Two-year follow-up of brain structural changes in patients who recovered from COVID-19: A prospective study.

The long-term effects of COVID-19 on brain structure remain unclear. A prospective study was conducted to explore the changes in brain structure in COVID-19 survivors at one and two years after discharge (COVID-19one, COVID-19two). The difference in gray matter volume (GMV) was analyzed using the voxel-based morphometry method, and correlation analyses were conducted. The dynamic changes in clinical sequelae varied. The GMVs in the cerebellum and vermis were reduced in COVID-19one and COVID-19two, positively correlated with lymphocyte count, and negatively correlated with neutrophil count, neutrophil/lymphocyte ratio (COVID-19one), and systemic immune-inflammation index (COVID-19two). The decreased GMVs in the left middle frontal gyrus, inferior frontal gyrus of the operculum, right middle temporal gyrus, and inferior temporal gyrus returned to normal in COVID-19two. The decreased GMV in the left frontal lobe was negatively correlated with the Athens Insomnia Scale (AIS). The GMV in the left temporal lobe was aggravated in COVID-19two and positively correlated with C-reactive protein. In conclusion, GMV recovery coexisted with injury, which was associated with AIS and inflammatory factors. This may shed some light on the dynamic changes in brain structure and the possible predictors that may be related to GMV changes in COVID-19two.

Mental health status among non-medical college students returning to school during the COVID-19 pandemic in Zhanjiang city: A cross-sectional study.

The coronavirus disease-2019 (COVID-19) pandemic has brought huge and continuous damage to mental health. The mental health of non-medical college students after returning to school remains largely unknown and the influencing factors were awaited to be deciphered. This cross-sectional study was launched among 1,083 non-medical students in Zhanjiang city by means of online survey (WeChat App) from August 1st, 2022 to August 7th, 2022. Knowledge about COVID-19 and attitude toward COVID-19 were assessed by using 7-items and 5-items questionnaires, respectively. Sleep quality, anxiety and depression symptoms were evaluated by Pittsburgh sleep quality index (PSQI), Hamilton depression rating scale-17 (HDRS-17) and self-rating anxiety scale (SAS), respectively. The results showed that more than half of the participants were knowledgeable about COVID-19. The majority of the participants held positive attitude toward COVID-19. The data demonstrated that 6.8% students had poor sleep quality, and 1.86, 0.37 and 0.37% students had mild, moderate and severe anxiety, respectively. About 26.7, 4.7 and 1.7% students had minimal, mild-moderate and severe depression. Female students showed higher proportions of anxiety (p = 0.02) and depression (p < 0.0001) than male students. Students with monthly household income below 3,000 RMB were more vulnerable to anxiety (p = 0.017) and depression (p = 0.004). Correlation analysis and Multivariate logistic regression analysis results showed that lower grade was positively related with anxiety and depression. Female students, income lower than 3,000 RMB/month, poor knowledge about COVID-19 and negative attitude toward COVID-19 were associated with insomnia, anxiety and depression. This study indicated that during the COVID-19 pandemic, a majority of non-medical students returning to school remained good sleep quality and a small number of students suffered from depression and anxiety. To our knowledge, this is a novel study revealing the mental health of non-medical college students concerning COVID-19 in Zhanjiang.

Dynamic white matter changes in recovered COVID-19 patients: a two-year follow-up study.

Background and purpose: Long COVID with regard to the neurological system deserves more attention, as a surge of treated patients are being discharged from the hospital. As the dynamic changes in white matter after two years remain unknown, this characteristic was the focus of this study. Methods: We investigated 17 recovered COVID-19 patients at two years after discharge. Diffusion tensor imaging, neurite orientation dispersion and density imaging were performed to identify white matter integrity and changes from one to two years after discharge. Data for 13 revisited healthy controls were collected as a reference. Subscales of the Wechsler Intelligence scale were used to assess cognitive function. Repeated-measures ANOVA was used to detect longitudinal changes in 17 recovered COVID-19 patients and 13 healthy controls after one-year follow-up. Correlations between diffusion metrics, cognitive function, and other clinical characteristics (i.e., inflammatory factors) were also analyzed. Results: Longitudinal analysis showed the recovery trends of large-scale brain regions, with small-scale brain region deterioration from one year to two years after SARS-CoV-2 infection. However, persistent white matter abnormalities were noted at two years after discharge. Longitudinal changes of cognitive function showed no group difference. But cross-sectional cognitive difference between recovered COVID-19 patients and revisited HCs was detected. Inflammation levels in the acute stage correlated positively with white matter abnormalities and negatively with cognitive function. Moreover, the more abnormal the white matter was at two years, the greater was the cognitive deficit present. Conclusion: Recovered COVID-19 patients showed longitudinal recovery trends of white matter. But also had persistent white matter abnormalities at two years after discharge. Inflammation levels in the acute stage may be considered predictors of cognition and white matter integrity, and the white matter microstructure acts as a biomarker of cognitive function in recovered COVID-19 patients. These findings provide an objective basis for early clinical intervention.

