Personalized dynamic risk assessment in nephrology is a next step in prognostic research

Association of longitudinal cardiac troponin trajectory with adverse events in patients with cardiac sarcoidosis

BACKGROUND

Although high-sensitivity cardiac troponins may be sensitive and easily repeatable markers of disease activity in patients with cardiac sarcoidosis (CS), the association between longitudinal cardiac troponin trajectory and adverse events remains unclear. This study aimed to clarify whether longitudinal cardiac troponin levels were associated with adverse events in patients with CS.

METHODS

We examined 63 consecutive CS-initiated prednisolone (PSL) patients with available longitudinal high-sensitivity cardiac troponin T (cTnT) data between December 2013 and March 2023. The area under the cTnT trajectory, which reflected cumulative cTnT release, was calculated to assess the association between longitudinal cTnT levels and adverse events. Patients were divided into two groups according to the median area under the cTnT trajectory per month. The primary outcome was a composite of sustained ventricular tachycardia or fibrillation, worsening heart failure, and sudden cardiac death (SCD).

RESULTS

In total, 463 cTnT measurements were collected over a median follow-up period of 30.4 (interquartile range [IQR] 15.6-34.2) months. The primary outcome was observed in 12 (19%) patients. A higher area under the cTnT trajectory was significantly associated with an increased incidence of the primary outcome (P = 0.027), while cTnT levels before and one month after initiation of PSL, and these changes were not related to adverse events (P = 0.179, 0.096, and 0.95, respectively).

CONCLUSIONS

Longitudinal cTnT trajectory following PSL initiation was associated with adverse cardiac events in patients with CS, suggesting that longitudinal measurement of cTnT would be useful for the early identification of high-risk patients.

Weight Loss, Lifestyle Intervention, and Metformin Affect Longitudinal Relationship of Insulin Secretion and Sensitivity

CONTEXT

Insulin secretion and sensitivity regulate glycemia, with inadequately compensated deficiencies leading to diabetes.

OBJECTIVE

We investigated effects of weight loss, an intensive lifestyle intervention (ILS), and metformin on the relationship between insulin secretion and sensitivity using repository data from 2931 participants in the Diabetes Prevention Program clinical trial in adults at high risk of developing type 2 diabetes.

METHODS

Insulin secretion and sensitivity were estimated from insulin and glucose concentrations in fasting and 30-minute postload serum samples at baseline and 1, 2, and 3 years after randomization, during the active intervention phase. The nonlinear relationship of secretion and sensitivity was evaluated by standardized major axis regression to account for variability in both variables. Insulin secretory demand and compensatory insulin secretion were characterized by distances along and away from the regression line, respectively.

RESULTS

ILS and metformin decreased secretory demand while increasing compensatory insulin secretion, with greater effects of ILS. Improvements were directly related to weight loss; decreased weight significantly reduced secretory demand (b=-0.144 SD; 95% CI (-0.162, -0.125)/5 kg loss) and increased compensatory insulin secretion (b = 0.287 SD, 95% CI (0.261, 0.314)/5 kg loss). In time-dependent hazard models, increasing compensatory insulin secretion (hazard ratio [HR] = 0.166 per baseline SD, 95% CI 0.133, 0.206) and weight loss (HR = 0.710 per 5 kg loss, 95% CI 0.613, 0.819) predicted lower diabetes risk.

CONCLUSION

Diabetes risk reduction was directly related to the amount of weight loss, an effect mediated by lowered insulin secretory demand (due to increased insulin sensitivity) coupled with improved compensatory insulin secretion.

Determinants of the Evolution of Kidney Function With Age

Introduction

Kidney function declines with age, but its determinants in the general population remain incompletely understood. We investigated the rate and determinants of kidney function decline in the general population.

Methods

Participants with information on kidney function were selected from a population-based cohort study. Joint models were used to investigate the evolution of the estimated glomerular filtration rate (eGFR, expressed in ml/min per 1.73 m² per year) and the urine albumin-to-creatinine ratio (ACR, expressed in mg/g per year) with age. We stratified for 8 potential determinants of kidney function decline, including sex, cardiovascular risk factors, and cardiovascular disease.

Results

We included 12,062 participants with 85,922 eGFR assessments (mean age 67.0 years, 58.7% women) and 3522 participants with 5995 ACR measurements. The annual eGFR decline was 0.82 and the ACR increase was 0.05. All determinants appeared detrimental for eGFR and ACR, except for prediabetes and higher body mass index which proved only detrimental for ACR. In participants without the determinants, eGFR decline was 0.75 and ACR increase was 0.002. Higher baseline eGFR but faster eGFR decline with age was detected in men (0.92 vs. 0.75), smokers (0.90 vs. 0.75), and participants with diabetes (1.07 vs. 0.78).

