Prognostic Signature Of Chronic Kidney Disease in Advanced Age: Secondary Analysis From The InGAH Study With One-Year Follow-Up

Abstract: The negative impact of chronic kidney disease (CKD) on health status and quality of life in older patients has been well documented. However, data on frailty trajectories and long-term outcomes of older CKD patients undergoing structured Comprehensive Geriatric Assessment (CGA) with multidimensional frailty evaluation are sparse. Here, we analyzed records from 375 CKD patients admitted to our university hospital (mean age 77.5 (SD 6.1) years, 36% female) who had undergone a CGA-based calculation of the frailty score with the multidimensional prognostic index (MPI) as well as follow-up evaluations at 3, 6 and 12 months after discharge. Based on the MPI score at admission, 21% of the patients were frail and 56% were prefrail. MPI values were significantly associated with KDIGO CKD stages (p = 0.003) and rehospitalization after 6 months (p = 0.027) and mortality at 3, 6 and 12 months (p = 0.001), independent of chronological age. Kidney transplant recipients (KTR) showed significantly lower frailty compared to patients with renal replacement therapy (RRT, p = 0.028). The association between frailty and mortality after 12 months appeared particularly strong for KTR (mean MPI 0.43 KTR vs. 0.52 RRT, p < 0.001) and for patients with hypoalbuminemia (p < 0.001). Interestingly, RRT was per se not significantly associated with mortality during follow-up. However, compared to patients on RRT those with KTR had a significantly lower grade of care (p = 0.031) and lower rehospitalization rates at 12 months (p = 0.010). The present analysis shows that the large majority of older CKD inpatients are prefrail or frail and that the risk for CKD-related adverse outcomes on the long term can be accurately stratified by CGA-based instruments. Further studies are needed to explore the prognostic and frailty-related signature of laboratory biomarkers in CKD. 

Keywords: chronic kidney disease; frailty; kidney transplantation; laboratory signature; prognosis; renal replacement therapy (RRT) 

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1. Introduction 

As life expectancy continues to improve, kidney aging has become an important challenge in clinical practice [1]. In an intra- and interindividual heterogenous way, kidney function decreases with increasing age, mainly due to vascular stiffening and fibrosis. Kidneys are among the organs with the most prominent changes during aging [2,3], some of the latter being associated to pathologic manifestations and others being part of the physiological aging process [4]. A decline in total nephron size and number, tubulointerstitial changes, glomerular basement membrane thickening and increased glomerulosclerosis (nephrosclerosis) are observed [4]. In addition, altered hemodynamic, physiologic and transcriptomic behavior at rest impact on response to renal insults [2]. As a consequence, the ability of the kidney to withstand and recover from injury declines with age and the risk of developing progressive chronic kidney disease (CKD) increases [4]. CKD is a complex condition generally arising from a disordered kidney filtration barrier within glomeruli and is defined as damage of the glomerular filter (i.e., albuminuria) or decreased kidney function (i.e., glomerular filtration rate [GFR] <60 mL/min per 1.73 m2 ) lasting 3 months or longer, irrespective of clinical diagnosis [5,6] (Figure 1). CKD and its management are classified according to the 2012 KDIGO (Kidney Disease: Improving Global Outcomes) CKD guidelines; disease severity stages based upon GFR and albuminuria [7]. Due to the recent demographic change and predicted steep increase of the oldest-old population [8], CKD is a global public health priority. CKD affects more than 10% of the world's population [5] and patients with CKD account for 20% of all medicare expenditures in people over 65 years of age [9,10]. In addition to the age-related changes mentioned above, the causes of CKD are as heterogeneous as aging itself and affect the kidney structure and function, such as hypertension, diabetes, and hyperlipidemia. In turn, CKD is associated with an increased risk of cardiovascular diseases, overall mortality, end-stage renal disease (ESRD) [11–14], frailty as well as high hospitalization rates and disability [15–17]. 

