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 anesthesiologists...

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Published in:	Journal of clinical monitoring and computing Vol. 31; no. 2; pp. 435 - 442
Main Authors:	Ronen, M., Weissbrod, R., Overdyk, F. J., Ajizian, S.
Format:	Journal Article
Language:	English
Published:	Dordrecht Springer Netherlands 01.04.2017 Springer Nature B.V
Subjects:	Adult Algorithms Anesthesiology Capnography - instrumentation Capnography - methods Child Child, Preschool Cluster Analysis Critical Care Medicine Electronics Fuzzy Logic Health Sciences Humans Infant Inference Intensive Lung Mathematical models Medicine Medicine & Public Health Models, Theoretical Monitoring Monitoring, Physiologic - instrumentation Monitoring, Physiologic - methods Nurses Original Research Oximetry - instrumentation Oximetry - methods Patients Physicians Prospective Studies Pulmonary Gas Exchange Reproducibility of Results Respiration Respiratory Rate Respiratory Therapy Retrospective Studies ROC Curve Sensitivity analysis Signal Processing, Computer-Assisted Statistics for Life Sciences Surveys and Questionnaires Waveforms Respiratory monitoring IPI Capnography Respiratory compromise Composite index
ISSN:	1387-1307, 1573-2614, 1573-2614
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Abstract	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.
AbstractList	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. Continuous electronic monitoring of patient respiratory status frequently includes PetCO sub(2) (end tidal CO sub(2)), RR (respiration rate), SpO sub(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 sub(2), RR, PR, and PetCO sub(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 sub(2), RR, PR, and PetCO sub(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 plus or minus 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. Continuous electronic monitoring of patient respiratory status frequently includes PetCO2 (end tidal CO2), RR (respiration rate), SpO2 (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 SpO2, RR, PR, and PetCO2 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 SpO2, RR, PR, and PetCO2 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.Continuous electronic monitoring of patient respiratory status frequently includes PetCO2 (end tidal CO2), RR (respiration rate), SpO2 (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 SpO2, RR, PR, and PetCO2 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 SpO2, RR, PR, and PetCO2 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. Continuous electronic monitoring of patient respiratory status frequently includes PetCO2 (end tidal CO2), RR (respiration rate), SpO2 (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 SpO2, RR, PR, and PetCO2 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 SpO2, RR, PR, and PetCO2 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. Continuous electronic monitoring of patient respiratory status frequently includes PetCO (end tidal CO ), RR (respiration rate), SpO (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 , RR, PR, and PetCO 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 , RR, PR, and PetCO 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. Continuous electronic monitoring of patient respiratory status frequently includes PetCO2 (end tidal CO2), RR (respiration rate), SpO2 (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 SpO2, RR, PR, and PetCO2 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 SpO2, RR, PR, and PetCO2 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.
Author	Ronen, M. Overdyk, F. J. Ajizian, S. Weissbrod, R.
Author_xml	– sequence: 1 givenname: M. surname: Ronen fullname: Ronen, M. organization: Medtronic – sequence: 2 givenname: R. surname: Weissbrod fullname: Weissbrod, R. email: Rachel.weissbrod@medtronic.com organization: Medtronic – sequence: 3 givenname: F. J. surname: Overdyk fullname: Overdyk, F. J. organization: Department of Anesthesiology, Roper St Francis Medical Center – sequence: 4 givenname: S. surname: Ajizian fullname: Ajizian, S. organization: Medtronic
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Keywords	Respiratory monitoring IPI Capnography Respiratory compromise Composite index
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Snippet	Continuous electronic monitoring of patient respiratory status frequently includes PetCO 2 (end tidal CO 2 ), RR (respiration rate), SpO 2 (arterial oxygen... Continuous electronic monitoring of patient respiratory status frequently includes PetCO (end tidal CO ), RR (respiration rate), SpO (arterial oxygen... Continuous electronic monitoring of patient respiratory status frequently includes PetCO2 (end tidal CO2), RR (respiration rate), SpO2 (arterial oxygen... Continuous electronic monitoring of patient respiratory status frequently includes PetCO sub(2) (end tidal CO sub(2)), RR (respiration rate), SpO sub(2)...
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SubjectTerms	Adult Algorithms Anesthesiology Capnography - instrumentation Capnography - methods Child Child, Preschool Cluster Analysis Critical Care Medicine Electronics Fuzzy Logic Health Sciences Humans Infant Inference Intensive Lung Mathematical models Medicine Medicine & Public Health Models, Theoretical Monitoring Monitoring, Physiologic - instrumentation Monitoring, Physiologic - methods Nurses Original Research Oximetry - instrumentation Oximetry - methods Patients Physicians Prospective Studies Pulmonary Gas Exchange Reproducibility of Results Respiration Respiratory Rate Respiratory Therapy Retrospective Studies ROC Curve Sensitivity analysis Signal Processing, Computer-Assisted Statistics for Life Sciences Surveys and Questionnaires Waveforms
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Title	Smart respiratory monitoring: clinical development and validation of the IPI™ (Integrated Pulmonary Index) algorithm
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