Dataset Information

Estimation of Wave Condition Number From Pressure Waveform Alone and Its Changes With Advancing Age in Healthy Women and Men.

ABSTRACT:

Introduction

The wave condition number (WCN) is a non-dimensional number that determines the state of arterial wave reflections. WCN is equal to HR × L _eff /PWV where HR, L _eff , and PWV are the heart rate, effective length, and pulse wave velocity, respectively. It has been shown that a value of WCN = 0.1 indicates the optimum state of arterial wave reflection in which left ventricle workload is minimized. The pressure wave, flow wave, and PWV are all required to compute WCN, which may limit the potential clinical utility of WCN. The aims of this study are as follows: (1) to assess the feasibility of approximating WCN from the pressure waveform alone (WCN _Pinf ), and (2) to provide the proof-of-concept that WCN _Pinf can capture age related differences in arterial wave reflection among healthy women and men.

Methods

Previously published retrospective data composed of seventeen patients (age 19-54 years; 34.3 ± 9.6) were used to assess the accuracy of WCN _Pinf . The exact value of WCN was computed from PWV (measured by foot-to-foot method), HR, and L _eff . A quarter wavelength relationship with minimum impedance modulus were used to compute L _eff . WCN _Pinf was calculated using HR and the reflected wave arrival time. Previously published analyses from a healthy subset of the Anglo-Cardiff Collaborative Trial (ACCT) study population were used to investigate if non-invasive WCN _Pinf captures age related differences in arterial wave reflection among healthy women and men.

Results

A strong correlation (r = 0.83, p-value <0.0001) between WCN _Pinf and WCN was observed. The accuracy of WCN _Pinf was independent from relevant physiological parameters such as PWV, pulse pressure (PP), and HR. Similar changes in WCN _Pinf with advancing age were observed in both healthy men and healthy women. In young, healthy individuals (women and men) the WCN _Pinf was around 0.1 (the optimum value), and reduced with aging.

Conclusion

WCN can be approximated from a single pressure waveform and can capture age related arterial wave reflection alteration. These results are clinically significant since WCN can be extracted from a single non-invasive pressure waveform. Future studies will focus on investigating if WCN is associated with risk for onset of cardiovascular disease events.

SUBMITTER: Pahlevan NM

PROVIDER: S-EPMC7161432 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Estimation of Wave Condition Number From Pressure Waveform Alone and Its Changes With Advancing Age in Healthy Women and Men.

Pahlevan Niema M NM Mazandarani Sohrab P SP

Frontiers in physiology 20200409

<h4>Introduction</h4>The wave condition number (WCN) is a non-dimensional number that determines the state of arterial wave reflections. WCN is equal to HR × L <sub><i>eff</i></sub> /PWV where HR, L <sub><i>eff</i></sub> , and PWV are the heart rate, effective length, and pulse wave velocity, respectively. It has been shown that a value of WCN = 0.1 indicates the optimum state of arterial wave reflection in which left ventricle workload is minimized. The pressure wave, flow wave, and PWV are all ...[more]

