Shiraz Emedical Journal
Volume:23 Issue: 5, May 2022

Diabetes is a chronic, underlying, and common disease worldwide that imposes an enormous burden on the health system. Diabetic retinopathy (DR) is a serious complication in the eye caused by diabetes and may lead to visual impairment and blindness. The knowledge about the risk factors of DR is critical for the prevention of disease and developing treatment options. Moreover, DR is a multifactorial disease, and many studies have demonstrated various risk factors associated with it, such as hyperglycemia, hypertension, hyperlipidemia, etc. In this review study, we survey the main risk factors of the development and progression of DR.

The aim of this study was to determine the effect of a team-based educational program through smartphone applications on Iranian nursing students’ problem-solving ability and clinical skills.

This quasi-experimental study with two groups, including an experimental and a control group, was conducted among 60 nursing students who spent internship period in post CCU and CCU wards for 16 weeks. The control group received routine training, and the students of the experimental group received a team-based program through a smartphone application in addition to routine training. Students involved in the program were invited to complete the clinical skills questionnaire and Heppner’s Problem-Solving Inventory at baseline and week four, and week 12 of follow-up. Data were analyzed using SPSS software (Version 22).

A significant improvement was found in nursing students’ clinical skills and problem-solving ability at week four and week 12 of follow-up compared with baseline (P < 0.001). However, the mean scores increased more in the experimental group.

This study suggests that team-based training through smartphone applications can enhance problem-solving perception and clinical skills in nursing students. It is expected that in the future, team-based training through smartphone applications may be used in the internship training of nursing students continuously.

One of the symptoms of mental health disorders is social isolation which refers to unfavorable social relationships with other people. Today, Internet use is an important predictor of social isolation.

The present study aimed to investigate the relationship between Internet use and social isolation (objective-subjective) in young and middle-aged individuals in the city of Shiraz.

This cross-sectional study was conducted on 600 young and middle-aged (15 - 65 years old) individuals in Shiraz, Iran. Data were collected using three questionnaires (objective isolation with four subscales, subjective isolation with two subscales, and the amount of Internet use). Regression analyses were used to analyze the data.

Regression analysis showed that in objective isolation, Internet use increased just two subscales, including network diversity (P < 0.001) and the level of social participation (P < 0.001). It can be argued that the Internet has partly reduced social isolation in the objective dimension. In the subjective dimension, Internet use has increased the received social support (P < 0.001). Thus, Internet use would reduce the level of social isolation in the subjective dimension (P < 0.001). Although the significance level of the relationship between Internet use and social isolation is almost the same in both generations, the intensity of middle-aged relationships is higher than that in young people.

Internet use has reduced social isolation; however, considering the low intensity of the reduction of isolation, it is argued that Internet use does not isolate people but just does not upgrade them much.

While chemotherapy is an effective method for the treatment of patients with cancer, it is a complex, multidisciplinary, and error-prone process. Paper-based protocols are commonly applied in chemotherapy; however, they fail to eliminate the complexity of this process. Therefore, a new guideline-based workflow software (GWS) system is needed to improve the workflow and quality of chemotherapy process.

Planning was initiated 11 months before the system implementation and it involved a multidisciplinary group to analyze the current chemotherapy workflow and protocols for identifying the workflow components, analyzing paper-based protocols, developing computer-based protocols, and designing of systems based on an object-oriented analysis. To implement the GWS, we applied a system based on Python programming language and SQL language.

The conceptual model was developed based on need assessments and chemotherapy steps. A minimum dataset was developed for the electronic health records. We established examination forms for the patient management system (PMS), as well as specific standard forms for chemotherapy ordering, prescription verification and administration templates. Finally, developed GWS system consisted of a PMS, computerized provider order entry (CPOE), prescription verification system (PVS), and nursing administration system (NAS).

A PMS, a PVS, a NAS, and a guideline-based clinical decision support system were integrated into the CPOE system to improve the chemotherapy process. Elimination of iterations and unnecessary steps in old chemotherapy workflow, improving patient safety, improvement of communication and coordination between healthcare providers, and use of updated evidence-based medicine in direct chemotherapy orders justify the deployment of GWS in the cancer care settings.

