The relationship between demographic factors and known risk factors with breast cancer in women aged 30-69.

Background: Breast cancer is one of the most important causes of cancer deaths in women. The present study was conducted to determine the relationship between demographic factors and known risk factors with breast cancer in women aged 30-69. Method: This case-control study was conducted with two matched and unmatched control groups. Three hundred fifty women aged 30-69 with breast cancer, 350 age-matched women without cancer, and 350 not age-matched women were included in the study. Controls were selected from the records of women whose breast cancer screening results were normal. Study subjects were evaluated regarding the risk factors for breast cancer. The data collection tool was a checklist including the risk factors investigated in the integrated health system. The collected data were analyzed utilizing SPSS22 software at a significance level of less than 0.05. Results: The average age in the case group was 46.63±11.77 years and 49.61±8.39 in the unmatched control group. The average age of marriage in the case group was 21.54±4.31, and the average age of women at first pregnancy in the case group was 24.06±3.39 years. In the case group, 163 people (46.57%) lived in the city, 221 people (63.14%) were over 40 years old, and 337 people (96.28%) were married. In multivariate analysis, the variable 'age of marriage' 0.821 (0.691-0.976) and 'age of first pregnancy' 1.213 (1.020-1.443) showed a significant relationship with breast cancer which were observed as predictors of breast cancer in comparison to the unmatched control group (P-value <0.05). Conclusion: The age of the first pregnancy and the type of delivery were observed as predictors of breast cancer. Therefore, by performing breast cancer screening in women who are exposed to these risk factors, early diagnosis of the disease and increasing the speed of their treatment can be significantly helped.

Determining the challenges and opportunities of virtual teaching during the COVID-19 pandemic: a mixed method study in the north of Iran.

The aim of this study was to determine the challenges and opportunities of virtual education during the COVID-19 pandemic. This study was conducted in 2022-2023 with a mixed method. During the quantitative phase, we chose 507 students from Mazandaran Province medical universities (both governmental and non-governmental) by stratified random sampling and during the qualitative phase 16 experts were collected by purposive sampling until we reached data saturation. Data collecting tools consisted of questionnaires during the quantitative phase and semi-structured interview during the qualitative phase. Data was analyzed using SPSS21 and MAXQDA10. Mean scores of the total score was 122.28±23.96. We found a significant association between interaction dimension and background variables (P < 0.001). The most important privilege of virtual education is uploading the teaching material in the system so that students can access the material constantly and the most important challenge regarding virtual education is lack of proper network connection and limited bandwidth. Virtual education proved to be a suitable alternate to traditional methods of medical education during the COVID-19 pandemic in theoretical topics, we recommend that educational policymakers would take the necessary actions to provide the requirements and facilities needed to improve the quality of virtual education.

Recurrent viral RNA positivity and candidiasis findings in hospitalized patients with COVID-19.

Background: The aim of this study was to evaluate reinfection and fungal infections among 785 patients with COVID-19 disease admitted to Baqiyatallah Hospital in Northeastern Iran after the onset of the COVID-19 epidemic. Materials & Methods: In this descriptive-analytic study (20 February-21 July 2020), reinfection and fungal infections among 785 patients were investigated using epidemiological questionnaire, clinical trials, Real-time PCR and CT scan (chest computed tomography) from the hospital HIS (hospital's information system) and collected samples. Results: Reinfection and one oral candidiasis were diagnosed in one 68-year-old man and one 47-year-old man 63 and 42 days after the initial infection, respectively. Conclusion: The research results showed that exposure to COVID-19 may not establish long-term protective immunity to all patients.

Preclinical Western Blot in the Era of Digital Transformation and Reproducible Research, an Eastern Perspective.

