in patients with primary hyperparathyroidism (PHPT) compared to controls. 30 postmenopausal PHPT women (15 hypertensive and 15 normotensive) and 30 normotensive controls underwent biochemical evaluation of mineral metabolism and measurements of arterial stiffness by 24 hour ambulatory blood pressure monitoring. Retinal microcirculation was imaged by a Retinal Vessel Analyzer. PHPT patients also underwent bone mineral density measurements and kidney ultrasound. PHPT patients had higher mean calcium and parathyroid hormone values compared to controls. Evaluating macro-vascular compartment, we found higher values of 24 hours-systolic, diastolic blood pressure, aortic pulse wave velocity (aPWV) and aortic augmentation index (Aix) in hypertensive PHPT, but not in normotensive PHPT compared to controls. The eye examination showed narrowing arterial and venular diameters of retinal vessels in both hypertensive and normotensive PHPT compared to controls. In hypertensive PHPT, 24 hours systolic blood pressure was associated only with parathyroid hormone (PTH) levels (beta = 0.36, p = 0.04). aPWV was associated with retinal diameter (beta = −0.69, p = 0.003), but not with PTH. Retinal artery diameter was associated with PTH (beta = −0.6, p = 0.008). In the normotensive PHPT, only PTH was associated with retinal artery diameter (beta = −0.60, p = 0.01) and aortic AIx (beta = 0.65, p = 0.02). In conclusion, we found macro-vascular impairment in PHPT and that micro-vascular impairment is negatively associated with PTH, regardless of hypertension in PHPT