Diabetic cardiomyopathy is a distinct primary disease process, independent of coronary artery disease, which leads to heart failure in diabetic patients. Epidemiological and clinical trial data have confirmed the greater incidence and prevalence of heart failure in diabetes. Novel echocardiographic and MR (magnetic resonance) techniques have enabled a more accurate means of phenotyping diabetic cardiomyopathy. Experimental models of diabetes have provided a range of novel molecular targets for this condition, but none have been substantiated in humans. Similarly, although ultrastructural pathology of the microvessels and cardiomyocytes is well described in animal models, studies in humans are small and limited to light microscopy. With regard to treatment, recent data with thiazoledinediones has generated much controversy in terms of the cardiac safety of both these and other drugs currently in use and under development. Clinical trials are urgently required to establish the efficacy of currently available agents for heart failure, as well as novel therapies in patients specifically with diabetic cardiomyopathy.

Consumption of energy drinks has been increasing dramatically in the last two decades, particularly amongst adolescents and young adults. Energy drinks are aggressively marketed with the claim that these products give an energy boost to improve physical and cognitive performance. However, studies supporting these claims are limited. In fact, several adverse health effects have been related to energy drink; this has raised the question of whether these beverages are safe. This review was carried out to identify and discuss the published articles that examined the beneficial and adverse health effects related to energy drink. It is concluded that although energy drink may have beneficial effects on physical performance, these products also have possible detrimental health consequences. Marketing of energy drinks should be limited or forbidden until independent research confirms their safety, particularly among adolescents. Disclosure of benefit:This work was not supported by any drug or commercial company. Manufacturers recently have shifted their consumer focus from athletes to young people. Energy drinks are aggressively marketed in places popular with teens and young adults. Approximately, two thirds of energy drink consumers are 13-35 years old, and boys are two thirds of the market. (4) In the U.S., energy drinks are the second most common dietary supplement used by young people; about 30% consume energy drinks on a regular basis. (5) The popularity of energy drinks in the Kingdom of Saudi Arabia does not seem to differ from other parts of the world. Around half of the Saudi University students who participated in a survey admitted to regular consumption of energy. (6) Energy drinks are designed to give an "energy boost" to the drinker by a combination of stimulants and energy boosters. The major constituent in most energy drinks is caffeine. They usually contain 80-150 mg of caffeine per 8 ounces, which is equivalent to 5 ounces of coffee or two 12-ounce cans of caffeinated soda. (7) Most of the brands on the market contain large amounts of glucose while some brands offer artificially sweetened versions. Other commonly used constituents are taurine, methylxanthines, vitamin B, ginseng, guarana, yerba mate, acai, maltodextrin, inositol, carnitine, creatine, glucuronolactone, and ginkgo biloba. CorrespondenceCurrently, significant concerns have been raised about the safety of these products. There have been several reports that showed adverse health effects associated with energy drink. Despite this, manufactures of energy drinks claim these products are suitable for consumers

No abstract

Background:The sequelae of COVID-19 pneumonia on pulmonary function and airways inflammation are still an area of active research.Objective: This research aimed to explore the long-term impact of COVID-19 pneumonia on the lung function after three months from recovery. Methods: Fifty subjects (age 18-60 years) were recruited and classified into two groups: the control group (30 subjects) and the post-COVID-19 pneumonia group (20 patients). Pulmonary function tests, spirometry, body plethysmography [lung volumes and airway resistance (R aw )], diffusion capacity for carbon monoxide (DL CO ), and fractional exhaled nitric oxide (FeNO), were measured after at least 3 months post-recovery. Results: Significant reduction in total lung capacity (TLC), forced vital capacity (FVC), forced expiratory volume (FEV 1 ), FEV 1 /FEV, and diffusing capacity for carbon monoxide (DL CO ) was observed in post-COVID-19 subjects compared to controls. Restrictive lung impairment was observed in 50% of post-COVID-19 cases (n = 10) compared to 20% in the control group (n = 6, P = 0.026). In addition, mild diffusion defect was detected in 35% (n = 7) of the post-COVID-19 group compared to 23.3% (n = 7) in the controls (P = 0.012). Conclusion: COVID-19 pneumonia has an impact on the lung functions in terms of restrictive lung impairment and mild diffusion defect after three months from recovery. Therefore, a long-term follow-up of the lung function in post-COVID-19 survivors is recommended.

