The effect of a novel, digital physical activity and emotional well-being intervention on health-related quality of life in people with chronic kidney disease: trial design and baseline data from a multicentre prospective, wait-list randomised controlled trial (kidney BEAM)

Background: Physical activity and emotional self-management has the potential to enhance health-related quality of life (HRQoL), but few people with chronic kidney disease (CKD) have access to resources and support. The Kidney BEAM trial aims to evaluate whether an evidence-based physical activity and emotional wellbeing self-management programme (Kidney BEAM) leads to improvements in HRQoL in people with CKD.  Methods: This was a prospective, multicentre, randomised waitlist-controlled trial, with health economic analysis and nested qualitative studies. In total, three hundred and four adults with established CKD were recruited from 11 UK kidney units. Participants were randomly assigned to the intervention (Kidney BEAM) or a wait list control group (1:1). The primary outcome was the between-group difference in Kidney Disease Quality of Life (KDQoL) mental component summary score (MCS) at 12 weeks. Secondary outcomes included the KDQoL physical component summary score, kidney-specific scores, fatigue, life participation, depression and anxiety, physical function, clinical chemistry, healthcare utilisation and harms. All outcomes were measured at baseline and 12 weeks, with long-term HRQoL and adherence also collected at six months follow-up. A nested qualitative study explored experience and impact of using Kidney BEAM.  Results: 340 participants were randomised to Kidney BEAM (n = 173) and waiting list (n = 167) groups. There were 96 (55%) and 89 (53%) males in the intervention and waiting list groups respectively, and the mean (SD) age was 53 (14) years in both groups. Ethnicity, body mass, CKD stage, and history of diabetes and hypertension were comparable across groups. The mean (SD) of the MCS was similar in both groups, 44.7 (10.8) and 45.9 (10.6) in the intervention and waiting list groups respectively.  Conclusion: Results from this trial will establish whether the Kidney BEAM self management programme is a cost-effective method of enhancing mental and physical wellbeing of people with CKD.  Trial Registration: NCT04872933. Registered 5th May 2021.</p

The effect of a novel, digital physical activity and emotional well-being intervention on health-related quality of life in people with chronic kidney disease: trial design and baseline data from a multicentre prospective, wait-list randomised controlled trial (kidney BEAM)

Background Physical activity and emotional self-management has the potential to enhance health-related quality of life (HRQoL), but few people with chronic kidney disease (CKD) have access to resources and support. The Kidney BEAM trial aims to evaluate whether an evidence-based physical activity and emotional wellbeing self-management programme (Kidney BEAM) leads to improvements in HRQoL in people with CKD. Methods This was a prospective, multicentre, randomised waitlist-controlled trial, with health economic analysis and nested qualitative studies. In total, three hundred and four adults with established CKD were recruited from 11 UK kidney units. Participants were randomly assigned to the intervention (Kidney BEAM) or a wait list control group (1:1). The primary outcome was the between-group difference in Kidney Disease Quality of Life (KDQoL) mental component summary score (MCS) at 12 weeks. Secondary outcomes included the KDQoL physical component summary score, kidney-specific scores, fatigue, life participation, depression and anxiety, physical function, clinical chemistry, healthcare utilisation and harms. All outcomes were measured at baseline and 12 weeks, with long-term HRQoL and adherence also collected at six months follow-up. A nested qualitative study explored experience and impact of using Kidney BEAM. Results 340 participants were randomised to Kidney BEAM (n = 173) and waiting list (n = 167) groups. There were 96 (55%) and 89 (53%) males in the intervention and waiting list groups respectively, and the mean (SD) age was 53 (14) years in both groups. Ethnicity, body mass, CKD stage, and history of diabetes and hypertension were comparable across groups. The mean (SD) of the MCS was similar in both groups, 44.7 (10.8) and 45.9 (10.6) in the intervention and waiting list groups respectively. Conclusion Results from this trial will establish whether the Kidney BEAM self management programme is a cost-effective method of enhancing mental and physical wellbeing of people with CKD.</p

Incorporating kidney disease measures into cardiovascular risk prediction: Development and validation in 9 million adults from 72 datasets

Background: Chronic kidney disease (CKD) measures (estimated glomerular filtration rate [eGFR] and albuminuria) are frequently assessed in clinical practice and improve the prediction of incident cardiovascular disease (CVD), yet most major clinical guidelines do not have a standardized approach for incorporating these measures into CVD risk prediction. “CKD Patch” is a validated method to calibrate and improve the predicted risk from established equations according to CKD measures. Methods: Utilizing data from 4,143,535 adults from 35 datasets, we developed several “CKD Patches” incorporating eGFR and albuminuria, to enhance prediction of risk of atherosclerotic CVD (ASCVD) by the Pooled Cohort Equation (PCE) and CVD mortality by Systematic COronary Risk Evaluation (SCORE). The risk enhancement by CKD Patch was determined by the deviation between individual CKD measures and the values expected from their traditional CVD risk factors and the hazard ratios for eGFR and albuminuria. We then validated this approach among 4,932,824 adults from 37 independent datasets, comparing the original PCE and SCORE equations (recalibrated in each dataset) to those with addition of CKD Patch. Findings: We confirmed the prediction improvement with the CKD Patch for CVD mortality beyond SCORE and ASCVD beyond PCE in validation datasets (Δc-statistic 0.027 [95% CI 0.018–0.036] and 0.010 [0.007–0.013] and categorical net reclassification improvement 0.080 [0.032–0.127] and 0.056 [0.044–0.067], respectively). The median (IQI) of the ratio of predicted risk for CVD mortality with CKD Patch vs. the original prediction with SCORE was 2.64 (1.89–3.40) in very high-risk CKD (e.g., eGFR 30–44 ml/min/1.73m2 with albuminuria ≥30 mg/g), 1.86 (1.48–2.44) in high-risk CKD (e.g., eGFR 45–59 ml/min/1.73m2 with albuminuria 30–299 mg/g), and 1.37 (1.14–1.69) in moderate risk CKD (e.g., eGFR 60–89 ml/min/1.73m2 with albuminuria 30–299 mg/g), indicating considerable risk underestimation in CKD with SCORE. The corresponding estimates for ASCVD with PCE were 1.55 (1.37–1.81), 1.24 (1.10–1.54), and 1.21 (0.98–1.46). Interpretation: The “CKD Patch” can be used to quantitatively enhance ASCVD and CVD mortality risk prediction equations recommended in major US and European guidelines according to CKD measures, when available. Funding: US National Kidney Foundation and the NIDDK