Gender differences in health protective behaviours and its implications for COVID-19 pandemic in Taiwan: a population-based study.

INTRODUCTION: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection produces more severe symptoms and a higher mortality in men than in women. The role of biological sex in the immune response to SARS-CoV-2 is believed to explain this sex disparity. However, the contribution of gender factors that influence health protective behaviors and therefore health outcomes, remains poorly explored. METHODS: We assessed the contributions of gender in attitudes towards the COVID-19 pandemic, using a hypothetical influenza pandemic data from the 2019 Taiwan Social Change Survey. Participants were selected through a stratified, three-stage probability proportional-to-size sampling from across the nation, to fill in questionnaires that asked about their perception of the hypothetical pandemic, and intention to adopt health protective behaviors. RESULTS: A total of 1,990 participants (median age = 45·92 years, 49% were women) were included. Significant gender disparities (p < .001) were observed. The risk perception of pandemic (OR = 1·28, 95% CI [1·21 - 1·35], p < .001), older age (OR = 1·06, 95% CI [1·05 - 1·07], p < .001), female gender (OR = 1·18, 95% CI [1·09-1·27], p < .001), higher education (OR = 1·10, 95% CI [1·06 - 1·13], p < .001), and larger family size (OR = 1·09, 95% CI [1·06 - 1·15], p < .001) were positively associated with health protective behaviors. The risk perception of pandemic (OR = 1·25, 95% CI [1·15 - 1·36]), higher education (OR = 1·07, 95% CI [1·02 - 1·13], p < .05), being married (OR = 1·17, 95% CI [1·01-1·36, p < .05), and larger family size (OR = 1·33, 95% CI [1·25 - 1·42], p < .001), were positively associated with intention to receive a vaccine. However, female gender was negatively associated with intention to receive a vaccine (OR = 0·85, 95% CI [0·75 - 0·90], p < ·01) and to comply with contact-tracing (OR = 0·95, 95% CI [0·90 - 1·00], p < .05) compared to men. Living with children was also negatively associated with intention to receive vaccines (OR = 0·77, 95% CI [0·66 - 0·90], p < .001). CONCLUSION: This study unveils gender differences in risk perception, health protective behaviors, vaccine hesitancy, and compliance with contact-tracing using a hypothetical viral pandemic. Gender-specific health education raising awareness of health protective behaviors may be beneficial to prevent future pandemics.

Effect of methylprednisolone treatment on COVID-19: An inverse probability of treatment weighting analysis.

OBJECTIVES: While corticosteroids have been hypothesized to exert protective benefits in patients infected with SARS-CoV-2, data remain mixed. This study sought to investigate the outcomes of methylprednisone administration in an Italian cohort of hospitalized patients with confirmed SARS-CoV-2 infection. METHODS: Patients with confirmatory testing for SARS-CoV-2 were retrospectively enrolled from a tertiary university hospital in Milan, Italy from March 1st to April 30th, 2020 and divided into two groups by administration of corticosteroids. Methylprednisolone was administered to patients not responding to pharmacological therapy and ventilatory support at 0.5-1mg/kg/day for 4 to 7 days. Inverse probability of treatment weighting (IPTW) was used to adjust for baseline differences between the steroid and non-steroid cohorts via inverse probability of treatment weight. Primary outcomes included acute respiratory failure (ARF), shock, and 30-day mortality among surviving patients. RESULTS: Among 311 patients enrolled, 71 patients received steroids and 240 did not receive steroids. The mean age was 63.1 years, 35.4% were female, and hypertension, diabetes, heart disease, and chronic pulmonary disease were present in 3.5%, 1.3%, 14.8% and 12.2% respectively. Crude analysis revealed no statistically significant reduction in the incidence of 30-day mortality (36,6% vs 21,7%; OR, 2.09; 95% CI, 1.18-3.70; p = 0.011), shock (2.8% vs 4.6%; OR, 0.60; 95% CI = 0.13-2.79; p = 0.514) or ARF (12.7% vs 15%; OR, 0.82; 95% CI = 0.38-1.80; p = 0.625) between the steroid and non-steroid groups. After IPTW analysis, the steroid-group had lower incidence of shock (0.9% vs 4.1%; OR, 0.21; 95% CI,0.06-0.77; p = 0.010), ARF (6.6% vs 16.0%; OR, 0.37; 95% CI, 0.22-0.64; p<0.001) and 30-day mortality (20.3% vs 22.8%; OR 0.86; 95% CI, 0.59-1.26 p = 0.436); even though, for the latter no statistical significance was reached. Steroid use was also associated with increased length of hospital stay both in crude and IPTW analyses. Subgroup analysis revealed that patients with cardiovascular comorbidities or chronic lung diseases were more likely to be steroid responsive. No significant survival benefit was seen after steroid treatment. CONCLUSIONS: Physicians should avoid routine methylprednisolone use in SARS-CoV-2 patients, since it does not reduce 30-day mortality. However, they must consider its use for severe patients with cardiovascular or respiratory comorbidities in order to reduce the incidence of either shock or acute respiratory failure.