The prevalence of poisoning is on the rise in Iran. A poisoning registry is a key source of information about poisoning patterns used for decision-making and healthcare provision, and a minimum dataset (MDS) is a prerequisite for developing a registry.

This study aimed to design a MDS for a poisoning registry.

This applied study was conducted in 2021. A poisoning MDS was developed with a four-stage process: (1) conducting a systematic review of the Web of Science, Scopus, PubMed, and EMBASE, (2) examining poisoning-related websites and online forms, (3) classification of data elements in separate meetings with three toxicology specialists, and (4) validating data elements using the two-stage Delphi technique. A researcher-made checklist was employed for this purpose. The content validity of the checklist was examined based on the opinions of five health information management and medical informatics experts with respect to the topic of the study. Its test-retest reliability was also confirmed with the recruitment of 25 experts (r = 0.8).

Overall, 368 data elements were identified from the articles and forms, of which 358 were confirmed via the two-stage Delphi technique and classified into administrative (n = 88) and clinical data elements (n = 270).

The creation of a poisoning registry requires identifying the information needs of healthcare centers, and an integrated and comprehensive framework should be developed to meet these needs. To this end, a MDS contains the essential data elements that form a framework for integrated and standard data collection.

Anxiety during pregnancy may affect maternal-fetal attachment (MFA) and the prevalence of pregnancy symptoms.

The present study aimed to assess the correlation of anxiety with pregnancy symptoms and MFA.

This cross-sectional study was conducted on 220 pregnant women in the health centers of Tabriz, Iran, in 2020. Samples were selected by the cluster sampling method. Data were collected using the socio-demographic questionnaire, Pregnancy-related Anxiety Questionnaire-revised 2 (PRAQ-R2), MFA Scale (MFAS), and Pregnancy Symptoms Inventory (PSI), all of which were completed as self-administered in the second half of pregnancy. The Pearson’s correlation coefficient and adjusted general linear model were used for data analysis.

The results of Pearson’s correlation showed no correlation between anxiety during pregnancy and MFA among nulliparous (r = -0.003, P = 0.976) and multiparous (r = -0.003, P = 0.712) pregnant women. However, anxiety and pregnancy symptoms were significantly correlated among nulliparous (r = 0.424, P < 0.001) and multiparous (r = 0.227, P = 0.028) pregnant women. According to the general linearmodel, after adjusting the socio-demographic variables, a significant correlation was observed between anxiety and pregnancy symptoms (P < 0.001), while no relationship was found between anxiety and MFA (P = 0.705).

Given the significant correlation between anxiety and pregnancy symptoms, pregnant women with anxiety symptoms need to be screened and treated by an expert psychological team if their disorder is confirmed.

Coronavirus disease 2019 (COVID-19) is a life-threatening disease that has spread globally and received international concern. Iran is one of the countries severely affected by this pandemic, implementing social lockdown and restrictive strategies. According to Persian medicine, restrictions like quarantine have psychological and social consequences.

This study aimed to investigate the relationship between sleep quality and anger behaviors in Iran and compare it with Persian medicine viewpoints.

In this cross-sectional study, 739 participants were interviewed in April 2020 in Shiraz, Iran. The questionnaire included the Pittsburgh Sleep Quality Index (PSQI), the Multidimensional Anger Inventory (MAI), and items on demographics, temperament, and the quarantine situation social factors. All participants completed the questionnaires willingly and were ensured of data confidentiality.

We found that 58.3% of the participants had low sleep quality. Females showed higher scores on anger and its related aspects (P < 0.05). In addition, people with lower education and income levels revealed higher anger scores (P < 0.05). Moreover, the mean scores of anger and its related factors were higher in participants with low sleep quality, higher sleep latency, daytime dysfunction, and experience of using sleep medications (P < 0.05). Also, after adjustment for demographics and other social factors, the mean scores of anger and all of its aspects were higher in those with a sleep disorder, use of sleep medications, and daytime dysfunction (P < 0.05).

