Purpose of the studyThe aim of our study was to investigate potential adverse reactions in healthcare professionals working in Level 3 barrier protection personal protective equipment (L3PPE) to treat patients with COVID-19.Study designBy using a convenience sampling approach, 129 out of 205 randomly selected healthcare professionals from the First Affiliated Hospital of Zhejiang University School of Medicine were invited to take part in a WeChat messaging app survey, Questionnaire Star, via a survey link. Healthcare personnel details were collected, including profession, years of professional experience and adverse reactions while wearing L3PPE. Survey results were divided by profession and years of professional experience; differences in adverse reactions were compared.ResultsAmong the 129 healthcare professionals surveyed, 21 (16.28%) were doctors and 108 (83.72%) were nurses. A total of 122 (94.57%) healthcare professionals experienced discomfort while wearing L3PPE to treat patients with COVID-19. The main reasons for adverse reactions and discomfort include varying degrees of adverse skin reactions, respiratory difficulties, heat stress, dizziness and nausea. Doctors had a lower incidence of rashes (χ2=4.519, p=0.034) and dizziness (χ2=4.123, p=0.042) when compared with nurses. Junior (8.5 years of experience or fewer) healthcare personnel also experienced a higher rate of heat stress when compared with senior personnel (more than 8.5 years greater) (χ2=5.228, p=0.022).ConclusionMore attention should be offered to healthcare personnel wearing L3PPE to treat patients with COVID-19 because they are susceptible to developing adverse reactions.

BackgroundPost-acute coronavirus disease 2019 (COVID-19) symptoms occurred in most of the COVID-19 survivors. However, few studies have examined the issue of whether hospitalization results in different post-acute COVID-19 symptom risks. This study aimed to compare potential COVID-19 long-term effects in hospitalized and non-hospitalized COVID-19 survivors.MethodsThis study is designed as a systematic review and meta-analysis of observational studies. A systematic search of six databases was performed for identifying articles published from inception until April 20th, 2022, which compared post-acute COVID-19 symptom risk in hospitalized and non-hospitalized COVID-19 survivors using a predesigned search strategy included terms for SARS-CoV-2 (eg, COVID, coronavirus, and 2019-nCoV), post-acute COVID-19 Syndrome (eg, post-COVID, post COVID conditions, chronic COVID symptom, long COVID, long COVID symptom, long-haul COVID, COVID sequelae, convalescence, and persistent COVID symptom), and hospitalization (hospitalized, in hospital, and home-isolated). The present meta-analysis was conducted according to The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement using R software 4.1.3 to create forest plots. Q statistics and the I2 index were used to evaluate heterogeneity in this meta-analysis.ResultsSix observational studies conducted in Spain, Austria, Switzerland, Canada, and the USA involving 419 hospitalized and 742 non-hospitalized COVID-19 survivors were included. The number of COVID-19 survivors in included studies ranged from 63 to 431, and follow-up data were collected through visits in four studies and another two used an electronic questionnaire, visit and telephone, respectively. Significant increase in the risks of long dyspnea (OR = 3.18, 95% CI = 1.90–5.32), anxiety (OR = 3.09, 95% CI = 1.47–6.47), myalgia (OR = 2.33, 95% CI = 1.02–5.33), and hair loss (OR = 2.76, 95% CI = 1.07–7.12) risk were found in hospitalized COVID-19 survivors compared with outpatients. Conversely, persisting ageusia risk was significantly reduced in hospitalized COVID-19 survivors than in non-hospitalized patients.ConclusionThe findings suggested that special attention and patient-centered rehabilitation service based on a needs survey should be provided for hospitalized COVID-19 survivors who experienced high post-acute COVID-19 symptoms risk.

Salt stress severely restricts the growth of plants and threatens the development of agriculture throughout the world. Worldwide studies have shown that exogenous melatonin (MT) can effectively improve the growth of plants under salt stress. Through a meta-analysis of 549 observations, this study first explored the effects of salt stress characteristics and MT application characteristics on MT regulated plant growth under salt stress. The results show that MT has a wide range of regulatory effects on plant growth indicators under salt stress, of which the regulatory effect on root indexes is the strongest, and this regulatory effect is not species-specific. The intensity of salt stress did not affect the positive effect of MT on plant growth, but the application effect of MT in soil was stronger than that in rooting medium. This meta-analysis also revealed that the foliar application of a concentration between 100–200 μM is the best condition for MT to enhance plant growth under salt stress. The results can inspire scientific research and practical production, while seeking the maximum improvement in plant salt tolerance under salt stress.

The purpose of this study was to investigate the diagnosis of patients in the early low-incidence area of coronavirus disease 2019 (COVID-19) and the mental health of staff based on genetic algorithm- (GA-) based computed tomography (CT) images. In this study, 136 COVID-19 patients admitted to our hospital were divided into a critical group (94 cases) and a general group (42 cases). In addition, a questionnaire was used to investigate the mental health of COVID-19 patients in early low-incidence areas, including 147 medical staff members and 213 nonmedical staff members. The effects were compared between the optimized GA template matching (OGATM) algorithm proposed in this study and traditional GATM, which were applied in CT images of COVID-19 patients. The results showed that the proposed algorithm could improve the accuracy of pneumonia detection and reduce the false-positive rate. The average age of patients in the severe group was markedly higher than that of the general group ( P < 0.05 ). The number of cases with diabetes mellitus (49.6%) from the severe group was more than that from the general group (12.4%) ( P < 0.05 ). Lymphocyte count in patients from the severe group (0.68 ± 0.26 × 109/L) was sharply lower than that of the general group (1.12 ± 0.34 × 109/L) ( P < 0.05 ). The total T lymphocyte count in patients from the severe group reduced steeply in contrast to that of the general group ( P < 0.05 ). The anxiety and depression scores of medical patients (39.45 ± 9.45 points and 47.58 ± 10.47 points) were obviously lower than the scores of nonmedical patients (43.57 ± 9.54 points and 52.48 ± 10.25 points) ( P < 0.05 ). In conclusion, the elderly and staffs with diabetes mellitus were more likely to develop severe COVID-19. Moreover, the total T lymphocytes of COVID-19 patients were lower than their normal levels, and nonmedical staffs had more psychological stress than medical staffs.

Background Epilepsy is a prevalent comorbidity in patients with brain metastases (BM) and could result in sudden and accidental damage, as well as increased disease burden due to its rapid onset. Foreseeing the potential for the development of epilepsy may permit timely and efficient measures. This study aimed to analyze the influencing factors of epilepsy in advanced lung cancer (ALC) patients with BM and construct a nomogram model to predict the likelihood of developing epilepsy. Methods Socio-demographic and clinical data of ALC patients with BM were retrospectively collected from the First Affiliated Hospital of Zhejiang University School of Medicine between September 2019 and June 2021. Univariate and multivariate logistic regression analyses were applied to determine the influencing factors for epilepsy in ALC patients with BM. Based on the results of the logistic regression analysis, a nomogram was built to represent the contribution of each influencing factor in predicting the probability of epilepsy development in ALC patients with BM. The Hosmer-Lemeshow test and receiver operating characteristic (ROC) curve were utilized to evaluate the goodness of fit and prediction performance of the model. Results The incidence of epilepsy among 138 ALC patients with BM was 29.7%. On the multivariate analysis, having a higher number of supratentorial lesions (odds ratio [OR] = 1.727; p = 0.022), hemorrhagic foci (OR = 4.922; p = .021), and a high-grade of peritumoral edema (OR = 2.524; p < .001) were independent risk factors for developing epilepsy, while undergoing gamma knife radiosurgery (OR = .327; p = .019) was an independent protective factor. The p-value of the Hosmer-Lemeshow test was .535 and the area under the ROC curve (AUC) was .852 (95% CI: .807–.897), suggesting the model had a good fit and exhibited strong predictive accuracy. Conclusion The nomogram was constructed that can predict the probability of epilepsy development for ALC patients with BM, which is helpful for healthcare professionals to identify high-risk groups early and allows for individualized interventions.