Neuro-ophthalmic manifestations of coronavirus disease 19.

PURPOSE OF REVIEW: To provide a summary of the neuro-ophthalmic manifestations of coronavirus disease 19 (COVID-19), documented in the literature thus far. RECENT FINDINGS: A small but growing literature documents cases of new onset neuro-ophthalmic disease, in the setting of COVID-19 infection. Patients with COVID-19 have experienced acute onset vision loss, optic neuritis, cranial neuropathies, and Miller Fisher syndrome. In addition, COVID-19 increases the risk of cerebrovascular diseases that can impact the visual system. SUMMARY: The literature on COVID-19 continues to evolve. Although COVID-19 primarily impacts the respiratory system, there are several reports of new onset neuro-ophthalmic conditions in COVID-infected patients. When patients present with new onset neuro-ophthalmic issues, COVID-19 should be kept on the differential. Testing for COVID-19 should be considered, especially when fever or respiratory symptoms are also present. When screening general patients for COVID-19-associated symptoms, frontline physicians can consider including questions about diplopia, eye pain, pain with extraocular movements, decreased vision, gait issues, and other neurologic symptoms. The presence of these symptoms may increase the overall probability of viral infection, especially when fever or respiratory symptoms are present. More research is needed to establish a causal relationship between COVID-19 and neuro-ophthalmic disease, and better understand pathogenesis.

[The status of ENT health care workers at the forefront of fighting against COVID-19 in Wuhan and some response options].

It is a critical period of fighting against new coronavirus（SARS-CoV-2） disease now，since its outbreak on December 2019 in Wuhan.Even though the front line staffs are thought heroes，the ENT doctors and nurses are also indispensable power in defending the disease.The number of outpatients of ENT is huge.The early stage of SARS-CoV-2 pneumonia（COVID-19） may present pharyngalgia or cough without fever.Thus，the ENT doctors have high risks of being consulted by early stage COVID-19 patients.This paper means to talk about the contributions of ENT doctors and nurses in defending against SARS-CoV-2 virus，as well as the mental status of them.

Meta-analysis of diagnostic performance of serological tests for SARS-CoV-2 antibodies up to 25 April 2020 and public health implications.

We reviewed the diagnostic accuracy of SARS-CoV-2 serological tests. Random-effects models yielded a summary sensitivity of 82% for IgM, and 85% for IgG and total antibodies. For specificity, the pooled estimate were 98% for IgM and 99% for IgG and total antibodies. In populations with ≤ 5% of seroconverted individuals, unless the assays have perfect (i.e. 100%) specificity, the positive predictive value would be ≤ 88%. Serological tests should be used for prevalence surveys only in hard-hit areas.

Covid-19 (Sars-Cov-2 Infection) Information for Patients with Predialytic Chronic Kidney Disease.

Patients with Chronic Kidney Disease are among those individuals at increased risk for developing more serious forms of Covid-19. This increased risk starts in the pre-dialysis phase of the disease. Providing useful information for these patients, in language that facilitates the understanding of the disease, can help nephrologists and other healthcare professionals to establish a more effective communication with these patients and help minimize contagion and the risks of serious illness in this population.

NEUROPROTECTIVE AND ANTIOXIDANT POTENTIAL OF MONTELUKAST-ACETYLCYSTEINE COMBINATION THERAPY FOR BRAIN PROTECTION IN PATIENTS WITH COVID-19 INDUCED PNEUMONIA.

