Federated Learning for Privacy Preservation of Healthcare Data from Smartphone-based Side-Channel Attacks

Federated Learning for Privacy Preservation of Healthcare Data from Smartphone-based Side-Channel Attack

The Kidney Failure Risk Equation for prediction of end stage renal disease in UK primary care: An external validation and clinical impact projection cohort study

BACKGROUND: The Kidney Failure Risk Equation (KFRE) uses the 4 variables of age, sex, urine albumin-to-creatinine ratio (ACR), and estimated glomerular filtration rate (eGFR) in individuals with chronic kidney disease (CKD) to predict the risk of end stage renal disease (ESRD), i.e., the need for dialysis or a kidney transplant, within 2 and 5 years. Currently, national guideline writers in the UK and other countries are evaluating the role of the KFRE in renal referrals from primary care to secondary care, but the KFRE has had limited external validation in primary care. The study's objectives were therefore to externally validate the KFRE's prediction of ESRD events in primary care, perform model recalibration if necessary, and assess its projected impact on referral rates to secondary care renal services. METHODS AND FINDINGS: Individuals with 2 or more Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) eGFR values < 60 ml/min/1.73 m2 more than 90 days apart and a urine ACR or protein-to-creatinine ratio measurement between 1 December 2004 and 1 November 2016 were included in the cohort. The cohort included 35,539 (5.6%) individuals (57.5% female, mean age 75.9 years, median CKD-EPI eGFR 51 ml/min/1.73 m2, median ACR 3.2 mg/mmol) from a total adult practice population of 630,504. Overall, 176 (0.50%) and 429 (1.21%) ESRD events occurred within 2 and 5 years, respectively. Median length of follow-up was 4.7 years (IQR 2.8 to 6.6). Model discrimination was excellent for both 2-year (C-statistic 0.932, 95% CI 0.909 to 0.954) and 5-year (C-statistic 0.924, 95% 0.909 to 0.938) ESRD prediction. The KFRE overpredicted risk in lower (<20%) risk groups. Reducing the model's baseline risk improved calibration for both 2- and 5-year risk for lower risk groups, but led to some underprediction of risk in higher risk groups. Compared to current criteria, using referral criteria based on a KFRE-calculated 5-year ESRD risk of ≥5% and/or an ACR of ≥70 mg/mmol reduced the number of individuals eligible for referral who did not develop ESRD, increased the likelihood of referral eligibility in those who did develop ESRD, and referred the latter at a younger age and with a higher eGFR. The main limitation of the current study is that the cohort is from one region of the UK and therefore may not be representative of primary care CKD care in other countries. CONCLUSIONS: In this cohort, the recalibrated KFRE accurately predicted the risk of ESRD at 2 and 5 years in primary care. Its introduction into primary care for referrals to secondary care renal services may lead to a reduction in unnecessary referrals, and earlier referrals in those who go on to develop ESRD. However, further validation studies in more diverse cohorts of the clinical impact projections and suggested referral criteria are required before the latter can be clinically implemented

Association between native T1 mapping of the kidney and renal fibrosis in patients with IgA nephropathy.

INTRODUCTION: IgA nephropathy (IgAN) is the commonest global cause of glomerulonephritis. Extent of fibrosis, tubular atrophy and glomerulosclerosis predict renal function decline. Extent of renal fibrosis is assessed with renal biopsy which is invasive and prone to sampling error. We assessed the utility of non-contrast native T1 mapping of the kidney in patients with IgAN for assessment of renal fibrosis. METHODS: Renal native T1 mapping was undertaken in 20 patients with IgAN and 10 healthy subjects. Ten IgAN patients had a second scan to assess test-retest reproducibility of the technique. Native T1 times were compared to markers of disease severity including degree of fibrosis, eGFR, rate of eGFR decline and proteinuria. RESULTS: All patients tolerated the MRI scan and analysable quality T1 maps were acquired in at least one kidney in all subjects. Cortical T1 times were significantly longer in patients with IgAN than healthy subjects (1540 ms ± 110 ms versus 1446 ± 88 ms, p = 0.038). There was excellent test-retest reproducibility of the technique, with Coefficient-of-variability of axial and coronal T1 mapping analysis being 2.9 and 3.7% respectively. T1 correlated with eGFR and proteinuria (r = - 0.444, p = 0.016; r = 0.533, p = 0.003 respectively). Patients with an eGFR decline > 2 ml/min/year had increased T1 times compared to those with a decline  0, compared to those with a 'T'-score of 0 (1575 ± 106 ms versus 1496 ± 105 ms, p = 0.131), though not to significance. CONCLUSIONS: Cortical native T1 time is significantly increased in patients with IgAN compared to healthy subjects and correlates with markers of renal disease. Reproducibility of renal T1 mapping is excellent. This study highlights the potential utility of native T1 mapping in IgAN and other progressive nephropathies, and larger prospective studies are warranted

An Innovative Chemical Adherence Test Demonstrates Very High Rates of Nonadherence to Oral Cardio-Metabolic Medications

