Influences of Two FEV1 Reference Equations (GLI-2012 and GIRH-2017) on Airflow Limitation Classification Among COPD Patients.

Objective: To explore the clinical effects of different forced expiratory volume in 1s (FEV1) reference equations on chronic obstructive pulmonary disease (COPD) airflow limitation (AFL) classification. Methods: We conducted a COPD screening program for residents over 40 years old from 2019 to 2021. All residents received the COPD screening questionnaire (COPD-SQ) and spirometry. Postbronchodilator FEV1/FVC (forced vital capacity) <0.7 was used as the diagnostic criterion of COPD and two reference equations of FEV1 predicted values were used for AFL severity classification: the European Respiratory Society Global Lung Function Initiative reference equation in 2012 (GLI-2012) and the Guangzhou Institute of Respiratory Health reference equation in 2017 (GIRH-2017). Clinical characteristics of patients in GOLD (Global Initiative for Chronic Obstructive Pulmonary Disease) 1-4 grades classified by the two reference equations were compared. Results: Among 3524 participants, 659 subjects obtained a COPD-SQ score of 16 or more and 743 participants were found to have AFL. The COPD-SQ showed high sensitivity (59%) and specificity (91%) in primary COPD screening. Great differences in COPD severity classification were found when applying the two equations (p < 0.001). Compared with GIRH-2017, patients with AFL classified by GLI-2012 equations were significantly severer. The relationship between symptom scores, acute exacerbation (AE) history distributions and COPD severities classified by the two equations showed a consistent trend of positive but weak correlation. Group A, B, C and D existed in all GOLD 1 to 3 COPD patients, but in GOLD 4, only Groups B and D existed. However, no clear significant differences were found in symptoms, AE risk assessments, risk factors exposure and even the combined ABCD grouping under the two equations. Conclusion: There were significant differences in COPD AFL severity classification with GLI-2012 and GIRH-2017 FEV1 reference equations. But these severity estimation differences did not affect symptoms, AE risk assessments and ABCD grouping of patients at all GOLD grades.

Higher benefit-risk ratio of COVID-19 vaccination in patients with schizophrenia and major depressive disorder versus patients with bipolar disorder when compared to controls.

Patients with major psychiatric disorders (MPD) that include schizophrenia (SCH), bipolar disorder (BP), and major depressive disorder (MDD) are at increased risk for coronavirus disease 2019 (COVID-19). However, the safety and efficacy of COVID-19 vaccines in MPD patients have not been fully evaluated. This study aimed to investigate adverse events (AEs)/side effects and efficacy of COVID-19 vaccines in MPD patients. This retrospective study included 2034 patients with SCH, BP, or MDD who voluntarily received either BBIBP-CorV or Sinovac COVID-19 vaccines, and 2034 matched healthy controls. The incidence of AEs/side effects and the efficacy of COIVD-19 vaccinations among the two groups were compared. The risk ratio (RR) of side effects in patients with MPD was 0.60 (95% confidence interval [CI]: 0.53-0.68) after the first dose and 0.80 (95% CI: 0.65-0.99) following the second dose, suggesting a significantly lower risk in the MPD group versus healthy controls. The RRs of AEs did not differ between patients and controls. Notably, fully vaccinated patients exhibited a decreased risk of influenza with or without fever compared with controls (RR=0.38, 95% CI: 0.31-0.46; RR=0.23, 95% CI: 0.17-0.30; respectively). Further subgroup comparisons revealed a significantly lower risk of influenza with fever in MDD (RR=0.13, 95% CI: 0.08-0.21) and SCH (RR=0.24, 95% CI: 0.17-0.34) than BP (RR=0.85, 95% CI: 0.69-1.06) compared to controls. We conclude that the benefit-risk ratio of COVID-19 vaccination was more favorable in SCH or MDD versus BP when compared with controls. These data indicate that COVID-19 vaccines are safe and protective in patients with MPD from COVID-19.

Prognostic Value of Machine Learning in Patients with Acute Myocardial Infarction.

