The burden of age-related disease is increasing at an alarming rate. The number of individuals aged ≥65 years globally is expected to surpass 1.5 billion by 2050, with India - which currently has more than 140 million older adults - undergoing one of the fastest demographic shifts ever recorded [1]. In this milieu, the interplay between chronic kidney disease (CKD), cognitive impairment, and frailty in the elderly presents a complex and burgeoning geriatric syndrome deserving of thorough study [2].

Frailty, a condition of vulnerability to stressors due to age-related decline in multiple physiological systems, impacts 10-15% of elderly in the community and 50% of CKD patients [3,4]. The frailty index (FI) - a cumulative frailty score based on the number of health deficits - has proven to be a strong predictor of adverse health outcomes such as hospitalisation, disability and death in the general population and in those with CKD [5]. Biologically, the association between CKD and frailty is bidirectional: low-grade inflammation, uremic toxins, metabolic acidosis, and nutritional abnormalities commonly found in CKD patients hasten frailty development, while frailty-related sarcopenia, physical inactivity and medication noncompliance contribute to progression of CKD [6,7].

Cognitive impairment (CI), which includes mild cognitive impairment (MCI) and dementia, is more common among CKD patients than in their age- and sex-matched counterparts [8]. Epidemiological evidence reveals a 1.5-2.4 fold higher prevalence of CI in CKD due to common vascular risk factors, accumulation of uremic neurotoxins (especially indoxyl sulfate and p-cresyl sulfate), cerebral hypoperfusion from anemia, as well as altered calcium-phosphorus balance and impaired neuronal signaling [9,10]. On the other hand, CI can potentially impact renal function through its effects on self-care, medication compliance, fluid and dietary control and the ability to seek timely medical care for symptomatic deterioration [11].

While these associations are plausible from a pathophysiological standpoint and of clinical consequence, few studies have provided retrospective data quantifying the role of frailty and CI in the rapid loss of renal function (RRFD) - defined as eGFR decline of ≥5 mL/min/1.73 m² per annum [12]. The majority of studies have investigated frailty and CI independently and those that do not include elderly South Asian populations, for whom the phenotype of CKD is distinct, with earlier age onset, greater prevalence of diabetes and hypertension, and different socioeconomic risk factors [13,14].

Moreover, the interaction of frailty and cognition in CKD has not been rigorously explored using established frailty indices (FI vs Fried phenotype), or comprehensive neuropsychological test batteries suitable for the multilingual elderly in India [15]. The Montreal Cognitive Assessment (MoCA), in its Hindi, Tamil and Bengali versions, is a sensitive and widely applicable tool for screening CI in Indian populations [16].

The primary objective of this study was to retrospectively examine the independent and synergistic associations between CI (assessed by MoCA), frailty (quantified by 36-item FI), and RRFD over 36 months in a multiethnic, multicenter Indian elderly cohort. Secondary objectives included characterizing the dose-response relationship between FI score and eGFR decline rate, identifying frailty-cognition interaction effects, and developing a predictive risk score for RRFD in routine clinical practice [17,18].

2.1 Study Design and Participants This was a multicenter, retrospective cohort study conducted across five centers in India: Christian Medical College (CMC), Vellore; AIIMS, Bhubaneswar; NIMHANS, Bengaluru; SGPGI, Lucknow; and ICMR-National Institute of Immunohaematology (NIIH), Mumbai. Adults aged ≥65 years were enrolled between January 2020 and December 2020 and followed until December 2024 (36-month minimum follow-up). Eligibility required: documented baseline eGFR ≥15 mL/min/1.73 m² on two measurements ≥90 days apart; and community-dwelling or hospital-attending status. Exclusion criteria included: acute kidney injury within 3 months; active malignancy; severe psychiatric illness; and terminal illness with <12-month prognosis. 2.2 Assessment Tools Cognitive function was assessed using the MoCA (validated vernacular versions: Hindi, Tamil, Kannada, Bengali, Marathi) at enrollment, 12, 24, and 36 months. CI was defined as MoCA score <26/30. Frailty was quantified using the 36-item Frailty Index (FI-36), derived from the Comprehensive Geriatric Assessment (CGA), encompassing cognitive, functional, clinical, and psychosocial health deficits. FI score = number of deficits present / total deficits assessed (0–1 scale). Frailty was defined as FI >0.25 (pre-frailty: 0.10–0.25; robust: <0.10). The Fried phenotype criteria were concurrently assessed for construct validation. 2.3 Primary and Secondary Outcomes The primary outcome was RRFD, defined as annual eGFR decline ≥5 mL/min/1.73 m² calculated by mixed-effects linear regression of serial eGFR measurements at 0, 6, 12, 18, 24, 30, and 36 months. Secondary outcomes included: all-cause mortality; incident CKD stage 5 or dialysis initiation; hospitalization rate; fall rate; and disability progression (assessed by ADL/IADL). eGFR was calculated using the 2021 CKD-EPI creatinine equation. 2.4 Covariates and Statistical Methods Pre-specified covariates included: age, sex, education level, baseline eGFR, diabetes, hypertension, cardiovascular disease, depressive symptoms (GDS-15), medication count, serum albumin, hemoglobin, and urinary albumin-creatinine ratio (UACR). Multivariable Cox proportional hazards regression was performed with RRFD as time-to-event outcome. Frailty×CI interaction was formally tested using a multiplicative interaction term. Propensity score-weighted sensitivity analyses were conducted. Spearman's rho was used for FI-eGFR correlation analysis. All analyses used STATA v17.0 (StataCorp) and R v4.3.1.

