Literature DB >> 34891712

Detection of COVID-19 Using Heart Rate and Blood Pressure: Lessons Learned from Patients with ARDS.

Milad Asgari Mehrabadi, Seyed Amir Hossein Aqajari, Iman Azimi, Charles A Downs, Nikil Dutt, Amir M Rahmani.   

Abstract

The world has been affected by COVID-19 coronavirus. At the time of this study, the number of infected people in the United States is the highest globally (31.2 million infections). Within the infected population, patients diagnosed with acute respiratory distress syndrome (ARDS) are in more life-threatening circumstances, resulting in severe respiratory system failure. Various studies have investigated the infections to COVID-19 and ARDS by monitoring laboratory metrics and symptoms. Unfortunately, these methods are merely limited to clinical settings, and symptom-based methods are shown to be ineffective. In contrast, vital signs (e.g., heart rate) have been utilized to early-detect different respiratory diseases in ubiquitous health monitoring. We posit that such biomarkers are informative in identifying ARDS patients infected with COVID-19. In this study, we investigate the behavior of COVID-19 on ARDS patients by utilizing simple vital signs. We analyze the long-term daily logs of blood pressure (BP) and heart rate (HR) associated with 150 ARDS patients admitted to five University of California academic health centers (containing 77,972 samples for each vital sign) to distinguish subjects with COVID-19 positive and negative test results. In addition to the statistical analysis, we develop a deep neural network model to extract features from the longitudinal data. Our deep learning model is able to achieve 0.81 area under the curve (AUC) to classify the vital signs of ARDS patients infected with COVID-19 versus other ARDS diagnosed patients. Since our proposed model uses only the BP and HR, it would be possible to review data prior to the first reported cases in the U.S. to validate the presence or absence of COVID-19 in our communities prior to January 2020. In addition, by utilizing wearable devices, and monitoring vital signs of subjects in everyday settings it is possible to early-detect COVID-19 without visiting a hospital or a care site.

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Mesh:

Year:  2021        PMID: 34891712      PMCID: PMC9009359          DOI: 10.1109/EMBC46164.2021.9629794

Source DB:  PubMed          Journal:  Annu Int Conf IEEE Eng Med Biol Soc        ISSN: 2375-7477


  10 in total

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4.  Risk Factors Associated With Acute Respiratory Distress Syndrome and Death in Patients With Coronavirus Disease 2019 Pneumonia in Wuhan, China.

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5.  Estimating the efficacy of symptom-based screening for COVID-19.

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Review 6.  Acute respiratory failure in COVID-19: is it "typical" ARDS?

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7.  COVID-19 pneumonia: ARDS or not?

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8.  Comparison of Hospitalized Patients With ARDS Caused by COVID-19 and H1N1.

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Journal:  Chest       Date:  2020-03-26       Impact factor: 9.410

9.  Individualizing Risk Prediction for Positive Coronavirus Disease 2019 Testing: Results From 11,672 Patients.

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10.  Comparison of the Clinical Course of COVID-19 Pneumonia and Acute Respiratory Distress Syndrome in 2 Passengers from the Cruise Ship Diamond Princess in February 2020.

Authors:  Kazuki Matsumura; Yukitoshi Toyoda; Shokei Matsumoto; Yoshiaki Kawai; Takaaki Mori; Kosei Omasa; Takuya Fukada; Masaki Yamada; Taku Kazamaki; Shintaro Furugori; Nao Hiroe; Satomi Senoo; Masayuki Shimizu; Tomohiro Funabiki; Motoyasu Yamazaki
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  10 in total

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