Chronic kidney disease (CKD) is one of the leading causes of death worldwide. About 13% of the world’s population are living with CKD; and over the last 20 years, there has been over a 40% increase in mortality rates due to CKD.1,2 Compared to patients without CKD, CKD stages G3a to G4 (estimated glomerular filtration rate 15–60 ml/min per 1.73 m2) is associated with a 2 to 3 fold increase in risk of cardiovascular disease mortality.3 It is estimated that about 17% to 74% of patients with CKD are nonadherent to their medications.4 Improvement in adherence has been identified as a key strategy to enhance cardiovascular outcomes.5 However, the diagnosis of nonadherence, until recently, was difficult due to the lack of objective tools in busy clinics because some subjective methods have been found to be unreliable.6 Chemical adherence testing (CAT) is a novel, objective, robust and clinically reliable test that uses liquid-chromatography tandem mass spectrometry to assess adherence to medications. A random spot urine or blood sample is screened to determine the presence or absence of 70 of the most common cardio-metabolic medications (Supplementary Table S1) (including antihypertensives, lipid lowering medications, and glucose lowering drugs).7 There are guidelines available to help implement the use of the test and address common questions about the clinical use of the test.7 Currently, CAT is being used in routine care in some specialist hypertension clinics across Europe and has been recommended by the European Society of Cardiology and the European Society of Hypertension as the method to be used to measure adherence in patients with suspected resistant hypertension.8 The use of CAT is limited outside of hypertension and to the best of our knowledge there has been no publication that has used CAT to diagnose medication nonadherence in renal patients. The aim of this study was therefore to demonstrate and highlight the usefulness of CAT to determine the prevalence of nonadherence to cardio-metabolic medications in patients attending routine renal clinics.</p

Measuring progress and projecting attainment on the basis of past trends of the health-related Sustainable Development Goals in 188 countries: an analysis from the Global Burden of Disease Study 2016

Background The UN's Sustainable Development Goals (SDGs) are grounded in the global ambition of “leaving no one behind”. Understanding today's gains and gaps for the health-related SDGs is essential for decision makers as they aim to improve the health of populations. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016), we measured 37 of the 50 health-related SDG indicators over the period 1990–2016 for 188 countries, and then on the basis of these past trends, we projected indicators to 2030. Methods We used standardised GBD 2016 methods to measure 37 health-related indicators from 1990 to 2016, an increase of four indicators since GBD 2015. We substantially revised the universal health coverage (UHC) measure, which focuses on coverage of essential health services, to also represent personal health-care access and quality for several non-communicable diseases. We transformed each indicator on a scale of 0–100, with 0 as the 2·5th percentile estimated between 1990 and 2030, and 100 as the 97·5th percentile during that time. An index representing all 37 health-related SDG indicators was constructed by taking the geometric mean of scaled indicators by target. On the basis of past trends, we produced projections of indicator values, using a weighted average of the indicator and country-specific annualised rates of change from 1990 to 2016 with weights for each annual rate of change based on out-of-sample validity. 24 of the currently measured health-related SDG indicators have defined SDG targets, against which we assessed attainment. Findings Globally, the median health-related SDG index was 56·7 (IQR 31·9–66·8) in 2016 and country-level performance markedly varied, with Singapore (86·8, 95% uncertainty interval 84·6–88·9), Iceland (86·0, 84·1–87·6), and Sweden (85·6, 81·8–87·8) having the highest levels in 2016 and Afghanistan (10·9, 9·6–11·9), the Central African Republic (11·0, 8·8–13·8), and Somalia (11·3, 9·5–13·1) recording the lowest. Between 2000 and 2016, notable improvements in the UHC index were achieved by several countries, including Cambodia, Rwanda, Equatorial Guinea, Laos, Turkey, and China; however, a number of countries, such as Lesotho and the Central African Republic, but also high-income countries, such as the USA, showed minimal gains. Based on projections of past trends, the median number of SDG targets attained in 2030 was five (IQR 2–8) of the 24 defined targets currently measured. Globally, projected target attainment considerably varied by SDG indicator, ranging from more than 60% of countries projected to reach targets for under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria, to less than 5% of countries projected to achieve targets linked to 11 indicator targets, including those for childhood overweight, tuberculosis, and road injury mortality. For several of the health-related SDGs, meeting defined targets hinges upon substantially faster progress than what most countries have achieved in the past. Interpretation GBD 2016 provides an updated and expanded evidence base on where the world currently stands in terms of the health-related SDGs. Our improved measure of UHC offers a basis to monitor the expansion of health services necessary to meet the SDGs. Based on past rates of progress, many places are facing challenges in meeting defined health-related SDG targets, particularly among countries that are the worst off. In view of the early stages of SDG implementation, however, opportunity remains to take actions to accelerate progress, as shown by the catalytic effects of adopting the Millennium Development Goals after 2000. With the SDGs' broader, bolder development agenda, multisectoral commitments and investments are vital to make the health-related SDGs within reach of all populations. Funding Bill & Melinda Gates Foundation