PMID: 32328003

Similar Datasets

Project description:ImportanceIncreased intracranial pressure (ICP) is associated with adverse neurological outcomes, but needs invasive monitoring.ObjectiveDevelopment and validation of an AI approach for detecting increased ICP (aICP) using only non-invasive extracranial physiological waveform data.DesignRetrospective diagnostic study of AI-assisted detection of increased ICP. We developed an AI model using exclusively extracranial waveforms, externally validated it and assessed associations with clinical outcomes.SettingMIMIC-III Waveform Database (2000-2013), a database derived from patients admitted to an ICU in an academic Boston hospital, was used for development of the aICP model, and to report association with neurologic outcomes. Data from Mount Sinai Hospital (2020-2022) in New York City was used for external validation.ParticipantsPatients were included if they were older than 18 years, and were monitored with electrocardiograms, arterial blood pressure, respiratory impedance plethysmography and pulse oximetry. Patients who additionally had intracranial pressure monitoring were used for development (N=157) and external validation (N=56). Patients without intracranial monitors were used for association with outcomes (N=1694).ExposuresExtracranial waveforms including electrocardiogram, arterial blood pressure, plethysmography and SpO2.Main outcomes and measuresIntracranial pressure > 15 mmHg. Measures were Area under receiver operating characteristic curves (AUROCs), sensitivity, specificity, and accuracy at threshold of 0.5. We calculated odds ratios and p-values for phenotype association.ResultsThe AUROC was 0.91 (95% CI, 0.90-0.91) on testing and 0.80 (95% CI, 0.80-0.80) on external validation. aICP had accuracy, sensitivity, and specificity of 73.8% (95% CI, 72.0%-75.6%), 99.5% (95% CI 99.3%-99.6%), and 76.9% (95% CI, 74.0-79.8%) on external validation. A ten-percentile increment was associated with stroke (OR=2.12; 95% CI, 1.27-3.13), brain malignancy (OR=1.68; 95% CI, 1.09-2.60), subdural hemorrhage (OR=1.66; 95% CI, 1.07-2.57), intracerebral hemorrhage (OR=1.18; 95% CI, 1.07-1.32), and procedures like percutaneous brain biopsy (OR=1.58; 95% CI, 1.15-2.18) and craniotomy (OR = 1.43; 95% CI, 1.12-1.84; P < 0.05 for all).Conclusions and relevanceaICP provides accurate, non-invasive estimation of increased ICP, and is associated with neurological outcomes and neurosurgical procedures in patients without intracranial monitoring.

Project description:Morphological alterations in intracranial pressure (ICP) pulse waveform (ICPW) secondary to intracranial hypertension (ICP >20 mmHg) and a reduction in intracranial compliance (ICC) are well known indicators of neurological severity. The exclusive exploration of modifications in ICPW after either the loss of skull integrity or surgical procedures for intracranial hypertension resolution is not a common approach studied. The present study aimed to assess the morphological alterations in ICPW among neurocritical care patients with skull defects and decompressive craniectomy (DC) by comparing the variations in ICPW features according to elevations in mean ICP values. Patients requiring ICP monitoring because of acute brain injury were included. A continuous record of 10 min-length for the beat-by-beat analysis of ICPW was performed, with ICP elevation produced by means of ultrasound-guided manual internal jugular vein compression at the end of the record. ICPW features (peak amplitude ratio (P2/P1), time interval to pulse peak (TTP) and pulse amplitude) were counterweighed between baseline and compression periods. Results were distributed for three groups: intact skull (exclusive burr hole for ICP monitoring), craniotomy/large fractures (group 2) or DC (group 3). 57 patients were analyzed. A total of 21 (36%) presented no skull defects, 21 (36%) belonged to group 2, whereas 15 (26%) had DC. ICP was not significantly different between groups: ±15.11 for intact, 15.33 for group 2 and ±20.81 mmHg for group 3, with ICP-induced elevation also similar between groups (p = 0.56). Significant elevation was observed for the P2/P1 ratio for groups 1 and 2, whereas a reduction was observed in group 3 (elevation of ±0.09 for groups 1 and 2, but a reduction of 0.03 for group 3, p = 0.01), and no significant results were obtained for TTP and pulse amplitudes. In the present study, intracranial pressure pulse waveform analysis indicated that intracranial compliance was significantly more impaired among decompressive craniectomy patients, although ICPW indicated DC to be protective for further influences of ICP elevations over the brain. The analysis of ICPW seems to be an alternative to real-time ICC assessment.

Dataset Information

Estimation of Wave Condition Number From Pressure Waveform Alone and Its Changes With Advancing Age in Healthy Women and Men.

Introduction

Methods

Results

Conclusion

Publications

Estimation of Wave Condition Number From Pressure Waveform Alone and Its Changes With Advancing Age in Healthy Women and Men.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets