Background: The effect of related factors on recovery or death rates may vary from country to country. Therefore, we aimed to investigate the relationship between demographic, clinical, laboratory factors on the survival rates of confirmed cases of COVID-19 in Shahroud, Iran. Methods: This is an analytical study of the estimation of the survival of patients with COVID-19. Patients who had positive PCR test were considered as COVID-19 cases, and the 2-month survival of these patients was estimated. Among the diseases, heart disease and diabetes were considered as separate variables, and the patients' histories of other diseases were included in the model as comorbidities. Results: Of 396 confirmed patients hospitalized, 109 patients (27.5%) had a history of heart disease, 100 (25.3%) were diabetic, and 80 (20.2%) had a history of other comorbidities. The number of deaths due to the disease was 59 (14.9%). The median age of those who died was 76 years. The multivariate Cox regression analysis shows that heart disease increases hazard ratio more than two times (HR=2.37, 95% CI: 1.33-4.23). The neutrophil-to-lymphocyte ratio (NLR) factor, (HR=1.15, 95% 1.08-1.22), and older age (HR=1.06, 95% CI: 1.03-1.08) increases the risk of death significantly. Conclusion: The heart disease history, NLR factor and older age are associated with death of COVID-19 and may be helpful for the early warning and prediction of disease progression.

Aim This study aimed to evaluate the effect of prenatal interventions on maternal foetal attachment. Design Systematic review and meta‐analysis. Methods In this study, a comprehensive review was performed to find articles published from January 2000 ‐ December 2019 in the form of randomized and non‐randomized clinical trials. To this end, online databases including PubMed, Scopus, Google Scholar, ScienceDirect, Proquest, Ovid, CINAHL and JAMA were searched. Duplicate articles were also excluded using Endnote X7 Reference. The results were then analysed via RevMan 5.3 software. Results The results showed that foetal movement counting did not seem to be effective in increasing MFA by itself. But, this intervention alongside other attachment behaviours such as touching the belly and talking to foetus could enhance MFA. Therefore, the best interventions to improve MFA might be combined ones implemented in the form of counselling and training sessions.

The Support Vector Regression (SVR) model has been broadly used for response prediction. However, few researchers have used SVR for survival analysis. In this study, a new SVR model is proposed and SVR with different kernels and the traditional Cox model are trained. The models are compared based on different performance measures. We also select the best subset of features using three feature selection methods: combination of SVR and statistical tests, univariate feature selection based on concordance index, and recursive feature elimination. The evaluations are performed using available medical datasets and also a Breast Cancer (BC) dataset consisting of 573 patients who visited the Oncology Clinic of Hamadan province in Iran. Results show that, for the BC dataset, survival time can be predicted more accurately by linear SVR than nonlinear SVR. Based on the three feature selection methods, metastasis status, progesterone receptor status, and human epidermal growth factor receptor 2 status are the best features associated to survival. Also, according to the obtained results, performance of linear and nonlinear kernels is comparable. The proposed SVR model performs similar to or slightly better than other models. Also, SVR performs similar to or better than Cox when all features are included in model.

Background: Early diagnosis and supportive treatments are essential to patients with coronavirus disease 2019 (COVID-19). Therefore, the current study aimed to determine different patterns of syndromic symptoms and sensitivity and specificity of each of them in the diagnosis of COVID-19 in suspected patients. Study Design: Cross-sectional study Methods: In this study, the retrospective data of 1,539 patients suspected of COVID-19 were obtained from a local registry under the supervision of the officials at Shahroud University of Medical Sciences, Shahroud, Iran. A Latent Class Analysis (LCA) was carried out on syndromic symptoms, and the associations of some risk factors and latent subclasses were accessed using one-way analysis of variance and Chi-square test. Results: The LCA indicated that there were three distinct subclasses of syndromic symptoms among the COVID-19 suspected patients. The age, former smoking status, and body mass index were associated with the categorization of individuals into different subclasses. In addition, the sensitivity and specificity of class 2 (labeled as "High probability of polymerase chain reaction [PCR]+ ") in the diagnosis of COVID-19 were 67.43% and 76.17%, respectively. Furthermore, the sensitivity and specificity of class 3 (labeled as "Moderate probability of PCR+ ") in the diagnosis of COVID-19 were 75.92% and 50.23%, respectively. Conclusions: The findings of the present study showed that syndromic symptoms, such as dry cough, dyspnea, myalgia, fatigue, and anorexia, might be helpful in the diagnosis of suspected COVID-19 patients.

Objectives: Severe fear of childbirth (FOC) has adverse consequences for mother and child. This study aimed to update the global prevalence of severe FOC in low-risk pregnant women. Materials and Methods: Observational studies published in English were obtained through PubMed, Scopus, Science Direct, Wiley Online, and Google Scholar databases up to April 2020. After reviewing the title and introduction, the quality of the articles that had full text and met the inclusion criteria of the study was checked with the JBI checklist. Then, the final extracted data were entered into the STATA software. The overall prevalence of severe FOC and fear in subgroups were obtained using meta-analysis. Tests of publication bias and sensitivity analysis were also performed. Results: Overall, 27 observational studies were included (26014 participants). The global prevalence of severe FOC was 16% (95% CI: 14%–19%). The subgroup analysis showed that after 2015, the prevalence of fear was higher than before (%18 versus %14). The results also showed a higher prevalence of fear in women with a diploma and lower compared to women with a university education (%19 versus %13), in single/divorced women compared to married/cohabitation women (%21 versus %15), in nulliparous women compared to multiparous women (%17 versus %14) and in women experiencing the second trimester of pregnancy compared to women in the third trimester of pregnancy (%23 versus %14). Conclusions: The global prevalence of severe FOC was 16%. Diagnostic, preventive, therapeutic and follow-up strategies are needed to reduce fear in all countries.