Detection of Antibodies for COVID-19 from Reflectance Spectrum Using Supervised Machine Learning

Since the coronavirus disease 2019 occurred, the lateral flow immunoassay (LFIA) test strip has become a global testing tool for convenience and low cost. However, some studies have shown that LFIA strips perform poorly compared to other professional testing methods. This paper proposes a new method to improve the accuracy of LFIA strips using spectral signals. A spectrochip module is applied to disperse the reflected light from the LFIA strips. The obtained spectral signals will be used for supervised machine learning. After training, the trained model has 93.8% accuracy compared to the standard test. This result indicated that the evaluation method based on the spectrum of LFIA strips could enhance the detection performance. © 2022 IEEE.

Retrospective Multihospital Prevalence Study of COVID-19 Acute Neurological Manifestations

Objective: We aim to investigate the prevalence, characteristics and outcomes of COVID-19 patients with neurological manifestations Background: To date, SARS-CoV2 has infected 213 million population worldwide. It is a multisystem disease affecting primarily the respiratory system, but neurological manifestations have been increasingly described in the literature. Design/Methods: Consecutive patients diagnosed with SARS-CoV2 admitted to 5 hospitals in Detroit Medical Center from March 3rd, 2020-May 1st, 2020 were included. Basic demographics and clinical manifestations were included. Relevant laboratory findings and neuroimaging were reported. Results: 413 patients were included in the study. Patients' demographics were as follows: mean age-66 years, 212 (51%) male, 346 (87%) African-American. 219(53%) patients had neurological symptoms at presentation, 32 patients presented purely with neurological symptoms. Other symptoms at onset include-respiratory 312(76%), constitutional 250(61%) and gastrointestinal 104(25%). 121(29%) patients were admitted to ICU, mean days from admission to ICU was 3.14 days. Incidence of neurological presentations were as follows: Encephalopathy 191(46.25%), myalgia 51(12.35%), headache 27 (6.54%), vertigo 20 (4.84%), hypogeusia 14 (3.39%), anosmia 12 (2.9%), stroke 13(3.14%), seizure 11 (2.9%). For patients with encephalopathy, median GCS at the onset of encephalopathy was 13 with IQR4. 94 (49.21%) of these patients were admitted to ICU;53(27.75%) were without coexisting toxic, metabolic or hypoxic factors contributing to encephalopathy. For patients with stroke, 12 patients presented with acute ischemic stroke, 2 with hemorrhagic conversion and 1 patient had cerebral venous sinus thrombosis. Characteristics of stroke were as follows: 8-multiple vascular territory, 11-cryptogenic etiology, 3-concurrent thromboembolic event. Median D-dimer was 5.76mg/LFEU(IQR3.74) and fibrinogen 550mg/dl(IQR 2.1). 2 patients received thrombolysis and 1 underwent thrombectomy. Mortality was 77%, Modified Rankin Scale (MRS)at baseline was 0-2 and all except 1 patient had MRS of 4-6 on discharge. Conclusions: Neurological manifestation is common amongst patients with SARS-CoV-2. Presence of encephalopathy or stroke confers an increased risk of mortality and morbidity.

Acute Encephalopathy in COVID-19 patients Early Experience from an Inner-City Hospital

Objective: We aim to investigate the prevalence, characteristics and outcomes of COVID-19 patients with encephalopathy. Other neurological manifestations of COVID-19 were described. Background: SARS-CoV-2 has rapidly spread worldwide and has now affected more than 30 million people. Although respiratory symptoms are the primary clinical manifestations of COVID-19, neurological manifestations of COVID-19 are increasingly recognized. Encephalopathy is reported as a common neurological presentation of COVID-19. The characteristics of patients with COVID-19 associated encephalopathy, including potential confounding toxic/metabolic/hypoxic factors has not been explored. Design/Methods: We retrospectively reviewed all patients consulted to the neurology service at the Detroit Medical Centre, from March 3 , 2020 to May 1 2020 who were tested positive for SARS-COV2. Clinical and laboratory data were recorded. Characteristics of encephalopathic COVID-19 patients with or without confounders were compared. Statistical analysis was performed using SPSS. Results: 49 patients were included, 40 patients (81.6%) had encephalopathy, of whom 21 patients (52.5%) had no confounders. Most common confounders were hypoxia and uremia. Patients with confounders were more likely to have dementia at baseline (p=0.049), significantly elevated inflammatory markers-C-reactive protein (P=0.02), white blood cell count(p=0.019), Ddimer(p=0.015). They were also less likely to be discharged home (p=0.009). Overall mortality is high in patient with encephalopathy (65%). 5 patients had embolic strokes, 5 had new onset seizures and 2 patients had pleocytosis on cerebrospinal fluid examination. Conclusions: We found a high prevalence of COVID-19 associated encephalopathy, independent of confounders. COVID-19 associated encephalopathy can be attributed to stroke, seizure, meningoencephalitis or idiopathic. This early report is part of an ongoing study with a larger cohort of all COVID-19 patients that continue to be admitted to our center to investigate underlying etiological mechanisms of encephalopathy, including long-term follow up of these patients.