Direct critical attack of the coronavirus on the alveoli and the excessive release of a large number of cytokines (IL-6, IL-1, TNF-α, etc.) provides suitable conditions for the further development of acute respiratory distress syndrome (ARDS) and severe acute respiratory failure. Serious decrease in blood oxygenation often lead to the deterioration of macro- and microcirculation, irreversible brain damage and hence, persistent neurological and mental disorders despite background intensive therapy and adequate respiratory support. Therefore, the aim of our open prospective observational study was to investigate the neuroprotective and antioxidant effectiveness of montelukast-acetylcysteine combination therapy for brain protection in patients with COVID-19 viral pneumonia. A study was performed for five hundred seventy-eight (n=578) outpatients who were tested positive for novel coronavirus (SARS-CoV-2) by nasopharyngeal swap. The median age of patients was 62±17.45 years. In addition to clinical features and RT-PCR results, chest CT and chest X-ray (CXR) with high sensitivity were also very helpful for the early identification of viral pneumonia and COVID-19 disease assessment. Considering the severity of Covid-19 pneumonia and the level of arterial oxygen saturation (transcutaneous hemoglobin oxygen saturation) on room air, all patients were divided into three major groups. Group 1 (n=288) consisted of patients with a mild shift in oxygen saturation (SpO2 ≥ 95%) and well-defined pulmonary lesions (within 1-2 segments) without concomitant diseases; the second group (Group 2, n=250) included patients with clinical manifestations of moderate severity associated with a current saturation of 90-95% (SpO2) and small pulmonary lesions on chest X-ray in the presence of concomitant diseases: arterial hypertension (stage III) or CHF (FC/NYHA-2), coronary heart disease or type 2 diabetes, cancer, tuberculosis, etc. Most of the patients in third group (Group 3, n=48), during imaging studies, showed bilateral lung affection with low and peripheral distribution (with both - either ground glass opacities or multiple pulmonary nodules) and cardiomegaly. The respiratory failure of stage II-III (current oxygen saturation SpO2 75-90%), high respiratory rate (≥25 per minute), hemodynamic impairment (BP≤100/60 mm Hg. Art., heart rate ≥125/min) were the most common objective clinical findings seen in this subset of patients. Laboratory changes included leukopenia less than 4.0x109/L or leukocytosis (≥10.0X109/L). Background respiratory support with low-flow oxygen therapy and combined pharmacotherapy, where, along with montelukast and acetylcysteine, patients were prescribed a cephalosporin, a fluoroquinolone, an antifungal drug, a histamine blocker, an antiplatelet agent, a complex of B vitamins, led to a significant improvement in symptoms and laboratory parameters during the course of the disease. The mean values of the blood biomarkers (CRP - 21.46±4.43 mg/l, LDH - 410.71±40.63 U/l, procalcitonin - 1.08±0.31 ng/ml, and ferritin - 270.43±27.23 ng/ml) return to normal by the 20th day after the fever subsides. Laboratory parameters before and after treatment course showed statistically significant differences between variables (p<0.05). No patient in Group 3 received JAK inhibitors (tofacitinib and baricitinib), IL-6 (olokizumab), IL-17A (netakimab) and glucocorticosteroids, however, recovery rates were completely good. Assessment of the patient's neurological status (based on the NIHSS scores) revealed no signs of neurological changes. Thus, based on the data given, it can be concluded that the high efficacy of the acetylcysteine/montelukast combination (as neuroprotectors) in pneumonia caused by COVID-19 is due to the effect of drugs on key mechanisms of pathogenesis: reduction of oxidative stress as drugs (combination) ensuring the free radical scavenging; stimulation of glutathione synthesis; suppression of cytokine storm; reduction of bronchospasm, mucus secretion and airway edema; lowering of BBB permeability and the ability to improve cerebral microcirculatory perfusion in the presence of antiplatelet agents. In conclusion, the combination of montelukast and acetylcysteine may provide an effective, safe, multicomponent approach to the prevention of hypoxic brain injury in patients with COVID-19 pneumonia.

The role of triage in the prevention and control of COVID-19.

OBJECTIVE: To prevent and control public health emergencies, we set up a prescreening and triage workflow and analyzed the effects on coronavirus disease 2019 (COVID-19). METHODS: In accordance with the requirements of the level 1 emergency response of public health emergencies in Shaanxi Province, China, a triage process for COVID-19 was established to guide patients through a 4-level triage process during their hospital visits. The diagnosis of COVID-19 was based on positive COVID-19 nucleic acid testing according to the unified triage standards of the Guidelines for the Diagnosis and Treatment of Novel Coronavirus Pneumonia (Trial version 4),4 issued by the National Health Commission of the People's Republic of China. RESULTS: The screened rate of suspected COVID-19 was 1.63% (4 of 246) in the general fever outpatient clinic and 8.28% (13 of 157) in the COVID-19 outpatient clinic, and they showed a significant difference (P = .00). CONCLUSIONS: The triage procedure effectively screened the patients and identified the high-risk population.

Adaptive Feature Selection Guided Deep Forest for COVID-19 Classification With Chest CT.

Chest computed tomography (CT) becomes an effective tool to assist the diagnosis of coronavirus disease-19 (COVID-19). Due to the outbreak of COVID-19 worldwide, using the computed-aided diagnosis technique for COVID-19 classification based on CT images could largely alleviate the burden of clinicians. In this paper, we propose an Adaptive Feature Selection guided Deep Forest (AFS-DF) for COVID-19 classification based on chest CT images. Specifically, we first extract location-specific features from CT images. Then, in order to capture the high-level representation of these features with the relatively small-scale data, we leverage a deep forest model to learn high-level representation of the features. Moreover, we propose a feature selection method based on the trained deep forest model to reduce the redundancy of features, where the feature selection could be adaptively incorporated with the COVID-19 classification model. We evaluated our proposed AFS-DF on COVID-19 dataset with 1495 patients of COVID-19 and 1027 patients of community acquired pneumonia (CAP). The accuracy (ACC), sensitivity (SEN), specificity (SPE), AUC, precision and F1-score achieved by our method are 91.79%, 93.05%, 89.95%, 96.35%, 93.10% and 93.07%, respectively. Experimental results on the COVID-19 dataset suggest that the proposed AFS-DF achieves superior performance in COVID-19 vs. CAP classification, compared with 4 widely used machine learning methods.