Authors: Jiafang Li, Qunli Chen, Yi Xu
Categories: Review, Chronic kidney disease, Heart failure, Kansas city cardiomyopathy questionnaire, Patient self-reported outcomes
Source: BMC Nephrology
Authors: Jiafang Li, Qunli Chen, Yi Xu
Chronic kidney disease (CKD) patients face an increased risk of cardiovascular disease, particularly heart failure (HF). The combination of CKD and HF (CKD-HF) presents significant challenges in diagnosis, assessment, and management due to the unique pathophysiological features of this patient population. The Kansas City Cardiomyopathy Questionnaire (KCCQ), a patient-reported outcomes measure widely used in clinical trials of HF, shows promise in addressing these challenges. However, the effectiveness and application of KCCQ in CKD patients, especially those with heart failure, have not been fully explored. This article aims to review the current evidence of KCCQ in CKD patients, highlighting its potential value while acknowledging the limitations of current research, and suggesting potential clinical applications that warrant further validation.
The morbidity and mortality of chronic kidney disease (CKD) have been increasing globally, which imposes a significant burden on public health. Cardiovascular disease (CVD) is the leading cause of death in CKD, with heart failure (HF) being the most common cardiovascular complication [1]. The combination of CKD and HF (CKD-HF) is highly prevalent and often associated with a poor prognosis [2]. The complex interplay between the two conditions presents significant challenges in diagnosis, assessment and management, necessitating a multidisciplinary approach. Patient-Reported Outcomes (PROs) have gained recognition as valuable tools in assessing patients’ health status and can accurately identify potential health problems in patients [3]. The Kansas City Cardiomyopathy Questionnaire (KCCQ), a widely used PROs measure in heart failure, is primarily employed as a clinical endpoint to assess the efficacy of new drugs and to predict patient prognosis based on score changes [4, 5]. Furthermore, it has been successively mentioned in heart failure guidelines as a tool for monitoring symptomatic changes in heart failure patients and for assessing health-related quality of life in Asian patients with heart failure [6, 7]. The KCCQ has also been used in a few clinical studies of CKD. However, despite its established application in heart failure management, the effectiveness and clinical utility of KCCQ in CKD patients, particularly those with concomitant heart failure, remain underexplored. In this review, we conducted a comprehensive literature review of studies evaluating KCCQ in patients with chronic kidney disease and heart failure published from 1981 to 2025. We conducted searches in PubMed, Embase and Cochrane databases using standardized terms (including “Kansas City Cardiomyopathy Questionnaire”, “heart failure”, “chronic kidney disease”, “renal insufficiency”, and “prognosis”). Based on this foundation, we will summarize the current research status regarding heart failure in patients with CKD, and propose an application framework to meet the needs of this specific group of people.
CKD combined with HF is very common [2]. Studies have shown that in contrast to the nearly 30% prevalence of heart failure in CKD patients, heart failure is present in only 6% of non-CKD patients [8]. The prevalence of heart failure in CKD patients increases with the severity of CKD, with approximately 44% of patients on end-stage dialysis suffering from heart failure [2]. Patients with CKD-HF have a higher risk of death than patients with CKD or HF alone. Research indicates that the two-year survival rate for patients with CKD-HF is 65%, while those with CKD alone or HF alone have two-year survival rates of 75% and 83%, respectively [9]. The prognosis for patients with CKD-HF is extremely poor [10].
According to the 2021 European Society of Cardiology (ESC) guidelines, heart failure assessment involves clinical symptoms, imaging, biomarker testing, electrocardiograms, and exercise tests [6]. However, these assessment methods have several limitations when applied to patients with the dual diagnosis of CKD and heart failure. The 2024 Kidney Disease: Improving Global Outcomes (KDIGO) guidelines note that CKD patients often present with symptoms like volume overload and electrolyte imbalances that overlap with heart failure, complicating diagnosis. Imaging examinations in CKD patients are affected by renal dysfunction, leading to reduced diagnostic accuracy. Heart failure biomarkers like N-Terminal pro-Brain Natriuretic Peptide (NT-proBNP) are often abnormally elevated in CKD patients, making it challenging to assess cardiac function accurately [11].
