Iranian Red Crescent Medical Journal
Year:2021 | Volume:23 | Issue:7|Papers Count:10

Background: Universal health coverage is considered a prerequisite for human health and security. Objectives: The current study aimed to evaluate and compare the healthcare system functions in Iran with those in successful developing countries in terms of universal health coverage (UHC). Methods: In this comparative study, three developing countries, namely Turkey, Thailand, and China were selected based on former studies, and the model presented by the World Health Organization in 2000 was used to compare and analyze the data. The required information from the selected countries was collected through searching the Pub Med and Scopus databases using the following keywords: “ Health system review” , “ Health system transition” , “ International profiles of healthcare systems” , “ Financing” , “ Resource generation” , “ Service provision” , “ Universal health coverage” , and “ Health system reform” . Results: The evaluation of the healthcare system’ s function in four countries showed that the public sector’ s share of total health expenditures was much higher than the private sector in both Thailand and Turkey. The issues that need to be addressed include the integration of insurance funds and risk accumulation, as well as the existence of a strong buyer organization. The comparison of the payment system in the studied countries indicated that the per capita method was used in all domains of primary care, and the inpatient diagnostic group (diagnosis-related group), fee for service, and salaries and rewards were more focused in the context of hospitalization. The majority of hospitals in the studied countries were state-owned; however, the important point was the presence of different non-university public hospitals in these countries, compared to Iran. Conclusion: In general, one way to reach the UHC is to utilize the experiences of successful countries in establishing and maintaining this issue.

Background: Effectiveness of autologous stem cell transplantation (ASCT) in patients with relapsed/refractory lymphoma is accepted by all authors. After ASCT, the 5-year overall survival rates can reach up to 80%. However, returning to work after ASCT and the employment status of these patients are unknown. Objectives: This study aimed to examine the rate of not returning to work in the post-treatment period and the factors that may affect the employment status of patients who underwent ASCT with the diagnosis of relapsed/refractory lymphoma. Methods: This cross-sectional study was conducted from January to June 2020. It was performed on patients within the age ranges of 18-65 who had undergone ASCT with the diagnosis of relapsed or refractory lymphoma and were in remission without recurrence one year after ASCT. Results: In total, 80 (74. 8%) out of 107 patients included in the study were male, and the median age was 49. 0 (21-63). Majority of participants were primary school graduates (n=66, 61. 7%) and married (n=90, 84. 1%). Before ASCT, 30 (28. 0%) patients worked in the private sector and 17 (15. 9%) of them were self-employed. The median follow-up time was 34. 8 months (12. 4-124. 7 months). During this follow-up period, 35 (57. 3%) out of 61 patients did not return to work. Most of these patients had retired (n=29, 47. 5%). It was observed that having a higher education level (OR: 0. 32 [0. 14-1. 22] 95% CI, p: 0. 041) and being a public employee (OR: 0. 30 (0. 12-0. 97) 95% CI, p: 0. 033) are independent factors that reduce the risk of not returning to work. Conclusion: It was found that more than half of the patients did not return to work. The low level of education and employment in non-public sectors posed the risk of not returning to work. It may be possible for patients to return to work with well-planned options, such as part-time shifts.

Background: Pain, anxiety, and depression are common but often neglected problems in patients with cancer. Objectives: Considering the importance and impact of anxiety and depression as common psychiatric symptoms in people with cancer, the present study aimed to assess the effectiveness of escitalopram in the reduction of pain, anxiety, and depression in patients with breast cancer. Methods: This single-blind controlled trial was conducted on 32 patients diagnosed with breast cancer who were referred for modified radical mastectomy (2018-2019). The intervention group received daily oral capsules containing 10 milligrams of escitalopram for four weeks, while the control group received placebo capsules containing starch on a daily basis. Hospital Anxiety and Depression Scale (HADS) and Visual Analogue Scale were administered to the patients at the commencement of the study and four weeks after the intervention. In addition, at baseline examination, personality factors were assessed by the NEO Five-Factor Inventory-3 questionnaire. Results: Based on the results, the scores of HADS anxiety, total HADS, and pain reduced after the intervention in the case group; however, the HADS depression score demonstrated a slight increase. A significant difference was observed between the case and control groups for HADS anxiety score after the intervention (P=0. 01). The correlation of personality characteristics with HADS anxiety and depression subscales pointed out a significant negative correlation between the HADS depression score and conscientiousness (r=-0. 40; P<0. 05). Conclusion: Due to minor side effects of escitalopram, this drug is suggested to be used for the reduction of anxiety symptoms and pain intensity in patients with breast cancer.