Conclusion

We identify prediabetes, smoking, and blood pressure as modifiable risk factors for kidney function decline. As with diabetes, hyperfiltration seems important in accelerated kidney function decline in men and smokers. The interpretation of kidney function decline may require adjustment for age and sex to prevent overdiagnosis of chronic kidney disease in aging populations.

Serum Albumin Trends in Relation With Prognosis of Individuals Receiving Hemodialysis Therapy

Introduction

Hypoalbuminemia is recognized as an indication of protein-energy depletion in several disease states. According to many studies, hemodialysis (HD) patients who have decreased baseline serum albumin levels exhibit a poor prognosis. However, serum albumin does not stay at a constant level with the progress of the disease, considering that only a baseline value may not precisely reflect prognostic value. The study objective was to ascertain whether there is a link between serum albumin trajectories and all-cause mortality in incident HD patients. 

Methods

Retrospective cohort analysis was conducted in the HD unit at the University of Health Sciences, Kayseri Training and Research Hospital, Nephrology Clinic between June 19, 2010, and December 29, 2017. A total of 408 individuals aged 18 years or older, who had at least one measurement of serum albumin at baseline, were enrolled. The outcome was all-cause death. Time-dependent Cox regression and joint model were used to investigate the associations between serum albumin trend in time and the risk of all-cause mortality.

Results

Mean (SD) age was 62.17 (12.33) years, and 50.7% were male. At baseline, the mean (SD) albumin level was 3.59 (0.27). A faster decrease (per 1-SD increase in negative slope) in serum albumin levels was associated with increased risk of all-cause mortality (HR, 1.63; 95% CI, 1.08-2.84; p=0.023) in a fully adjusted joint model with slope parameterization. Also, an annual 1-SD increase in albumin level declined the hazard of all-cause mortality by 22% (HR, 0.78; 95% CI, 0.66-0.92; p=0.008) in a fully adjusted joint model with value parameterization. Similar results were obtained from time-dependent Cox models.

Conclusion

These findings suggest that longitudinal albumin evaluation, including the rate of change as a slope parameter, may be valuable for risk stratification of patients receiving HD.

Individualized prediction for the occurrence of acute kidney injury during the first postoperative week following cardiac surgery

STUDY OBJECTIVE

To develop individualized dynamic predictions for the occurrence of acute kidney injury (AKI) during the first postoperative week after cardiac surgery.

DESIGN

Observational retrospective cohort study.

SETTING

Single university teaching hospital in Madrid, Spain.

PATIENTS

3960 cases of major cardiac surgery performed from January 2002 to December 2013.

MEASUREMENTS

Baseline demographic and clinical characteristics, intraoperative risk factors, and repeated postoperative estimated glomerular filtration rates (eGFR). The primary outcome was AKI during the first postoperative week (stage 1 or higher of the Acute Kidney Injury Network). The dataset was split in two random samples (exploratory and validation). By combining time-to-event outcomes (AKI), and longitudinal data (repeated postoperative eGFR), we developed two different joint models for patients with normal and high baseline levels of serum creatinine (sCr).

MAIN RESULTS

AKI occurred in 1105 patients (31%, 95% confidence interval [CI] 29.5-32.5) in the exploratory sample and 128 (32.2%, 95% CI 27.6-36.8) in the validation sample. For high baseline sCr patients, the risk of an AKI event was associated with the eGFR trajectory (hazard ratio [HR] 0.91, 95% CI 0.90-0.92), as well as with age, and cardiopulmonary bypass time. The normal baseline sCr model incorporated the same covariates and intraoperative transfusion. In this second model, the risk of an AKI event was associated with both the eGFR trajectory (HR 0.91, 95% CI 0.91-0.92, for the current value of eGFR), and with its slope at that point (HR 0.96, 95% CI 0.94-0.99). So AKI risk decreased when the eGFR values increased, in accordance with the speed of this rise. Internal validation showed good discrimination and calibration of both joint models. The AUCs were always higher than 0.7.

CONCLUSIONS

The joint models obtained combining both patient risk factors and postoperative eGFR values, are useful to predict individualized risk of cardiac surgery-associated AKI. Predictions can be updated as new information is gathered.