While current heart failure assessment tools can be applied to CKD patients with proper consideration of renal dysfunction, their use remains challenging due to the complex interplay of both conditions. As a result, there is a growing need for improved assessment strategies tailored to this population. The 2024 KDIGO guidelines highlight that uremic symptoms in CKD are often underrecognized, intensify with disease progression, and significantly impair health-related quality of life. Reflecting this, patients increasingly prioritize symptom relief and quality of life over traditional endpoints. Thus, KDIGO recommends a greater focus on PROs and subjective symptom assessment in CKD management to better address these priorities [11].
The PROs can provide a more comprehensive reflection of patients’ overall health status, including cardiac function, which may offer an improved assessment approach to meet the unique needs of patients with CKD and heart failure comorbidity [12]. However, to ensure accurate assessment of patient health status, these assessment tools must be interpreted in the context of the patient’s CKD background. This perspective further emphasizes the importance of incorporating PROs into the management of CKD patients.
The United States Food and Drug Administration (FDA) defined PROs in 2009 as reports coming directly from patients, highlighting their value in capturing patients’ perspectives on health status and quality of life [12]. Subsequent studies demonstrate that PROs are valuable in CKD by enabling assessment of patient symptoms, supporting patient-centered care, and improving both health-related quality of life and prognosis [13, 14].
There is currently a lack of dedicated PROs tools specifically designed for patients with CKD and comorbid heart failure. Several PROs instruments are commonly used in CKD patients, including the Kidney Disease Quality of Life Questionnaire (KDQOL-36), the Kidney Disease Quality of Life Short Form (KDQOL-SF), the Integrated Renal Outcome Scale for Rehabilitative Care (IPOS-Renal) and the Physical Composite Score of 12-Item Short-Form Health Survey (PCS-12) [15, 16]. However, each has distinct limitations in assessing heart failure symptoms. The KDQOL-SF and KDQOL-36 comprehensively assess CKD-related symptom burden and quality of life, but have limited capability in evaluating heart failure-related symptoms such as dyspnea and cardiac functional limitations [17]. The IPOS-Renal, designed for advanced CKD patients in palliative care settings, effectively captures CKD-specific symptoms such as pruritus and restless legs syndrome but provides relatively limited assessment of common heart failure symptoms [18]. The PCS-12, while offering rapid assessment of overall physical and mental health status, lacks specificity for both kidney disease and heart failure symptoms [19].
Although PROs are not specifically designed for heart failure assessment in CKD patients, some of the symptom and quality of life components addressed in them may provide useful complementary information for the comprehensive assessment of heart failure. A meta-analysis showed that CKD patients with multiple comorbidities had a higher symptom burden and lower health-related quality of life; PROs were effective in capturing heart failure-related symptoms such as fatigue, dyspnea, and edema. Moreover, lower PROs scores were closely linked to worse prognosis in these patients [20].
In this context, the KCCQ, as a PROs tool widely used in the assessment of heart failure, may play an important role in assessing the symptom burden and quality of life in the CKD-HF patients. The KCCQ captures patients’ subjective experiences and provides clinicians with meaningful insights for comprehensive evaluation and individualized management. Although originally designed for heart failure, given the symptom overlap and the growing emphasis on PROs in CKD care, applying the KCCQ to CKD-HF populations may enhance symptom assessment, inform clinical decisions, and improve patient-centered outcomes.