This study demonstrates increased nerve fibre and microvascular pathology in relation to enhanced expression of VEGF and its receptors in a non-compressed nerve in diabetic compared with non-diabetic patients with CTS. It therefore provides a potential molecular and pathological basis for the predisposition of diabetic patients to the development of CTS.

No abstract

Purpose: The objective of this study was to find out the association between mobile use and physiological parameters of poor sleep quality. It also aimed to find out the prevalence of mobile-related sleep risk factors (MRSRF) and their effects on sleep in mobile users. Materials and Methods: This cross-sectional study was conducted on 1925 students (aged 17-23yrs) from multiple Colleges of Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia. The study tools used were Pittsburgh sleep quality index (PSQI) and MRSRF online questionnaires. Results: The mean age (±SD) of participants was 19.91 ± 2.55 years. Average mobile screen usage time was 8.57±4.59/24 hours, whereas average mobile screen usage time in the bed after the lights have been turned off was 38.17±11.7 minutes. Only 19.7% of subjects used airplane mode, while 70% kept the mobile near the pillow while sleeping. The blue light filter feature was used by only 4.2% of the participants. "Screen usage time of ≥8 hours" was positively correlated with sleep disturbances and decrease in the length of actual sleeping time (p =0.023 and 0.022). "Using the mobile for at least 30 minutes (without blue light filter) after the lights have been turned off" showed positive correlation with poor sleep quality, daytime sleepiness, sleep disturbances and increased sleep latency (p= 0.003, 0.004 and 0.001). "Keeping the mobile near the pillow while sleeping" was also positively correlated with daytime sleepiness, sleep disturbances and increased sleep latency (p =0.003, 0.004 and 0.001). Conclusion:This study concludes that using mobile screen ≥8 hours/24 hours, using the mobile for at least 30 minutes before sleeping after the lights have been turned off and keeping the mobile near the pillow are positively associated with poor sleep quality. Moreover, we observed that MRSRF were highly prevalent amongst the mobile users.

Objective:To identify the determinants of misconceptions about diabetes in patients registered with a diabetes clinic at a tertiary care hospital in Eastern Saudi Arabia.Materials and Methods:This cross-sectional survey was carried out at a diabetes clinic of a tertiary care hospital in Eastern Saudi Arabia, from January to December 2012. A total of 200 diabetic patients were interviewed using a questionnaire comprising 36 popular misconceptions. The total misconception score was calculated and categorized into low (0-12), moderate (13-24) and high (25-36) scores. The association of misconception score with various potential determinants was calculated using Chi-square test. Step-wise logistic regression was applied to the variables showing significant association with the misconception score in order to identify the determinants of misconceptions.Results:The mean age was 39.62 ± 16.7 and 112 (56%) subjects were females. Type 1 diabetics were 78 (39%), while 122 (61%) had Type 2 diabetes. Insulin was being used by 105 (52.5%), 124 (62%) were self-monitoring blood glucose and 112 (56%) were using diet control. Formal education on diabetes awareness had been received by 167 (83.5%) before the interview. The mean misconception score was 10.29 ± 4.92 with 115 (57.5%) subjects had low misconception scores (<12/36). On the Chi-square test, female gender, rural area of residence, little or no education, <5 or >15 years since diagnosis, no self-monitoring, no dietary control and no diabetes education were all significantly (P < 0.05) associated with higher misconception scores. Step-wise logistic regression suggested that diabetes education, gender, education and time since diagnosis were significant (P < 0.05) predictors of misconception scores.Conclusions:The strongest determinants of misconceptions about diabetes in our study population were female gender, rural area of residence, illiteracy or little education, <5 or >15 years since diagnosis, no self-monitoring, no diet control and no education about diabetes.