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1.
Management Accountant ; 58(4):13, 2023.
Article in English | ProQuest Central | ID: covidwho-2299423

ABSTRACT

Due to increased lifespan and the rapid development of chronic diseases, there is a growing demand for chronic disease-related healthcare. The dramatic increase of Covid19 lead to the growth of digital healthcare driven by technology to improve patient satisfaction. The present study attempts to understand how different types of digital health care bring patient satisfaction, the concept of Telemedicine and finally, presents primary survey-based evidence of patient satisfaction as a result of Telemedicine using WHOQOLBRIEF Patient Satisfaction Assessment.

2.
mSphere ; 6(2)2021 04 28.
Article in English | MEDLINE | ID: covidwho-1207481

ABSTRACT

Effective methods for predicting COVID-19 disease trajectories are urgently needed. Here, enzyme-linked immunosorbent assay (ELISA) and coronavirus antigen microarray (COVAM) analysis mapped antibody epitopes in the plasma of COVID-19 patients (n = 86) experiencing a wide range of disease states. The experiments identified antibodies to a 21-residue epitope from nucleocapsid (termed Ep9) associated with severe disease, including admission to the intensive care unit (ICU), requirement for ventilators, or death. Importantly, anti-Ep9 antibodies can be detected within 6 days post-symptom onset and sometimes within 1 day. Furthermore, anti-Ep9 antibodies correlate with various comorbidities and hallmarks of immune hyperactivity. We introduce a simple-to-calculate, disease risk factor score to quantitate each patient's comorbidities and age. For patients with anti-Ep9 antibodies, scores above 3.0 predict more severe disease outcomes with a 13.42 likelihood ratio (96.7% specificity). The results lay the groundwork for a new type of COVID-19 prognostic to allow early identification and triage of high-risk patients. Such information could guide more effective therapeutic intervention.IMPORTANCE The COVID-19 pandemic has resulted in over two million deaths worldwide. Despite efforts to fight the virus, the disease continues to overwhelm hospitals with severely ill patients. Diagnosis of COVID-19 is readily accomplished through a multitude of reliable testing platforms; however, prognostic prediction remains elusive. To this end, we identified a short epitope from the SARS-CoV-2 nucleocapsid protein and also a disease risk factor score based upon comorbidities and age. The presence of antibodies specifically binding to this epitope plus a score cutoff can predict severe COVID-19 outcomes with 96.7% specificity.


Subject(s)
Antibodies, Viral/blood , COVID-19/diagnosis , Coronavirus Nucleocapsid Proteins/immunology , SARS-CoV-2/immunology , Severity of Illness Index , COVID-19/pathology , Cell Surface Display Techniques , Enzyme-Linked Immunosorbent Assay , Epitopes/blood , Epitopes/immunology , Humans , Nucleocapsid/immunology , Phosphoproteins/immunology , Prognosis , Risk Factors
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