Aims and ObjectivesTo determine the global prevalence of nursing burnout syndrome and time trends for the last 10 years.BackgroundThe prevalence of burnout syndrome varied greatly in different regions in the last 10 years, so the average prevalence and time trends of nursing burnout syndrome for the last 10 years were not completely clear.DesignA meta‐analysis conducted in the PRISMA guidelines.MethodsCINAHL, Web of Science, and PubMed were searched for trials on the prevalence of nursing burnout syndrome from 2012 to 2022 systematically. Hoy's quality assessment tool was used to evaluate the risk of bias. The global prevalence of nursing burnout syndrome was estimated, and subgroup analysis was used to explore what caused heterogeneity. Time trends for the last 10 years were evaluated by meta‐regression using Stata 11.0.ResultsNinety‐four studies reporting the prevalence of nursing burnout were included. The global prevalence of nursing burnout was 30.0% [95% CI: 26.0%–34.0%]. Subgroup analysis indicated that the specialty (p < .001) and the region (p < .001) and the year (p < .001) were sources of the high heterogeneity. Meta‐regression indicated that it tended to increase gradually for the last 10 years (t = 3.71, p = .006). The trends increased in Europe (t = 4.23, p = .006), Africa (t = 3.75, p = .006) and obstetrics (t = 3.66, p = .015). However, no statistical significance was found in ICU (t = −.14, p = .893), oncology (t = −0.44, p = .691) and emergency department (t = −0.30, p = .783).ConclusionsA significant number of nurses were found to have moderate‐high levels of burnout syndrome for the last 10 years. The meta‐analysis also indicated an increased trend over time. Therefore, more attention to the prevalence of nursing burnout syndrome is urgently required.Relevance to Clinical PracticeHigh prevalence of nursing burnout may attract more attention from the public. This analysis may serve as an impetus for relevant policy to change nurses' working conditions and reduce the occurrence of burnout.

Background: Loneliness is a common public health problem that influences people’s physical and mental health. There is a high incidence of loneliness in adolescents. Some research suggested that smartphone or Internet addiction (SA or IA) may be a factor. But the relationship between loneliness and SA or IA is not completely clear among adolescents. We aim to estimate the correlation coefficient r between them. Methods: Databases, consisting of PubMed and Web of Science, were retrieved systematically for studies of the association between adolescents’ loneliness and SA or IA. The Newcastle-Ottawa Scale was chosen as an assessment tool in this analysis. We estimated the correlation coefficient r between loneliness and SA or IA and drew a forest plot. Moreover, moderator analyses were also conducted to explore what leads to heterogeneity in our study. Results: 21 studies were finally included in our analysis with 27,843 samples. The pooled correlation coefficient r was 0.252 (95% confidence interval: [0.173, 0.329]; p < 0.001) with low heterogeneity (I2 = 0.000%; Q = 23.616; p < 0.001), indicating a moderate positive association. The funnel plot indicated small publication bias. A one-study removal sensitivity analysis indicated there was no significant difference between these studies. Meta-regression indicated no significant difference between the results and age (Q = 11.94, df = 18, p = 0.8504). Conclusions: Our analysis indicated a moderate positive association between loneliness and SA or IA. The results may attract the attention of some experts who study adolescent psychological problems and behavioral problems and may provide ideas for their research in the future.

Objective The purpose of this study was to develop a model for predicting severe Mycoplasma pneumoniae pneumonia (SMPP) in pediatric patients with Mycoplasma pneumoniae pneumonia (MPP) on admission by laboratory indicators. Methods Pediatric patients with MPP from January 2019 to December 2020 in our hospital were enrolled in this study. SMPP was diagnosed according to guideline for diagnosis and treatment of community-acquired pneumonia in children (2019 version). Prediction model was developed according to the admission laboratory indicators. Receiver operating characteristic curve and Goodness-of-fit test were analyzed for the predictive value. Results A total of 233 MPP patients were included in the study, with 121 males and 112 females, aged 4.541 (1–14) years. Among them, 84 (36.1%, 95% CI 29.9–42.6%) pediatric patients were diagnosed as SMPP. Some admission laboratory indicators (immunoglobulins M (IgM), eosinophil proportion, eosinophil count, hemoglobin, erythrocyte sedimentation rate (ESR), total protein, albumin and prealbumin) were found statistically different (p &lt; 0.05) between non-SMPP group and SMPP group. Logistic regress analysis showed IgM, eosinophil proportion, eosinophil count, ESR and prealbumin were independent risk factors for SMPP. According to these five admission laboratory indicators, the prediction model for SMPP in pediatric patients was developed. The area under curve of the prediction model was 0.777, and the goodness-of-fit test showed that the predicted SMPP incidence by the model was consistent with the actual incidence (χ2 = 244.51, p = 0.203). Conclusion We developed a model for predicting SMPP in pediatric patients by admission laboratory indicators. This model has good discrimination and calibration, which provides a basis for the early identification SMPP on admission. However, this model should be validated by multicenter studies with large sample.

Background: QTc prolongation is one of the possible complications in patients with schizophrenia taking antipsychotics, which leads to malignant cardiac arrhythmia. No meta-analysis has been reported assessing the prevalence and correlated risk factors for QTc prolongation. Methods: This meta-analysis aimed to assess the evidence for the prevalence of QTc prolongation and correlated risk factors in patients with schizophrenia taking antipsychotics. Web of Science and PubMed were searched according to preset strategy. The quality of research was assessed by the Newcastle–Ottawa Scale (NOS). Results: In all, 15 studies covering 15,540 patients with schizophrenia taking antipsychotics were included. Meta-analysis showed that the prevalence of QTc prolongation in patients with schizophrenia taking antipsychotics was about 4.0% (95% confidence interval (CI): 3.0%–5.0%, p < 0.001). The prevalence was about 4.0% in Asia (95%CI: 3.0%–6.0%, p < 0.001), about 5.0% in Europe (95%CI: 2.0%–7.0%, p < 0.001), and about 2.0% in America (95%CI: 1.0%–3.0%, p < 0.001). Sensitivity analyses indicated the robustness of the result. Publication bias analysis reported a certain publication bias ( t = 3.37, p = 0.012). Meta-regression suggested that female and elderly patients were clinically associated with a higher prevalence of QTc prolongation. According to included studies, smoking, comorbidity of cardiovascular disease, and abnormal levels of high-density lipoprotein/low-density lipoprotein might be related to QTc prolongation in patients with schizophrenia taking antipsychotics. Conclusions: The prevalence of QTc prolongation in patients with schizophrenia taking antipsychotics was about 4.0%. Female and elderly patients were more likely to experience QTc prolongation. Close electrocardiogram monitoring was suggested in these at-risk populations.