Clinical analysis of secondary glaucoma in Central China.

To describe the epidemiology, clinical and social characteristics, management, and outcomes of patients with secondary glaucoma in Central China, a total of 1,129 cases (1,158 eyes) among 710 males (62.89%) and 419 females (37.11%) were analyzed. The mean age was 53.75 ± 17.11 years. The New Rural Cooperative Medical System (NCMS) played the most important role in reimbursement (60.32%) for secondary glaucoma-related medical expenses. The predominant occupation was "farmer" (53.41%). Neovascularization and trauma were the leading causes of secondary glaucoma. Cases of trauma-induced glaucoma decreased substantially during the coronavirus disease 2019 (COVID-19) pandemic. An education level of senior high school or above was uncommon. Ahmed glaucoma valve implantation was the most commonly performed surgery. At the final follow-up, the overall intraocular pressure (IOP) in patients with vascular disease- and trauma-related secondary glaucoma was 19.53 ± 10.20 mmHg, 20.26 ± 11.75 mmHg, and 16.90 ± 6.72 mmHg, while the mean visual acuity (VA) was 0.33 ± 0.32, 0.34 ± 0.36, and 0.43 ± 0.36. In 814 (70.29%) eyes, the VA was < 0.01. Effective preventive measures for at-risk populations, increased NCMS coverage and the promotion of higher education are necessary. These findings will help ophthalmologists detect secondary glaucoma early and manage it in a timely manner.

Evaluation on quality of internet-based reporting of COVID-19 in Ningxia, 2020-2021

Objective: To find out the existing problems and provide reference for further improving the quality of report information by analyzing the report cards of COVID-19 and the positive report cards of primary screening reported in Ningxia. Methods All COVID-19 case cards from 2020 to 2021 and initial screening positive cards were derived from the Chinese Information System for Disease Control and Prevention according to final review date. The timeliness of case reporting, timeliness of case review, completeness and accuracy of the case cards were analyzed. Results In Ningxia, the first case of COVID-19 was reported on January 20, 2020, and as of December 31, 2021, 122 confirmed cases and 4 symptomatic infected cases were reported. In 2021, the timely reporting rate of COVID-19 was 98.00%, which increased by 8.24% compared with 2020 (90.54%). Compared with 2020, the average time limit for diagnosis to reporting of COVID-19 in 2021 was shortened by 83.12%;in 2021, the timely review rate of COVID-19 was 100.00%, which increased by 13.84% compared with 2020 (87.84%). Compared with 2020, the time from reporting to final review was shortened by 98.91%. In 2021, the timely rate of positive reports in COVID-19 in Ningxia was 90.00%, among which the timely rate of reports by county (district) nucleic acid detection institutions was the highest (92.31%), followed by municipal (91.67%) and autonomous region (81.82%). Conclusions At the beginning of the epidemic in 2020, the timeliness of COVID-19 in Ningxia was poor, and through the implementation of measures such as technical training, supervision and inspection to continuously optimize the staffing of medical institutions and disease control institutions, the timeliness of reporting COVID-19 in Ningxia in 2021 was substantially improved, but there were still some weak links. In the future work, technical guidance and training should be carried out for weak links, and efforts should be made to improve the quality of reports.

Early physical therapy for a patient affected by coronavirus disease 2019 (COVID-19) on awake veno-venous extracorporeal membrane oxygenation: a case report.

Since December 8, 2019, an acute respiratory illness has spread rapidly in China, causing 3,097 people to die as of March 7, and it has become a global crisis. The common symptoms are fever, fatigue, dry cough, myalgia, and dyspnea. This case report presents a 36-year-old male who was diagnosed with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infected pneumonia on February 2, 2020. This patient received veno-venous extracorporeal membrane oxygenation (V-V ECMO) last for 10 days as salvage treatment as his condition became critical in the acute setting. As soon as his status became stable, he began to receive an early rehabilitation program performed by our rehabilitation team. After 43 days of treatment under the efforts of our teamwork, the patient was able to walk 800 meters, and then was discharged the next day. To our knowledge, this is the first report of early physical therapy for a patient with coronavirus disease 2019 (COVID-19) who was receiving extracorporeal membrane oxygenation (ECMO) whilst awake. This case indicates that early physical rehabilitation is safe and feasible and resulted in an expedited recovery using ECMO whilst awake. The goals for physiotherapy management include avoiding atelectasis, airway clearance, weaning and increasing the functional level. This report may contribute to the current literature on early physical therapy rehabilitation programs for awake ECMO patients.

