Background Pandemics threaten lives and economies. This article addresses the global threat of the anticipated overlap of COVID-19 with seasonal-influenza. Objectives Scientific evidence based on simulation methodology is presented to reveal the impact of a dual outbreak, with scenarios intended for propagation analysis. This article aims at researchers, clinicians of family medicine, general practice and policy-makers worldwide. The implications for the clinical practice of primary health care are discussed. Current research is an effort to explore new directions in epidemiology and health services delivery. Methods Projections consisted of machine learning, dynamic modelling algorithms and whole simulations. Input data consisted of global indicators of infectious diseases. Four simulations were run for ‘20% versus 60% flu-vaccinated populations’ and ‘10 versus 20 personal contacts’. Outputs consisted of numerical values and mathematical graphs. Outputs consisted of numbers for ‘never infected’, ‘vaccinated’, ‘infected/recovered’, ‘symptomatic/asymptomatic’ and ‘deceased’ individuals. Peaks, percentages, R0, durations are reported. Results The best-case scenario was one with a higher flu-vaccination rate and fewer contacts. The reverse generated the worst outcomes, likely to disrupt the provision of vital community services. Both measures were proven effective; however, results demonstrated that ‘increasing flu-vaccination rates’ is a more powerful strategy than ‘limiting social contacts’. Conclusions Results support two affordable preventive measures: (i) to globally increase influenza-vaccination rates, (ii) to limit the number of personal contacts during outbreaks. The authors endorse changing practices and research incentives towards multidisciplinary collaborations. The urgency of the situation is a call for international health policy to promote interdisciplinary modern technologies in public health engineering.
Background/Aims: This study aimed to evaluate the relationship between irritable bowel syndrome (IBS) and plasma and tissue ghrelin levels. Materials and Methods: Patients who had undergone gastroscopy procedure for any reason previously were enrolled in the study. Among these, patients with IBS symptoms were evaluated according to the Roma III criteria. The healthy control group comprised patients with no IBS symptom and had undergone gastroscopy procedure for another reason. The plasma ghrelin level and tissue ghrelin level obtained by immunohistochemical examination of biopsy specimens taken from the gastric antrum and corpus were evaluated in all participants. Results: The mean age of 90 participants was 43.64±12.64 years. The median value of the plasma ghrelin level was 3.29 (1.2-12.7) in the diarrhea group (IBS-D), 1.49 (0.82-7.08) in the constipation group (IBS-C), and 1.5 (0.2-3.7) in the control group. The plasma ghrelin levels between the groups were found to be significantly higher in IBS-D than in IBS-C and the control groups (p=0.001 and p=0.001, respectively). On comparing antral mucosal gland biopsy outcomes among the groups, staining intensity score was found to be significantly high in IBS-C as compared with the control group, whereas no significant difference was observed between IBS-D and the control groups (p=0.020 and p=0.429, respectively). Conclusion: The plasma ghrelin level in IBS-D and the staining intensity in the antral mucosal gland in IBS-C were found to be significantly higher. In addition, there was no difference between the groups in terms of ghrelin staining intensity in the gastric corpus.
The frequency of sarcopenia in obese diabetic patients is found to be lower when skeletal muscle index and ALM/BMI ratio is used, but higher with body muscle ratio.
Introduction Body mass index (BMI) is unable to make a distinction between muscle mass and fat mass. Therefore, new anthropometric measurements, such as a body shape index (ABSI), body round index (BRI), and body adiposity index (BAI), have been formulated in recent years. Many studies have reported a correlation between BMI and thyroid function. In this study, we aimed to investigate the relationship between the above-mentioned new anthropometric measurements and thyroid functions in euthyroid obese subjects. Methods We included 675 euthyroid (TSH ≥ 0.4 and < 4.5 mIU/l) individuals from the obesity outpatient clinic, aged between 18 and 65 years old, with BMI ≥ 30. Thyroid-stimulating hormone (TSH), free T4 (fT4) and free T3 (fT3), anthropometric measurements (weight, height, and waist circumference), and bioelectric impedance analyses [percent body fat (PBF) and fat-free mass (FFM)] of individuals were measured and recorded. ABSI, BRI, and BAI were calculated with the data from these measurements. Anthropometric measurements were compared to thyroid function tests. Results Eighty percent of the subjects were female. The mean age and BMI were 38 ± 17 years and 38 ± 6 kg/m 2 , respectively. TSH was found to be negatively correlated with ABSI (p = 0.006) and positively correlated with BAI (p < 0.001), but a statistically significant relationship with BRI (p = 0.193) was not determined. Free T4 was not associated with any of the anthropometric measurements.While fT3 was determined to be positively correlated with ABSI (p = 0.008) and negatively correlated with PBF and BAI (p = 0.001, p = 0.002, respectively), no statistically significant relationship with fT3 and BRI was determined. Conclusion TSH is positively correlated with measurements of adiposity such as BMI, PBF, BAI while indexes in which abdominal obesity increases, such as waist circumference (WC), waist-hip ratio (WHR), and ABSI, are correlated with fT3 levels.
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