The Incidence of Perioperative Hypotension in Patients Undergoing Major Abdominal Surgery with the Use of Arterial Waveform Analysis and the Hypotension Prediction Index Hemodynamic Monitoring—A Retrospective Analysis
Intraoperative hypotension (IH) is common in patients receiving general anesthesia and can lead to serious complications such as kidney failure, myocardial injury and increased mortality. The Hypotension Prediction Index (HPI) algorithm is a machine learning system that analyzes the arterial pressur...
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MDPI AG
2024-02-01
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| Series: | Journal of Personalized Medicine |
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| Online Access: | https://www.mdpi.com/2075-4426/14/2/174 |
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| author | Jakub Szrama Agata Gradys Tomasz Bartkowiak Amadeusz Woźniak Zuzanna Nowak Krzysztof Zwoliński Ashish Lohani Natalia Jawień Piotr Smuszkiewicz Krzysztof Kusza |
| author_facet | Jakub Szrama Agata Gradys Tomasz Bartkowiak Amadeusz Woźniak Zuzanna Nowak Krzysztof Zwoliński Ashish Lohani Natalia Jawień Piotr Smuszkiewicz Krzysztof Kusza |
| author_sort | Jakub Szrama |
| collection | DOAJ |
| description | Intraoperative hypotension (IH) is common in patients receiving general anesthesia and can lead to serious complications such as kidney failure, myocardial injury and increased mortality. The Hypotension Prediction Index (HPI) algorithm is a machine learning system that analyzes the arterial pressure waveform and alerts the clinician of an impending hypotension event. The purpose of the study was to compare the frequency of perioperative hypotension in patients undergoing major abdominal surgery with different types of hemodynamic monitoring. The study included 61 patients who were monitored with the arterial pressure-based cardiac output (APCO) technology (FloTrac group) and 62 patients with the Hypotension Prediction Index algorithm (HPI group). Our primary outcome was the time-weighted average (TWA) of hypotension below < 65 mmHg. The median TWA of hypotension in the FloTrac group was 0.31 mmHg versus 0.09 mmHg in the HPI group (<i>p</i> = 0.000009). In the FloTrac group, the average time of hypotension was 27.9 min vs. 8.1 min in the HPI group (<i>p</i> = 0.000023). By applying the HPI algorithm in addition to an arterial waveform analysis alone, we were able to significantly decrease the frequency and duration of perioperative hypotension events in patients who underwent major abdominal surgery. |
| first_indexed | 2024-03-07T22:24:35Z |
| format | Article |
| id | doaj.art-3dcb07cefe0f49bfa9bbdadcc2b012a6 |
| institution | Directory Open Access Journal |
| issn | 2075-4426 |
| language | English |
| last_indexed | 2024-03-07T22:24:35Z |
| publishDate | 2024-02-01 |
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| record_format | Article |
| series | Journal of Personalized Medicine |
| spelling | doaj.art-3dcb07cefe0f49bfa9bbdadcc2b012a62024-02-23T15:23:46ZengMDPI AGJournal of Personalized Medicine2075-44262024-02-0114217410.3390/jpm14020174The Incidence of Perioperative Hypotension in Patients Undergoing Major Abdominal Surgery with the Use of Arterial Waveform Analysis and the Hypotension Prediction Index Hemodynamic Monitoring—A Retrospective AnalysisJakub Szrama0Agata Gradys1Tomasz Bartkowiak2Amadeusz Woźniak3Zuzanna Nowak4Krzysztof Zwoliński5Ashish Lohani6Natalia Jawień7Piotr Smuszkiewicz8Krzysztof Kusza9Department of Anesthesiology, Intensive Therapy and Pain Management, Poznan University of Medical Sciences, 60-355 Poznan, PolandDepartment of Anesthesiology, Intensive Therapy and Pain Management, Poznan University of Medical Sciences, 60-355 Poznan, PolandDepartment of Anesthesiology, Intensive Therapy and Pain Management, Poznan University of Medical Sciences, 60-355 Poznan, PolandDepartment of Anesthesiology, Intensive Therapy and Pain Management, Poznan University of Medical Sciences, 60-355 Poznan, PolandDepartment of Anesthesiology, Intensive Therapy and Pain Management, Poznan University of Medical Sciences, 60-355 Poznan, PolandDepartment of Anesthesiology, Intensive Therapy and Pain