The KCCQ is a PROs measurement tool widely used in clinical research to evaluate heart failure. It is primarily designed based on patient experiences and perceptions regarding how heart failure affects various aspects of their lives [21]. And the KCCQ uses a two-week retrospective period and comprises 23 questions across seven symptom frequency, symptom burden, symptom stability, physical limitations, social limitations, quality of life, and self-efficacy. It employs a 0-100 scoring system where lower scores indicate more severe symptoms and limitations [22, 23]. Cross-sectional KCCQ scores provide straightforward health status 0–24 points represent very poor to poor health, 25–49 points indicate poor to general health, 50–74 points signify general to good health, and scores > 75 points reflect good to excellent health. Changes of 5, 10, and 20 points reflect clinically important small, moderate, and large clinical changes, respectively [22, 24].
With the FDA decision to certify the KCCQ as a Medical Device Development Tool (MDDT) in 2016, it has been concluded that the KCCQ could be used in clinical trials of medical devices for heart failure to assess the effectiveness of treatments [25]. In 2016 and 2021, it was successively mentioned in heart failure guidelines as an assessment tool to monitor symptomatic changes in HF patients and assess health-related quality of life in Asian heart failure patients [7, 26]. The KCCQ has become widely used in the cardiovascular field and can effectively describe the impact of heart failure on patients’ lives [27–30]. Clinical research has confirmed that this questionnaire correlates with the evolution of clinical events and provides significant value in identifying high-risk patients, evaluating treatment effects, and predicting prognosis [22, 31–34].
There is growing evidence supporting the value of KCCQ in patients with CKD (Table 1). Studies have demonstrated that the KCCQ effectively identifies subclinical heart failure and predicts adverse outcomes in CKD patients [35–37]. However, further research is needed to validate its clinical applications and establish optimal implementation frameworks for routine use in CKD patients.
Table 1Clinical studies of KCCQ in CKD patientsAuthor/ReferenceJournal / YearResearch designResearch populationParametersResultsConclusionShlipak et al./Reference [36]J Card Fail/ 2011Cross-sectional analysisAdults 21–74 years with CKD (eGFR 20–70) without HF.The eGFR (creatinine and cystatin C), hemoglobin, demographics, comorbidities.25% of CKD patients had KCCQ < 75. Lower eGFRcys and hemoglobin were independently associated with HF-type symptoms.CKD patients have substantial burden of HF-type symptoms, particularly with lower kidney function and hemoglobin levels.Mishra et al./Reference [37]Circ Heart Fail/2015Prospective cohort studyAdults 21–74 years with CKD (eGFR 20–70) without HF.Time-updated KCCQ score, demographics, clinical variables, NT-proBNP.211 HF hospitalizations occurred. Lowest KCCQ quartile had 3.3-fold increased risk.KCCQ score independently predicts incident HF hospitalization in CKD patients.Tummalapalli et al./Reference [46]J Am Heart Assoc/2020Cross-sectional and longitudinal cohort analysisAdults 21–74 years with CKD (eGFR 20–70).Five cardiac GDF-15, galectin-3, NT-proBNP.Cross-sectional: GDF-15 and galectin-3 associated with KCCQ < 75.Longitudinal: GDF-15, NT-proBNP predicted KCCQ decline.Cardiac biomarkers, especially GDF-15, reflect early HF symptoms in CKD and may guide risk assessment.Walther et al./Reference [47]Int J Obes/2022Cross-sectional analysis using machine learning (random forest)Adults 21–74 years with CKD (eGFR 20–70) without HF.99 clinical variables across demographics, cardiac, kidney, and other health dimensions.BMI was important predictor of KCCQ scores. KCCQ declined by 5 points when BMI increased from optimal (24.3 kg/m²) to 35.7 kg/m².BMI was closely associated with KCCQ scores in CKD patients, suggesting that weight management may help improve HF-type symptoms.Walther et al./Reference [35]AJKD/2023Prospective cohort studyAdults 21–74 years with CKD (eGFR 20–70) without HF.Demographics, comorbidities, laboratory values, echocardiographic parameters.Five KCCQ trajectories identified. Stable low-score group had highest HF incidence/mortality and stable high-score group had the lowest incidence of heart