Intrarenal Venous Flow Pattern Changes Do Relate With Renal Function Alterations in Acute Heart Failure

BACKGROUND

There is scarce evidence supporting the clinical utility of congestive intrarenal venous flow (IRVF) patterns in patients with acute heart failure.

OBJECTIVES

This study aims to: 1) investigate the association between IRVF patterns and the odds of worsening renal function (WRF); 2) track the longitudinal changes of serum creatinine (sCr) across IRVF at predetermined points and its association with decongestion; and 3) explore the relationship between IRVF/WRF categories and patient outcomes.

METHODS

IRVF was assessed at baseline (pre-decongestive therapy), 72 hours, and 30 and 90 days postdischarge. Changes in sCr trajectories across dynamic IRVF variations and parameters of decongestion were assessed using linear mixed effect models. The association between IRVF/WRF categories and outcomes was evaluated using univariable/multivariable models.

RESULTS

In this prospective, multicenter study with 188 participants, discontinuous IRVF patterns indicated higher odds of WRF (OR: 3.90 [95% CI: 1.24-12.20]; P = 0.020 at 72 hours; and OR: 5.76 [95% CI: 1.67-19.86]; P = 0.006 at 30 days) and an increase in sCr (Δ-72 hours 0.14 mg/dL [95% CI: 0.06-0.22]; P = 0.001; Δ-discharge 0.13 mg/dL [95% CI: 0.03-0.23]; P = 0.007). However, the diuretic response and decongestion significantly influenced the magnitude of these changes. Patients exhibiting both WRF and discontinuous IRVF at 30 days experienced an increased hazard of adverse events (HR: 5.96 [95% CI: 2.63-13.52]; P < 0.001).

CONCLUSIONS

Discontinuous IRVF identifies patients with higher odds of WRF during admission and postdischarge periods. Nonetheless, adequate diuretic response and decongestion could modify this association. Patients showing both WRF and discontinuous IRVF at 30 days had increased rates of adverse events.

Different kidney function trajectory patterns before dialysis in elderly patients: clinical implications and outcomes

Background. Identifying trajectories of kidney disease progression in chronic kidney disease (CKD) patients may help to deliver better care. We aimed to identify and characterize trajectories of renal function decline in CKD patients and to investigate their association with mortality after dialysis.

Methods. This retrospective cohort study included 378 CKD patients who initiated dialysis (aged 65 years and over) between 2009 and 2016. Were considered mixed models using linear quadratic and cubic models to define the trajectories, and we used probabilistic clustering procedures. Patient characteristics and care practices at and before dialysis were examined by multivariable multinomial logistic regression. The association of these trajectories with mortality after dialysis was examined using Cox models.

Results. Four distinct groups of eGFR trajectories decline before dialysis were identified: slower decline (18.3%), gradual decline (18.3%), early rapid decline (41.2%), and rapid decline (22.2%). Patients with rapid eGFR decline were more likely to have diabetes, more cognitive impairment, to have been hospitalized before dialysis, and were less likely to have received pre-dialysis care compared to the patients with a slower decline. They had a higher risk of death within the first and fourth year after dialysis initiation, and after being more than 4 years in dialysis.

Conclusions. There are different patterns of eGFR trajectories before dialysis initiation in the elderly, that may help to identify those who are more likely to experience an accelerated decline in kidney function, with impact on pre ESKD care and in the mortality risk after dialysis.

Assessing Risk of Rapid Progression in Autosomal Dominant Polycystic Kidney Disease and Special Considerations for Disease-Modifying Therapy

Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited cause of kidney failure, accounting for 5%-10% of cases. Predicting which patients with ADPKD will progress rapidly to kidney failure is critical to assess the risk-benefit ratio of any intervention and to consider early initiation of long-term kidney protective measures that will maximize the cumulative benefit of slowing disease progression. Surrogate prognostic biomarkers are required to predict future decline in kidney function. Clinical, genetic, environmental, epigenetic, and radiologic factors have been studied as predictors of progression to kidney failure in ADPKD. A complex interaction of these prognostic factors determines the number of kidney cysts and their growth rates, which affect total kidney volume (TKV). Age-adjusted TKV, represented by the Mayo imaging classification, estimates each patient's unique rate of kidney growth and provides the most individualized approach available clinically so far. Tolvaptan has been approved to slow disease progression in patients at risk of rapidly progressive disease. Several other disease-modifying treatments are being studied in clinical trials. Selection criteria for patients at risk of rapid progression vary widely among countries and are based on a combination of age, baseline glomerular filtration rate (GFR), GFR slope, baseline TKV, and TKV rate of growth. This review details the approach in assessing the risk of disease progression in ADPKD and identifying patients who would benefit from long-term therapy with disease-modifying agents.