Multivariate Longitudinal Assessment of Kidney Function Outcomes on Graft Survival after Kidney Transplantation Using Multivariate Joint Modeling Approach: A Retrospective Cohort Study

Background

The performance of a transplanted kidney is evaluated by monitoring variations in the value of the most important markers. These markers are measured longitudinally, and their variation is influenced by other factors. The simultaneous use of these markers increases the predictive power of the analytical model. This study aimed to determine the simultaneous longitudinal effect of serum creatinine and blood urea nitrogen (BUN) markers, and other risk factors on allograft survival after kidney transplantation.

Methods

In a retrospective cohort study, the medical records of 731 renal transplant patients, dated July 2000 to December 2013, from various transplant centers in Mashhad (Iran) were examined. Univariate and multivariate joint models of longitudinal and survival data were used, and the results from both models were compared. The R package joineRML was used to implement joint models. P values <0.05 were considered statistically significant.

Results

Results of the multivariate model showed that allograft rejection occurred more frequently in patients with elevated BUN levels (HR=1.68, 95% CI: 1.24-2.27). In contrast, despite a positive correlation between serum creatinine and allograft rejection (HR=1.49, 95% CI: 0.99-2.22), this relationship was not statistically significant.

Conclusion

Results of the multivariate model showed that longitudinal measurements of BUN marker play a more important role in the investigation of the allograft rejection.

Dynamic prediction models for graft failure in paediatric kidney transplantation

BACKGROUND

Several models have been proposed to predict kidney graft failure in adult recipients but none in younger recipients. Our objective was to propose a dynamic prediction model for graft failure in young kidney transplant recipients.

METHODS

We included 793 kidney transplant recipients waitlisted before the age of 18 years who received a first kidney transplantation before the age of 21 years in France in 2002-13 and survived >90 days with a functioning graft. We used a Cox model including baseline predictors only (sex, age at transplant, primary kidney disease, dialysis duration, donor type and age, human leucocyte antigen matching, cytomegalovirus serostatus, cold ischaemia time and delayed graft function) and two joint models also accounting for post-transplant estimated glomerular filtration rate (eGFR) trajectory. Predictive performances were evaluated using a cross-validated area under the curve (AUC) and R2 curves.

RESULTS

When predicting the risk of graft failure from any time within the first 7 years after paediatric kidney transplantation, the predictions for the following 3 or 5 years were accurate and much better with the joint models than with the Cox model (AUC ranged from 0.83 to 0.91 for the joint models versus 0.56 to 0.64 for the Cox model).

CONCLUSION

Accounting for post-transplant eGFR trajectory strongly increased the accuracy of graft failure prediction in young kidney transplant recipients.

Personalized screening intervals for kidney function in patients with chronic heart failure: a modeling study

Background

High mortality and rehospitalization rates demonstrate that improving risk assessment in heart failure patients remains challenging. Individual temporal evolution of kidney biomarkers is associated with poor clinical outcome in these patients and hence may carry the potential to move towards a personalized screening approach.

Methods

In 263 chronic heart failure patients included in the prospective Bio-SHiFT cohort study, glomerular and tubular biomarker measurements were serially obtained according to a pre-scheduled, fixed trimonthly scheme. The primary endpoint (PE) comprised cardiac death, cardiac transplantation, left ventricular assist device implantation or heart failure hospitalization. Personalized scheduling of glomerular and tubular biomarker measurements was compared to fixed scheduling in individual patients by means of a simulation study, based on clinical characteristics of the Bio-SHiFT study. For this purpose, repeated biomarker measurements and the PE were jointly modeled. For personalized scheduling, using this fitted joint model, we determined the optimal time point of the next measurement based on the patient’s individual risk profile as estimated by the joint model and the maximum information gain on the patient’s prognosis. We compared the schedule’s capability of enabling timely intervention before the occurrence of the PE and number of measurements needed.

Results

As compared to a pre-defined trimonthly scheduling approach, personalized scheduling of glomerular and tubular biomarker measurements showed similar performance with regard to prognostication, but required a median of 0.4–2.7 fewer measurements per year.

Conclusion

Personalized scheduling is expected to reduce the number of patient visits and healthcare costs. Thus, it may contribute to efficient monitoring of chronic heart failure patients and could provide novel opportunities for timely adaptation of treatment.

Graphic abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s40620-021-01014-0.

