mohsen saheban maleki

Considering the increasing demand and costs of health care, it is necessary to know the practical aspects of digital health as a new field in service provision and doctor-patient interaction. The aim of the present study was to analyze the applications of digital health in Iran with a scientometric approach.

The current study is an applied research in terms of objectives, descriptive in terms of data collection method, and was carried out with an scientometric approach. All publications in the field of digital health in PubMed, Web of Science, Scopus and IEEE Xplore databases were retrieved by searching and extracting words according to medical subject headings and authoritative texts within target years. The VOSviewer and HistCite softwares were used to draw the word co-occurrence map.

The results of this study showed that the annual increase in digital health studies has occurred from 2012 to 2022. The highest frequency of vocabulary was observed in machine learning (33 cases), and mobile health (24 cases), and the lowest was observed in gamification and robotics (2 cases). In addition, the scientific map showed that out of 198 nodes, the four main clusters in the field of digital health in Iran, including deep learning, mobile-based programs, humans, virtual reality and artificial intelligence, have been considered more, and in areas such as COVID-19, pregnancy and other subcategories, mobile phone-based programs have been developed.

Analysis of the applications of digital health in Iran showed that although some topics such as deep learning and virtual reality have emerged, providing appropriate infrastructure, training different groups of users, and making a favorable transformation in the field of health and treatment are highly significant, which should be taken into account by managers and policymakers.

The recent novel coronavirus disease 2019 (COVID-19) pandemic has underlined the importance of risk score models in public health emergencies. This study aimed to develop a risk prediction score to identify high-risk hospitalized patients for disease progression on admission.

This prospective cohort study included 171 COVID-19 patients, identified through the reverse transcription polymerase chain reaction test, admitted to Bohlool Hospital in Gonabad City, Iran, between April 4 and June 5, 2021. The patients’ demographic, clinical, and laboratory data were collected upon admission, and clinical outcomes were monitored until the end of the study. The discovery dataset (80% of the data) was used to develop the risk score model based on clinical and laboratory features and patient characteristics to predict COVID-19 progression. An additive risk score model was developed based on the regression coefficients of the significant variables in a multiple logistic regression model. The performance of the risk score model was evaluated on the validation dataset (20% of the data) using the receiver operating characteristic (ROC) curve. Statistical analyses were performed with SPSS software, version 21.

The Mean±SD for age of participants was 59.54±20.52 years, and 48.6% were male. Most patients (82.5%) fully recovered or showed improvement, while 5.2% experienced disease progression and 12.3% died. Three variables, interleukin-6, neutrophil-to-lymphocyte ratio, and lung involvement, were found to be significant in predicting risk, with a good discriminatory ability, having an area under the ROC curve of 0.970 (95% CI, 0.935%, 1.00%) in the discovery set and 0.973 (95% CI, 0.923%, 1.00%) in the validation set.

The developed risk score model in this study can be used as a clinical diagnostic tool to identify COVID-19 patients at higher risk of disease progression and aid in informed decision-making and resource utilization in similar situations, such as respiratory disease outbreaks in the post-corona era.

Digital health technologies are transforming healthcare delivery globally. The purpose of the current study was to identify and map the current status of digital health applications in Iran through providing graphical/tabular classifications on the studies conducted in this field.

Following PRISMA guidelines, relevant English-language papers on digital health in Iran published from 2012 until 2023 in online scientific databases, including PubMed, Scopus, Web of Science and IEEE Xplore were screened. A total of 97 papers were selected for data extraction data including digital heath technologies, medical fields, application areas and users.

The number of publications has grown considerably since 2016. The most common digital health technologies were artificial intelligence including machine learning (34%), mobile health (25%) and telehealth (16%). These were mostly applied in infections (16%), nutrition/metabolism disorders (13%), mental health (20%) and cancers (12%). The key application areas were education (21%), therapy (16%) and diagnosis (15%). The primary users were patients (45%) and healthcare professionals (42%).

Digital health studies in Iran are continuously evolving. The activities are focused on a few technologies like artificial intelligence, with applications in diverse medical subfields for objectives like education and diagnosis. These results help identify research gaps and future directions for advancing digital health in Iran.