(1) Background: Patients with acute myocardial infarction (AMI) still experience many major adverse cardiovascular events (MACEs), including myocardial infarction, heart failure, kidney failure, coronary events, cerebrovascular events, and death. This retrospective study aims to assess the prognostic value of machine learning (ML) for the prediction of MACEs. (2) Methods: Five-hundred patients diagnosed with AMI and who had undergone successful percutaneous coronary intervention were included in the study. Logistic regression (LR) analysis was used to assess the relevance of MACEs and 24 selected clinical variables. Six ML models were developed with five-fold cross-validation in the training dataset and their ability to predict MACEs was compared to LR with the testing dataset. (3) Results: The MACE rate was calculated as 30.6% after a mean follow-up of 1.42 years. Killip classification (Killip IV vs. I class, odds ratio 4.386, 95% confidence interval 1.943-9.904), drug compliance (irregular vs. regular compliance, 3.06, 1.721-5.438), age (per year, 1.025, 1.006-1.044), and creatinine (1 µmol/L, 1.007, 1.002-1.012) and cholesterol levels (1 mmol/L, 0.708, 0.556-0.903) were independent predictors of MACEs. In the training dataset, the best performing model was the random forest (RDF) model with an area under the curve of (0.749, 0.644-0.853) and accuracy of (0.734, 0.647-0.820). In the testing dataset, the RDF showed the most significant survival difference (log-rank p = 0.017) in distinguishing patients with and without MACEs. (4) Conclusions: The RDF model has been identified as superior to other models for MACE prediction in this study. ML methods can be promising for improving optimal predictor selection and clinical outcomes in patients with AMI.

The screening value of RT-LAMP and RT-PCR in the diagnosis of COVID-19: systematic review and meta-analysis.

The purpose of this systematic review is to evaluate the test accuracy of reverse-transcription loop-mediated isothermal amplification (RT-LAMP) and reverse transcription-PCR (RT-PCR) for the diagnosis of coronavirus disease 2019 (COVID-19). We comprehensively searched PUBMED, Web of Science, the Cochrane Library, the Chinese National Knowledge Infrastructure, and the Chinese Biomedical Literature Service System until September 1, 2021. We included clinical studies assessing the sensitivity and specificity of RT-PCR and RT-LAMP using respiratory samples. Thirty-three studies were included with 9360 suspected cases of SARS-CoV-2 infection. The RT-PCR or other comprehensive diagnostic method was defined as the reference method. The results showed that the overall pooled sensitivity of RT-PCR and RT-LAMP was 0.96 (95 % CI, 0.93-0.98) and 0.92 (95 % CI, 0.85-0.96), respectively. RT-PCR and RT-LAMP had a 0.06 (95 % CI, 0.04-0.08) and 0.12 (95 % CI, 0.06-0.16) false-negative rates (FNR), respectively. Moreover, subgroup analysis showed mixed sampling and multiple target gene diagnosis methods had better diagnostic value than single-site sampling and a single target gene. The sensitivity and FNR were also significantly affected by the reference method. Comparing RT-LAMP with established suboptimal RT-PCR may exaggerate the performance of RT-LAMP. RT-PCR and RT-LAMP showed high values in the diagnosis of COVID-19, but there was still a FNR of about 6%-12%.

Identifying the Subtypes and Characteristics of Mental Workload Among Chinese Physicians in Outpatient Practice: A Latent Profile Analysis

Objective: The purpose of this study is to investigate the mental workload level of physicians in outpatient practice since the normalization of prevention and control of the COVID-19 pandemic in China and explore the subtypes of physicians regarding their mental workload. Methods: A cross-sectional survey of 1,934 physicians primarily in 24 hospitals in 6 provinces in Eastern, Central, and Western China was conducted from November 2020 to February 2021. A latent profile analysis was performed to identify clusters based on the six subscales of the Chinese version of physician mental workload scale developed by our research team. Chi-square tests were performed to explore the differences in demographic characteristics of the subtypes among the subgroups, and multinomial logistic regression analysis was further conducted to identify the determinants of the subtypes of physicians. Results: Overall, the participating physicians reported high levels of task load but with high self-assessed performance (68.01 ± 14.25) while performing communication work tasks characterized by direct patient interaction in outpatient clinics. About 33.8% of the participating physicians were identified as “high workload and high self-assessment” subtype, compared to 49.7% “medium workload and medium self-assessment” subtype and 16.4% “low workload and low self-assessment” subtype. Physicians in “high workload and high self-assessment” subtype had the highest mean mental workload score. Physicians who were female, younger, married, worse health status, those who had lower educational level and an average monthly income of 5,001–10,000 RMB, those who worked in tertiary A hospitals, more hours per week and more than 40 h per week in outpatient clinics, and those who saw more outpatients per day, and spent more time per patient but with higher outpatient satisfaction were more likely to belong to “high workload and high self-assessment” subtype. Conclusion: Our findings can help provide a solid foundation for developing targeted interventions for individual differences across physicians regarding their mental workload. We suggest the hospital managers should pay more attention to those physicians with characteristics of the “high workload and high self-assessment” subtype and strengthen the management of the workload of this subtype of physicians to reduce the risks of their mental health, and to maintain their high work performance in outpatient clinics.