Ruxolitinib attenuates secondary injury after traumatic spinal cord injury.

Excessive inflammation post-traumatic spinal cord injury (SCI) induces microglial activation, which leads to prolonged neurological dysfunction. However, the mechanism underlying microglial activation-induced neuroinflammation remains poorly understood. Ruxolitinib (RUX), a selective inhibitor of JAK1/2, was recently reported to inhibit inflammatory storms caused by SARS-CoV-2 in the lung. However, its role in disrupting inflammation post-SCI has not been confirmed. In this study, microglia were treated with RUX for 24 hours and then activated with interferon-γ for 6 hours. The results showed that interferon-γ-induced phosphorylation of JAK and STAT in microglia was inhibited, and the mRNA expression levels of pro-inflammatory cytokines tumor necrosis factor-α, interleukin-1ß, interleukin-6, and cell proliferation marker Ki67 were reduced. In further in vivo experiments, a mouse model of spinal cord injury was treated intragastrically with RUX for 3 successive days, and the findings suggest that RUX can inhibit microglial proliferation by inhibiting the interferon-γ/JAK/STAT pathway. Moreover, microglia treated with RUX centripetally migrated toward injured foci, remaining limited and compacted within the glial scar, which resulted in axon preservation and less demyelination. Moreover, the protein expression levels of tumor necrosis factor-α, interleukin-1ß, and interleukin-6 were reduced. The neuromotor function of SCI mice also recovered. These findings suggest that RUX can inhibit neuroinflammation through inhibiting the interferon-γ/JAK/STAT pathway, thereby reducing secondary injury after SCI and producing neuroprotective effects.

CT Quantification of COVID-19 Pneumonia at Admission Can Predict Progression to Critical Illness: A Retrospective Multicenter Cohort Study.

Objective: Early identification of coronavirus disease 2019 (COVID-19) patients with worse outcomes may benefit clinical management of patients. We aimed to quantify pneumonia findings on CT at admission to predict progression to critical illness in COVID-19 patients. Methods: This retrospective study included laboratory-confirmed adult patients with COVID-19. All patients underwent a thin-section chest computed tomography (CT) scans showing evidence of pneumonia. CT images with severe moving artifacts were excluded from analysis. Patients' clinical and laboratory data were collected from medical records. Three quantitative CT features of pneumonia lesions were automatically calculated using a care.ai Intelligent Multi-disciplinary Imaging Diagnosis Platform Intelligent Evaluation System of Chest CT for COVID-19, denoting the percentage of pneumonia volume (PPV), ground-glass opacity volume (PGV), and consolidation volume (PCV). According to Chinese COVID-19 guidelines (trial version 7), patients were divided into noncritical and critical groups. Critical illness was defined as a composite of admission to the intensive care unit, respiratory failure requiring mechanical ventilation, shock, or death. The performance of PPV, PGV, and PCV in discrimination of critical illness was assessed. The correlations between PPV and laboratory variables were assessed by Pearson correlation analysis. Results: A total of 140 patients were included, with mean age of 58.6 years, and 85 (60.7%) were male. Thirty-two (22.9%) patients were critical. Using a cutoff value of 22.6%, the PPV had the highest performance in predicting critical illness, with an area under the curve of 0.868, sensitivity of 81.3%, and specificity of 80.6%. The PPV had moderately positive correlation with neutrophil (%) (r = 0.535, p < 0.001), erythrocyte sedimentation rate (r = 0.567, p < 0.001), d-Dimer (r = 0.444, p < 0.001), high-sensitivity C-reactive protein (r = 0.495, p < 0.001), aspartate aminotransferase (r = 0.410, p < 0.001), lactate dehydrogenase (r = 0.644, p < 0.001), and urea nitrogen (r = 0.439, p < 0.001), whereas the PPV had moderately negative correlation with lymphocyte (%) (r = -0.535, p < 0.001). Conclusions: Pneumonia volume quantified on initial CT can non-invasively predict the progression to critical illness in advance, which serve as a prognostic marker of COVID-19.