3.1 Baseline Characteristics

A total of 1,156 participants were enrolled (CMC: n=248; AIIMS-Bbsr: n=224; NIMHANS: n=218; SGPGI: n=232; ICMR-NIIH: n=234). Mean age was 72.8 ± 7.1 years and 47.8% (n=553) were female. Baseline eGFR was 46.2 ± 14.8 mL/min/1.73 m². CI was prevalent in 38.2% (n=442) and frailty in 41.4% (n=479). Co-occurrence of both CI and frailty was observed in 22.8% (n=264). Participants with both conditions were significantly older, more functionally dependent, and had lower baseline eGFR, higher UACR, and greater comorbidity burden. Table 1 presents full baseline characteristics stratified by frailty-CI status.

Table 1. Baseline Characteristics Stratified by Cognitive Impairment and Frailty Status (n = 1,156)

CI: cognitive impairment (MoCA <26); Frailty: FI >0.25; MoCA: Montreal Cognitive Assessment; UACR: urinary albumin-creatinine ratio; GDS: Geriatric Depression Scale; IQR: interquartile range; eGFR: estimated glomerular filtration rate.

3.2 Frailty, Cognitive Impairment, and eGFR Trajectory

Over 36 months, RRFD occurred in 22.4% of neither-group participants, 38.3% with frailty alone, 42.1% with CI alone, and 65.3% with both conditions. The cumulative incidence curves showed early divergence from 6 months onwards, with the combined frailty+CI group demonstrating a steeper incidence gradient (Figure 1). The annualized eGFR decline rate was −2.8 mL/min/yr (neither), −5.1 mL/min/yr (frailty alone), −5.6 mL/min/yr (CI alone), and −9.4 mL/min/yr (both; p<0.001 for all pairwise comparisons vs neither group). Table 2 details eGFR trajectory data across subgroups.

Table 2. Longitudinal eGFR Trajectory and Rapid Renal Decline by Frailty–Cognitive Impairment Profile (n = 1,156)

*p<0.001 vs neither group; †p<0.05 vs frailty-only and CI-only groups. RRFD: rapid renal function decline (annual eGFR loss ≥5 mL/min/1.73 m²); CI: cognitive impairment; eGFR: estimated glomerular filtration rate.

Figure 1 Legend: Cumulative incidence of rapid renal function decline (RRFD) over 36 months by frailty-cognitive impairment profile. Shaded bands represent 95% confidence intervals. Events censored at death or dialysis initiation.

3.3 Correlation Between Frailty Index and eGFR Decline

Frailty index score demonstrated a strong inverse correlation with annual eGFR decline rate across the full cohort (Spearman's rho = −0.63; p<0.001). This relationship was most pronounced in participants with concurrent CI (rho = −0.71; p<0.001) compared to those without CI (rho = −0.54; p<0.001). For every 0.10-unit increment in FI score, annual eGFR decline increased by 1.8 mL/min/yr (95% CI 1.4–2.2; p<0.001) after adjustment for age, diabetes, proteinuria, and medication count.

Figure 2 Legend: Scatter plot of frailty index score vs annual eGFR decline rate in a representative subsample (n=280). Blue points: no cognitive impairment; pink points: cognitive impairment present. Dashed line: linear regression (r=−0.63, p<0.001).

