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Prediction of non-responsiveness to pre-dialysis care program in patients with chronic kidney disease: a retrospective cohort analysis.

ABSTRACT: The responsiveness of patients with chronic kidney disease (CKD) to nephrologists' care is unpredictable. We defined the longitudinal stages (LSs) 1-5 of estimated glomerular filtration rate (eGFR) by group-based trajectory modeling for repeated eGFR measurements of 7135 patients with CKD aged 20-90 years from a 13-year pre-end-stage renal disease (ESRD) care registry. Patients were considered nonresponsive to the pre-dialysis care if they had a more advanced eGFR LS compared with the baseline. Conversely, those with improved or stable eGFR LS were considered responsive. The proportion of patients with CKD stage progression increased with the increase in the baseline CKD stage (stages 1-2: 29.2%; stage 4: 45.8%). The adjusted times to ESRD and all-cause mortality in patients with eGFR LS-5 were 92% (95% confidence interval [CI] 86-96%) and 57% (95% CI 48-65%) shorter, respectively, than in patients with eGFR LS-3A. Among patients with baseline CKD stages 3 and 4, the adjusted times to ESRD and all-cause death in the nonresponsive patients were 39% (95% CI 33-44%) and 20% (95% CI 14-26%) shorter, respectively, than in the responsive patients. Our proposed Renal Care Responsiveness Prediction (RCRP) model performed significantly better than the conventional Kidney Failure Risk Equation in discrimination, calibration, and net benefit according to decision curve analysis. Non-responsiveness to nephrologists' care is associated with rapid progression to ESRD and all-cause mortality. The RCRP model improves early identification of responsiveness based on variables collected during enrollment in a pre-ESRD program. Urgent attention should be given to characterize the underlying heterogeneous responsiveness to pre-dialysis care.

SUBMITTER: King EK

PROVIDER: S-EPMC8260802 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Prediction of non-responsiveness to pre-dialysis care program in patients with chronic kidney disease: a retrospective cohort analysis.

King Emily K EK Hsieh Ming-Han MH Chang David R DR Lu Cheng-Ting CT Ting I-Wen IW Wang Charles C N CCN Chen Pei-Shan PS Yeh Hung-Chieh HC Chiang Hsiu-Yin HY Kuo Chin-Chi CC

Scientific reports 20210706 1

The responsiveness of patients with chronic kidney disease (CKD) to nephrologists' care is unpredictable. We defined the longitudinal stages (LSs) 1-5 of estimated glomerular filtration rate (eGFR) by group-based trajectory modeling for repeated eGFR measurements of 7135 patients with CKD aged 20-90 years from a 13-year pre-end-stage renal disease (ESRD) care registry. Patients were considered nonresponsive to the pre-dialysis care if they had a more advanced eGFR LS compared with the baseline. ...[more]

PMID: 34230524

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Project description:Rationale & objectiveEstimates of the incidence of hyperkalemia in patients with chronic kidney disease (CKD) vary widely. Our objective was to estimate hyperkalemia incidence in patients with CKD from routine clinical care, including by level of kidney damage or function and among important patient subgroups.Study designRetrospective cohort study.Setting & participants1,771,900 patients with stage 1-4 CKD identified from the US Optum De-Identified electronic health records database.Exposures or predictorsImpaired kidney damage or function level at baseline based on urinary albumin-creatinine ratio (UACR) and estimated glomerular filtration rate (eGFR), respectively, and selected patient subgroups.OutcomesHyperkalemia: 2 elevated serum potassium values (≥5.5 mmol/L) from the inpatient setting (2-24 hours apart) or outpatient setting (maximum 7 days apart), or 1 elevated serum potassium value plus pharmacotherapy initiation or hyperkalemia diagnosis (maximum 3 days apart).Analytical approachIncidence rates of hyperkalemia were calculated. Estimates were stratified by UACR and eGFR level at baseline and patient subgroups.ResultsOver a mean follow-up of 3.9 years, the incidence of hyperkalemia was 3.37 events/100 person-years (95% confidence intervals, 3.36-3.38). Higher incidence rates were observed with increased UACR and lower eGFR. Highest rates were observed with UACR ≥3,500 (up to 19.1/100 person-years) irrespective of decreased eGFR level. High rates also occurred in patients with type 2 diabetes mellitus (T2DM, 5.43/100 person-years), heart failure (8.7/100 person-years), and those prescribed steroidal mineralocorticoid receptor antagonists (sMRAs, 7.7/100 person-years).LimitationsPotential misclassification of variables from possible medical coding errors; potential data incompleteness issues if patients received care at institutions not included in Optum.ConclusionsHyperkalemia is a frequent occurrence in CKD, particularly in patients with T2DM, heart failure, or prescribed sMRAs, indicating the need for regular serum potassium and UACR monitoring in this patient population to help mitigate risk.