failure.Distinct symptom trajectories support personalized CKD management.Yang et al./Reference [49]Eur J Heart Fail/2023Cross-sectional analysis of clinical trialsDiagnosed with heart failureAnd having complete KCCQ score data.Demographics, comorbidities, NYHA functional class, Laboratory values, echocardiographic parameters.CKD associated with lower KCCQ scores (difference: 4.2 points in HFrEF, 3.4 points in HFpEF). Impact less than COPD, angina, and anemia.In HF patients, CKD may has a modest impact on KCCQ scores, which may support the application value of KCCQ in HF patients with comorbid CKD.Packer et al./Reference [48]N Engl J Med/2025Randomized, double-blind, placebo-controlled trial.HFpEF and obesity (BMI ≥ 30 kg/m²).Demographics, comorbidities, laboratory values KCCQ scores, and functional capacity.CKD patients were older with more severe heart failure (lower KCCQ scores) than non-CKD patients. Tripeptide significantly improved KCCQ scores in both groups, with similar magnitude of improvement.KCCQ demonstrates good sensitivity as primary endpoint in large-scale randomized controlled trial including substantial CKD population, with consistent efficacy across kidney function levels.
To highlight the advantages of KCCQ in the assessment of heart failure in CKD patients, we compared it with the New York Heart Association (NYHA) classification and the Minnesota Heart Failure Questionnaire (MLHFQ), thereby supporting its practical application in this specific population.
The NYHA functional classification remains widely used for assessing heart failure severity. However, it has several limitations. This classification system lacks standardized symptom assessment and objective scoring mechanisms, primarily relying on healthcare professionals’ subjective judgments based on limited clinical observations, which leads to significant assessment variability and poor reproducibility [38]. Moreover, the boundaries between NYHA classes are ambiguous, resulting in marked overlap, for example, up to 93% of patients in NYHA I and II have similar NT-proBNP levels [39]. Critically, the system shows limited prognostic even among NYHA I patients, those with elevated NT-proBNP (≥ 1600 pg/mL) are at significantly increased risk of adverse events (Hazard Ratio [HR] = 3.43) compared to those with lower levels. These findings underscore that NYHA classification alone is insufficient for accurately identifying high-risk patients [39].
In CKD patients, NYHA classification limitations become more pronounced. Fluid retention and electrolyte imbalances in CKD cause symptom variability, while fatigue and dyspnea may overlap with or be masked by renal dysfunction manifestations, potentially leading to misclassification or severity underestimation [11]. In contrast, the repeatable KCCQ may better assess heart failure severity [40]. Studies show CKD patients with lower KCCQ scores face higher heart failure hospitalization risk [37], highlighting KCCQ’s potential value in this population.
Although direct comparisons in CKD populations are limited, several studies in patients with heart failure have demonstrated that the KCCQ provides superior prognostic value and sensitivity to clinical changes compared to the NYHA classification [40–42]. For example, a ≥ 5-point improvement in KCCQ score was significantly associated with reduced all-cause mortality (HR = 0.84), whereas changes in NYHA class were not (HR = 0.91) [40]. Furthermore, KCCQ has shown greater sensitivity in capturing symptom fluctuations and substantially overlaps with NYHA classes, challenging the latter’s ability to reflect patient quality of life [42]. Lastly, KCCQ scores may enable clinicians to assess patients’ health status with greater accuracy than the NYHA classification [37]. Substantial overlap in KCCQ scores across NYHA classes (e.g.73.6% between II and III, 88.3% between III and IV) suggests that NYHA class alone may not fully capture differences in quality of life. Therefore, combining KCCQ with NYHA assessment may allow for a more comprehensive evaluation of heart failure severity [40].
In conclusion, the KCCQ shows advantages over NYHA classification in assessing symptom burden and prognosis in heart failure patients. However, combined assessment of both provides a more detailed and precise evaluation of patient health status, leading to improved assessment accuracy.
