Man With Hoarse Voice and Dyspnea on Exertion.
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ABSTRACT:
SUBMITTER: Kravitz MS
PROVIDER: S-EPMC8685409 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Dyspnea is one of the most common symptoms of many respiratory diseases, including COVID-19. Clinical assessment of dyspnea relies mainly on self-reporting, which contains subjective biases and is problematic for frequent inquiries. This study aims to determine if a respiratory score in COVID-19 patients can be assessed using a wearable sensor and if this score can be deduced from a learning model based on physiologically induced dyspnea in healthy subjects. Noninvasive wearable respiratory sensors were employed to retrieve continuous respiratory characteristics with user comfort and convenience. Overnight respiratory waveforms were collected on 12 COVID-19 patients, and a benchmark on 13 healthy subjects with exertion-induced dyspnea was also performed for blind comparison. The learning model was built from the self-reported respiratory features of 32 healthy subjects under exertion and airway blockage. A high similarity between respiratory features in COVID-19 patients and physiologically induced dyspnea in healthy subjects was observed. Learning from our previous dyspnea model of healthy subjects, we deduced that COVID-19 patients have consistently highly correlated respiratory scores in comparison with normal breathing of healthy subjects. We also performed a continuous assessment of the patient’s respiratory scores for 12–16 h. This study offers a useful system for the symptomatic evaluation of patients with active or chronic respiratory disorders, especially the patient population that refuses to cooperate or cannot communicate due to deterioration or loss of cognitive functions. The proposed system can help identify dyspneic exacerbation, leading to early intervention and possible outcome improvement. Our approach can be potentially applied to other pulmonary disorders, such as asthma, emphysema, and other types of pneumonia.
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Project description:We hypothesized that among patients presenting with dyspnea on exertion (DOE), those who were found to have hyperdynamic left ventricle (i.e. LVEF ≥ 70%) on stress radionuclide myocardial perfusion imaging (RNMPI), are more likely to have features of diastolic dysfunction on transthoracic echocardiography.Medical records of 1892 consecutive patients who presented between February 2011 and September 2012 with the chief complaint of DOE and were referred to stress RNMPI were reviewed. Among these, patients who had no evidence of reversible ischemia and had hyperdynamic left ventricle on perfusion imaging, were selected and their recent echocardiograms were reviewed for evidence of diastolic dysfunction. Logistic regression analysis was used to develop an equation to predict diastolic dysfunction with the ejection fraction as the predictor. A two-way analysis of variance model was used to detect differential patterns of ejection fraction across diastolic dysfunction and gender.A hyperdynamic left ventricle identified on stress RNMPI was found to be a significant predictor of diastolic dysfunction on echocardiography in logistic regression analysis (odds ratio = 1.24, 95% CI = 1.13-1.35, p < 0.0001). A hyperdynamic left ventricle on stress RNMPI has a specificity of 96.77% (CI 83.24-99.46%) and a positive predictor value of 97.83% (CI 88.43-99.64%) in identifying diastolic dysfunction.In patients presenting with DOE who have no evidence of reversible ischemia on radionuclide stress testing but have hyperdynamic left ventricle, a search should be made for alternate cardiac etiology for this complaint such as diastolic dysfunction and heart failure with preserved ejection fraction.
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