Background: Recently, melatonin has attracted massive attention due to its anticancer effect on various human malignancies. It has also been demonstrated that melatonin is useful in combating resistance against conventional chemotherapeutics. Objectives: This study aimed to evaluate melatonin’ s effects on multidrug resistance (MDR) in human myelogenous leukemia cells. Methods: Melatonin’ s cytotoxicity on the K562 and K562/doxorubicin (DOX) cell lines was assessed using 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide (MTT) assay. The expression and activity of P-glycoprotein (P-gp) were measured as well. The mRNA and protein expression levels of tensin homolog deleted on chromosome ten (PTEN) was assessed in cells. Eventually, apoptosis in cancer cells was measured through Annexin V/PI staining. Results: Treatment with melatonin significantly increased the cytotoxicity of DOX in resistant K562 cells. The expression and activity of P-gp were attenuated following melatonin treatment. In addition, melatonin upregulated PTEN in K562/DOX cells. Melatonin also augmented apoptosis in combination with DOX. Conclusion: Melatonin effectively increased the cytotoxic effects of DOX in K562/DOX cells through down-regulation of P-gp and up-regulation of PTEN in resistant K562 cells.

Background: Nowadays, it can be seen that changes have taken place in the process of diseases and their clinical parameters. Accordingly, in some cases, general medical science and the use of clinical statistics based on the experiences of the physicians are not enough for the provision of sufficient tools for an early and accurate diagnosis. Therefore, medical science increasingly seeks to use unconventional methods and machine learning techniques. The issue of diagnosis in the medical world and the error rate of physicians in this regard are among the main challenges of the condition of patients and diseases. For this reason, in recent years, artificial intelligence tools have been used to help physicians. However, one of the main problems is that the effectiveness of machine learning tools is not studied much. Due to the sensitivity and high prevalence of diseases, especially gastrointestinal cancer, there is a need for a systematic review to identify methods of machine learning and artificial intelligence and compare their impact on the diagnosis of lower gastrointestinal cancers. Objectives: This systematic review aimed to identify the machine learning methods used for the diagnosis of lower gastrointestinal cancers. Moreover, it aimed to classify the presented methods and compare their effectiveness and evaluation indicators. Methods: This systematic review was conducted using six databases. The systematic literature review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement for systematic reviews. The search strategy consisted of four expressions, namely “ machine learning algorithm” , “ lower gastrointestinal” , “ cancer” , and “ diagnosis and screening” , in that order. It should be mentioned that studies based on treatment were excluded from this review. Similarly, studies that presented guidelines, protocols, and instructions were excluded since they only require the focus of clinicians and do not provide progression along an active chain of reasoning. Finally, studies were excluded if they had not undergone a peer-review process. The following aspects were extracted from each article: authors, year, country, machine learning model and algorithm, sample size, the type of data, and the results of the model. The selected studies were classified based on three criteria: 1) machine learning model, 2) cancer type, and 3) effect of machine learning on cancer diagnosis. Results: In total, 00 studies were included in this systematic literature review. The earliest article was published in 2010, and the most recent was from 2012. Among the studies reviewed in this systematic review, one study was performed on the rectum (rectal cancer), one was about the small bowel (small bowel cancer), and 02 studies were on the colon (colon cancer, colorectal cancer, and colonic polyps). In total, 12 out of the 00 (034) articles from the systematic literature review presented a deep learning model, and 22 (274) articles used classic machine learning. The models worked mostly on image and all of them were supervised learning models. All studies with deep learning models used Convolutional Neural Network and were published between 2011 and 2012. The studies with classic machine learning models used diverse methods, mostly Support Vector Machine, K-Nearest Neighbors, and Artificial Neural Network. Conclusion: Machine learning methods are suitable tools in the field of cancer diagnosis, especially in cases related to the lower gastrointestinal tract. These methods can not only increase the accuracy of diagnosis and help the doctor to make the right decision, but also help in the early diagnosis of cancer and reduce treatment costs. The methods presented so far have focused more on image data and more than anything else have helped to increase the accuracy of physicians in making the correct diagnosis. Achievement of the right method for early diagnosis requires more accurate data sets and analyses.

Background: Performance evaluation of accreditation schemes can improve the quality of hospital accreditation significantly. An effective accreditation system is one that performs the accreditation process properly and achieves acceptable results. Objectives: This study aimed to design and validate the performance evaluation model of national accreditation schemes in hospitals. Methods: This study was performed in a mixed method. The performance evaluation dimensions of the national accreditation models for hospitals were identified, classified, and modeled using the qualitative research method. The quantitative aspect of the obtained model was tested using structural equation modeling. Results: All identified variables were classified into six dimensions including causal conditions, strategic conditions, axial phenomenon, context conditions, intermediary/interventional conditions, and consequence. The results of the quantitative part suggested that the proposed model had a good fit and its validity and reliability were confirmed. Conclusion: The results of the present study revealed that the performance evaluation model of national accreditation schemes in hospitals had a good fit and might be used as an effective model in accreditation organizations as a roadmap to better evaluate accreditation schemes, such as those used in hospitals.