The MLHFQ and the KCCQ are two important tools for assessing health-related quality of life in heart failure patients [43]. They differ in terms of assessment content and predictive ability. A meta-analysis in 2023 found that the MLHFQ has limited evaluation of social functioning (such as work, social interactions, family life), and focuses more on assessing patients’ symptoms and emotional functions. In contrast, the KCCQ covers seven domains. Although there is no dedicated module to assess psychological well-being, certain questions can still provide insight into a patient’s mental state, allowing a more comprehensive assessment of their overall health from multiple angles, including symptoms, functional capacity and social functioning [44]. In patients with CKD, this multidimensional assessment is particularly important, as these patients often face complex symptoms and functional limitations [11]. The multidimensional assessment approach of the KCCQ may be able to capture changes in these symptoms more accurately [36].
Recent studies demonstrate that KCCQ outperforms MLHFQ in predicting adverse outcomes. Specifically, in patients with heart failure with reduced ejection fraction (HFrEF), KCCQ showed a significantly higher area under the curve (AUC) compared to MLHFQ for predicting mortality, transplantation, left ventricular assist device (LVAD) implantation, and rehospitalization (0.702 vs. 0.658; p < 0.001) [45]. In contrast, MLHFQ is more influenced by subjective symptom perceptions and less correlated with objective measures, while KCCQ demonstrates stronger associations with both quality of life and prognosis (HR = 2.34 vs. 1.56, P < 0.01) [43, 44]. Although dedicated data in CKD populations remain limited, these advantages suggest the KCCQ may have greater clinical value in this group.
Given the unique advantage of the KCCQ in assessing symptoms in heart failure patients, particularly in those with concurrent CKD, its clinical application becomes especially significant. The following will discuss the specific applications of KCCQ in CKD patients and its potential benefits.
Firstly, the KCCQ can facilitate the early detection and diagnosis of HF in CKD patients. Shlipak et al. [36] used the KCCQ to evaluate heart failure-related symptoms in 2833 CKD patients without diagnosed heart failure, finding that 25% demonstrated a significant symptom burden. In a 4.3-year follow-up study of 3,093 CKD patients, Mishra et al. [37] found those in the lowest quartile of KCCQ scores (≤ 74.5 points) had significantly higher risk of new-onset HF hospitalization compared to the highest quartile (> 99 points) (Odds Ratio [OR] = 3.30, 95% Confidence Interval [CI]: 1.66–6.52). These findings suggest that KCCQ could serve as an effective monitoring and predictive tool for this population. However, it is important to note that while KCCQ assesses general HF symptoms, it lacks specificity in CKD patients. Cardiac biomarkers significantly correlate with KCCQ scores in this population. Cross-sectional analysis revealed associations between KCCQ scores < 75 and elevated growth differentiation factor-15 (GDF-15) (OR = 1.42, 99% CI:1.19–1.68) and Galectin-3 (OR = 1.28, 99% CI:1.12–1.48). Longitudinally, GDF-15 (HR = 1.36, 99% CI:1.12–1.65) and NT-proBNP (HR = 1.30, 99% CI:1.08–1.56) predicted KCCQ decline to < 75 during follow-up [46]. While these biomarkers may detect early symptomatic changes in heart failure, they might also associate with lower KCCQ scores through non-cardiac mechanisms like inflammation, highlighting the need for comprehensive evaluation to distinguish cardiac and non-cardiac contributions to KCCQ scores in CKD patients.