Project description:BackgroundChronic Kidney Disease (CKD) is common and its prevalence has increased steadily over several decades. Monitoring of rates and severity of CKD across populations is critical for policy development and resource planning. Administrative health data alone has insufficient sensitivity for this purpose, therefore utilizing population level laboratory data and novel methodology is required for population-based surveillance. The aims of this study include a) develop the Manitoba CKD Cohort, b) estimate CKD prevalence, c) identify individuals at high risk of progression to kidney failure and d) determine rates of comorbid health conditions.MethodsAdministrative health and laboratory data from April 1996 to March 2012 were linked from the data repository at the Manitoba Centre for Health Policy. Prevalence was estimated using three methods: a) all CKD cases in administrative and laboratory databases; b) all CKD cases captured only through the laboratory data; c) and the capture-recapture method. Patients were stratified by risk by estimated Glomerular Filtration Rate (eGFR) and albuminuria based on Kidney Disease Improving Global Outcomes (KDIGO) criteria. For comorbid health conditions, the counts were modelled using a Generalized Linear Model (GLM).ResultsThe Manitoba CKD Cohort consisted of 55,876 people with CKD. Of these, 18,342 were identified using administrative health data, 27,393 with laboratory data, and 10,141 people were identified in both databases. The CKD prevalence was 5.6% using the standard definition, 10.6% using only people captured by the laboratory data and 10.6% using the capture-recapture method. Of the identified cases, 46% were at high risk of progression to end-stage kidney disease (ESKD), 41% were at low risk and 13% were not classified, due to unavailable laboratory data. High risk cases had a higher burden of comorbid conditions.ConclusionThis study reports a novel methodology for population based CKD surveillance utilizing a combination of administrative health and laboratory data. High rates of CKD at risk of progression to ESKD have been identified with this approach. Given the high rates of comorbidity and associated healthcare costs, these data can be used to develop a targeted and comprehensive public health surveillance strategy that encompass a range of interrelated chronic diseases.

Project description:BackgroundInitiation of maintenance dialysis therapy for patients with chronic kidney failure is a period of high risk for adverse patient outcomes. Whether indications for dialysis therapy initiation are associated with mortality in this population is unknown.Study designRetrospective cohort study.Setting & participants461 patients who initiated dialysis therapy (hemodialysis, 437; peritoneal dialysis, 24) from January 1, 2004, through December 31, 2012, and were treated in facilities operated by a single dialysis organization. Follow-up for the primary outcome was through December 31, 2013.PredictorClinically documented primary indication for dialysis therapy initiation, as categorized into 4 groups: laboratory evidence of kidney function decline (reference category), uremic symptoms, volume overload or hypertension, and other/unknown.OutcomesAll-cause mortality.ResultsDuring a median follow-up of 2.4 years, 183 (40%) patients died. Crude mortality rates were 10.0 (95% CI, 6.8-14.7), 12.7 (95% CI, 10.2-15.7), 21.7 (95% CI, 16.4-28.6), and 12.2 (95% CI, 6.8-14.7) deaths/100 patient-years among patients initiating dialysis therapy primarily for laboratory evidence of kidney function decline, uremic symptoms, volume overload or hypertension, and other/unknown reason, respectively. Following adjustment for demographic variables, coexisting illnesses, and estimated glomerular filtration rate, initiation of dialysis therapy for uremic symptoms, volume overload or hypertension, or other/unknown reasons was associated with 1.12 (95% CI, 0.72-1.77), 1.69 (95% CI, 1.02-2.80), and 1.28 (95% CI, 0.73-2.26) times higher risk, respectively, for subsequent mortality compared to initiation for laboratory evidence of kidney function decline.LimitationsPossibility of residual confounding by unmeasured variables; reliance on clinical documentation to ascertain exposure.ConclusionsPatients initiating dialysis therapy due to volume overload may have increased risk for mortality compared with patients initiating dialysis due to laboratory evidence of kidney function decline. Further studies are needed to identify and test interventions that might reduce this risk.

