Dataset Information

Analysis of Pulse Arrival Time as an Indicator of Blood Pressure in a Large Surgical Biosignal Database: Recommendations for Developing Ubiquitous Blood Pressure Monitoring Methods.

ABSTRACT: As non-invasive continuous blood pressure monitoring (NCBPM) has gained wide attraction in the recent decades, many pulse arrival time (PAT) or pulse transit time (PTT) based blood pressure (BP) estimation studies have been conducted. However, most of the studies have used small homogeneous subject pools to generate models of BP based on particular interventions for induced hemodynamic change. In this study, a large open biosignal database from a diverse group of 2309 surgical patients was analyzed to assess the efficacy of PAT, PTT, and confounding factors on the estimation of BP. After pre-processing the dataset, a total of 6,777,308 data pairs of BP and temporal features between electrocardiogram (ECG) and photoplethysmogram (PPG) were extracted and analyzed. Correlation analysis revealed that PAT or PTT extracted from the intersecting-tangent (IT) point of PPG showed the highest mean correlation to BP. The mean correlation between PAT and systolic blood pressure (SBP) was -0.37 and the mean correlation between PAT and diastolic blood pressure (DBP) was -0.30, outperforming the correlation between BP and PTT at -0.12 for SBP and -0.11 for DBP. A linear model of BP with a simple calibration method using PAT as a predictor was developed which satisfied international standards for automatic oscillometric BP monitors in the case of DBP, however, SBP could not be predicted to a satisfactory level due to higher errors. Furthermore, multivariate regression analyses showed that many confounding factors considered in previous studies had inconsistent effects on the degree of correlation between PAT and BP.

SUBMITTER: Lee J

PROVIDER: S-EPMC6912522 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Analysis of Pulse Arrival Time as an Indicator of Blood Pressure in a Large Surgical Biosignal Database: Recommendations for Developing Ubiquitous Blood Pressure Monitoring Methods.

Lee Joonnyong J Yang Seungman S Lee Saram S Kim Hee Chan HC

Journal of clinical medicine 20191024 11

As non-invasive continuous blood pressure monitoring (NCBPM) has gained wide attraction in the recent decades, many pulse arrival time (PAT) or pulse transit time (PTT) based blood pressure (BP) estimation studies have been conducted. However, most of the studies have used small homogeneous subject pools to generate models of BP based on particular interventions for induced hemodynamic change. In this study, a large open biosignal database from a diverse group of 2309 surgical patients was analy ...[more]

PMID: 31653002

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Project description:Various models have been proposed for the estimation of blood pressure (BP) from pulse transit time (PTT). PTT is defined as the time delay of the pressure wave, produced by left ventricular contraction, measured between a proximal and a distal site along the arterial tree. Most researchers, when they measure the time difference between the peak of the R-wave in the electrocardiogram signal (corresponding to left ventricular depolarisation) and a fiducial point in the photoplethysmogram waveform (as measured by a pulse oximeter attached to the fingertip), describe this erroneously as the PTT. In fact, this is the pulse arrival time (PAT), which includes not only PTT, but also the time delay between the electrical depolarisation of the heart's left ventricle and the opening of the aortic valve, known as pre-ejection period (PEP). PEP has been suggested to present a significant limitation to BP estimation using PAT. This work investigates the impact of PEP on PAT, leading to a discussion on the best models for BP estimation using PAT or PTT. We conducted a clinical study involving 30 healthy volunteers (53.3% female, 30.9 ± 9.35 years old, with a body mass index of 22.7 ± 3.2 kg/m[Formula: see text]). Each session lasted on average 27.9 ± 0.6 min and BP was varied by an infusion of phenylephrine (a medication that causes venous and arterial vasoconstriction). We introduced new processing steps for the analysis of PAT and PEP signals. Various population-based models (Poon, Gesche and Fung) and a posteriori models (inverse linear, inverse squared and logarithm) for estimation of BP from PTT or PAT were evaluated. Across the cohort, PEP was found to increase by 5.5 ms ± 4.5 ms from its baseline value. Variations in PTT were significantly larger in amplitude, - 16.8 ms ± 7.5 ms. We suggest, therefore, that for infusions of phenylephrine, the contribution of PEP on PAT can be neglected. All population-based models produced large BP estimation errors, suggesting that they are insufficient for modelling the complex pathways relating changes in PTT or PAT to changes in BP. Although PAT is inversely correlated with systolic blood pressure (SBP), the gradient of this relationship varies significantly from individual to individual, from - 2946 to - 470.64 mmHg/s in our dataset. For the a posteriori inverse squared model, the root mean squared errors (RMSE) for systolic and diastolic blood pressure (DBP) estimation from PAT were 5.49 mmHg and 3.82 mmHg, respectively. The RMSEs for SBP and DBP estimation by PTT were 4.51 mmHg and 3.53 mmHg, respectively. These models take into account individual calibration curves required for accurate blood pressure estimation. The best performing population-based model (Poon) reported error values around double that of the a posteriori inverse squared model, and so the use of population-based models is not justified.

Project description:Background Hypertension and diabetes frequently coexist. However, little is known about the interaction between high blood pressure (BP) and hyperglycemia in the development of cardiovascular disease (CVD). Methods and Results We conducted an observational cohort study that included 3 336 363 patients (median age, 43 years old; men, 57.2%). People taking BP- or glucose-lowering medications or those with prior history of CVD were excluded. We defined stage 1 hypertension as having systolic BP of 130 to 139 mm Hg or diastolic BP of 80 to 89 mm Hg and stage 2 hypertension as having systolic BP of ≥140 mm Hg or diastolic BP of ≥90 mm Hg. We defined prediabetes as having fasting plasma glucose of 100 to 125 mg/dL and diabetes as having fasting plasma glucose of ≥126 mg/dL. Over a mean follow-up period of 1185 ± 942 days, 5665 myocardial infarction, 52 475 angina pectoris, 25 436 stroke, 54 508 heart failure, and 12 932 atrial fibrillation events occurred. The BP and fasting plasma glucose categories additively increased the risk of myocardial infarction, angina pectoris, stroke, heart failure, and atrial fibrillation. However, the relative risk of stage 1 and stage 2 hypertension developing into CVD was attenuated with deteriorating glycemic status. Similarly, the relative risk of prediabetes and diabetes developing into CVD was attenuated with increasing BP. For example, the relative risk reduction of stage 2 hypertension for heart failure was 53.5% in individuals with normal fasting plasma glucose, 46.4% in those with prediabetes, and 37.2% in those with diabetes. The robustness of our findings was confirmed using a multitude of sensitivity analyses. Conclusions Although hypertension and hyperglycemia additively increase the risk of developing CVD, the relative contribution of hypertension to the development of CVD decreased with deteriorating glycemic status and that of hyperglycemia was attenuated with increasing BP. Our results indicate a potential interaction between hypertension and hyperglycemia in the development of CVD.

Dataset Information

Analysis of Pulse Arrival Time as an Indicator of Blood Pressure in a Large Surgical Biosignal Database: Recommendations for Developing Ubiquitous Blood Pressure Monitoring Methods.

Publications

Analysis of Pulse Arrival Time as an Indicator of Blood Pressure in a Large Surgical Biosignal Database: Recommendations for Developing Ubiquitous Blood Pressure Monitoring Methods.

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