Novel Risk Factors for Progression of Diabetic and Nondiabetic CKD: Findings From the Chronic Renal Insufficiency Cohort (CRIC) Study

RATIONALE & OBJECTIVE

Identification of novel risk factors for chronic kidney disease (CKD) progression may inform mechanistic investigations and improve identification of high-risk subgroups. The current study aimed to characterize CKD progression across levels of numerous risk factors and identify independent risk factors for CKD progression among those with and without diabetes.

STUDY DESIGN

The Chronic Renal Insufficiency Cohort (CRIC) Study is a prospective cohort study of adults with CKD conducted at 7 US clinical centers.

SETTING & PARTICIPANTS

Participants (N=3,379) had up to 12.3 years of follow-up; 47% had diabetes.

PREDICTORS

30 risk factors for CKD progression across sociodemographic, behavioral, clinical, and biochemical domains at baseline.

OUTCOMES

Study outcomes were estimated glomerular filtration rate (eGFR) slope and the composite of halving of eGFR or initiation of kidney replacement therapy.

ANALYTICAL APPROACH

Stepwise selection of independent risk factors was performed stratified by diabetes status using linear mixed-effects and Cox proportional hazards models.

RESULTS

Among those without and with diabetes, respectively, mean eGFR slope was-1.4±3.3 and-2.7±4.7mL/min/1.73m² per year. Among participants with diabetes, multivariable-adjusted hazard of the composite outcome was approximately 2-fold or greater with higher levels of the inflammatory chemokine CXCL12, the cardiac marker N-terminal pro-B-type natriuretic peptide (NT-proBNP), and the kidney injury marker urinary neutrophil gelatinase-associated lipocalin (NGAL). Among those without diabetes, low serum bicarbonate and higher high-sensitivity troponin T, NT-proBNP, and urinary NGAL levels were all significantly associated with a 1.5-fold or greater rate of the composite outcome.

LIMITATIONS

The observational study design precludes causal inference.

CONCLUSIONS

Strong associations for cardiac markers, plasma CXCL12, and urinary NGAL are comparable to that of systolic blood pressure≥140mm Hg, a well-established risk factor for CKD progression. This warrants further investigation into the potential mechanisms that these markers indicate and opportunities to use them to improve risk stratification.

Real-Time Prediction of Acute Kidney Injury in Hospitalized Adults: Implementation and Proof of Concept

RATIONALE & OBJECTIVE

Acute kidney injury (AKI) is diagnosed based on changes in serum creatinine concentration, a late marker of this syndrome. Algorithms that predict elevated risk for AKI are of great interest, but no studies have incorporated such an algorithm into the electronic health record to assist with clinical care. We describe the experience of implementing such an algorithm.

STUDY DESIGN

Prospective observational cohort study.

SETTING & PARTICIPANTS

2,856 hospitalized adults in a single urban tertiary-care hospital with an algorithm-predicted risk for AKI in the next 24 hours>15%. Alerts were also used to target a convenience sample of 100 patients for measurement of 16 urine and 6 blood biomarkers.

EXPOSURE

Clinical characteristics at the time of pre-AKI alert.

OUTCOME

AKI within 24 hours of pre-AKI alert (AKI₂₄).

ANALYTICAL APPROACH

Descriptive statistics and univariable associations.

RESULTS

At enrollment, mean predicted probability of AKI₂₄ was 19.1%; 18.9% of patients went on to develop AKI₂₄. Outcomes were generally poor among this population, with 29% inpatient mortality among those who developed AKI₂₄ and 14% among those who did not (P<0.001). Systolic blood pressure<100mm Hg (28% of patients with AKI₂₄ vs 18% without), heart rate>100 beats/min (32% of patients with AKI₂₄ vs 24% without), and oxygen saturation<92% (15% of patients with AKI₂₄ vs 6% without) were all more common among those who developed AKI₂₄. Of all biomarkers measured, only hyaline casts on urine microscopy (72% of patients with AKI₂₄ vs 25% without) and fractional excretion of urea nitrogen (20% [IQR, 12%-36%] among patients with AKI₂₄ vs 34% [IQR, 25%-44%] without) differed between those who did and did not develop AKI₂₄.

LIMITATIONS

Single-center study, reliance on serum creatinine level for AKI diagnosis, small number of patients undergoing biomarker evaluation.

