Causal relationships between COVID-19 and osteoporosis: a two-sample Mendelian randomization study in European population.

Introduction: The causal relationship between Coronavirus disease 2019 (COVID-19) and osteoporosis (OP) remains uncertain. We aimed to assess the effect of COVID-19 severity (severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, COVID-19 hospitalization, and severe COVID-19) on OP by a two-sample Mendelian randomization (MR) study. Methods: We conducted a two-sample MR analysis using publicly available genome-wide association study (GWAS) data. Inverse variance weighting (IVW) was used as the main analysis method. Four complementary methods were used for our MR analysis, which included the MR-Egger regression method, the weighted median method, the simple mode method, and the weighted mode method. We utilized the MR-Egger intercept test and MR pleiotropy residual sum and outlier (MR-PRESSO) global test to identify the presence of horizontal pleiotropy. Cochran's Q statistics were employed to assess the existence of instrument heterogeneity. We conducted a sensitivity analysis using the leave-one-out method. Results: The primary results of IVW showed that COVID-19 severity was not statistically related to OP (SARS-CoV-2 infection: OR (95% CI) = 0.998 (0.995 ~ 1.001), p = 0.201403; COVID-19 hospitalization: OR (95% CI) =1.001 (0.999 ~ 1.003), p = 0.504735; severe COVID-19: OR (95% CI) = 1.000 (0.998 ~ 1.001), p = 0.965383). In addition, the MR-Egger regression, weighted median, simple mode and weighted mode methods showed consistent results. The results were robust under all sensitivity analyses. Conclusion: The results of the MR analysis provide preliminary evidence that a genetic causal link between the severity of COVID-19 and OP may be absent.

Both underweight and obesity are associated with an increased risk of corona virus disease 2019(COVID-19) severity (preprint)

Background: As COVID-19 evolved into a global pandemic. Increasing numbers of reports have linked obesity to more severe COVID-19 illness and death (1-3). However, almost all the studies focused on the proportion of people entering the ICU or mortality. Is obesity also associated with severity of pneumonia in common pneumonia patients? How about underweight patients? The answer is lack. So, our research below will answer the question. Methods: We collected and analyzed epidemiological, demographic, clinical, and laboratory data from 193 confirmed cases of COVID-19 at Union Hospital, Tongji Medical College, Huazhong University of Science and Technology in Wuhan, China, between January 1, 2020, and March 13, 2020. They were followed up until April 15, 2020. Results: Among these patients, 5.70% were underweight, 58.03% were normal weight, 27.98% were overweight and 8.29% were obese. underweight patients were more likely to have headache (P=0.029) Obese patients were more likely to experience a decline in lymphocyte counts(P=0.042), an increase in CRP(P=0.020), bilateral multiple mottling and groundglass opacity (P=0.008). Besides, the proportion of patients receiving human immunoglobulin+systematic corticosteroids treatment is the highest among the obese group compared with other BMI groups. After adjusting for potential confounders, Underweight patients had 6.483-fold higher(P=0.012)，and obesity patients showed 5.965-fold higher odds developing acute lung injury(ALI) than normal weight patients(P=0.022). Underweight patients were 3.255 times more likely than normal-weight patients to develop secondary infections (P=0.041). Conclusions: Our study shows that in patients with common pneumonia, both underweight and obese people tend to develop ALI compared with normal weight patients.

Both Underweight and Obesity Are Associated With an Increased Risk of Coronavirus Disease 2019 (COVID-19) Severity.