3.4 Multivariable Analysis and Interaction Effects

On fully adjusted multivariable Cox regression, frailty (HR 2.46; 95% CI 1.78–3.40; p<0.001), CI (HR 2.19; 95% CI 1.58–3.04; p<0.001), and their co-occurrence (HR 3.92; 95% CI 2.64–5.82; p<0.001) independently predicted RRFD. The interaction term between FI and CI was statistically significant (p_interaction = 0.004), indicating a greater-than-additive synergistic effect. Table 3 presents the full multivariable model including all significant predictors.

Table 3. Multivariable Cox Proportional Hazards Regression: Predictors of Rapid Renal Function Decline (n = 1,156)

HR: hazard ratio; CI: confidence interval; FI: frailty index; MoCA: Montreal Cognitive Assessment; UACR: urinary albumin-creatinine ratio; GDS: Geriatric Depression Scale. Model adjusted for education level, serum albumin, center, and medication count. Harrell's C-statistic = 0.79 (95% CI 0.76–0.82). p_interaction (FI × CI) = 0.004.

3.5 Secondary and Subgroup Outcomes

Both CI and frailty were associated with significantly elevated all-cause mortality (HR 2.84; 95% CI 1.76–4.60 for combined group), increased hospitalization rates (IRR 2.42; 95% CI 1.86–3.15), greater fall incidence (HR 3.18; 95% CI 2.24–4.52), and faster disability progression (ADL score change −1.8 vs −0.3 points/year in neither group; p<0.001). Importantly, the addition of frailty-cognition profile to a model containing traditional CKD risk factors improved the C-statistic from 0.71 to 0.79 (p<0.001), indicating substantial incremental predictive value. Table 4 provides comprehensive secondary outcome data.

Table 4. Secondary Clinical Outcomes at 36 Months by Frailty–Cognitive Impairment Profile

*p<0.001 vs neither group; †p<0.05 vs frailty-only and CI-only groups. ADL: Activities of Daily Living; IADL: Instrumental ADL; GDS: Geriatric Depression Scale.

Table 5. Diagnostic Performance of Frailty Index Thresholds for Predicting Rapid Renal Function Decline

PPV: positive predictive value; NPV: negative predictive value; FI: frailty index; MoCA: Montreal Cognitive Assessment. AUC for FI alone: 0.76 (95% CI 0.73–0.79); AUC for combined FI + MoCA: 0.82 (95% CI 0.79–0.85).

Table 6. Frailty Domain Contributions to Rapid Renal Function Decline Risk: Deficit-Specific Analysis (n = 1,156)

HR: hazard ratio; RRFD: rapid renal function decline; ADL: Activities of Daily Living; FI: frailty index. All models adjusted for age, sex, baseline eGFR, diabetes, hypertension, and UACR.

The present retrospective study of 1,156 older adults represents, to our knowledge, the biggest and most fully documented Indian cohort that supports a synergistic effect of frailty and cognitive impairment (CI) on rapid renal function decline (RRFD). The discovery of a nearly four-fold elevated hazard of RRFD in the context of CI and frailty (HR 3.92) - which far exceeds the individual effects of these conditions - is an important and practical contribution of our study, extending the findings from smaller studies from Western populations [18,19].

Our findings are broadly supportive of the landmark study by Johansen et al. [20], which pioneered the description of frailty as a predictor of CKD progression and death in the ESRD population, and the prospective results from the SPRINT trial sub-study by Beddhu et al. [21], which showed an increased decline in eGFR among frail hypertensive adults. Our study adds uniquely to the field by subjecting the frailty-CI interaction term (statistically significant at p=0.004) to formal testing, which suggests that neural and physical frailty amplify each other's adverse effects on the kidney via overlapping mechanisms that go beyond simple summation [22].

The underlying mechanisms for this synergy should be considered. First, CI and frailty have an inflammatory basis: increased interleukin-6, tumor necrosis factor-alpha and C-reactive protein are reported in both CI and frailty, and are independently related to glomerular damage and tubular atrophy [23]. Second, the cognitive-behavioral pathway, in which CI leads to impaired self-monitoring, dietary compliance, fluid intake, medication adherence and appropriate presentation to healthcare services for worsening symptoms, results in sustained exposure to modifiable nephrotoxic stressors, which gradually depletes residual renal reserve [24]. Third, frailty-related sarcopenia reduces creatinine production, which may conceal eGFR deterioration when it starts and an eGFR estimated by cystatin C would show greater deterioration, a phenomenon that may explain systematic underestimation of eGFR in frail elderly patients [25].