CONCLUSIONS

A real-time AKI risk model was successfully integrated into the EHR.

Longitudinal Estimated GFR Trajectories in Patients With and Without Type 2 Diabetes and Nephropathy

BACKGROUND

In clinical practice and clinical trials, changes in serum creatinine concentrations are used to evaluate changes in kidney function. It has been assumed that these changes follow a linear pattern when serum creatinine concentration is converted to estimated glomerular filtration rate (eGFR). However, the paradigm that kidney function declines linearly over time has been questioned by studies showing either linear or nonlinear patterns. To verify how this impacts on kidney end points in intervention trials, we analyzed eGFR trajectories in multiple clinical trials of patients with and without diabetes.

STUDY DESIGN

Longitudinal observational study.

SETTING & PARTICIPANTS

6 clinical trials with repeated measurements of serum creatinine.

PREDICTOR

Patient demographic and clinical parameters.

OUTCOMES

Probability of nonlinear eGFR function trajectory calculated for each patient from a Bayesian model of individual eGFR trajectories.

RESULTS

The median probability of a nonlinear eGFR decline in all trials was 0.26 (interquartile range, 0.13-0.48). The median probability was 0.28 in diabetes versus 0.09 in nondiabetes trials (P<0.01). The percentage of patients with a >50% probability of nonlinear eGFR decline was generally low, ranging from 19.3% to 31.7% in the diabetes trials and from 15.1% to 21.2% in the nondiabetes trials. In the pooled data set, multivariable linear regression showed that higher baseline eGFR, male sex, diabetes status, steeper eGFR slope, and non-renin-angiotensin-aldosterone-system antihypertensives were independently associated with a greater probability of a nonlinear eGFR trajectory.

LIMITATIONS

Relatively short follow-up and no measured GFR.

CONCLUSIONS

In both diabetes and nondiabetes trials, the majority of patients show a more or less linear eGFR decline. These data support the paradigm that in diabetic and nondiabetic kidney disease, eGFR decline progresses linearly over time during a clinical trial period. However, in diabetes, one should take the nonlinearity proportion into account in the design of a clinical trial.

Estimated GFR Trajectories of People Entering CKD Stage 4 and Subsequent Kidney Disease Outcomes and Mortality

BACKGROUND

Estimated glomerular filtration rate (eGFR) trajectories of people entering chronic kidney disease (CKD) stage 4 and their associations with subsequent kidney disease outcomes or death are not known.

STUDY DESIGN

Longitudinal observational cohort study.

SETTING & PARTICIPANTS

26,246 patients in the Veterans Affairs Healthcare System who entered CKD stage 4 in fiscal year 2008 followed up until October 2013.

FACTORS

5-year eGFR trajectories, demographic and health characteristics.

OUTCOMES

Composite kidney disease outcome of kidney failure, dialysis therapy or transplantation, and death.

RESULTS

Latent class group modeling and functional characterization suggest the presence of 3 distinct trajectory classes: class 1 (72%), consistent slow decline with absolute eGFR change of -2.45 (IQR, -3.89 to -1.16) mL/min/1.73m(2) per year; class 2 (18%), consistent fast decline and eGFR change of -8.60 (IQR, -11.29 to -6.66) mL/min/1.73m(2) per year; and class 3 (10%), early nondecline and late fast decline with eGFR change of -0.4mL/min/1.73m(2) per year in years 1 to 3 and -7.98 and -21.36mL/min/1.73m(2) per year in years 4 and 5, respectively. During 4.34 years of follow-up, 9,809 (37%) patients had the composite kidney disease outcome and 14,550 (55%) patients died. Compared to the referent group (trajectory class 1), HRs for 1-year risk for composite kidney disease outcome for trajectory classes 2 and 3 were 1.13 (95% CI, 1.05-1.22) and 0.67 (95% CI, 0.59-0.75), whereas HRs for 1-year risk for death for classes 2 and 3 were 1.17 (95% CI, 1.10-1.28) and 1.29 (95% CI, 1.18-1.42), respectively. The 1-year risk for composite kidney disease outcome was 32% and was 42% more likely than the risk for death in trajectory classes 1 and 2, respectively, whereas the risk for death was 67% more likely than the risk for composite kidney disease outcome in trajectory class 3.

LIMITATIONS

Inclusion criteria and mostly male participants limit generalizability of study results.

CONCLUSIONS

We characterized 3 different eGFR trajectory classes of people entering CKD stage 4. Our results suggest that the pattern of eGFR trajectory informs the risk for kidney disease outcomes and death.