Trends and hot topics in radiology, nuclear medicine and medical imaging from 2011-2021: a bibliometric analysis of highly cited papers.

PURPOSE: To spotlight the trends and hot topics looming from the highly cited papers in the subject category of Radiology, Nuclear Medicine & Medical Imaging with bibliometric analysis. MATERIALS AND METHODS: Based on the Essential Science Indicators, this study employed a bibliometric method to examine the highly cited papers in the subject category of Radiology, Nuclear Medicine & Medical Imaging in Web of Science (WoS) Categories, both quantitatively and qualitatively. In total, 1325 highly cited papers were retrieved and assessed spanning from the years of 2011 to 2021. In particular, the bibliometric information of the highly cited papers based on WoS database such as the main publication venues, the most productive countries, and the top cited publications was presented. An Abstract corpus was built to help identify the most frequently explored topics. VoSviewer was used to visualize the co-occurrence networks of author keywords. RESULTS: The top three active journals are Neuroimage, Radiology and IEEE T Med Imaging. The United States, Germany and England have the most influential publications. The top cited publications unrelated to COVID-19 can be grouped in three categories: recommendations or guidelines, processing software, and analysis methods. The top cited publications on COVID-19 are dominantly in China. The most frequently explored topics based on the Abstract corpus and the author keywords with the great link strengths overlap to a great extent. Specifically, phrases such as magnetic resonance imaging, deep learning, prostate cancer, chest CT, computed tomography, CT images, coronavirus disease, convolutional neural network(s) are among the most frequently mentioned. CONCLUSION: The bibliometric analysis of the highly cited papers provided the most updated trends and hot topics which may provide insights and research directions for medical researchers and healthcare practitioners in the future.

Clinical Characteristics and Outcomes of Childbearing-Age Women With COVID-19 in Wuhan: Retrospective, Single-Center Study.

BACKGROUND: Since December 2019, an outbreak of the coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread rapidly in Wuhan and worldwide. However, previous studies on pregnant patients were limited. OBJECTIVE: The aim of this study is to evaluate the clinical characteristics and outcomes of pregnant and nonpregnant women with COVID-19. METHODS: This study retrospectively collected epidemiological, clinical, laboratory, imaging, management, and outcome data of 43 childbearing-age women patients (including 17 pregnant and 26 nonpregnant patients) who presented with laboratory-confirmed COVID-19 in Tongji Hospital, Wuhan, China from January 19 to March 2, 2020. Clinical outcomes were followed up to March 28, 2020. RESULTS: Of the 43 childbearing-age women in this study, none developed a severe adverse illness or died. The median ages of pregnant and nonpregnant women were 33.0 and 33.5 years, respectively. Pregnant women had a markedly higher proportion of history exposure to hospitals within 2 weeks before onset compared to nonpregnant women (9/17, 53% vs 5/26, 19%, P=.02) and a lower proportion of other family members affected (4/17, 24% vs 19/26, 73%, P=.004). Fever (8/17, 47% vs 18/26, 69%) and cough (9/17, 53% vs 12/26, 46%) were common onsets of symptoms for the two groups. Abdominal pain (n=4, 24%), vaginal bleeding (n=1, 6%), reduced fetal movement (n=1, 6%), and increased fetal movement (n=2, 13%) were observed at onset in the 17 pregnant patients. Higher neutrophil and lower lymphocyte percent were observed in the pregnant group compared to the nonpregnant group (79% vs 56%, P<.001; 15% vs 33%, P<.001, respectively). In both groups, we observed an elevated concentration of high-sensitivity C-reactive protein, erythrocyte sedimentation rate, aminotransferase, and lactate dehydrogenase. Concentrations of alkaline phosphatase and D-dimer in the pregnant group were significantly higher than those of the nonpregnant group (119.0 vs 48.0 U/L, P<.001; 2.1 vs 0.3µg/mL, P<.001, respectively). Both pregnant (4/10, 40%) and nonpregnant (8/15, 53%) women tested positive for influenza A virus. A majority of pregnant and nonpregnant groups received antiviral (13/17, 76% vs 25/26, 96%) and antibiotic (13/17, 76% vs 23/26, 88%) therapy. Additionally, both pregnant (2/11, 18%) and nonpregnant (2/19, 11%) recovered women redetected positive for SARS-CoV-2 after discharge. CONCLUSIONS: The epidemiology and clinical and laboratory features of pregnant women with COVID-19 were diverse and atypical, which increased the difficulty of diagnosis. Most pregnant women with COVID-19 were mild and moderate, and rarely developed severe pneumonia or severe adverse outcomes.