The current research is an interdisciplinary endeavor to develop a necessary tool in preclinical protein studies of diseases or disorders through western blotting. In the era of digital transformation and open access principles, an interactive cloud-based database called East-West Blot ( https://rancs-lab.shinyapps.io/WesternBlots ) is designed and developed. The online interactive subject-specific database built on the R shiny platform facilitates a systematic literature search on the specific subject matter, here set to western blot studies of protein regulation in the preclinical model of TBI. The tool summarizes the existing publicly available knowledge through a data visualization technique and easy access to the critical data elements and links to the study itself. The application compiled a relational database of PubMed-indexed western blot studies labeled under HHS public access, reporting downstream protein regulations presented by fluid percussion injury model of traumatic brain injury. The promises of the developed tool include progressing toward implementing the principles of 3Rs (replacement, reduction, and refinement) for humane experiments, cultivating the prerequisites of reproducible research in terms of reporting characteristics, paving the ways for a more collaborative experimental design in basic science, and rendering an up-to-date and summarized perspective of current publicly available knowledge.

Environmental impact reduction as a new dimension for quality measurement of healthcare services.

PURPOSE: The purpose of this paper is to provide a detailed accounting of energy and materials consumed during magnetic resonance imaging (MRI). DESIGN/METHODOLOGY/APPROACH: The first and second stages of ISO standard (ISO 14040:2006 and ISO 14044:2006) were followed to develop life cycle inventory (LCI). The LCI data collection took the form of observations, time studies, real-time metered power consumption, review of imaging department scheduling records and review of technical manuals and literature. FINDINGS: The carbon footprint of the entire MRI service on a per-patient basis was measured at 22.4 kg CO2eq. The in-hospital energy use (process energy) for performing MRI is 29 kWh per patient for the MRI machine, ancillary devices and light fixtures, while the out-of-hospital energy consumption is approximately 260 percent greater than the process energy, measured at 75 kWh per patient related to fuel for generation and transmission of electricity for the hospital, plus energy to manufacture disposable, consumable and reusable products. The actual MRI and standby energy that produces the MRI images is only about 38 percent of the total life cycle energy. RESEARCH LIMITATIONS/IMPLICATIONS: The focus on methods and proof-of-concept meant that only one facility and one type of imaging device technology were used to reach the conclusions. Based on the similar studies related to other imaging devices, the provided transparent data can be generalized to other healthcare facilities with few adjustments to utilization ratios, the share of the exam types, and the standby power of the facilities' imaging devices. PRACTICAL IMPLICATIONS: The transparent detailed life cycle approach allows the data from this study to be used by healthcare administrators to explore the hidden public health impact of the radiology department and to set goals for carbon footprint reductions of healthcare organizations by focusing on alternative imaging modalities. Moreover, the presented approach in quantifying healthcare services' environmental impact can be replicated to provide measurable data on departmental quality improvement initiatives and to be used in hospitals' quality management systems. ORIGINALITY/VALUE: No other research has been published on the life cycle assessment of MRI. The share of outside hospital indirect environmental impact of MRI services is a previously undocumented impact of the physician's order for an internal image.

Scope for energy improvement for hospital imaging services in the USA.

OBJECTIVE: To aid radiologists by measuring the carbon footprint of CT scans by quantifying in-hospital and out-of-hospital energy use and to assess public health impacts. METHOD: The study followed a standard life cycle assessment protocol to measure energy from a CT scan then expanding to all hospital electrical energy related to CT usage. In addition, all the fuel energy used to generate electricity and to manufacture the CT consumables was measured. The study was conducted at two hospitals. RESULTS: The entire life cycle energy for a CT scan was 24-34 kWh of natural resource energy per scan. The actual active patient scan energy that produces the images is only about 1.6% of this total life cycle energy. This large multiplier to get total CT energy is a previously undocumented environmental response to the direct radiology order for a patient CT scan. The CT in-hospital energy related to idle periods, where the machine is on but no patients are being scanned and is 14-30-fold higher than the energy used for the CT image. The in-hospital electrical energy of a CT scan makes up only about 25% of the total energy footprint. The rest is generated outside the hospital: 54-62% for generation and transmission of the electricity, while 13-22% is for all the energy to make the consumables. Different CT scanners have some influences on the results and could help guide purchase of CT equipment. CONCLUSIONS: The transparent, detailed life cycle approach allows the data from this study to be used by radiologists to examine details of both direct and of unseen energy impacts of CT scans. The public health (outside-the-hospital) impact (including the patients receiving a CT) needs to be measured and included.