Knowing the factors that lead to job satisfaction is essential for employees and employers to improve the work environment. This study investigates the relationship between job satisfaction and the prevalence of musculoskeletal symptoms in the Allameh Behlool Gonabadi Hospital in 2021.

This cross-sectional study was performed on 107 employees of Allameh Behlool Hospital in Gonabad in 2021. A demographic information checklist, Nordic standard questionnaire, and Minnesota job satisfaction questionnaire were used. Collected data were entered into SPSS software version 24 and interpreted using descriptive and analytical statistics. The significance level for all analyses was considered 0.05.

 The mean age of the participants was 31.10±6.45, and the mean job satisfaction score was 55.08± 10.34. According to the Minnesota Job Satisfaction Questionnaire, 48 people had average satisfaction, and 59 had unsatisfactory satisfaction. There was no significant relationship between musculoskeletal symptoms and job satisfaction; however, musculoskeletal symptoms were higher in people with unfavorable job satisfaction.

 The prevalence of musculoskeletal disorders and job dissatisfaction in hospital staff is high, which can play an essential role in reducing their work efficiency and disability. Therefore, due to the special position of hospital staff in the health system, measures are recommended to improve workplace ergonomics and solve the psychological problems of these people.

Traumatic brain injury (TBI) is one of leading cause of death and disability in Iran that has serious consequences on people’s health. Understanding of epidemiology of TBI can be helpful for policy making in health care management. Therefore, this study aimed to examine the epidemiology of TBI in Iran.

PubMed, Web of Science, Scopus, Google scholar, and internal databases including, SID, Magiran, and IranMedex were searched to identify the relevant published studies up to Feb 2022. Moreover, the references list of key studies was scanned to find more records. The Joanna Briggs Institute (JBI) tool was used to assess the quality of included studies. The Excel and Comprehensive Meta-Analysis software were to analyze the data.

Overall, 23,446 patients from 15 studies were included in the study. The overall mean age of the patients was 31.36 ± 0.13 yr (95%CI: 31.10 to 31.61). The majority of the patients were male (74.37%), with a male to female ratio of 3:1. The incidence rate of TBI was 15.3 to 144 per 100,000 population. The mortality rate of TBI was esti-mated to be 10.4% (95%CI: 5% to 19%). The most common causes of injury were road traffic accidents (RTAs) (60%; 95%CI: 49% to 70%), and falling (20%; 95%CI: 16% to 26%), respectively. The most frequent type of head injury was subdural hematoma.

Our findings highlight that appropriate control and prevention strategies should be focused on male, road traffic accidents, and the group under 40 yr.

There are many well-known biologic and anthropometric risk factor for developing cardiovascular diseases (CVD). Shift work (SW) may be associated with CVD risk factors.

This study was performed to investigate the relationship of shift work and some of CVD risk factors.

This analytical cross-sectional study was done in Occupational Medicine Center of Gonabad University of Medical Sciences from April to December in 2021. A total of 743 workers who referred for periodic health examination were selected by simple random sampling. Those workers with at least one year of work experience who had Satisfaction for participation were included to the study. Having congenital heart disease, heart failure, kidney disease, Taking drugs that increase blood pressure, blood lipid and sugar and pregnant women were excluded.  Demographic data, Physical examination and Blood cholesterol, triglyceride and glucose measures were collected. Data analysis was performed using Mann–Whitney U test, student t-test, Chi-Square and Multivariate Linear Regression model with SPSS software version 21 at a significant level of 0.05.

Of total, 73.4% were men and 47.3% were shift workers. The mean (Standard Deviation) of age was 33.9 (5.07) among shift workers, and 36.32 (5.81) among Day-time workers. There was significant independent association between shift work and triglyceride (B=7.5, 95%CI=1.02,1.21, P=0.03) and cholesterol (B=7.2, 95%CI=1.12,1.22, P=0.028) values.

The results of the present study showed that the concentration of blood triglycerides and cholesterol is higher in shift workers than day-time workers. Therefore, particular follow-up of shift workers should be recommended for screening and preventing cardiovascular risk factors

 Postoperative shivering is unpleasant and annoying for the patient, occurring in up to 65% of cases undergoing general anesthesia. Various mechanisms were suggested for postoperative shivering. Shivering after anesthesia can cause complications, such as cardiovascular conditions, bleeding, and infection. This study compared the effects of dexamethasone, pethidine, and ketamine on the prevention of shivering after general anesthesia.