Secondly, the KCCQ can monitor changes in heart failure symptom burden in CKD patients. Walther et al. [35] conducted a 5.5-year prospective study of 3044 CKD patients, identifying five distinct KCCQ trajectory stable high-score (41.7%, average KCCQ 96, mildest symptoms), stable moderate-score (35.6%, average KCCQ 81, relatively mild symptoms), stable low-score (15.6%, average KCCQ 52, significant symptoms), declining score (4.9%, average decrease of 31 points), and improving score (2.2%, average increase of 33 points, highest baseline cardiovascular disease proportion). Clinical outcomes varied significantly among these groups, with incident heart failure rates of 3% in stable high-score, 11% in stable moderate-score, 12% in declining score, 10% in improving score, and 18% in stable low-score groups. These results demonstrate that KCCQ effectively reflects long-term heart failure symptom changes in CKD patients and is associated with prognosis, supporting its application in this population. However, limitations include the single-center design potentially limiting generalizability, and focus solely on KCCQ scores without considering other factors like treatments and comorbidities. Future studies should include larger, diverse populations and examine broader influencing factors.
Thirdly, the KCCQ scores are closely associated with multiple clinical variables in CKD patients. Walther et al. [47] assessed 3,426 CKD patients to investigate relationships between clinical variables and KCCQ scores. Body mass index (BMI) showed the strongest correlation, with scores highest at BMI 24.3 kg/m² and decreasing by up to 5 points when BMI reached 35.7 kg/m². Hemoglobin, blood glucose, and age were also associated with KCCQ scores.
Moreover, research further investigated the impact of CKD on the health status of heart failure patients. Packer et al. [48] studied heart failure with preserved ejection fraction (HFpEF) patients with obesity, finding those with concomitant CKD had more severe heart failure (34.7% vs. 16.2% NYHA class III symptoms and lower KCCQ 51.8 ± 18.7 vs. 56.0 ± 17.7 points). Despite these differences, tripeptide improved KCCQ similarly across renal function groups. These findings demonstrate KCCQ’s effectiveness in assessing symptom burden and treatment outcomes in HFpEF patients with varying kidney function. Yang et al. [49] investigated the differential impact of comorbidities on health status as measured by the KCCQ in 12,172 heart failure patients. In this study, the prevalence of CKD was 33.9% in HFrEF patients and 48.7% in HFpEF patients. Their analysis demonstrated statistically significant reductions in KCCQ scores associated with CKD: a 4.2-point decrease in HFrEF patients and a 3.4-point decrease in HFpEF patients relative to their non-CKD counterparts. Notably, the magnitude of this effect was less pronounced than that observed with other comorbidities such as chronic obstructive pulmonary disease (COPD), angina, and anemia. This finding suggests that the influence of CKD on the KCCQ score may be relatively limited.
Notably, dialysis patients face elevated cardiovascular risks, with heart failure symptoms often masked by dialysis-related discomfort. Traditional biomarkers and imaging show limited sensitivity in ESRD patients, leading to delayed diagnosis [11, 50]. While KCCQ shows utility in CKD patients (Table 1), research in dialysis populations is virtually nonexistent, highlighting the need for multicenter studies to evaluate its effectiveness in this unique group.
Currently, cardiac function assessment in CKD patients still faces numerous clinical challenges, leading to frequent underestimation or delayed recognition of heart failure in this population, which seriously impacts treatment decisions and prognosis [11]. Against this background, KCCQ, as a heart failure assessment tool, may provide a novel research perspective for cardiac function evaluation in CKD patients. Therefore, although direct evidence is yet to be further accumulated, we draw upon mature guidelines from the heart failure field [51], and by deeply considering the unique pathophysiological characteristics of CKD populations and existing clinical research findings, propose recommendations for heart failure detection in CKD patients.
