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Smart respiratory monitoring: clinical development and validation of the IPI™ (Integrated Pulmonary Index) algorithm
Continuous electronic monitoring of patient respiratory status frequently includes PetCO(2) (end tidal CO(2)), RR (respiration rate), SpO(2) (arterial oxygen saturation), and PR (pulse rate). Interpreting and integrating these vital signs as numbers or waveforms is routinely done by anesthesiologist...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5346135/ https://www.ncbi.nlm.nih.gov/pubmed/26961501 http://dx.doi.org/10.1007/s10877-016-9851-7 |
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author | Ronen, M. Weissbrod, R. Overdyk, F. J. Ajizian, S. |
author_facet | Ronen, M. Weissbrod, R. Overdyk, F. J. Ajizian, S. |
author_sort | Ronen, M. |
collection | PubMed |
description | Continuous electronic monitoring of patient respiratory status frequently includes PetCO(2) (end tidal CO(2)), RR (respiration rate), SpO(2) (arterial oxygen saturation), and PR (pulse rate). Interpreting and integrating these vital signs as numbers or waveforms is routinely done by anesthesiologists and intensivists but is challenging for clinicians in low acuity areas such as medical wards, where continuous electronic respiratory monitoring is becoming more common place. We describe a heuristic algorithm that simplifies the interpretation of these four parameters in assessing a patient’s respiratory status, the Integrated Pulmonary Index (IPI). The IPI algorithm is a mathematical model combining SpO(2), RR, PR, and PetCO(2) into a single value between 1 and 10 that summarizes the adequacy of ventilation and oxygenation at that point in time. The algorithm was designed using a fuzzy logic inference model to incorporate expert clinical opinions. The algorithm was verified by comparison to experts’ scoring of clinical scenarios. The validity of the index was tested in a retrospective analysis of continuous SpO(2), RR, PR, and PetCO(2) readings obtained from 523 patients in a variety of clinical settings. IPI correlated well with expert interpretation of the continuous respiratory data (R = 0.83, p <<< 0.001), with agreement of −0.5 ± 1.4. Receiver operating curves analysis resulted in high levels of sensitivity (ranging from 0.83 to 1.00), and corresponding specificity (ranging from 0.96 to 0.74), based on IPI thresholds 3−6. The IPI reliably interpreted the respiratory status of patients in multiple areas of care using off-line continuous respiratory data. Further prospective studies are required to evaluate IPI in real time in clinical settings. |
format | Online Article Text |
id | pubmed-5346135 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-53461352017-03-22 Smart respiratory monitoring: clinical development and validation of the IPI™ (Integrated Pulmonary Index) algorithm Ronen, M. Weissbrod, R. Overdyk, F. J. Ajizian, S. J Clin Monit Comput Original Research Continuous electronic monitoring of patient respiratory status frequently includes PetCO(2) (end tidal CO(2)), RR (respiration rate), SpO(2) (arterial oxygen saturation), and PR (pulse rate). Interpreting and integrating these vital signs as numbers or waveforms is routinely done by anesthesiologists and intensivists but is challenging for clinicians in low acuity areas such as medical wards, where continuous electronic respiratory monitoring is becoming more common place. We describe a heuristic algorithm that simplifies the interpretation of these four parameters in assessing a patient’s respiratory status, the Integrated Pulmonary Index (IPI). The IPI algorithm is a mathematical model combining SpO(2), RR, PR, and PetCO(2) into a single value between 1 and 10 that summarizes the adequacy of ventilation and oxygenation at that point in time. The algorithm was designed using a fuzzy logic inference model to incorporate expert clinical opinions. The algorithm was verified by comparison to experts’ scoring of clinical scenarios. The validity of the index was tested in a retrospective analysis of continuous SpO(2), RR, PR, and PetCO(2) readings obtained from 523 patients in a variety of clinical settings. IPI correlated well with expert interpretation of the continuous respiratory data (R = 0.83, p <<< 0.001), with agreement of −0.5 ± 1.4. Receiver operating curves analysis resulted in high levels of sensitivity (ranging from 0.83 to 1.00), and corresponding specificity (ranging from 0.96 to 0.74), based on IPI thresholds 3−6. The IPI reliably interpreted the respiratory status of patients in multiple areas of care using off-line continuous respiratory data. Further prospective studies are required to evaluate IPI in real time in clinical settings. Springer Netherlands 2016-03-09 2017 /pmc/articles/PMC5346135/ /pubmed/26961501 http://dx.doi.org/10.1007/s10877-016-9851-7 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Research Ronen, M. Weissbrod, R. Overdyk, F. J. Ajizian, S. Smart respiratory monitoring: clinical development and validation of the IPI™ (Integrated Pulmonary Index) algorithm |
title | Smart respiratory monitoring: clinical development and validation of the IPI™ (Integrated Pulmonary Index) algorithm |
title_full | Smart respiratory monitoring: clinical development and validation of the IPI™ (Integrated Pulmonary Index) algorithm |
title_fullStr | Smart respiratory monitoring: clinical development and validation of the IPI™ (Integrated Pulmonary Index) algorithm |
title_full_unstemmed | Smart respiratory monitoring: clinical development and validation of the IPI™ (Integrated Pulmonary Index) algorithm |
title_short | Smart respiratory monitoring: clinical development and validation of the IPI™ (Integrated Pulmonary Index) algorithm |
title_sort | smart respiratory monitoring: clinical development and validation of the ipi™ (integrated pulmonary index) algorithm |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5346135/ https://www.ncbi.nlm.nih.gov/pubmed/26961501 http://dx.doi.org/10.1007/s10877-016-9851-7 |
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