In conclusion, our findings illustrated that various factors, including low sleep quality, are associated with anger in individuals with the experience of home quarantine during the COVID-19 outbreak. The outcome is compatible with Persian medicine evidence.

The rapid coronavirus disease 2019 (COVID-19) outbreak has overwhelmed many healthcare systems worldwide and put them at the edge of collapsing. As the capacity of intensive care units (ICUs) is limited, deciding on the proper allocation of required resources is crucial.

This study aimed to create a machine learning (ML)-based predictive model of ICU admission among COVID-19 inhospital patients at the initial presentation.

This retrospective study was conducted on 1225 laboratory-confirmed COVID-19 hospitalized patients during January 9, 2020 - January 20, 2021. The top clinical parameters contributing to COVID-19 ICU admission were identified based on a correlation coefficient at P-value < 0.05. Next, the predictive models were constructed using five ML algorithms. Finally, to evaluate the performances of models, the metrics derived from the confusion matrix, classification error, and receiver operating characteristic were calculated.

Following feature selection, a total of 11 parameters were selected as the top predictors to build the prediction models. The results showed that the best performance belonged to the random forest (RF) algorithm with the mean accuracy of 99.5%, mean specificity of 99.7%, mean sensitivity of 99.4%, Kappa metric of 95.7%, and root mean squared error of 0.015.

The ML algorithms, particularly RF, enable a reasonable level of accuracy and certainty in predicting disease progression and ICU admission for COVID-19 patients. The proposed models have the potential to inform frontline clinicians and health authorities with quantitative tools to assess illness severity and optimize resource allocation under time-sensitive and resourceconstrained situations.

Plasma cell leukemia (PCL) is a rare and clinically aggressive form of plasma cell dyscrasia. Despite the significant role of BRAF mutation in plasma cell neoplasms, this mutation has been rarely considered in these cases. Finding evidence guiding us toward assessing the BRAF mutation in patients with plasma cell neoplasms could help make the suitable decision for targeted therapy.

A 79-year-old man presented with leukocytosis. Peripheral blood smear exhibited marked lymphocytosis and infiltration of about 50% abnormal lymphoid cells with slender cell-surface projections and oval shape nucleus. These findings raised the provisional diagnosis of hairy cell leukemia (HCL) or HCL variants (HCL-v). Molecular analysis confirmed the presence of BRAFV600E mutation, which was in agreement with HCL diagnosis, albeit the flow cytometric assessment of abnormal lymphocytes corroborated PCL.

Together with the previous comprehensive analysis regarding the association of cytoplasmic projections and BRAF mutations, our findings could suggest this morphological characteristic in plasma cells (PCs) as an indication for the assessment of BRAF V600E mutation in PC dyscrasias.

The implementation of WHO safe surgery checklist (SSC) was proposed by the Ministry of Health and Medical Education in the operation rooms of Iranian hospitals in 2011, but was canceled after several years due to some challenges in implementation.

This study aimed to investigate the barriers and facilitators of the effective implementation of the SSC.

This cross-sectional study was performed in public hospitals of Tabriz city in 2019. The study population consisted of operation room working staff, and the purposive sampling was used. The research tool was a researcher-made questionnaire designed through literature review and included three parts of demographic variables, barriers, and facilitating factors. Data were analyzed with SPSS-22.

The mean of barriers to implementation of the SSC was 3.03 out of 5. The most important barrier to implementing the checklist was the weakness in team working (3.18), while checklist barriers were the least important (2.98). The mean score of facilitating factors was 3.46. Among the facilitators, the highest score was for team working facilitators with a score of 3.47 and the lowest score was for the facilitators associated with the checklist with a score of 3.37.

This is one of the first studies that explored the barriers and facilitators of SSC implementation in Iranian hospitals. We identified weak team working as the most important barrier to implementing the checklist. These results help policymakers and hospital managers to implement the checklist more effectively.