Guidelines for COVID-19 Laboratory Testing for Emergency Departments From the New Diagnostic Technology Team of the Taiwan Society of Emergency Medicine

COVID-19 tests have different turnaround times (TATs), accuracy levels, and limitations, which emergency physicians should be aware of. Nucleic acid amplification tests (NAATs) can be divided into standard high throughput tests and rapid molecular diagnostic tests at the point of care (POC). The standard NAAT has the advantages of high throughput and high accuracy with a TAT of 3–4 hours. The POC molecular test has the same advantages of high accuracy as standard high throughput PCR, but can be done in 13–45 minutes. Roche cobas Liat is the most commonly used machine in Taiwan, displaying 99%–100% sensitivity and 100% specificity, respectively. Abbott ID NOW is an isothermal PCR-based POC machine with a sensitivity of 79% and a specificity of 100%. A high rate of false positives and false negatives is associated with rapid antigen testing. Antibody testing is mostly used as part of public health surveys and for testing for immunity.

Safety and Seroconversion of Immunotherapies against SARS-CoV-2 Infection: A Systematic Review and Meta-Analysis of Clinical Trials.

Clinical trials evaluating the safety and antibody response of strategies to manipulate prophylactic and therapeutic immunity have been launched. We aim to evaluate strategies for augmentation of host immunity against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. We searched clinical trials registered at the National Institutes of Health by 25 May 2021 and conducted analyses on inoculated populations, involved immunological processes, source of injected components, and trial phases. We then searched PubMed, Embase, Scopus, and the Cochrane Central Register of Controlled Trials for their corresponding reports published by 25 May 2021. A bivariate, random-effects meta-analysis was used to derive the pooled estimate of seroconversion and adverse events (AEs). A total of 929,359 participants were enrolled in 389 identified trials. The working mechanisms included heterologous immunity, active immunity, passive immunity, and immunotherapy, with 62.4% of the trials on vaccines. A total of 9072 healthy adults from 27 publications for 22 clinical trials on active immunity implementing vaccination were included for meta-analyses. The pooled odds ratios (ORs) of seroconversion were 13.94, 84.86, 106.03, and 451.04 (all p < 0.01) for vaccines based on protein, RNA, viral vector, and inactivated virus, compared with that of respective placebo/control treatment or pre-vaccination sera. The pooled ORs for safety, as defined by the inverse of systemic adverse events (AEs) were 0.53 (95% CI = 0.27-1.05; p = 0.07), 0.35 (95% CI = 0.16-0.75; p = 0.007), 0.32 (95% CI = 0.19-0.55; p < 0.0001), and 1.00 (95% CI = 0.73-1.36; p = 0.98) for vaccines based on protein, RNA, viral vector, and inactivated virus, compared with that of placebo/control treatment. A paradigm shift from all four immune-augmentative interventions to active immunity implementing vaccination was observed through clinical trials. The efficacy of immune responses to neutralize SARS-CoV-2 for these vaccines was promising, although systemic AEs were still evident for RNA-based and viral vector-based vaccines.

Chest CT Images for COVID-19: Radiologists and Computer-Based Detection.

BACKGROUND: Characteristic chest computed tomography (CT) manifestation of 2019 novel coronavirus (COVID-19) was added as a diagnostic criterion in the Chinese National COVID-19 management guideline. Whether the characteristic findings of Chest CT could differentiate confirmed COVID-19 cases from other positive nucleic acid test (NAT)-negative patients has not been rigorously evaluated. PURPOSE: We aim to test whether chest CT manifestation of 2019 novel coronavirus (COVID-19) can be differentiated by a radiologist or a computer-based CT image analysis system. METHODS: We conducted a retrospective case-control study that included 52 laboratory-confirmed COVID-19 patients and 80 non-COVID-19 viral pneumonia patients between 20 December, 2019 and 10 February, 2020. The chest CT images were evaluated by radiologists in a double blind fashion. A computer-based image analysis system (uAI System, Lianying Inc., Shanghai, China) detected the lesions in 18 lung segments defined by Boyden classification system and calculated the infected volume in each segment. The number and volume of lesions detected by radiologist and computer system was compared with Chi-square test or Mann-Whitney U test as appropriate. RESULTS: The main CT manifestations of COVID-19 were multi-lobar/segmental peripheral ground-glass opacities and patchy air space infiltrates. The case and control groups were similar in demographics, comorbidity, and clinical manifestations. There was no significant difference in eight radiologist identified CT image features between the two groups of patients. There was also no difference in the absolute and relative volume of infected regions in each lung segment. CONCLUSION: We documented the non-differentiating nature of initial chest CT image between COVID-19 and other viral pneumonia with suspected symptoms. Our results do not support CT findings replacing microbiological diagnosis as a critical criterion for COVID-19 diagnosis. Our findings may prompt re-evaluation of isolated patients without laboratory confirmation.