Trajectory of extracellular fluid volume over time and subsequent risks of end-stage kidney disease and mortality in chronic kidney disease: a prospective cohort study

BACKGROUND

Extracellular fluid volume (ECF) is independently associated with chronic kidney disease (CKD) progression and mortality in patients with CKD, but the prognostic value of the trajectory of ECF over time beyond that of baseline value is unknown.

OBJECTIVES

To characterize ECF trajectory and evaluate its association with the risks of end-stage kidney disease (ESKD) and mortality.

METHODS

From the prospective tricentric NephroTest cohort, we included 1588 patients with baseline measured glomerular filtration rate (mGFR) ≥15 mL min^-1 /1.73 m² and ECF measurement. ECF and GFR were measured repeatedly using the distribution volume and clearance of ⁵¹ Cr-EDTA, respectively. ESKD and mortality were traced through record linkage with the national registries. Adjusted shared random-effect joint models were used to analyse the association between the trajectory of ECF over time and the two competing outcomes.

RESULTS

Patients were mean age 58.7 years, 66.7% men, mean mGFR of 43.6 ± 18.6 mL min^-1 /1.73 m² and mean ECF of 16.1 ± 3.6 L. Over a median follow-up of 5.3 [IQR: 3.0;7.4] years, ECF increased by 136 [95%CI 106;167] mL per year on average, whilst diuretic prescription and 24-hour urinary sodium excretion remained stable. ESKD occurred in 324 (20.4%) patients, and 185 (11.6%) patients died before ESKD. A higher current value of ECF was associated with increased hazards of ESKD (adjusted hazard ratio [aHR]: 1.12 [95%CI 1.06;1.18]; P < 0.001 per 1 L increase in ECF), and death before ESKD (aHR: 1.10 [95%CI 1.04;1.17]; P = 0.002).

CONCLUSIONS

The current value of ECF was associated with the risks of ESKD and mortality, independent of multiple potential confounders, including kidney function decline. This highlights the need for a close monitoring and adjustment of treatment to avoid fluid overload in CKD patients.

Renal tubular damage and worsening renal function in chronic heart failure: Clinical determinants and relation to prognosis (Bio-SHiFT study)

Background

It is uncertain that chronic heart failure (CHF) patients are susceptible to renal tubular damage with that of worsening renal function (WRF) preceding clinical outcomes.

Hypothesis

Changes in tubular damage biomarkers are stronger predictors of subsequent clinical events than changes in creatinine (Cr), and both have different clinical determinants.

Methods

During 2.2 years, we repeatedly simultaneously collected a median of 9 blood and 8 urine samples per patient in 263 CHF patients. We determined the slopes (rates of change) of the biomarker trajectories for plasma (Cr) and urinary tubular damage biomarkers N‐acetyl‐β‐d‐glucosaminidase (NAG), and kidney‐injury‐molecule (KIM)‐1. The degree of tubular injury was ranked according to NAG and KIM‐1 slopes: increase in neither, increase in either, or increase in both; WRF was defined as increasing Cr slope. The composite endpoint comprised HF‐hospitalization, cardiac death, left ventricular assist device placement, and heart transplantation.

Results

Higher baseline NT‐proBNP and lower eGFR predicted more severe tubular damage (adjusted odds ratio, adj. OR [95%CI, 95% confidence interval] per doubling NT‐proBNP: 1.26 [1.07‐1.49]; per 10 mL/min/1.73 m² eGFR decrease 1.16 [1.03‐1.31]). Higher loop diuretic doses, lower aldosterone antagonist doses, and higher eGFR predicted WRF (furosemide per 40 mg increase: 1.32 [1.08‐1.62]; spironolactone per 25 mg decrease: 1.76 [1.07‐2.89]; per 10 mL/min/1.73 m² eGFR increase: 1.40 [1.20‐1.63]). WRF and higher rank of tubular injury individually entailed higher risk of the composite endpoint (adjusted hazard ratios, adj. HR [95%CI]: WRF 1.9 [1.1‐3.4], tubular 8.4 [2.6‐27.9]; when combined risk was highest 15.0 [2.0‐111.0]).

Conclusion

Slopes of tubular damage and WRF biomarkers had different clinical determinants. Both predicted clinical outcome, but this association was stronger for tubular injury. Prognostic effects of both appeared independent and additive.

Evolution of renal function and predictive value of serial renal assessments among patients with acute coronary syndrome: BIOMArCS study

BACKGROUND

Impaired renal function predicts mortality in acute coronary syndrome (ACS), but its evolution immediately following index ACS and preceding next ACS has not been described in detail. We aimed to describe this evolution using serial measurements of creatinine, glomerular filtration rate [eGFR_Cr] and cystatin C [CysC].