Project description:Rationale & objectiveConcerns about nonadherent behaviors often prevent dialysis patients from entering waitlists for transplant even though there is an inconsistent association of these behaviors with posttransplant outcomes. We examined the association between plausible metrics of nonadherence related to dialysis treatment and posttransplant outcomes.Study designRetrospective cohort. We linked national dialysis treatment data with transplant registry data.Setting and participantsAdult patients receiving maintenance hemodialysis from January 1, 2004, through December 31, 2014, who received a kidney transplant at a US center.ExposuresWe examined 5 nonadherence metrics: serum potassium level (≥5.2 mEq/L), serum phosphorus level (>5.5 mg/dL), interdialytic weight gain (IDWG; ≥5 L), shortened treatments (≥30 min), and missed treatments (≥1); missed treatment data were available only for 2004-2009. These metrics were characterized per proportion of time under observation. Dialysis observation time was divided into 3-month intervals (quarters), and the number of nonadherent measurements in each domain was calculated for each quarter.OutcomesAllograft loss, mortality, and acute rejection in the first posttransplant year.Analytical approachUsing Cox proportional hazards and logistic regression, we estimated the hazard ratios for graft loss and mortality and odds ratios for rejection.Results9,543 patients met inclusion criteria. In our primary model, hyperphosphatemia (adjusted hazard ratio [aHR], 1.27 [95% CI, 1.08-1.49]), large IDWG (aHR, 1.39 [95% CI, 1.23-1.59]), and shortened treatments (aHR, 1.54 [95% CI, 1.12-2.13]) were associated with greater rates of allograft loss, but hyperkalemia was not. Large IDWG (aHR, 1.49 [95% CI, 1.29-1.73]) and shortened treatments (aHR, 1.34 [95% CI, 1.13-1.58]) were associated with mortality, whereas hyperkalemia and hyperphosphatemia were not. Only shortened treatments were associated with an increased risk of acute rejection (adjusted odds ratio, 3.88 [95% CI, 1.98-7.58]). In models limited to the years 2004-2009 that included missed treatments, missed treatments were associated only with mortality.LimitationsUnmeasured confounding (eg, dietary data); adherence metrics used may have multiple, complex causes.ConclusionsPlausible measures of dialysis nonadherence have long-term associations with allograft and patient survival. Behavioral metrics were more closely associated with outcomes than laboratory markers were. The implications of nonadherent behaviors for dialysis patients must be carefully considered before patients are excluded from transplantation.

Project description:Background and objectivesHistorically, length of pretransplant dialysis was associated with premature graft loss and mortality after kidney transplantation, but with recent advancements in RRT it is unclear whether this negative association still exists.Design, setting, participants, &measurementsThis is a retrospective cohort study evaluating 6979 first kidney allograft recipients from the Austrian Registry transplanted between 1990 and 2013. Duration of pretransplant dialysis treatment was used as categoric predictor classified by tertiles of the distribution of time on dialysis. A separate category for pre-emptive transplantation was added and defined as kidney transplantation without any dialysis preceding the transplant. Outcomes were death-censored graft loss, all-cause mortality, and the composite of both.ResultsMedian duration of follow-up was 8.2 years, and 1866 graft losses and 2407 deaths occurred during the study period. Pre-emptive transplantation was associated with a lower risk of graft loss (hazard ratio, 0.76; 95% confidence interval, 0.59 to 0.98), but not in subgroup analyses excluding living transplants and transplants performed since 2000. The association between dialysis duration and graft loss did not depend on the year of transplantation (P=0.40) or donor source (P=0.92). Longer waiting time on dialysis was not associated with a higher rate of graft loss, but the rate of death was higher in patients on pretransplant dialysis for >1.5 years (hazard ratio, 1.62; 95% confidence interval, 1.43 to 1.83) compared with pretransplant dialysis for <1.5 years.ConclusionsOur findings support the evidence that pre-emptive transplantation is associated with superior graft survival compared with pretransplant dialysis, although this association was weaker in transplants performed since 2000. However, our analysis shows that length of dialysis was no longer associated with a higher rate of graft loss, although longer waiting times on dialysis were still associated with a higher rate of death.

Dataset Information

Prediction of non-responsiveness to pre-dialysis care program in patients with chronic kidney disease: a retrospective cohort analysis.

Publications

Prediction of non-responsiveness to pre-dialysis care program in patients with chronic kidney disease: a retrospective cohort analysis.

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