Introduction: As coronavirus Disease 2019 (COVID-19) has evolved into a global pandemic, increasing numbers of reports have linked obesity to more severe COVID-19 illness and death. However, almost all the studies focused on an increased risk of mortality or intensive care unit (ICU) admission among hospitalized obese patients with COVID-19. Is obesity also associated with the incidence of acute lung injury (ALI) in the patients with COVID-19? How about underweight patients? The answer is lacking. Therefore, our following research will answer the above two questions. Methods: We collected and analyzed epidemiologic, demographic, clinical, and laboratory data from 193 confirmed cases of COVID-19 at Union Hospital, Tongji Medical College, Huazhong University of Science and Technology in Wuhan, China, between January 1, 2020, and March 13, 2020. They were followed up until April 15, 2020. Underweight was defined by body mass index (BMI) lower than 18.5 kg/m2, normal weight by 18.5-23.9 kg/m2, overweight by 24.0-27.9 kg/m2, and obesity as ≥28 kg/m2. Results: Among these patients, 5.70% were underweight, 58.03% were normal weight, 27.98% were overweight, and 8.29% were obese. Underweight patients were more likely to have a headache (P = 0.029). Obese patients were more likely than other groups to experience a decline in lymphocyte counts (P = 0.038), an increase in C-reactive protein (CRP; P = 0.023), bilateral multiple mottling, and ground glass opacity in the lungs (P = 0.007). Besides, the proportion of patients receiving human immunoglobulin + systematic corticosteroids treatment is the highest among the obese group compared with other BMI groups. After adjusting for potential confounders, underweight patients had a 6.483-fold higher (P = 0.012), and obese patients showed a 5.965-fold higher odds for developing ALI than normal-weight patients (P = 0.022). In addition, underweight patients were 3.255 times more likely than normal-weight patients to develop secondary infections (P = 0.041). Conclusions: Our study showed that both underweight and obese patients with COVID-19 tend to develop ALI compared with normal-weight patients. Underweight patients were more likely to develop a secondary infection than other patients.

Public Interest in Cosmetic Surgical and Minimally Invasive Plastic Procedures During the COVID-19 Pandemic: Infodemiology Study of Twitter Data.

BACKGROUND: The unprecedented COVID-19 pandemic has brought drastic changes to the field of plastic surgery. It is critical for stakeholders in this field to identify the changes in public interest in plastic procedures to be adequately prepared to meet the challenges of the pandemic. OBJECTIVE: The aim of this study is to examine tweets related to the public interest in plastic procedures during the COVID-19 pandemic and to help stakeholders in the field of plastic surgery adjust their practices and sustain their operations during the current difficult situation of the pandemic. METHODS: Using a web crawler, 73,963 publicly accessible tweets about the most common cosmetic surgical and minimally invasive plastic procedures were collected. The tweets were grouped into three phases, and the tweeting frequencies and Google Trends indices were examined. Tweeting frequency, sentiment, and word frequency analyses were performed with Python modules. RESULTS: Tweeting frequency increased by 24.0% in phase 2 and decreased by 9.1% in phase 3. Tweets about breast augmentation, liposuction, and abdominoplasty ("tummy tuck") procedures consecutively increased over the three phases of the pandemic. Interest in Botox and chemical peel procedures revived first when the lockdown was lifted. The COVID-19 pandemic was associated with a negative impact on public sentiment about plastic procedures. The word frequency pattern significantly changed after phase 1 and then remained relatively stable. CONCLUSIONS: According to Twitter data, the public maintained their interest in plastic procedures during the COVID-19 pandemic. Stakeholders should consider refocusing on breast augmentation, liposuction, and abdominoplasty procedures during the current phase of the pandemic. In the case of a second wave of COVID-19, stakeholders should prepare for a temporary surge of Botox and chemical peel procedures.

CT changes of severe coronavirus disease 2019 based on prognosis.

This study aimed to determine the characteristics of CT changes in patients with severe coronavirus disease 2019 (COVID-19) based on prognosis. Serial CT scans in 47 patients with severe COVID-19 were reviewed. The patterns, distribution and CT score of lung abnormalities were assessed. Scans were classified according to duration in weeks after onset of symptoms. These CT abnormalities were compared between discharged and dead patients. Twenty-six patients were discharged, whereas 21 passed away. Discharged patients were characterized by a rapid rise in CT score in the first 2 weeks followed by a slow decline, presence of reticular and mixed patterns from the second week, and prevalence of subpleural distribution of opacities in all weeks. In contrast, dead patients were characterized by a progressive rise in CT score, persistence of ground-glass opacity and consolidation patterns in all weeks, and prevalence of diffuse distribution from the second week. CT scores of death group were significantly higher than those of discharge group (P < 0.05). The CT changes differed between the discharged and dead patients. An understanding of these differences can be of clinical significance in the assessment of the prognosis of severe COVID-19 patients.

Influence of the pandemic dissemination of COVID-19 on facial rejuvenation: A survey of Twitter.