Figure 1. Structural and functional changes in the aging kidney. Cell senescence leading to microscopic and macroscopic changes implies changes in kidney function. These are accompanied by clinical changes. (Modified from [1,4,18–20]), EZM: extracellular matrix; GFR: glomerular filtration rate; CKD: chronic kidney disease; AKI: acute kidney injury; RAS: renin-angiotensin-system; NO: nitrogen). 

In the past recent years, effective treatment options have been developed that can prevent the progress to renal failure in addition to reducing complication rates and the risk of cardiovascular disease and, therefore, improving survival and quality of life [21–25]. In advanced age, however, the success of interventions is often limited by overall frailty, disability, and geriatric syndromes [26]. 

Therefore, personalized strategies tailored to the patient's functional status and risk are highly warranted [5,17,27,28]. Tailored interventions need to be established upon a solid base of evidence, but there is a substantial lack of data on the long-term outcomes of clinically well-characterized older CKD patients. To close this gap of knowledge, the present analysis aimed at investigating the overall frailty status and prognosis of older CKD inpatients treated in a highly specialized Nephrology unit and undergoing a structured Comprehensive Geriatric Assessment (CGA) with the calculation of prognosis and multidimensional frailty according to a highly validated tool, the Multidimensional Prognostic Index (MPI) [29–32]. 

2. Material and Methods 

2.1. Patients and Methods 

The data presented here result from the secondary analysis of the MPI-InGAH study, which was conducted between June 2016 and July 2020, as previously described [28,33,34]. In this prospective, observational study, a total of 565 patients were recruited (Figure 2). This study was conducted according to the World Medical Association's 2008 Declaration of Helsinki, the Guidelines for Good Clinical Practice and the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. The Ethical Committee of the University Hospital of Cologne approved the study (EK 16-213). All patients (or proxy respondents, when medical records indicated incapacity to give informed consent) signed informed consent to participate. Recruitment was carried out at the Department of Nephrology, Rheumatology, Diabetology and General Internal Medicine of the University Hospital of Cologne. Inclusion criteria were age over 65 years, multimorbidity (defined as the coexistence of multiple (two or more) conditions, requiring long-term treatment [35]) and a hospitalization period longer than four days. Exclusion criteria were refusal to participate in the study, language barrier, and a hospitalization period of less than four days. Patients underwent a CGA with a prognosis calculation using the MPI as described before [32]. Briefly, Activities of Daily Living (ADL) [36], Instrumental Activities of Daily Living (IADL) [37], Mini-Nutritional assessment form (MNA-SF) [38], Short Portable Mental Status Questionnaire (SPMSQ) [39], Cumulative Illness Rating Scale (CIRS) [40] and Exton Smith Scale (ESS) [41]-as well as number of drugs taken by the patient and living conditions-were collected to calculate the MPI, which generates continuous values between 0 and 1. These can be used to subgroup patients into MPI-1 (robust, 0.00–0.33), MPI-2 (prefrail, 0.34–0.66) and MPI-3 (frail, 0.67–1.00) classes, to inform about low (MPI-1), medium (MPI-2) and high (MPI-3) risk, respectively, of mortality, rehospitalization, admission to long-term care facilities and increase of nursing needs within 1, 6 and 12 months after initial evaluation [42]. Additional information was collected regarding the presence of 16 geriatric syndromes (GS) and 11 resources (GR) [28], as well as their reciprocal relationships. Information on grade of care (GC, level of care and nursing needs according to the German nursing care insurance (grade 0 to 5, with 0 indicating no dependence [43])) was also available for all patients. All patients received follow-up calls 3, 6 and 12 months after discharge and were asked for the following information: mortality, length of hospital stay (LHS), GC, institutionalization, number of medications, rehospitalization and home care. 

Furthermore, data obtained in the context of curative care such as laboratory data (blood and urine samples) were evaluated retrospectively for blood on admission (±3 days) and on discharge (±3 days); for urine, we only collected one sample-if several samples were preserved, we only analysed the first sample.