Hypertension in Patients Hospitalized with COVID-19 in Wuhan, China.

It is unclear whether patients with hypertension are more likely to be infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) than the general population and whether there is a difference in the severity of coronavirus disease (COVID-19) pneumonia in patients who have taken ACEI/ARB drugs compared with those who have not.This observational study included data from all patients with clinically confirmed COVID-19 admitted to Hankou Hospital, Wuhan, China, between January 5 and March 8, 2020. Data were extracted from clinical and laboratory records. Follow-up was cut off on March 8, 2020.A total of 274 patients, 75 with hypertension and 199 without hypertension, were included in the analysis. Compared with patients without hypertension, patients with hypertension were older and were more likely to have preexisting comorbidities, including chronic renal insufficiency, cardiovascular disease, diabetes mellitus, and cerebrovascular disease. Moreover, patients with hypertension tended to have higher positive rate for SARS-CoV-2 PCR detection. Multivariate logistic regression analysis showed that age (P = 0.005) and gender (P = 0.019) were independent risk factors associated with the severity of pneumonia in patients on admission, whereas ACEI/ARB treatment (P = 0.184) was not.Patients with COVID-19 with hypertension were significantly older and were more likely to have underlying comorbidities, including chronic renal insufficiency, cardiovascular disease, diabetes mellitus, and cerebrovascular disease. ACEI/ARB drugs did not influence the severity of pneumonia in patients with SARS-CoV-2. In future studies, a larger sample size and multi-center clinical data would be needed to support these conclusions.

Machine learning models for predicting critical illness risk in hospitalized patients with COVID-19 pneumonia.

BACKGROUND: To develop machine learning classifiers at admission for predicting which patients with coronavirus disease 2019 (COVID-19) who will progress to critical illness. METHODS: A total of 158 patients with laboratory-confirmed COVID-19 admitted to three designated hospitals between December 31, 2019 and March 31, 2020 were retrospectively collected. 27 clinical and laboratory variables of COVID-19 patients were collected from the medical records. A total of 201 quantitative CT features of COVID-19 pneumonia were extracted by using an artificial intelligence software. The critically ill cases were defined according to the COVID-19 guidelines. The least absolute shrinkage and selection operator (LASSO) logistic regression was used to select the predictors of critical illness from clinical and radiological features, respectively. Accordingly, we developed clinical and radiological models using the following machine learning classifiers, including naive bayes (NB), linear regression (LR), random forest (RF), extreme gradient boosting (XGBoost), adaptive boosting (AdaBoost), K-nearest neighbor (KNN), kernel support vector machine (k-SVM), and back propagation neural networks (BPNN). The combined model incorporating the selected clinical and radiological factors was also developed using the eight above-mentioned classifiers. The predictive efficiency of the models is validated using a 5-fold cross-validation method. The performance of the models was compared by the area under the receiver operating characteristic curve (AUC). RESULTS: The mean age of all patients was 58.9±13.9 years and 89 (56.3%) were males. 35 (22.2%) patients deteriorated to critical illness. After LASSO analysis, four clinical features including lymphocyte percentage, lactic dehydrogenase, neutrophil count, and D-dimer and four quantitative CT features were selected. The XGBoost-based clinical model yielded the highest AUC of 0.960 [95% confidence interval (CI): 0.913-1.000)]. The XGBoost-based radiological model achieved an AUC of 0.890 (95% CI: 0.757-1.000). However, the predictive efficacy of XGBoost-based combined model was very close to that of the XGBoost-based clinical model, with an AUC of 0.955 (95% CI: 0.906-1.000). CONCLUSIONS: A XGBoost-based based clinical model on admission might be used as an effective tool to identify patients at high risk of critical illness.