Dynamic impact of negative public sentiment on agricultural product prices during COVID-19

The COVID-19 pandemic has had a significantly negative impact on public sentiment, which has resulted in panic and some irrational buying behavior, which in turn has had a complex impact on agricultural product prices. This study quantified online negative sentiment using micro-blog text mining and a time-varying parameter vector autoregressive model (TVP-VAR) to empirically analyze the dynamic impact of negative public emotions on agricultural product prices during the COVID-19 pandemic in China. It was found that the online negative sentiment impacted agricultural products prices during COVID-19 and had significant time-varying, lag, and life cycle characteristics, with the responses being most significant in the spread and recession periods. Differences were found in the price responses for different agricultural products and in different risk areas. The online negative sentiment was found to have the greatest impact on vegetable prices, with livestock products and vegetable prices being mainly positively impacted, fruit prices being mainly negatively impacted, and aquatic product prices being negatively impacted in the early stage and positively impacted in the middle and late stages. The online negative sentiment had the greatest impact on medium-risk area agricultural product prices, followed by low-risk areas, with the lowest impact found on the high-risk area agricultural product prices. Three policy suggestions for epidemic monitoring, public opinion guidance and control, and the timely release of agricultural product information are given based on the results.

Prosecution records reveal pangolin trading networks in China, 2014-2019.

In a precautionary response to the current coronavirus (COVID-19) pandemic, China's Ministries permanently banned eating and trading in terrestrial wild (non-livestock) animals on 24 February 2020, and extensively updated the list of Fauna under Special State Protection (LFSSP) in 2020 and 2021, in which pangolins (Manidae spp.) were upgraded to the highest protection level. Examining 509 pangolin prosecution records from China Judgements online prior to these changes (01/01/14-31/12/19), we identified that Guangdong, Guangxi and Yunnan Provinces were hotspots for trade in whole pangolins and their scales. Interrupting trade in these three principal southern provinces would substantially fragment the pangolin trade network and reduce supply of imports from other south-east Asian countries. In the context of the revised legislation and strategies intended to prevent wildlife trade, we conclude that targeting interventions at key trade nodes could significantly reduce illegal trade in pangolins, and that this approach could also be effective with other taxa.

A false alarm of COVID-19 pneumonia in lung cancer with anti-PD-1 related pneumonitis: a case report and review of the literature.

BACKGROUND: Pneumonitis belongs to the fatal toxicities of anti-PD-1/PD-L1 treatments. Its diagnosis is based on immunotherapeutic histories, clinical symptoms, and the computed tomography (CT) imaging. The radiological features were typically ground-glass opacities, similar to CT presentation of 2019 Novel Coronavirus (COVID-19) pneumonia. Thus, clinicians are cautious in differential diagnosis especially in COVID-19 epidemic areas. CASE PRESENTATION: Herein, we report a 67-year-old Han Chinese male patient presenting with dyspnea and normal body temperature on the 15th day of close contact with his son, who returned from Wuhan. He was diagnosed as advanced non-small cell lung cancer and developed pneumonitis post Sintilimab injection during COIVD-19 pandemic period. The chest CT indicated peripherally subpleural lattice opacities at the inferior right lung lobe and bilateral thoracic effusion. The swab samples were taken twice within 72 hours and real-time reverse-transcription polymerase-chain-reaction (RT-PCR) results were COVID-19 negative. The patient was thereafter treated with prednisolone and antibiotics for over 2 weeks. The suspicious lesion has almost absorbed according to CT imaging, consistent with prominently falling CRP level. The anti-PD-1 related pneumonitis mixed with bacterial infection was clinically diagnosed based on the laboratory and radiological evidences and good response to the prednisolone and antibiotics. CONCLUSION: The anti-PD-1 related pneumonitis and COVID-19 pneumonia possess similar clinical presentations and CT imaging features. Therefore, differential diagnosis depends on the epidemiological and immunotherapy histories, RT-PCR tests. The response to glucocorticoid is still controversial but helpful for the diagnosis.

