Risk-Based Triage for Nephrology Referrals Using the Kidney Failure Risk Equation

Hingwala, Jay; Wojciechowski, Peter; Hiebert, Brett; Bueti, Joe; Rigatto, Claudio; Komenda, Paul; Tangri, Navdeep

doi:10.1177/2054358117722782

Cited by 71 publications

(118 citation statements)

References 28 publications

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“…Our model also had lower sensitivity in younger age groups and in those with a kidney stone compared with persons with diabetes or hypertension. However, the false negative rate was 25% or lower for high-risk16 35 CKD across all strata.…”

Section: Discussionmentioning

confidence: 84%

“…Using this CKD screening strategy within such a context, in an Indian population where about 11% of persons have evidence of CKD on single time point testing and the cost of the more sensitive urine ACR testing is roughly 10-times the cost of a urine dipstick, our approach would have 60% lower screening costs than population-wide screening (out of 100 people, 35 would be required to obtain further blood and urine testing). Successful implementation of such an approach could identify a vast majority (90%) of patients at high risk for progression (ie, those with albuminuria and eGFR <60 mL/min/1.73 m 2 , classified as stage 3A2 or above)16 35 in a resource-limited setting where treatment for end-stage kidney disease is scarce and costly 2. Emerging treatments, such as sodium-glucose co-transporter 2 inhibitors, that potentially reduce the risk of progression of diabetic and non-diabetic CKD beyond that achieved by ACE inhibitors could further magnify the benefit for earlier CKD detection in LMICs 36 37…”

Section: Discussionmentioning

confidence: 99%

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Early detection of chronic kidney disease in low-income and middle-income countries: development and validation of a point-of-care screening strategy for India

et al. 2019

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IntroductionAlthough deaths due to chronic kidney disease (CKD) have doubled over the past two decades, few data exist to inform screening strategies for early detection of CKD in low-income and middle-income countries.MethodsUsing data from three population-based surveys in India, we developed a prediction model to identify a target population that could benefit from further CKD testing, after an initial screening implemented during home health visits. Using data from one urban survey (n=8698), we applied stepwise logistic regression to test three models: one comprised of demographics, self-reported medical history, anthropometry and point-of-care (urine dipstick or capillary glucose) tests; one with demographics and self-reported medical history and one with anthropometry and point-of-care tests. The ‘gold-standard’ definition of CKD was an estimated glomerular filtration rate <60 mL/min/1.73 m2 or urine albumin-to-creatinine ratio ≥30 mg/g. Models were internally validated via bootstrap. The most parsimonious model with comparable performance was externally validated on distinct urban (n=5365) and rural (n=6173) Indian cohorts.ResultsA model with age, sex, waist circumference, body mass index and urine dipstick had a c-statistic of 0.76 (95% CI 0.75 to 0.78) for predicting need for further CKD testing, with external validation c-statistics of 0.74 and 0.70 in the urban and rural cohorts, respectively. At a probability cut-point of 0.09, sensitivity was 71% (95% CI 68% to 74%) and specificity was 70% (95% CI 69% to 71%). The model captured 71% of persons with CKD and 90% of persons at highest risk of complications from untreated CKD (ie, CKD stage 3A2 and above).ConclusionA point-of-care CKD screening strategy using three simple measures can accurately identify high-risk persons who require confirmatory kidney function testing.

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Section: Discussionmentioning

confidence: 84%

Section: Discussionmentioning

confidence: 99%

Early detection of chronic kidney disease in low-income and middle-income countries: development and validation of a point-of-care screening strategy for India

et al. 2019

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“…[3][4][5] To inform patient counseling and advanced care planning, kidney failure risk calculators have been developed 6,7 and introduced in clinical practice. 8,9 These tools are largely based on standard methods for estimating time to kidney failure, in which observations are censored at death. 7 Although this approach is appropriate to estimate the association between a risk factor and the hazard, 10,11 it is problematic when studying disease incidence to predict individual risk.…”

mentioning

confidence: 99%

Influence of Mortality on Estimating the Risk of Kidney Failure in People with Stage 4 CKD