2.2. Data for Present Secondary Analysis 

In the present secondary analysis, patients were included if they (1) had a diagnosis of CKD, defined as kidney damage or eGFR < 90 mL/min/1.73 m2 for 3 months or more, irrespective of cause [5], or were kidney transplant recipients (KTR), and (2) had undergone CGA during hospitalization. Of the 565 screened patients, 375 met the criteria and were included for further analysis (Figure 2). The clinical information on kidney disease status was based on hospital records, with the main requirement of availability of CKD stage according to the KDIGO classification (KDIGO G2: GFR 60–89 mL/min/1.73 m2, G3a: GFR 45–59 mL/min/1.73 m2 , G3b: GFR 30–44 mL/min/1.73 m2 , G4: GFR 15–29 mL/min/1.73 m2 , G5: GFR < 15 mL/min/ 1.73 m2 ; A1: albuminuria < 30 mg/g creatinine, A2: albuminuria 30–300 mg/g creatinine, A3: albuminuria > 300 mg/g creatinine [44]). Based on the latter, patients requiring renal replacement therapy (RRT) were recorded as belonging to stage G5. CKD cause, laboratory values on admission and discharge as well as comorbidities and concomitant medications were collected. If patients had required RRT, pre- or in-hospital baseline was recorded, including access information-venous or peritoneal catheter vs. vascular access (shunt)-as well as on type of RRT (hemodialysis (HD) vs. peritoneal dialysis (PD)). If patients were KTR, the type of donation (deceased donor, living donor) and the date of renal transplantation were recorded.

2.3. Statistical Analysis

Descriptive statistics are expressed using absolute numbers and relative frequencies for categorical variables and means (standard deviation, SD) or medians (quartiles (Q) Q1–Q3) for continuous variables.

Normal distribution was tested by Kolmogorov–Smirnov tests. Depending on the distribution, continuous variables were compared by t-tests or non-parametric Mann–Whitney U tests between two groups, by Kruskal–Wallis tests between more than two groups. Rates were compared by the Chi-square test or Fisher's exact test. The variable "more GR than GS" was calculated by comparing the relative number of 16 GS with the relative number of 11 GR. If there were more GR than GS, this variable was rated "yes".

In Table 1, all CKD patients (n = 375) were subdivided according to their MPI risk group at admission (MPI-1 to MPI-3), p-values were calculated to test the association between MPI score and the tested variable and adjusted for age, gender and KDIGO G-stage with linear/logistic regression analysis. 

Notes: LHS = Length of hospital stay; MPI = Multidimensional Prognostic Index; CIRS = Cumulative Illness Rating Scale; ADL = Activities of Daily living; IADL = Instrumental Activities of Daily Living; MNA-SF = Mini Nutritional Assessment-Short form; SPMSQ = Short Portable Mental Status Questionnaire; ESS = Exton Smith Scale ◦ after linear/logistic regression analysis, results were adjusted for age, gender and KDIGO G-stadium. In Table 2, all CKD patients (n = 375) were compared based on KDIGO G-stage (G2-G5). Similarly, p-values were adjusted for age, gender and MPI with linear/logistic regression analysis.

Notes: Patients were subdivided into KDIGO-G group after the known prehospital diagnosis of CKD KDIGO, all patients being under RRT were classified as stage G5. If information according to the KDIGO group was missing, the best achieved GFR admission or discharge was used for classification. If there was one piece of information missing of GFR admission or discharge, patients were excluded from analysis. LHS = Length of hospital stay; MPI = Multidimensional Prognostic Index; CIRS = Cumulative Illness Rating Scale; ADL= Activities of Daily living; IADL = Instrumental Activities of Daily Living; MNA-SF = Mini Nutritional Assessment-Short form; SPMSQ = Short Portable Mental Status Questionnaire; ESS = Exton Smith Scale; ◦ after linear/logistic regression analysis, results were adjusted for age, gender and MPI. 

Table 3 tested the association of patients undergoing RRT (n = 138) with HD or PD, which has been adjusted for MPI with linear/logistic regression analysis.