Our observed robust negative association between FI score and eGFR annual decline (r=−0.63; p<0.001) is consistent with the Canadian Longitudinal Study on Aging (CLSA), which found that a 10-unit rise in FI was associated with a significantly higher odds of deterioration of renal function over 3 years [26]. More importantly, our frailty-cognition model exhibited an AUC of 0.82 - well above the 0.70-0.75 range typically reported with traditional models of CKD risk - suggesting that incorporating frailty and cognition screening may enhance the accuracy of CKD risk models [27].

In terms of clinical management, our results advocate for the routine screening for frailty and cognitive impairment as part of the multidisciplinary assessment in CKD, in line with current KDIGO 2024 guidelines, which specifically recommend geriatric assessment in older adults with CKD [28]. The MoCA, available in validated Indian language versions, taking 5-10 minutes to administer, is an accessible first-line cognitive screening instrument for incorporation in existing nephrology outpatient practice [29]. The deficit analysis in clinical domains (Table 6) suggests that hypoalbuminemia, altered orientation, impaired gait speed and polypharmacy are especially high-value targets for intervention in the frailty-CKD risk-reduction paradigm [30].

Our study has some limitations. The FI-36 was adapted from a standard CGA tool and may have not assessed some frailty elements (e.g., cardiovascular reserve) that may be more relevant to CKD-specific frailty. The diverse educational backgrounds of our patients may have resulted in ceiling or floor effects (despite employing age- and education-adjusted normative data) in MoCA scores. The 36-month loss to follow-up (14.2%) may have biased our results by preferentially losing frailer patients. Lastly, causality cannot be inferred from observational studies; reverse causality (i.e. subclinical renal dysfunction driving frailty and cognitive impairment) is thus not ruled out, although the retrospective nature of the study with 36-month follow-up data largely allays this concern [31].

Cognitive impairment and frailty independently and synergistically predict rapid renal function decline in elderly individuals, with their co-occurrence conferring a nearly four-fold elevated hazard beyond traditional CKD risk factors. The strong FI-eGFR correlation and the incremental predictive value of the combined frailty-cognition model highlight frailty and cognitive assessment as high-yield additions to CKD risk stratification in older adults. These findings support the integration of MoCA screening and frailty index quantification into routine geriatric nephrology practice, with targeted nephroprotective interventions directed at high-risk frailty-cognition phenotypes. Future randomized controlled trials examining the impact of frailty-directed interventions — including exercise rehabilitation, nutritional optimization, and cognitive training — on CKD progression trajectories are urgently warranted.

[1] United Nations Department of Economic and Social Affairs. World Population Ageing 2023. New York: United Nations; 2023.

[2] Clegg A, Young J, Iliffe S, Rikkert MO, Rockwood K. Frailty in elderly people. Lancet. 2013;381(9868):752–762.

[3] Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001;56(3):M146–M156.

[4] Johansen KL, Chertow GM, Jin C, Kutner NG. Significance of frailty among dialysis patients. J Am Soc Nephrol. 2007;18(11):2960–2967.

[5] Rockwood K, Mitnitski A. Frailty in relation to the accumulation of deficits. J Gerontol A Biol Sci Med Sci. 2007;62(7):722–727.

[6] McAdams-DeMarco MA, Law A, Salter ML, Boyarsky B, Gimenez L, Jaar BG, et al. Frailty as a novel predictor of mortality and hospitalization in individuals of all ages undergoing hemodialysis. J Am Geriatr Soc. 2013;61(6):896–901.

[7] Kurella Tamura M, Covinsky KE, Chertow GM, Yaffe K, Landefeld CS, McCulloch CE. Functional status of elderly adults before and after initiation of dialysis. N Engl J Med. 2009;361(16):1539–1547.

[8] Yaffe K, Ackerson L, Kurella Tamura M, Le Blanc P, Kusek JW, Sehgal AR, et al. Chronic kidney disease and cognitive function in older adults: findings from the chronic renal insufficiency cohort cognitive study. J Am Geriatr Soc. 2010;58(2):338–345.

[9] Bugnicourt JM, Godefroy O, Chillon JM, Choukroun G, Massy ZA. Cognitive disorders and dementia in CKD: the neglected kidney-brain axis. J Am Soc Nephrol. 2013;24(3):353–363.

[10] Thijssen S, Raimann JG, Usvyat LA, Levin NW, Kotanko P. The everpresent link between kidney function and the brain. Blood Purif. 2012;34(2):137–142.