We recommend routine KCCQ assessment for all CKD patients, with specific considerations according to CKD staging (detailed recommendations are shown in Table 2). Special attention might be warranted for the following high-risk (1) patients with cardiac dysfunction or structural abnormalities, including NYHA functional class III-IV, significantly reduced left ventricular ejection fraction (≤ 35%), cardiac structural abnormalities, and valvular heart disease; (2) patients with cardiovascular event history, including recent hospitalization for heart failure, history of myocardial infarction, and recent cardiac interventional procedures; (3) patients with unexplained decrease in exercise tolerance; (4) patients with comorbidities and metabolic disorders, including moderate to severe renal dysfunction (estimated Glomerular Filtration Rate [eGFR] < 45 mL/min/1.73 m²), hypertension and diabetes; (5) patients with lifestyle-related risk factors, including long-term smoking and obesity (BMI ≥ 30 kg/m²); (6) patients with treatment instability or fluctuating renal function. Consequently, due to their elevated risk of heart failure, these populations warrant closer monitoring and management [52]. It is worth noting that for patients with limited health literacy, we suggest using the simplified version of KCCQ-12 and providing enhanced support [53]. It is not recommended for patients with severe cognitive impairment, communication disorders or terminal illnesses [21].
Table 2Recommended KCCQ assessment and Follow-up workflow for patients with CKD and heart failureCKD stageAssessment FrequencySettingMedian value of NT-proBNP (pg/mL)Assessment ComponentsRecommended Actions/Management AdviceStage 1–2Every 12 monthsOutpatientStage 208Stage 831KCCQ, NT-proBNP, NYHA.If KCCQ decreases by ≥ 5 points or NT-proBNP increases, more frequent monitoring and medication adjustment are required.Stage 3–4Every 6 monthsOutpatientStage 799–2119Stage 3476–5004KCCQ, NT-proBNP, NYHA.High-risk stratification. Fluctuation in KCCQ scores and NT-proBNP levels should be comprehensively analyzed with fluid volume status. The treatment plan should be intensified when necessary.Stage 5 (pre- dialysis)Every 3 monthsOutpatient8377–11,215KCCQ, NT-proBNP, NYHA.Emphasis should be placed on fluid volume status and cardiac function. If KCCQ scores continues to decline or NT-proBNP increases by more than 20%, timely assessment and referral should be conducted.Stage 5 (dialysis)Every 3 monthsOutpatient8377–11,215KCCQ, NT-proBNP, NYHA, Dry body weight.For hemodialysis patients, data should be collected on non-dialysis days. For those with significant volume fluctuations, dynamic tracking should be carried out. Clinical decisions should be based on trends rather than isolated measurements.Acute HF InpatientAt admission and 1–2 weeks after dischargeInpatientStaged by CKDKCCQ, NT-proBNP, NYHA.The KCCQ score at discharge increases by ≥ 5 points compared to admission values, and NT-proBNP level decreases significantly, indicating effective treatment and guiding follow-up frequency after discharge.
Available evidence suggests that the value of KCCQ may be maximized when interpreted alongside objective indicators such as NT-proBNP, NYHA classification [11, 40, 46]. The literature indicates that a decrease in the KCCQ score (≥ 5 points) is generally considered clinically significant. This threshold was established in a 14-center study specifically designed to determine the clinical significance of KCCQ score changes, which found that a 0 to 5-point change reflects minimal important clinical changes in patients’ health status [24]. Studies exploring biomarkers in CKD patients have documented that NT-proBNP levels increase substantially as renal function declines. Jafri et al. [54] reported median plasma NT-proBNP concentrations ranging from 208 pg/mL at eGFR > 90 mL/min/1.73 m² to 8377–11,215 pg/mL at eGFR < 15 mL/min/1.73 m². Such data may provide context when interpreting KCCQ scores in CKD patients.
Comprehensive assessment of multiple parameters is conducive to achieving more accurate risk stratification and management optimization [11]. Especially for dialysis patients, it is necessary to jointly interpret the KCCQ score, dry body weight and biochemical indicators to accurately reflect the heart failure status [50]. Tables 2 and 3 outline implementation processes, with Table 2 assessments conducted by medical professionals and Table 3 elaborates on the implementation process of KCCQ in CKD-HF patients, which requires self-assessment by patients under the guidance of healthcare professionals [55]. This integrated approach by multidisciplinary teams aims to enhance risk identification and individualized treatment for CKD-HF patients, potentially improving prognosis and quality of life.