 In total, 164 patients with ASA classes one and two in the age range of 20-60 years under general anesthesia with orthopedic surgery, urology, and general surgery were included in the study. This study was a double-blind, randomized, placebo-controlled study. The study patients were divided into 4 groups of 41 subjects. After the induction of anesthesia and before surgery, in the first group, dexamethasone 0.15 mg/kg body weight, in the second group, ketamine 0.5 mg/kg, in the third group, pethidine 0.5 mg/kg, and in the fourth group, normal saline 0.9% were all given in 2 cc volume. After surgery, the examined patients were monitored for visible shivering by the researcher. The obtained data were analyzed using SPSS.

 The frequency and severity of shivering were lower in the dexamethasone (P=0.009), pethidine (P=0.004), and the ketamine (P=0.000) groups, compared to the control group. Besides, there was a significant difference between each of these 3 groups and the controls. The frequency and severity of shivering in the dexamethasone group were not significantly different from those of the pethidine group (P=0.565). The frequency and severity of shivering in the dexamethasone and ketamine groups were not statistically significant (P=0.071). The frequency and severity of shivering in the pethidine group with ketamine were not statistically significant (P=0.063).

 The obtained results indicated that dexamethasone, pethidine, and ketamine were effective in preventing postoperative shivering. There was no difference between these medications in the prevention of postoperative shivering.

The Rh blood group system is a complex blood group which includes different antigen specificities such as c antigen. Anti-c antibody is associated with both acute and delayed hemolytic transfusion reactions as well as hemolytic disease of the newborn (HDN). Rh mediated hemolytic transfusion reactions (HTR) are mostly immunoglobulin G (IgG) mediated and results in extravascular hemolysis and delayed HTR (DHTR). However, we are presenting a case of acute intravascular hemolytic transfusion reaction due to anti-c in a patient with acute subdural hematoma. A 77-year-old woman was referred to our hospital with a loss of conscious and left-sided hemiparesis. After an emergency MRI, she was diagnosed with Acute Subdural hematoma, and an emergency craniotomy was performed. Since Acute Subdural hematoma is a neurosurgery emergency, laboratory technician performed an Immediate-spincrossmatchedd for blood bag to preserve time. During the transfusion of the first packed cell, the patient developed severe hypotension and tachycardia. Thus, the transfusion was stopped. Laboratory results raised the suspicion of an Acute Intravascular Hemolysis. Antibody identification revealed that the patient had an irregular blood phenotype (C2+/c-/E-/e3+/K-), and the presence of alloantigen-c Rh antibody confirmed the suspicion of HTR. In patients with multi transfusion history and pregnant women, pre-transfusion screening of irregular antibodies must be performed. The immediate spincrossmatchh must be prevented in patients with a history of multi transfusions, even in emergency situations.

The prevalence of sleep disorders in the general population is between 26.4% and 39.4% in Asia, which has increased in Iran in recent decades. Low sleep quality and reduced sleep hours result in work impairment and physical and mental illnesses. This study aimed to improve sleep quality and determine the factors affecting the quality of sleep.

This cross-sectional study was performed in 2018 among 243 employees presenting to the Center for Occupational Medicine at Gonabad University of Medical Sciences. Demographic data such as age, shift work and education level were asked of the staff. Weight, blood pressure, height and waist circumference were measured. The sleep quality score was extracted by completing the Pittsburgh Sleep Quality Index. Glucose, triglyceride and cholesterol were also measured. Logistic regression analysis was performed. Significance level was set at 0.05.

Among 243 men studied, 99 men (40.7%) had low sleep quality and 126 men (51.9%) reported sleeping less than seven hours a day. age (p=0.021) and waist circumference (p=0.036) and shift work had a direct effect while education had a reverse effect on the quality of sleep. Fasting blood suger, cholesterol, triglesride, body mass index did not have a significant effect on sleep quality.

Low sleep quality and inadequate sleep hours causes physical and psychological complications, which mandates planning and training to reduce factors affecting low sleep quality.