[11] Murray AM. Cognitive impairment in the aging dialysis and chronic kidney disease populations: an occult burden. Adv Chronic Kidney Dis. 2008;15(2):123–132.

[12] Hamano T, Ota S, Nakano C, Ito T, Matsui I, Tomida K, et al. Frailty and renal failure: is it reversible? J Ren Nutr. 2015;25(2):185–188.

[13] Jha V. Current status of chronic kidney disease care in Southeast Asia. Semin Nephrol. 2009;29(5):487–496.

[14] Prasad N, Jha V. Hemodialysis in Asia. Kidney Dis (Basel). 2015;1(3):165–166.

[15] Malmstrom TK, Morley JE. SARC-F: a simple questionnaire to rapidly diagnose sarcopenia. J Am Med Dir Assoc. 2013;14(8):531–532.

[16] Nasreddine ZS, Phillips NA, Bédirian V, Charbonneau S, Whitehead V, Collin I, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695–699.

[17] Tangri N, Stevens LA, Griffith J, Tighiouart H, Djurdjev O, Naimark D, et al. A predictive model for progression of chronic kidney disease to kidney failure. JAMA. 2011;305(15):1553–1559.

[18] Chao CT, Huang JW; COGENT Study Group. Association of frailty and its individual components with renal function decline: a prospective cohort study. Aging (Albany NY). 2020;12(10):9693–9710.

[19] Wilhelm-Leen ER, Hall YN, Tamura MK, Chertow GM. Frailty and chronic kidney disease: the Third National Health and Nutrition Examination Survey. Am J Med. 2009;122(7):664–671.e2.

[20] Johansen KL, Dalrymple LS, Delgado C, Kaysen GA, Kornak J, Grimes B, et al. Comparison of self-reported and physical performance-based frailty definitions among patients receiving maintenance hemodialysis. J Ren Nutr. 2014;24(3):157–162.

[21] Beddhu S, Chertow GM, Cheung AK, Cushman WC, Rahman M, Greene T, et al. Influence of baseline diastolic blood pressure on effects of intensive compared with standard blood pressure control. Circulation. 2018;137(2):134–143.

[22] Mitnitski A, Rockwood K. The rate of aging: the rate of deficit accumulation does not change over the adult life span. Biogerontology. 2016;17(1):199–204.

[23] Shlipak MG, Stehman-Breen C, Fried LF, Song X, Siscovick D, Fried LP, et al. The presence of frailty in elderly persons with chronic renal insufficiency. Am J Kidney Dis. 2004;43(5):861–867.

[24] Murray AM, Tupper DE, Knopman DS, Gilbertson DT, Frederick PD, Kane RL, et al. Cognitive impairment in hemodialysis patients is common and associated with functional status. Neurology. 2006;67(2):216–223.

[25] Patel SS, Molnar MZ, Tayek JA, Ix JH, Noori N, Benner D, et al. Serum creatinine as a marker of muscle mass in chronic kidney disease: results of a cross-sectional study and review of literature. J Cachexia Sarcopenia Muscle. 2013;4(1):19–29.

[26] Theou O, Squires E, Mallery K, Lee JS, Fay S, Goldstein J, et al. What do we know about frailty in the acute care setting? A scoping review. BMC Geriatr. 2018;18(1):139.

[27] Levey AS, Inker LA, Matsushita K, Greene T, Willis K, Lewis E, et al. GFR decline as an end point for clinical trials in CKD: a scientific workshop sponsored by the National Kidney Foundation and the US Food and Drug Administration. Am J Kidney Dis. 2014;64(6):821–835.

[28] Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group. KDIGO 2024 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int. 2024;105(4S):S117–S314.

[29] Hoops S, Nazem S, Siderowf AD, Duda JE, Xie SX, Stern MB, et al. Validity of the MoCA and MMSE in the detection of MCI and dementia in Parkinson disease. Neurology. 2009;73(21):1738–1745.

[30] Roshanravan B, Khatri M, Robinson-Cohen C, Levin G, Patel KV, de Boer IH, et al. A prospective study of frailty in nephrology-referred patients with CKD. Am J Kidney Dis. 2012;60(6):912–921.

[31] Saran R, Robinson B, Abbott KC, Agodoa LYC, Bragg-Gresham J, Balkrishnan R, et al. US Renal Data System 2018 Annual Data Report: Epidemiology of Kidney Disease in the United States. Am J Kidney Dis. 2019;73(3 Suppl 1):A7–A8.