Assessment of cardiovascular risk in a slum population in Kenya : use of World Health Organisation/International Society of Hypertension (WHO/ISH) risk prediction charts - secondary analyses of a household survey

Objectives Although cardiovascular disease (CVD) is of growing importance in low- and middle-income countries (LMICs), there are conflicting views regarding CVD as a major public health problem for the urban poor, including those living in slums. We examine multivariable risk prediction in a slum population and assess the number of cardiovascular related deaths within 10 years of application of the tool. Setting We use data from the Nairobi Urban Health and Demographic Surveillance System (NUHDSS) population (residents of two slum communities) between May 2008 and April 2009. Design This is a secondary data analysis from a cross-sectional survey. We use the WHO/International Society of Hypertension (WHO/ISH) cardiovascular risk prediction tool to examine 10-year risk of major CVD events in a slum population. CVD deaths in the cohort, reported up until June 2018 and identified through verbal autopsy are also presented. Participants 3063 men and women aged over 40 years with complete data for variables needed for the WHO/ISH risk prediction tool were eligible to take part. Results The majority of study members (2895, 94.5%) were predicted to have ‘low’ risk (20% were identified as dying of CVD. Conclusions This study shows that there is a low risk profile of CVD in this slum population in Nairobi, Kenya, in comparison to results from application of multivariable risk prediction tools in other LMIC populations. This has implications for health service planning in these contexts

Real-Time Anti Spoofing Face Detection with Mask Using CNN

As COVID-19 spread the whole way across the world, a significant number of us got mindful of how significant face covers are. Medical services authorities and nearby foundations from one side of the planet to the other are encouraging individuals to wear masks ,as it is the best way to forestall the transmission of the infection. Masks have without a doubt frustrated the facial-acknowledgment industry; the innovation has likewise adjusted. It might sound odd yet wearing a cover does not really prevent a PC from recognizing somebody. We are intending to prepare our model to recognize whether the pictures are genuine or fake one even though individuals are wearing face cover. In this paper, we intend to make a liveness detector equipped for spotting counterfeit faces. To make a liveness detector, we will prepare a deep learning neural network fit for recognizing genuine versus counterfeit appearances. It deals with two correlative spaces: RGB space and multi-scale Retinex (MSR) space. The RGB space contains the point-by-point facial surfaces, yet it is sensitive to illumination whereas the MSR pictures can adequately catch the high recurrence data, which is discriminative for face recognition

Switching to Once-Weekly Insulin Icodec Versus Once-Daily Insulin Glargine U100 in Type 2 Diabetes Inadequately Controlled on Daily Basal Insulin: A Phase 2 Randomized Controlled Trial

OBJECTIVE Insulin icodec (icodec) is a novel once-weekly basal insulin analog. This trial investigated two approaches for switching to icodec versus once-daily insulin glargine U100 (IGlar U100) in people with type 2 diabetes receiving daily basal insulin and one or more oral glucose-lowering medications.RESEARCH DESIGN AND METHODS This multicenter, open-label, treat-to-target phase 2 trial randomized (1:1:1) eligible basal insulin–treated (total daily dose 10–50 units) people with type 2 diabetes (HbA1c 7.0–10.0% [53.0–85.8 mmol/mol]) to icodec with an initial 100% loading dose (in which only the first dose was doubled [icodec LD]), icodec with no loading dose (icodec NLD), or IGlar U100 for 16 weeks. Primary end point was percent time in range (TIR; 3.9–10.0 mmol/L [70–180 mg/dL]) during weeks 15 and 16, measured using continuous glucose monitoring. Key secondary end points included HbA1c, adverse events (AEs), and hypoglycemia.RESULTS Estimated mean TIR during weeks 15 and 16 was 72.9% (icodec LD; n = 54), 66.0% (icodec NLD; n = 50), and 65.0% (IGlar U100; n = 50), with a statistically significant difference favoring icodec LD versus IGlar U100 (7.9%-points [95% CI 1.8–13.9%]). Mean HbA1c reduced from 7.9% (62.8 mmol/mol) at baseline to 7.1% (54.4 mmol/mol icodec LD) and 7.4% (57.6 mmol/mol icodec NLD and IGlar U100); incidences and rates of AEs and hypoglycemic episodes were comparable.CONCLUSIONS Switching from daily basal insulin to once-weekly icodec was well tolerated and provided effective glycemic control. Loading dose use when switching to once-weekly icodec significantly increased percent TIR during weeks 15 and 16 versus once-daily IGlar U100, without increasing hypoglycemia risk.</h4