Clinical Features of Emergency Department Patients from Early COVID-19 Pandemic that Predict SARS-CoV-2 Infection: Machine-learning Approach.

INTRODUCTION: Within a few months coronavirus disease 2019 (COVID-19) evolved into a pandemic causing millions of cases worldwide, but it remains challenging to diagnose the disease in a timely fashion in the emergency department (ED). In this study we aimed to construct machine-learning (ML) models to predict severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection based on the clinical features of patients visiting an ED during the early COVID-19 pandemic. METHODS: We retrospectively collected the data of all patients who received reverse transcriptase polymerase chain reaction (RT-PCR) testing for SARS-CoV-2 at the ED of Baylor Scott & White All Saints Medical Center, Fort Worth, from February 23-May 12, 2020. The variables collected included patient demographics, ED triage data, clinical symptoms, and past medical history. The primary outcome was the confirmed diagnosis of COVID-19 (or SARS-CoV-2 infection) by a positive RT-PCR test result for SARS-CoV-2, and was used as the label for ML tasks. We used univariate analyses for feature selection, and variables with P<0.1 were selected for model construction. Samples were split into training and testing cohorts on a 60:40 ratio chronologically. We tried various ML algorithms to construct the best predictive model, and we evaluated performances with the area under the receiver operating characteristic curve (AUC) in the testing cohort. RESULTS: A total of 580 ED patients were tested for SARS-CoV-2 during the study periods, and 98 (16.9%) were identified as having the SARS-CoV-2 infection based on the RT-PCR results. Univariate analyses selected 21 features for model construction. We assessed three ML methods for performance: of the three methods, random forest outperformed the others with the best AUC result (0.86), followed by gradient boosting (0.83) and extra trees classifier (0.82). CONCLUSION: This study shows that it is feasible to use ML models as an initial screening tool for identifying patients with SARS-CoV-2 infection. Further validation will be necessary to determine how effectively this prediction model can be used prospectively in clinical practice.

How to Quantify and Interpret Treatment Effects in Comparative Clinical Studies of COVID-19.

Clinical trials of treatments for coronavirus disease 2019 (COVID-19) draw intense public attention. More than ever, valid, transparent, and intuitive summaries of the treatment effects, including efficacy and harm, are needed. In recently published and ongoing randomized comparative trials evaluating treatments for COVID-19, time to a positive outcome, such as recovery or improvement, has repeatedly been used as either the primary or key secondary end point. Because patients may die before recovery or improvement, data analysis of this end point faces a competing risk problem. Commonly used survival analysis techniques, such as the Kaplan-Meier method, often are not appropriate for such situations. Moreover, almost all trials have quantified treatment effects by using the hazard ratio, which is difficult to interpret for a positive event, especially in the presence of competing risks. Using 2 recent trials evaluating treatments (remdesivir and convalescent plasma) for COVID-19 as examples, a valid, well-established yet underused procedure is presented for estimating the cumulative recovery or improvement rate curve across the study period. Furthermore, an intuitive and clinically interpretable summary of treatment efficacy based on this curve is also proposed. Clinical investigators are encouraged to consider applying these methods for quantifying treatment effects in future studies of COVID-19.

Combining Procalcitonin and Rapid Multiplex Respiratory Virus Testing for Antibiotic Stewardship in Older Adult Patients With Severe Acute Respiratory Infection.

OBJECTIVES: Virus infection is underevaluated in older adults with severe acute respiratory infections (SARIs). We aimed to evaluate the clinical impact of combining point-of-care molecular viral test and serum procalcitonin (PCT) level for antibiotic stewardship in the emergency department (ED). DESIGN: A prospective twin-center cohort study was conducted between January 2017 and March 2018. SETTING AND PARTICIPANTS: Older adult patients who presented to the ED with SARIs received a rapid molecular test for 17 respiratory viruses and a PCT test. MEASURES: To evaluate the clinical impact, we compared the outcomes of SARI patients between the experimental cohort and a propensity score-matched historical cohort. The primary outcome was the proportion of antibiotics discontinuation or de-escalation in the ED. The secondary outcomes included duration of intravenous antibiotics, length of hospital stay, and mortality. RESULTS: A total of 676 patients were included, of which 169 patients were in the experimental group and 507 patients were in the control group. More than one-fourth (27.9%) of the patients in the experimental group tested positive for virus. Compared with controls, the experimental group had a significantly higher proportion of antibiotics discontinuation or de-escalation in the ED (26.0% vs 16.1%, P = .007), neuraminidase inhibitor uses (8.9% vs 0.6%, P < .001), and shorter duration of intravenous antibiotics (10.0 vs 14.5 days, P < .001). CONCLUSIONS AND IMPLICATIONS: Combining rapid viral surveillance and PCT test is a useful strategy for early detection of potential viral epidemics and antibiotic stewardship. Clustered viral respiratory infections in a nursing home is common. Patients transferred from nursing homes to ED may benefit from this approach.