Ravani

Fiocco

Liu

et al. 2019

JASN

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BackgroundMost kidney failure risk calculators are based on methods that censor for death. Because mortality is high in people with severe, nondialysis-dependent CKD, censoring for death may overestimate their risk of kidney failure.MethodsUsing 2002–2014 population-based laboratory and administrative data for adults with stage 4 CKD in Alberta, Canada, we analyzed the time to the earliest of kidney failure, death, or censoring, using methods that censor for death and methods that treat death as a competing event factoring in age, sex, diabetes, cardiovascular disease, eGFR, and albuminuria. Stage 4 CKD was defined as a sustained eGFR of 15–30 ml/min per 1.73 m2.ResultsOf the 30,801 participants (106,447 patient-years at risk; mean age 77 years), 18% developed kidney failure and 53% died. The observed risk of the combined end point of death or kidney failure was 64% at 5 years and 87% at 10 years. By comparison, standard risk calculators that censored for death estimated these risks to be 76% at 5 years and >100% at 7.5 years. Censoring for death increasingly overestimated the risk of kidney failure over time from 7% at 5 years to 19% at 10 years, especially in people at higher risk of death. For example, the overestimation of 5-year absolute risk ranged from 1% in a woman without diabetes, cardiovascular disease, or albuminuria and with an eGFR of 25 ml/min per 1.73 m2 (9% versus 8%), to 27% in a man with diabetes, cardiovascular disease, albuminuria >300 mg/d, and an eGFR of 20 ml/min per 1.73 m2 (78% versus 51%).ConclusionsKidney failure risk calculators should account for death as a competing risk to increase their accuracy and utility for patients and providers.

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“…First, clinical education and preventive programs need to be augmented to promote CKD recognition and the close monitoring of progression in individuals at risk of CKD or with established CKD. Multiple strategies have already been implemented, such as the publication of CKD management guidelines for GPs; the creation of mobile apps that provide guidance to primary health care providers and patients (eg, https://itunes.apple.com/au/app/ckd-go!/id1047480612?mt=8); and the provision of automated web‐based clinical risk prediction tools for CKD . These strategies were designed to counteract lack of awareness and low detection rates of people with CKD among primary health care physicians .…”

Section: Gaps In Health Care Delivery For Patients With End‐stage Kidmentioning

confidence: 99%

Impending challenges of the burden of end‐stage kidney disease in Australia

Lim¹,

Johnson

McDonald

et al. 2019

Medical Journal of Australia

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Summary Sex and age‐specific incidence rates of patients with treated end‐stage kidney disease (ESKD) in Australia are comparable to those in European countries, but substantially lower compared with those in the United States, Canada and many Asian countries. The incidence rates of treated ESKD in Australia increase with advancing age; however, the incidence of ESKD is likely to be underestimated because a proportion of patients with ESKD (about 50%) remain untreated. Late referral to nephrologists has reduced over the past decade, temporally associated with improved ESKD recognition. However, late referral still occurs in one in five Australians with ESKD. One in two Australians with ESKD has diabetes, with up to 35% of cases directly attributed to diabetes. Mortality rates for patients with ESKD remain substantially higher compared with the age‐matched general population, although there has been a significant improvement in survival over time. Cardiovascular disease and cancer are the two most common causes of death in patients with ESKD.

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Risk-Based Triage for Nephrology Referrals Using the Kidney Failure Risk Equation

Cited by 71 publications

References 28 publications

Early detection of chronic kidney disease in low-income and middle-income countries: development and validation of a point-of-care screening strategy for India

Early detection of chronic kidney disease in low-income and middle-income countries: development and validation of a point-of-care screening strategy for India

Influence of Mortality on Estimating the Risk of Kidney Failure in People with Stage 4 CKD

Impending challenges of the burden of end‐stage kidney disease in Australia

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