[Acute kidney injury in patients hospitalized with COVID-19 in Wuhan, China: a single-center retrospective observational study].

OBJECTIVE: To assess the predictors and outcomes of acute kidney injury (AKI) among patients with coronavirus disease 2019 (COVID-19). OBJECTIVE: This retrospective observational study was conducted among patients with a confirmed diagnosis of COVID-19 admitted to Hankou Hospital between January, 5 and March 8, 2020. We evaluated the association of AKI with the demographic and biochemical parameters and clinical outcomes of the patients using univariate regression analysis. OBJECTIVE: Atotal of 287 COVID-19 patients, including 55 with AKI and 232 without AKI, were included in the analysis. Compared with the patients without AKI, the patients with AKI were older, predominantly male, and were more likely to have hypoxia and pre-existing hypertension and cerebrovascular diseases. The patients with AKI also had higher levels of white blood cells, D-dimer, aspartate aminotransferase, total bilirubin, creatine kinase, lactate dehydrogenase, procalcitonin, C-reactive protein, a higher prevalence of hyperkalemia, lower lymphocyte counts, and higher chest computed tomographic scores. The incidence of stage 1 AKI was 14.3% and that of stage 2 or 3 AKI was 4.9%. The patients with AKI had much higher mortality rate than those without AKI. OBJECTIVE: AKI is an important complication of COVID-19. An older age, a male gender, multiple pre- existing comorbidities, lymphopenia, increased infection indicators, elevated D-dimer, and impaired heart and liver functions are all potential risk factors ofAKI. COVID- 19 patients with AKI that progresses into stages 2 or 3 AKI have a high mortality rate. Prevention of AKI and monitoring kidney function is critical in the care of COVID-19 patients.

2019 novel coronavirus (COVID-19) pneumonia: CT manifestations and pattern of evolution in 110 patients in Jiangxi, China.

OBJECTIVES: To elucidate the CT manifestations and patterns of evolution in patients with COVID-19 pneumonia. METHODS: This is a retrospective review of CT scans of 110 patients. All 110 patients had initial and second CT scans, 60 of 110 patients had three serial CT scans, and 17 of 60 patients had four serial CT scans. Numerous characteristics of pulmonary and extrapulmonary abnormalities and recognizable patterns of evolution were evaluated. RESULTS: Of the 110 initial CT scans, ground-glass opacities without consolidation (65.4%) were more common than a consolidation or mixed pattern. The most common findings were subpleural involvement (77.2%), multifocal involvement (80.7%), and bilateral involvement (67.3%). Three serial CT scans of 60 patients showed four patterns of CT evolution: type 1 showing relatively high CT scores on initial CT (averaged 4 days after symptom onset), with mild progression and improvement on follow-up CT scans (25%); type 2 with progression of CT findings from initial CT to first follow-up CT (averaged 9 days after symptom onset) with subsequent improvement on second follow-up CT (averaged 13 days after symptom onset, 61.7%); type 3 with no CT changes (5.0%); and type 4 pattern was similar to type 2 but with a more prolonged course and more severe CT findings (8.3%). CONCLUSIONS: Predominant findings at initial CT scans were bilateral multifocal subpleural GGO. The most commonly shown evolution pattern was type 2: progression of disease with increased extent and density of opacities on first follow-up CT followed by improvement on second follow-up CT. KEY POINTS: • Predominant findings at initial CT in patients with COVID-19 infection are bilateral multifocal subpleural ground-glass opacities. • Ill-defined patchy or nodular opacities were most commonly observed on CT scans with the right lower lobe most commonly involved. • The most commonly shown evolution pattern on chest CT was type 2: progression of CT findings from initial CT to first follow-up CT with subsequent improvement on second follow-up CT.