On the Role of the Genetic Features Selection for Intelligent Classification of Covid-19 Patients DOI
Cosimo Aliani, E. Rossi, Mateusz Soliński

et al.

Published: Jan. 1, 2023

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection can cause feared consequences such as those affecting microcirculation. These abnormalities are highly considered because they have been associated with prognosis in the phase. The use of genetic algorithms be helpful better understanding characteristics microcirculation that mainly affected by COVID-19.This study aimed to verify presence alterations Patients COVID-19 performing heart rate variability (HRV) analysis using peak-to-peak intervals extracted from photoplethysmographic (PPG) signals. dataset comprises 97 participants divided into two groups: healthy (50 subjects) and patients mild (47 subjects). parameters evaluated HRV were investigated three different subject selection strategies (two random subjects, five subjects tournament, roulette wheel selection), four classifiers (Discriminant Analysis Classification (DISCR), Binary Decision Tree (DT), K-Nearest Neighbor (KNN) Naive Bayes (NB)) assess which was most representative for each class. All consider features (meanRR, sd2/sd1, alpha1) particularly important. present respectively 94.2%, 78%, 80.2% subjects. Fitness End value remains about same among all methods classifier but changes instead classifiers. For method used, DT achieves best results regarding maximum fitness within population: 91.8% tournament 92.2% method. Subsequently, machine learning classifications performed training only features, result achieved obtaining an accuracy 82%, specificity 86%, sensitivity 79%. study's highlight ability algorithm determine discriminating between control groups. Further studies conducted on a population similar demographic groups necessary role microcirculatory COVID-19.

Language: Английский

Tracking peripheral vascular function for six months in young adults following SARS‐CoV‐2 infection DOI
Valesha M. Province, Rachel E. Szeghy, Nina L. Stute

et al.

Physiological Reports, Journal Year: 2022, Volume and Issue: 10(24)

Published: Dec. 1, 2022

SARS-CoV-2 infection is known to instigate a range of physiologic perturbations, including vascular dysfunction. However, little work has concluded how long these effects may last, especially among young adults with mild symptoms. To determine potential recovery from acute dysfunction in (8 M/8F, 21 ± 1 yr, 23.5 3.1 kg⋅m-2 ), we longitudinally tracked brachial artery flow-mediated dilation (FMD) and reactive hyperemia (RH) the arm hyperemic response passive limb movement (PLM) leg, Doppler ultrasound, as well circulating biomarkers inflammation (interleukin-6, C-reactive protein), oxidative stress (thiobarbituric acid substances, protein carbonyl), antioxidant capacity (superoxide dismutase), nitric oxide bioavailability (nitrite) monthly for 6-month period post-SARS-CoV-2 infection. FMD, marker macrovascular function, improved month (3.06 1.39%) 6 (6.60 2.07%; p < 0.001). FMD/Shear one (0.10 0.06 AU) six (0.18 0.70 AU; = 0.002). RH PLM markers microvascular did not change during months (p > 0.05). Circulating inflammation, stress, capacity, Together, results suggest some improvements macrovascular, but over following The data also persistent ramifications cardiovascular health those recovering illness young, otherwise healthy SARS-CoV-2.

Language: Английский

Citations

3
Investigating Autonomic Nervous System Dysfunction among Patients with Post- Covid Condition and Prolonged Cardiovascular Symptoms DOI Creative Commons

Fernanda Stábile da Silva,

Lívia Pimenta Bonifácio, Fernando Bellissimo‐Rodrigues

et al.

Research Square (Research Square), Journal Year: 2023, Volume and Issue: unknown

Published: Feb. 1, 2023

Abstract The variability of heart rate (HR) and arterial pressure (AP), their responses to head-up tilt test (HUTT) was investigated in post-Covid-19 syndrome (PCS) patients, reporting tachycardia and/or postural hypotension. PCS patients were tachycardic showed attenuation the following parameters: RMSSD; power RR spectra at HF; occurrence 2UV pattern (symbolic analysis); sample entropy. Basal AP LF systolic similar between control subjects; while 0V patterns exacerbated patients. Despite decrease RMSSD, no parameter changed during HUTT reassessed after 6 months higher HF percentage RR. Moreover, a lower AP, elicited HR identical subjects. suggest an autonomic dysfunction with sympathetic predominance patients; lack BP indices indicates marked impairment control. However, reassessment that noxious effect tended fade over time.

