Indwelling arterial lines, the clinical gold standard for continuous blood pressure (BP) monitoring in the pediatric intensive care unit (PICU), have significant drawbacks due to their invasive nature, ischemic risk, and impediment to natural body movement. A noninvasive, wireless, and accurate alternative would greatly improve the quality of patient care. Recently introduced classes of wireless, skin‐interfaced devices offer capabilities in continuous, precise monitoring of physiologic waveforms and vital signs in pediatric and neonatal patients, but have not yet been employed for continuous tracking of systolic and diastolic BP—critical for guiding clinical decision‐making in the PICU. The results presented here focus on materials and mechanics that optimize the system‐level properties of these devices to enhance their reliable use in this context, achieving full compatibility with the range of body sizes, skin types, and sterilization schemes typically encountered in the PICU. Systematic analysis of the data from these devices on 23 pediatric patients, yields derived, noninvasive BP values that can be quantitatively validated against direct recordings from arterial lines. The results from this diverse cohort, including those under pharmacological protocols, suggest that wireless, skin‐interfaced devices can, in certain circumstances of practical utility, accurately and continuously monitor BP in the PICU patient population.
In two-thirds of intensive care unit (ICU) patients and 90% of surgical patients, arterial blood pressure (ABP) is monitored non-invasively but intermittently using a blood pressure cuff. Since even a few minutes of hypotension increases the risk of mortality and morbidity, for the remaining (high-risk) patients ABP is measured continuously using invasive devices, and derived values are extracted from the recorded waveforms. However, since invasive monitoring is associated with major complications (infection, bleeding, thrombosis), the ideal ABP monitor should be both non-invasive and continuous. With large volumes of high-fidelity physiological waveforms, it may be possible today to impute a physiological waveform from other available signals. Currently, the state-of-the-art approaches for ABP imputation only aim at intermittent systolic and diastolic blood pressure imputation, and there is no method that imputes the continuous ABP waveform. Here, we developed a novel approach to impute the continuous ABP waveform non-invasively using two continuously-monitored waveforms that are currently part of the standard-of-care, the electrocardiogram (ECG) and photo-plethysmogram (PPG), by adapting a deep learning architecture designed for image segmentation. Using over 150,000 min of data collected at two separate health systems from 463 patients, we demonstrate that our model provides a highly accurate prediction of the continuous ABP waveform (root mean square error 5.823 (95% CI 5.806–5.840) mmHg), as well as the derived systolic (mean difference 2.398 ± 5.623 mmHg) and diastolic blood pressure (mean difference − 2.497 ± 3.785 mmHg) compared to arterial line measurements. Our approach can potentially be used to measure blood pressure continuously and non-invasively for all patients in the acute care setting, without the need for any additional instrumentation beyond the current standard-of-care.
more » « less- NSF-PAR ID:
- 10283461
- Publisher / Repository:
- Nature Publishing Group
- Date Published:
- Journal Name:
- Scientific Reports
- Volume:
- 11
- Issue:
- 1
- ISSN:
- 2045-2322
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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