Prediction of episode of hemodynamic instability using an electrocardiogram based analytic: a retrospective cohort study
Abstract Background Predicting the onset of hemodynamic instability before it occurs remains a sought-after goal in acute and critical care medicine. Technologies that allow for this may assist clinicians in preventing episodes of hemodynamic instability (EHI). We tested a novel noninvasive technolo...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-09-01
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| Series: | BMC Anesthesiology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12871-023-02283-x |
| _version_ | 1797556938817404928 |
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| author | Bryce Benson Ashwin Belle Sooin Lee Benjamin S. Bassin Richard P. Medlin Michael W. Sjoding Kevin R. Ward |
| author_facet | Bryce Benson Ashwin Belle Sooin Lee Benjamin S. Bassin Richard P. Medlin Michael W. Sjoding Kevin R. Ward |
| author_sort | Bryce Benson |
| collection | DOAJ |
| description | Abstract Background Predicting the onset of hemodynamic instability before it occurs remains a sought-after goal in acute and critical care medicine. Technologies that allow for this may assist clinicians in preventing episodes of hemodynamic instability (EHI). We tested a novel noninvasive technology, the Analytic for Hemodynamic Instability-Predictive Indicator (AHI-PI), which analyzes a single lead of electrocardiogram (ECG) and extracts heart rate variability and morphologic waveform features to predict an EHI prior to its occurrence. Methods Retrospective cohort study at a quaternary care academic health system using data from hospitalized adult patients between August 2019 and April 2020 undergoing continuous ECG monitoring with intermittent noninvasive blood pressure (NIBP) or with continuous intraarterial pressure (IAP) monitoring. Results AHI-PI’s low and high-risk indications were compared with the presence of EHI in the future as indicated by vital signs (heart rate > 100 beats/min with a systolic blood pressure < 90 mmHg or a mean arterial blood pressure of < 70 mmHg). 4,633 patients were analyzed (3,961 undergoing NIBP monitoring, 672 with continuous IAP monitoring). 692 patients had an EHI (380 undergoing NIBP, 312 undergoing IAP). For IAP patients, the sensitivity and specificity of AHI-PI to predict EHI was 89.7% and 78.3% with a positive and negative predictive value of 33.7% and 98.4% respectively. For NIBP patients, AHI-PI had a sensitivity and specificity of 86.3% and 80.5% with a positive and negative predictive value of 11.7% and 99.5% respectively. Both groups performed with an AUC of 0.87. AHI-PI predicted EHI in both groups with a median lead time of 1.1 h (average lead time of 3.7 h for IAP group, 2.9 h for NIBP group). Conclusions AHI-PI predicted EHIs with high sensitivity and specificity and within clinically significant time windows that may allow for intervention. Performance was similar in patients undergoing NIBP and IAP monitoring. |
| first_indexed | 2024-03-10T17:10:15Z |
| format | Article |
| id | doaj.art-8ee4171f916a4baf8d650efd26f74b63 |
| institution | Directory Open Access Journal |
| issn | 1471-2253 |
| language | English |
| last_indexed | 2024-03-10T17:10:15Z |
| publishDate | 2023-09-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Anesthesiology |
| spelling | doaj.art-8ee4171f916a4baf8d650efd26f74b632023-11-20T10:41:52ZengBMCBMC Anesthesiology1471-22532023-09-0123111010.1186/s12871-023-02283-xPrediction of episode of hemodynamic instability using an electrocardiogram based analytic: a retrospective cohort studyBryce Benson0Ashwin Belle1Sooin Lee2Benjamin S. Bassin3Richard P. Medlin4Michael W. Sjoding5Kevin R. Ward6Fifth Eye IncFifth Eye IncFifth Eye IncDepartment of Emergency Medicine, University of MichiganDepartment of Emergency Medicine, University of MichiganMax Harry Weil Institute for Critical Care Research and Innovation, University of MichiganDepartment of Emergency Medicine, University of MichiganAbstract Background Predicting the onset of hemodynamic instability before it occurs remains a sought-after goal in acute and critical care medicine. Technologies that allow for this may assist clinicians in preventing episodes of hemodynamic instability (EHI). We tested a novel noninvasive technology, the Analytic for Hemodynamic Instability-Predictive Indicator (AHI-PI), which analyzes a single lead of electrocardiogram (ECG) and extracts heart rate variability and morphologic waveform features to predict an EHI prior to its occurrence. Methods Retrospective cohort study at a quaternary care academic health system using data from hospitalized adult patients between August 2019 and April 2020 undergoing continuous ECG monitoring with intermittent noninvasive blood pressure (NIBP) or with continuous intraarterial pressure (IAP) monitoring. Results AHI-PI’s low and high-risk indications were compared with the presence of EHI in the future as indicated by vital signs (heart rate > 100 beats/min with a systolic blood pressure < 90 mmHg or a mean arterial blood pressure of < 70 mmHg). 4,633 patients were analyzed (3,961 undergoing NIBP monitoring, 672 with continuous IAP monitoring). 692 patients had an EHI (380 undergoing NIBP, 312 undergoing IAP). For IAP patients, the sensitivity and specificity of AHI-PI to predict EHI was 89.7% and 78.3% with a positive and negative predictive value of 33.7% and 98.4% respectively. For NIBP patients, AHI-PI had a sensitivity and specificity of 86.3% and 80.5% with a positive and negative predictive value of 11.7% and 99.5% respectively. Both groups performed with an AUC of 0.87. AHI-PI predicted EHI in both groups with a median lead time of 1.1 h (average lead time of 3.7 h for IAP group, 2.9 h for NIBP group). Conclusions AHI-PI predicted EHIs with high sensitivity and specificity and within clinically significant time windows that may allow for intervention. Performance was similar in patients undergoing NIBP and IAP monitoring.https://doi.org/10.1186/s12871-023-02283-xBlood pressureCritical careHeart rate variabilityHemodynamic instabilityHemodynamic monitoringHypotension |
| spellingShingle | Bryce Benson Ashwin Belle Sooin Lee Benjamin S. Bassin Richard P. Medlin Michael W. Sjoding Kevin R. Ward Prediction of episode of hemodynamic instability using an electrocardiogram based analytic: a retrospective cohort study BMC Anesthesiology Blood pressure Critical care Heart rate variability Hemodynamic instability Hemodynamic monitoring Hypotension |
| title | Prediction of episode of hemodynamic instability using an electrocardiogram based analytic: a retrospective cohort study |
| title_full | Prediction of episode of hemodynamic instability using an electrocardiogram based analytic: a retrospective cohort study |
| title_fullStr | Prediction of episode of hemodynamic instability using an electrocardiogram based analytic: a retrospective cohort study |
| title_full_unstemmed | Prediction of episode of hemodynamic instability using an electrocardiogram based analytic: a retrospective cohort study |
| title_short | Prediction of episode of hemodynamic instability using an electrocardiogram based analytic: a retrospective cohort study |
| title_sort | prediction of episode of hemodynamic instability using an electrocardiogram based analytic a retrospective cohort study |
| topic | Blood pressure Critical care Heart rate variability Hemodynamic instability Hemodynamic monitoring Hypotension |
| url | https://doi.org/10.1186/s12871-023-02283-x |
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