Prevalence and Risk Factors of Anxiety, Depression, and Sleep Problems Among Caregivers of People Living With Neurocognitive Disorders During the COVID-19 Pandemic.

Objectives: To estimate the prevalence of anxiety, depression, and sleep problems among caregivers of persons living with neurocognitive disorders (PLWND) during the COVID-19 pandemic in China and investigate whether the COVID-19-related experiences were associated with the presence of anxiety, depression, and sleep problems. Methods: From March 1 to 31, 2020, 160 caregivers of PLWND participated in an online cross-sectional survey on the prevalence of anxiety, depression, and sleep problems. The 7-item Generalized Anxiety Disorder Scale (GAD-7) was administered to measure anxiety symptoms, and the 2-item Patient Health Questionnaire (PHQ-2) was used to assess depressive symptoms. Questions on sleep duration and sleep quality enquired about sleep problems. Six items were used to explore the COVID-19-related experiences, including community-level infection contact and the level of exposure to media information. We computed the prevalence rate of anxiety, depressive symptoms, and sleep problems. Univariate and multivariate logistic regression analyses were performed to investigate factors associated with these mental health problems. Results: The prevalence rate of anxiety, depression, and sleep problems were 46.9%, 36.3%, and 9.4%. Approximately 55 participants (34.4%) presented with two or more mental health problems. Women had a higher risk of developing anxiety symptoms (OR, 5.284; 95% CI, 2.068-13.503; p = 0.001). Having a mental disorder (OR, 5.104; 95% CI, 1.522-17.114; p = 0.008) was associated with an increased risk of depressive symptoms. Caregivers who preferred to access positive information (OR, 0.215; 95% CI, 0.058-0.793; p = 0.021) was associated with decreased risk of sleep problems. Conclusion: Anxiety and depressive symptoms were common among caregivers of older adults with dementia or mild cognitive impairment during the COVID-19 pandemic. Being female was an independent risk factor for experiencing anxiety symptoms. Preexisting mental disorders increased the risk of depressive symptoms among caregivers, while caregivers who prefer to access positive media information decreased sleep problems.

Mental Health Multimorbidity among Caregivers of Older Adults During the COVID-19 Epidemic.

OBJECTIVE: To investigate mental health status and associated factors among caregivers of older adults during the COVID-19 epidemic in China. METHODS: From March 1 to 31, 2020, 916 caregivers of older adults participated in an online cross-sectional survey on the prevalence of anxiety, depression, and sleep problems. The seven-item Generalized Anxiety Disorder Scale (GAD-7) was administered to measure anxiety symptoms, the two-item Patient Health Questionnaire (PHQ-2) was used to assess depressive symptoms, and a self-developed questionnaire was used to assess sleep quality and duration. Six questions about COVID-19-related experiences were used to assess community-level infection contact and the level of exposure to media information. The prevalence rates of anxiety, depression and sleep problems were computed. The Wald χ2 were applied to compare the differences between subgroups. Multiple logistic regression analyses were performed to investigate factors associated with anxiety, depression, sleep problems, and multimorbidity. RESULTS: The prevalence rates of anxiety, depression, and sleep problems were 46.8%, 29.8%, and 10.8%, respectively. Approximately 263 participants (28.7%) presented with two or more mental health problems. Being female (OR, 2.254; 95% CI, 1.510-3.363), having community-level COVID-19 contact (OR, 1.856; 95% CI, 1.189-2.898), and having a mental disorder (OR, 3.610; 95% CI, 1.644-7.930) were associated with increased risk of multimorbidity among caregivers. Caregivers who preferred positive information (OR, 0.652; 95% CI, 0.472-0.899) had reduced risk of multimorbidity. CONCLUSION: Anxiety and depression were common among caregivers of older adults during the COVID-19 epidemic. Being female and having community-level COVID-19 contact were independent risk factors for experiencing multiple mental health problems. Preexisting mental disorders increased the risk of multimorbidity among caregivers, while enhanced access to positive media information decreased the risk of multimorbidity.