METHODS

From 844 ACS patients included in the BIOMArCS study, we analysed patient-specific longitudinal marker trajectories from the case-cohort of 187 patients to determine the risk of the endpoint (cardiovascular death or hospitalization for recurrent non-fatal ACS) during 1-year follow-up. Study included only patients with eGFR_Cr ≥ 30 ml/min/1.73 m². Survival analyses were adjusted for GRACE risk score and based on data >30 days after the index ACS (mean of 8 sample per patient).

RESULTS

Mean age was 63 years, 79% were men, 43% had STEMI, and 67% were in eGFR stages 2-3. During hospitalization for index ACS (median [IQR] duration: 5 (3-7) days), CysC levels indicated deterioration of renal function earlier than creatinine did (CysC peaked on day 3, versus day 6 for creatinine), and both stabilized after two weeks. Higher CysC levels, but not creatinine, predicted the endpoint independently of the GRACE score within the first year after index ACS (adjusted HR [95% CI] per 1SD increase: 1.68 [1.03-2.74]).

CONCLUSION

Immediately following index ACS, plasma CysC levels deteriorate earlier than creatinine-based indices do, but neither marker stabilizes during hospitalization but on average two weeks after ACS. Serially measured CysC levels predict mortality or recurrence of ACS during 1-year follow-up independently of patients' GRACE risk score.

Predicting kidney failure from longitudinal kidney function trajectory: A comparison of models

Rationale & objective

Early prediction of chronic kidney disease (CKD) progression to end-stage kidney disease (ESKD) currently use Cox models including baseline estimated glomerular filtration rate (eGFR) only. Alternative approaches include a Cox model that includes eGFR slope determined over a baseline period of time, a Cox model with time varying GFR, or a joint modeling approach. We studied if these more complex approaches may further improve ESKD prediction.

Study design

Prospective cohort.

Setting & participants

We re-used data from two CKD cohorts including patients with baseline eGFR >30ml/min per 1.73m². MASTERPLAN (N = 505; 55 ESKD events) was used as development dataset, and NephroTest (N = 1385; 72 events) for validation.

Predictors

All models included age, sex, eGFR, and albuminuria, known prognostic markers for ESKD.

Analytical approach

We trained the models on the MASTERPLAN data and determined discrimination and calibration for each model at 2 years follow-up for a prediction horizon of 2 years in the NephroTest cohort. We benchmarked the predictive performance against the Kidney Failure Risk Equation (KFRE).

Results

The C-statistics for the KFRE was 0.94 (95%CI 0.86 to 1.01). Performance was similar for the Cox model with time-varying eGFR (0.92 [0.84 to 0.97]), eGFR (0.95 [0.90 to 1.00]), and the joint model 0.91 [0.87 to 0.96]). The Cox model with eGFR slope showed the best calibration.

Conclusion

In the present studies, where the outcome was rare and follow-up data was highly complete, the joint models did not offer improvement in predictive performance over more traditional approaches such as a survival model with time-varying eGFR, or a model with eGFR slope.

Dynamic predictions of long-term kidney graft failure: an information tool promoting patient-centred care

Background

Informing kidney transplant recipients of their prognosis and disease progression is of primary importance in a patient-centred vision of care. By participating in decisions from the outset, transplant recipients may be more adherent to complex medical regimens due to their enhanced understanding.

Methods

We proposed to include repeated measurements of serum creatinine (SCr), in addition to baseline characteristics, in order to obtain dynamic predictions of the graft failure risk that could be updated continuously during patient follow-up. Adult recipients from the French Données Informatisées et VAlidées en Transplantation (DIVAT) cohort transplanted for the first or second time from a heart-beating or living donor and alive with a functioning graft at 1 year post-transplantation were included.

Results

The model was composed of six baseline parameters, in addition to the SCr evolution. We validated the dynamic predictions by evaluating both discrimination and calibration accuracy. The area under the receiver operating characteristic curve varied from 0.72 to 0.76 for prediction times at 1 and 6 years post-transplantation, respectively, while calibration plots showed correct accuracy. We also provided an online application tool (https://shiny.idbc.fr/DynPG).

Conclusion

We have created a tool that, for the first time in kidney transplantation, predicts graft failure risk both at an individual patient level and dynamically. We believe that this tool would encourage willing patients into participative medicine.