Management, Poznan University of Medical Sciences, 60-355 Poznan, PolandDepartment of Anesthesiology, Intensive Therapy and Pain Management, Poznan University of Medical Sciences, 60-355 Poznan, PolandDepartment of Anesthesiology, Intensive Therapy and Pain Management, Poznan University of Medical Sciences, 60-355 Poznan, PolandDepartment of Anesthesiology, Intensive Therapy and Pain Management, Poznan University of Medical Sciences, 60-355 Poznan, PolandDepartment of Anesthesiology, Intensive Therapy and Pain Management, Poznan University of Medical Sciences, 60-355 Poznan, PolandIntraoperative hypotension (IH) is common in patients receiving general anesthesia and can lead to serious complications such as kidney failure, myocardial injury and increased mortality. The Hypotension Prediction Index (HPI) algorithm is a machine learning system that analyzes the arterial pressure waveform and alerts the clinician of an impending hypotension event. The purpose of the study was to compare the frequency of perioperative hypotension in patients undergoing major abdominal surgery with different types of hemodynamic monitoring. The study included 61 patients who were monitored with the arterial pressure-based cardiac output (APCO) technology (FloTrac group) and 62 patients with the Hypotension Prediction Index algorithm (HPI group). Our primary outcome was the time-weighted average (TWA) of hypotension below < 65 mmHg. The median TWA of hypotension in the FloTrac group was 0.31 mmHg versus 0.09 mmHg in the HPI group (<i>p</i> = 0.000009). In the FloTrac group, the average time of hypotension was 27.9 min vs. 8.1 min in the HPI group (<i>p</i> = 0.000023). By applying the HPI algorithm in addition to an arterial waveform analysis alone, we were able to significantly decrease the frequency and duration of perioperative hypotension events in patients who underwent major abdominal surgery.https://www.mdpi.com/2075-4426/14/2/174perioperative hypotensionhemodynamic monitoringhypotension prediction indexarterial pressure-based cardiac output |
| spellingShingle | Jakub Szrama Agata Gradys Tomasz Bartkowiak Amadeusz Woźniak Zuzanna Nowak Krzysztof Zwoliński Ashish Lohani Natalia Jawień Piotr Smuszkiewicz Krzysztof Kusza The Incidence of Perioperative Hypotension in Patients Undergoing Major Abdominal Surgery with the Use of Arterial Waveform Analysis and the Hypotension Prediction Index Hemodynamic Monitoring—A Retrospective Analysis Journal of Personalized Medicine perioperative hypotension hemodynamic monitoring hypotension prediction index arterial pressure-based cardiac output |
| title | The Incidence of Perioperative Hypotension in Patients Undergoing Major Abdominal Surgery with the Use of Arterial Waveform Analysis and the Hypotension Prediction Index Hemodynamic Monitoring—A Retrospective Analysis |
| title_full | The Incidence of Perioperative Hypotension in Patients Undergoing Major Abdominal Surgery with the Use of Arterial Waveform Analysis and the Hypotension Prediction Index Hemodynamic Monitoring—A Retrospective Analysis |
| title_fullStr | The Incidence of Perioperative Hypotension in Patients Undergoing Major Abdominal Surgery with the Use of Arterial Waveform Analysis and the Hypotension Prediction Index Hemodynamic Monitoring—A Retrospective Analysis |
| title_full_unstemmed | The Incidence of Perioperative Hypotension in Patients Undergoing Major Abdominal Surgery with the Use of Arterial Waveform Analysis and the Hypotension Prediction Index Hemodynamic Monitoring—A Retrospective Analysis |
| title_short | The Incidence of Perioperative Hypotension in Patients Undergoing Major Abdominal Surgery with the Use of Arterial Waveform Analysis and the Hypotension Prediction Index Hemodynamic Monitoring—A Retrospective Analysis |
| title_sort | incidence of perioperative hypotension in patients undergoing major abdominal surgery with the use of arterial waveform analysis and the hypotension prediction index hemodynamic monitoring a retrospective analysis |
| topic | perioperative hypotension hemodynamic monitoring hypotension prediction index arterial pressure-based cardiac output |
| url | https://www.mdpi.com/2075-4426/14/2/174 |
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