Language: Английский

Citations

1
The effect of exercise using incentive spirometry on heart rate variability in patients after COVID-19 infection DOI

Hilman Harisuddin,

Imam Subadi,

Nuniek Nugraheni Sulistiawati

et al.

Bali Medical Journal, Journal Year: 2023, Volume and Issue: 12(1), P. 483 - 489

Published: Feb. 1, 2023

Background: COVID-19 infection causes various sequelae and complications after recovery. Changes in heart rate variability (HRV) were found patients with infection, suggesting a disturbance the autonomic system. Breathing exercises diaphragmatic breathing incentive spirometry have been shown to increase HRV by increasing lung capacity, respiratory muscle strength, pulmonary O2 pressure, which can affect baroreflex signals. Incentive is one of easy-to-use, safe, inexpensive rehabilitation that be done at home without supervision are accompanied visual display as guide patient. The purpose study was determine effect giving using Spirometry for four weeks on Heart Rate Variability post Method: This research an experimental pre-post-test control group design. treatment given Spirometry, while used five times day, seven per week, each group. measurement performed before intervention, parameter Root Mean Square Successive Differences between normal heartbeats (RMSSD), Standard Deviation N-N intervals (SDNN), LF/HF ratio (HRV). Result: There subject this 20 post-COVID-19 divided into (n=10) (n=10). no significant RMSSD, SDNN, pre post-intervention both groups, HRV. Conclusion: Exercise Diaphragmatic did not value patients.

Language: Английский

Citations

1
Genetic Algorithms for Feature Selection in the Classification of COVID-19 Patients DOI Creative Commons
Cosimo Aliani, E. Rossi, Mateusz Soliński

et al.

Bioengineering, Journal Year: 2024, Volume and Issue: 11(9), P. 952 - 952

Published: Sept. 23, 2024

Severe Acute Respiratory Syndrome CoronaVirus-2 (SARS-CoV-2) infection can cause feared consequences, such as affecting microcirculatory activity. The combined use of HRV analysis, genetic algorithms, and machine learning classifiers be helpful in better understanding the characteristics microcirculation that are mainly affected by COVID-19 infection.

Language: Английский

Citations

0
On the Role of the Genetic Features Selection for Intelligent Classification of Covid-19 Patients DOI
Cosimo Aliani, E. Rossi, Mateusz Soliński

et al.

Published: Jan. 1, 2023

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection can cause feared consequences such as those affecting microcirculation. These abnormalities are highly considered because they have been associated with prognosis in the phase. The use of genetic algorithms be helpful better understanding characteristics microcirculation that mainly affected by COVID-19.This study aimed to verify presence alterations Patients COVID-19 performing heart rate variability (HRV) analysis using peak-to-peak intervals extracted from photoplethysmographic (PPG) signals. dataset comprises 97 participants divided into two groups: healthy (50 subjects) and patients mild (47 subjects). parameters evaluated HRV were investigated three different subject selection strategies (two random subjects, five subjects tournament, roulette wheel selection), four classifiers (Discriminant Analysis Classification (DISCR), Binary Decision Tree (DT), K-Nearest Neighbor (KNN) Naive Bayes (NB)) assess which was most representative for each class. All consider features (meanRR, sd2/sd1, alpha1) particularly important. present respectively 94.2%, 78%, 80.2% subjects. Fitness End value remains about same among all methods classifier but changes instead classifiers. For method used, DT achieves best results regarding maximum fitness within population: 91.8% tournament 92.2% method. Subsequently, machine learning classifications performed training only features, result achieved obtaining an accuracy 82%, specificity 86%, sensitivity 79%. study's highlight ability algorithm determine discriminating between control groups. Further studies conducted on a population similar demographic groups necessary role microcirculatory COVID-19.

Language: Английский

Citations

0