Table 3Implementation process of KCCQStage/StepPractical measuresInformed consentBriefly introduce the purpose of the KCCQ assessment and obtain the consent of the patients.Execution and FrequencyEvaluate and record at the initial diagnosis, before and after treatment adjustment, and follow up regularly.Filling methodPaper or electronic form. Continuous electronic medical records facilitate data tracking and analysis.Division of personnelNurses conduct quality assurance for assessment completion, while physicians interpret results and make clinical decision.Scoring InterpretationKCCQ scores are categorized as 0–24 extremely poor25–49 poor50–74 average≥ 75 goodDynamic score changes indicate clinically improvement or ≥5 points, Mild, ≥10 points Moderate, ≥20 Substantial.Linkage measuresAdjust treatments and provide education based on KCCQ trends. Extremely low scores require comprehensive assessment and multidisciplinary consultation.
While KCCQ has demonstrated significant benefits in general heart failure populations [31–34], several important limitations must be acknowledged when extrapolating these findings to CKD patients. The pathophysiological differences between CKD and non-CKD populations may influence symptom manifestation and KCCQ score interpretation. CKD patients exhibit substantial symptom overlap between kidney disease and heart failure, potentially leading to symptom misattribution and inflated KCCQ scores that may not accurately reflect cardiac-specific functional limitations [11]. Additionally, the established minimally clinically important differences (5, 10, and 20 points) were derived from studies predominantly including patients with preserved kidney function [24], and whether these thresholds maintain their clinical relevance in CKD populations remains uncertain. Furthermore, most KCCQ validation studies have only involved general heart failure patients, which limits the generalizability of established KCCQ standards and prognostic associations to the CKD population. These limitations underscore the necessity of conducting specialized validation studies specifically for CKD patients.
Compared with general HF patients, research on the assessment of heart failure using KCCQ in CKD patients is still in its infancy. The issues of small sample size and insufficient study design have yet to be solved. Future research directions should include multicenter large-sample studies and long-term follow-up to observe the relationship between changes in KCCQ scores and the prognosis. Additionally, the KCCQ needs to be studied in various application scenarios in CKD-HF patients, such as diagnosis, efficacy testing, prognostic assessment, and monitoring the changes in patients’ conditions. These efforts will help standardize patient management, and compare its value with that of the NYHA classification. To comprehensively evaluate and validate the application of the KCCQ in the CKD-HF patients, more high-quality clinical studies are needed. These studies should include multicenter prospective designs and combining biomarkers and imaging indexes. Such efforts will provide a better understanding of the KCCQ’s application in CKD-HF patients and solid empirical evidence for its clinical use.
In this literature review, we synthesize emerging evidence that the KCCQ meaningfully captures HF-related symptoms burden, risk, and longitudinal trajectories in patients with CKD. Lower or declining KCCQ scores identify CKD patients with substantial symptom burden and higher risk of HF hospitalization and other adverse outcomes. Compared with traditional tools, the KCCQ offers greater granularity and responsiveness to change than NYHA and broader multidimensional coverage than the MLHFQ. The value of KCCQ may be maximized when interpreted alongside objective indicators such as NT-proBNP, particularly for dialysis patients where joint interpretation of KCCQ scores with dry body weight and biochemical indicators is necessary. These findings, along with recent guideline emphasis on PROs in CKD care, suggest potential for stage-adapted KCCQ application to augment early detection, monitor symptom dynamics, and inform individualized management, particularly when serial trends of ≥ 5point change from baseline are assessed alongside volume status and biomarkers. Nonetheless, extrapolation from general HF warrants caution. Symptom overlap between CKD and HF may confound attribution, and established KCCQ thresholds and minimally clinically important differences require validation across CKD stages and dialysis settings. Overall, the KCCQ provides a patientcentered, feasible layer of assessment that complements existing modalities and may improve risk identification and care personalization in CKDHF.