BACKGROUND: With the pandemic dissemination of COVID-19, attitude and sentiment surrounding facial rejuvenation have evolved rapidly. AIMS: The purpose of this study was to understanding the impact of pandemic on the attitude of people toward facial skin rejuvenation. METHODS: Twitter data related to facial rejuvenation were collected from January 1, 2020, to April 30, 2020. Sentiment analysis, frequency analysis, and word cloud were performed to analyze the data. Statistical analysis included two-tailed t tests and chi-square tests. RESULTS: In the post-declaration, the number of tweets about facial rejuvenation increased significantly, and the search volume in Google Trends decreased. Negative public emotions increased, but positive emotions still dominate. The words frequency of "discounts" and "purchase" decreased. The dominant words in word cloud were "Botox," "facelift," "hyaluronic," and "skin." CONCLUSION: The public has a positive attitude toward facial rejuvenation during the pandemic. In particular, minimally invasive procedures dominate the mainstream, such as "Botox," "Hyaluronic acid," and "PRP." The practitioners could understand the change of the public interest in facial rejuvenation in time and decide what to focus on.

Development and Validation of a Nomogram for Assessing Survival in Patients With COVID-19 Pneumonia.

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) has spread worldwide and continues to threaten peoples' health as well as put pressure on the accessibility of medical systems. Early prediction of survival of hospitalized patients will help in the clinical management of COVID-19, but a prediction model that is reliable and valid is still lacking. METHODS: We retrospectively enrolled 628 confirmed cases of COVID-19 using positive RT-PCR tests for SARS-CoV-2 in Tongji Hospital, Wuhan, China. These patients were randomly grouped into a training (60%) and a validation (40%) cohort. In the training cohort, LASSO regression analysis and multivariate Cox regression analysis were utilized to identify prognostic factors for in-hospital survival of patients with COVID-19. A nomogram based on the 3 variables was built for clinical use. AUCs, concordance indexes (C-index), and calibration curves were used to evaluate the efficiency of the nomogram in both training and validation cohorts. RESULTS: Hypertension, higher neutrophil-to-lymphocyte ratio, and increased NT-proBNP values were found to be significantly associated with poorer prognosis in hospitalized patients with COVID-19. The 3 predictors were further used to build a prediction nomogram. The C-indexes of the nomogram in the training and validation cohorts were 0.901 and 0.892, respectively. The AUC in the training cohort was 0.922 for 14-day and 0.919 for 21-day probability of in-hospital survival, while in the validation cohort this was 0.922 and 0.881, respectively. Moreover, the calibration curve for 14- and 21-day survival also showed high coherence between the predicted and actual probability of survival. CONCLUSIONS: We built a predictive model and constructed a nomogram for predicting in-hospital survival of patients with COVID-19. This model has good performance and might be utilized clinically in management of COVID-19.

Longitudinal characteristics of lymphocyte responses and cytokine profiles in the peripheral blood of SARS-CoV-2 infected patients.

BACKGROUND: The dynamic changes of lymphocyte subsets and cytokines profiles of patients with novel coronavirus disease (COVID-19) and their correlation with the disease severity remain unclear. METHODS: Peripheral blood samples were longitudinally collected from 40 confirmed COVID-19 patients and examined for lymphocyte subsets by flow cytometry and cytokine profiles by specific immunoassays. FINDINGS: Of the 40 COVID-19 patients enrolled, 13 severe cases showed significant and sustained decreases in lymphocyte counts [0·6 (0·6-0·8)] but increases in neutrophil counts [4·7 (3·6-5·8)] than 27 mild cases [1.1 (0·8-1·4); 2·0 (1·5-2·9)]. Further analysis demonstrated significant decreases in the counts of T cells, especially CD8+ T cells, as well as increases in IL-6, IL-10, IL-2 and IFN-γ levels in the peripheral blood in the severe cases compared to those in the mild cases. T cell counts and cytokine levels in severe COVID-19 patients who survived the disease gradually recovered at later time points to levels that were comparable to those of the mild cases. Moreover, the neutrophil-to-lymphocyte ratio (NLR) (AUC=0·93) and neutrophil-to-CD8+ T cell ratio (N8R) (AUC =0·94) were identified as powerful prognostic factors affecting the prognosis for severe COVID-19. INTERPRETATION: The degree of lymphopenia and a proinflammatory cytokine storm is higher in severe COVID-19 patients than in mild cases, and is associated with the disease severity. N8R and NLR may serve as a useful prognostic factor for early identification of severe COVID-19 cases. FUNDING: The National Natural Science Foundation of China, the National Science and Technology Major Project, the Health Commission of Hubei Province, Huazhong University of Science and Technology, and the Medical Faculty of the University of Duisburg-Essen and Stiftung Universitaetsmedizin, Hospital Essen, Germany.