Background: The simultaneous interpretation of computed tomography (CT) scans performed on patients with suspected clinical signs of coronavirus disease 2019 (COVID-19) or a history of contact may accelerate patient isolation, particularly during the peak of the pandemic. The use of an appropriate scoring system can lead to the conveyance of the findings in a more understandable way and the elimination of differences in interpretations. Objectives: This study aimed to evaluate the diagnostic performance of the coronavirus disease 2019 (COVID-19) imaging reporting and data system (CO-RADS) in admitted patients with suspected COVID-19 infection. Methods: This retrospective study included all patients admitted to our hospital with COVID-19 pneumonia suspicion within March 20-May 15, 2020, who were examined by both CT and real-time reverse transcription polymerase chain reaction (rRT-PCR) at initial presentation. Four radiologists, who were blinded to the rRT-PCR results and medical history, assessed all images independently and classified the CT findings according to the CO-RADS previously defined. Diagnostic value of the scoring system and interobserver agreement in rRT-PCR positive-negative groups and for CO-RADS 1-5 were evaluated. Results: In this study, 274 (153 men and 121 women; 48. 8± 17. 3 years) rRT-PCR positive and 437 (208 men and 229 women; 49. 0± 19. 5 years) rRT-PCR negative individuals were included. It was found that CO-RADS had a good diagnostic performance with area under the receiver operating characteristic roc curve of 0. 857. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were obtained at 81. 9%, 89. 4%, 75. 7%, 92. 5%, and 84. 8%, respectively. The interobserver agreement of four radiologists in CO-RADS 1 and 5 was substantial to almost perfect according to the kappa values. Other CO-RADS scores showed a fair to moderate agreement. The interrater agreement was slightly higher in the PCR (-) patient group than in the positive one. Conclusion: In conclusion, CO-RADS was a successful scoring system for distinguishing highly suspicious cases in terms of COVID-19 infection lung involvement, showing high interobserver agreement.

Background: Today, organization management in healthcare organizations needs to monitor and evaluate performance for better decision and policy making. Objectives: This study aimed at determining the Key Performance Indicators (KPIs) using software and a management dashboard. Methods: This study searched several articles discussing KPIs of emergency departments. A comprehensive list of indicators was obtained and presented to an expert panel with a wide range of experiences. The experts finalized the KPIs. A second round was performed to confirm the performance using Smart Pilates software. Based on the final panel’ s rating, a list of KPIs was developed to be used. The extracted data was prepared to be entered into the computer system to design the dashboard using QlickView software. Subsequently, according to the type of indicator, the dashboard was designed with special software. Results: The extracted 14 KPIs of emergency departments were determined in three dimensions of input, process, and output. Following that, the project team designed a dashboard with 14 KPIs. Conclusion: To design and develop a dashboard, the management of information was essential for organizations. It is recommended that managers use KPIs for evaluating and monitoring emergency departments. Moreover, it can be used for planning and evaluating the performance in emergency departments.

Background: Breast cancer is the most common malignancy and a leading cause of death in women. Viruses are known to be the risk factors for breast cancer. Objectives: This systematic review and meta-analysis aimed to evaluate the association between human papillomavirus (HPV) and the development of breast cancer in Iranian women. Methods: The international databases, including Web of Science, Embase, PubMed, Cochrane, and Scopus, were searched in this study. Furthermore, relevant studies published on the association between HPV and breast cancer were identified using the appropriate keywords. The data were analyzed in Stata software (version 14) using the random-effects model. Results: In total, 18 studies were found eligible to be included in this study. The total sample size was determined at 2466 cases with the mean ages of 47. 25 and 39. 9 years for experimental and control groups. The overall findings showed a significant relationship between developing breast cancer and HPV infection. The results also revealed that the HPV infection increased the risk of breast cancer in women 5. 02 fold more than those without HPV infection (95% CI: 3. 46-7. 29, I2=65. 2%, P=0. 003). In addition, the prevalence of HPV infection among women with breast cancer was estimated at 25. 66% (95% CI: 17. 34-34. 95, I2=86%, P=0. 000). Conclusion: HPV infections, especially high-risk HPVs, are significantly frequent in breast cancer samples and should be considered an important risk factor for developing breast cancer.

Background: Understanding the experiences of ICU patients with COVID‐ 11 helps to provide the unique care activities, improve the quality of care and promote health status, thereby creating a window for mutual understanding between the treatment team and the patients. Objectives: The present study aimed to explore lived experiences of critically ill patients with COVID-11 after discharge from intensive care units of hospitals in Iran. Methods: The present study was qualitative research with a hermeneutic phenomenological approach. Participants were purposefully selected from critically ill patients with COVID-11 who were discharged from the intensive care unit (ICU) and transferred to the general ward. Data were mostly collected through in-depth, semi-structured, face-to-face interviews and, in some cases, telephone calls. Data were analyzed using the method of Dickelman et al. (1196). Guba and Lincoln's (1191) criteria were used to achieve data authenticity. Results: Data were obtained from 15 COVID-11 recovered patients with a history of ICU admission. Twelve participants were female and four were male with a mean age of 26 years. The four main themes were identified along with their subthemes: perception of death before dying (worry, helplessness, and expecting a different death), social stigma (social isolation and stigma), a nurse as a symbol of rebirth (a compassionate and supportive nurse and the supportive role of others), and meaningful life (a change in outlook on life and the manifestation of spirituality). Conclusion: The results of the present study indicated that personal thoughts such as thinking about death and social treatments such as stigma can lead to threatening physical and psychological problems in COVID-11 patients. Nurses and family members can prevent many of these problems by providing holistic care and psychological support. Apart from the challenges posed by the disease, post-recovery changes in patients' attitudes toward life can be considered as a positive point.