Mobile Cellular Data and Wi-Fi Use Are Not Associated with Adverse Health Effects.

Background: Smartphone users frequently connect to the Internet via mobile data or Wi-Fi. Over the past two decades, the worldwide percentage of people who connect to the Internet using their mobile phones has increased drastically. Objective: This study aimed to evaluate the potential link between mobile cellular data/ and Wi-Fi use and adverse health effects. Material and Methods: This cross-sectional study was conducted on 2,796 employees (52% female and 48% male) of Shiraz University of Medical Sciences (SUMS), Shiraz, Iran. The sociodemographic data (e.g., gender, age, nationality, and education level) were collected for all the participants. They were also requested to provide information about their smartphone use including the characteristics of the connection to the Internet using their smartphones (mobile data and Wi-Fi). In addition, the participants' history of diabetes, hypertension, cardiac ischemia, myocardial infarction, renal failure, fatty liver, hepatitis, chronic lung disease, thyroid disease, kidney stone, gall bladder stone, rheumatoid disease, epilepsy, and chronic headache was recorded through face-to-face interviews. Results: 94% of people participating in this study reported using mobile/Wi-Fi internet. The mean (±SD) Internet usage per day was 117.85±122.70 minutes including 76±98 minutes of mobile data and 42±81 minutes of Wi-Fi use. Conclusion: Our findings showed no link between mobile phone Internet usage and the risk of the above-mentioned health problems. As in 2021, the global average daily time spent on the Internet using mobile phones was 155 minutes, the participants' lower use time could explain the failure to show any detrimental effects. Considering the study limitations, further large-scale studies are warranted.

Impact of antifungal stewardship interventions on the susceptibility of colonized Candida species in pediatric patients with malignancy.

There is a worldwide concern regarding the antimicrobial resistance and the inappropriate use of antifungal agents, which had led to an ever-increasing antifungal resistance. This study aimed to identify the antifungal susceptibility of colonized Candida species isolated from pediatric patients with cancer and evaluate the clinical impact of antifungal stewardship (AFS) interventions on the antifungal susceptibility of colonized Candida species. Candida species colonization was evaluated among hospitalized children with cancer in a tertiary teaching hospital, Shiraz 2017-2018. Samples were collected from the mouth, nose, urine, and stool of the patients admitted to our center and cultured on sabouraud dextrose agar. The isolated yeasts identified by polymerase chain reaction-restriction fragment length polymorphisms (PCR-RFLP). DNA Extracted and PCR amplification was performed using the ITS1 and ITS4 primer pairs and Msp I enzyme. The broth microdilution method was used to determine the minimum inhibitory concentrations (MICs) for amphotericin B, caspofungin, and azoles. The prevalence of Candida albicans in the present study was significantly higher than other Candida species. Candida albicans species were completely susceptible to the azoles. The susceptibility rate of C. albicans to amphotericin B and caspofungin was 93.1% and 97.1%, respectively. The fluconazole MIC values of Candida albicans decreased significantly during the post-AFS period (P < 0.001; mean difference: 72.3; 95% CI of the difference: 47.36-98.62). We found that 52.5% (53/117) of the isolated C. albicans were azole-resistant before AFS implementation, while only 1.5% (2/102) of the isolates were resistant after implementation of the AFS program (P < 0.001). C. albicans fluconazole and caspofungin resistant rate also decreased significantly (P < 0.001) after implementation of the AFS program [26 (32.9%) versus 0 (0.0%) and 11 (10.9%) versus 1 (0.9%), respectively]. Besides, fluconazole use (p < 0.05) and fluconazole expenditure reduced significantly (about one thousand US$ per year) after the AFS program. Our results confirm the positive effect of optimized antifungal usage and bedside intervention on the susceptibility of Candida species after the implementation of the AFS program. C. albicans and C. glabrata exhibited a significant increase in susceptibility after the execution of the AFS program.

Bloodstream infections in adult patients with malignancy, epidemiology, microbiology, and risk factors associated with mortality and multi-drug resistance.

BACKGROUND: This study aimed to investigate the epidemiology, microbiology, and risk factors associated with mortality and multi-drug resistance bacterial bloodstream infections (BSIs) among adult cancer patients in Shiraz, Iran. We also report a four-year trend of antimicrobial resistance patterns of BSIs. METHODS: We conducted a retrospective study at a referral oncology hospital from July 2015 to August 2019, which included all adults with confirmed BSI. RESULTS: 2393 blood cultures tested during the four-year study period; 414 positive cultures were included. The mean age of our patients was 47.57 ± 17.46 years old. Central Line-Associated BSI (CLABSI) was more common in solid tumors than patients with hematological malignancies. Gram-negative (GN) bacteria were more detected (63.3%, 262) than gram-positive bacteria (36.7%, 152). Escherichia coli was the most common gram-negative organism (123/262, 47%), followed by Pseudomonas spp. (82/262, 31%) and Klebsiella pneumoniae (38/262, 14.5%). Coagulase-negative staphylococci (CoNS) was the most frequently isolated pathogen among gram-positive bacteria (83/152, 54.6%). Acinetobacter spp., Pseudomonas spp., E. coli, and K. pneumoniae were the most common Extended-Spectrum Beta-Lactamase (ESBL) producers (100, 96.2, 66.7%, and 60.7, respectively). Acinetobacter spp., Pseudomonas spp., Enterobacter spp., E. coli, and K. pneumoniae were the most common carbapenem-resistant (CR) isolates (77.8, 70.7, 33.3, 24.4, and 13.2%, respectively). Out of 257 Enterobacterales and non-fermenter gram-negative BSIs, 39.3% (101/257) were carbapenem-resistant. Although the incidence of multi-drug resistance (MDR) gram-negative BSI increased annually during 2015-2018, the mortality rate of gram-negative BSI remains unchanged at about 20% (p-value = 0.55); however, the mortality rate was significantly greater (35.4%) in those with resistant gram-positive BSI (p-value = 0.001). The overall mortality rate was 21.5%. Early (7-day mortality) and late mortality rate (30-day mortality) were 10 and 3.4%, respectively. CONCLUSIONS: The emergence of MDR gram-negative BSI is a significant healthcare problem in oncology centers. The high proportion of the most frequently isolated pathogens were CR and ESBL-producing Enterobacterales and Pseudomonas spp. We have few effective choices against MDRGN BSI, especially in high-risk cancer patients, which necessitate newer treatment options.

Relationship between mental workload and salivary cortisol levels: A field study.

BACKGROUND: Mental workload (MW) assessment is a key point in research and development of human-machine interfaces in the workplace. OBJECTIVE: This study aimed to examine the relationship between mental workload and the amount of salivary cortisol amongst technicians of an Iranian combined cycle power plant. METHODS: A total of 18 technicians participated in this pilot study. First, task analysis was carried out to determine operation steps that forced us to separate them in to two groups. Next, the Visual, Auditory, Cognitive, and Psychomotor (VACP) technique and NASA Task Load Index (NASA-TLX) questionnaire were used to examine their mental workload. Then, the operator's salivary samples were collected at four specific times of both off and working days. Finally, the relationship between mental workload and salivary cortisol was examined with the analysis of Pearson correlation. RESULTS: The results of mental workload assessment with subjective methods showed a high level of mental workload amongst all technicians. No significant association was observed between the NASA-TLX questionnaire and VACP technique with concentration of salivary cortisol (p = 0.081). CONCLUSION: Based on the results, it can be concluded that salivary cortisol might not be an appropriate physiological method to assess mental workload, since cortisol levels are highly dependent on individuals' circadian rhythm.

Improved Kaplan-Meier Estimator in Survival Analysis Based on Partially Rank-Ordered Set Samples.

This study presents a novel methodology to investigate the nonparametric estimation of a survival probability under random censoring time using the ranked observations from a Partially Rank-Ordered Set (PROS) sampling design and employs it in a hematological disorder study. The PROS sampling design has numerous applications in medicine, social sciences and ecology where the exact measurement of the sampling units is costly; however, sampling units can be ordered by using judgment ranking or available concomitant information. The general estimation methods are not directly applicable to the case where samples are from rank-based sampling designs, because the sampling units do not meet the identically distributed assumption. We derive asymptotic distribution of a Kaplan-Meier (KM) estimator under PROS sampling design. Finally, we compare the performance of the suggested estimators via several simulation studies and apply the proposed methods to a real data set. The results show that the proposed estimator under rank-based sampling designs outperforms its counterpart in a simple random sample (SRS).

Prognostic Factors of Breast Cancer Survival in the Islamic Republic of Iran: an Additive Empirical Bayesian Approach.

Breast cancer is a public health challenge in the Islamic Republic of Iran. Relatively few studies have dealt with large dataset and advanced statistical methods. Therefore, we aimed to investigate the role of prognostic factors on breast cancer survival using Additive Empirical Bayesian model with large data set. Breast cancer data set included 1574 women diagnosed with breast cancer from 2002 to 2012 that registered from Cancer Registry in Fars Province, Islamic Republic of Iran. Overall survival rates at 2, 3, 5 and 10 years were 0.98, 0.94, 0.87 and 0.76, respectively. Five years survival at stages 1, 2 and 3 were 0.94, 0.92 and 0.74, respectively. The younger patients with characteristics such as zero involved nodes, negative progesterone receptor, free skin and good prognostic level had a higher survival chance than others. The 5-year survival probability by stage in Fars Province was nearly the same as that reported by the American Cancer Society. The Nottingham prognostic index (NPI) related to nodal status, tumour size and nuclear grade was the main indicator of breast cancer mortality.

A comparison of breast cancer survival among young, middle-aged, and elderly patients in southern Iran using Cox and empirical Bayesian additive hazard models.

OBJECTIVES: A survival analysis of breast cancer patients in southern Iran according to age has yet to be conducted. This study aimed to quantify the factors contributing to a poor prognosis, using Cox and empirical Bayesian additive hazard (EBAH) models, among young (20-39 years), middle-aged (40-64 years), and elderly (≥ 65 years) women. METHODS: Data from 1,574 breast cancer patients diagnosed from 2002 to 2012 in the cancer registry of Fars Province (southern Iran) were stratified into 3 age groups. The Kaplan-Meier method was used to estimate the overall survival rates. Cox and EBAH models were applied to each age category, and the Akaike information criterion was used to assess the goodness-of-fit of the 2 hazard models. RESULTS: As of December 2012, 212 women (13.5%) in our study population had died, of whom 43 were young (15.3%), 134 middle-aged (11.8%), and 35 elderly (22.3%). The 5-year survival probability by age category was 0.83 (standard error [SE], 0.03), 0.88 (SE, 0.01), and 0.75 (SE, 0.04), respectively. CONCLUSIONS: The Nottingham Prognostic Index was the most effective prognostic factor. The model based on Bayesian methodology performed better with various sample sizes than the Cox model, which is the most widely used method of survival analysis.