Chronic kidney disease (CKD) represents a significant global health challenge and is a leading cause of death from non-communicable diseases (Bello et al., 2024; Lancet (London, England), 2020). As CKD progresses to its final stage, uremia, patients require kidney replacement therapy (KRT) to sustain life and maintain internal homeostasis. Maintenance hemodialysis (MHD) is the most common form of KRT worldwide (Bello et al., 2022). Despite its life-sustaining nature, MHD imposes rigorous demands, including strict adherence to treatment schedules, dietary restrictions, and complex medication regimens. Consequently, patients often experience significant psychological distress, diminished self-management capabilities, and a profoundly reduced quality of life (Dembowska & Jaroń, 2022; Gebrie et al., 2023).

The MHD patient population is notably heterogeneous, with wide variability in comorbidity profiles (e.g., diabetes, cardiovascular disease), psychosocial factors (e.g., health literacy, social support), and functional status. This diversity poses a significant challenge to traditional nursing care models, which often fail to provide the tailored support needed to address individual patient risks and needs (Yuan & Zhang, 2020). Unlike conventional nursing, which typically applies a fixed-frequency follow-up schedule regardless of patient stability, innovative models are needed to allocate resources more efficiently. Therefore, enhancing medical management to improve health outcomes and quality of life for MHD patients has become a critical focus for nephrology care providers (Hu et al., 2023; Kang et al., 2015; Kim & Kang, 2018).

Nursing management is an essential complement to medical care. However, conventional nursing approaches often adopt a ‘one-size-fits-all’ strategy. This ‘one-size-fits-all’ pitfall, which fails to allocate nursing resources according to patient risk, can lead to inefficiencies and potentially suboptimal outcomes for both high- and low-risk individuals (Easthall & Barnett, 2017; Keivan et al., 2023; Pooresmaeil et al., 2023). Evidence from other chronic disease contexts suggests that risk stratification and tailored interventions can optimize resource allocation and improve patient outcomes (Xu et al., 2018).

The “Triangle” model of chronic care management offers a structured framework for risk stratification (Feachem et al., 2002). This model categorizes patients into high-, medium-, and low-risk tiers based on disease severity, allowing for a proportional allocation of professional healthcare services and self-management support. This study is grounded in the conceptual hypothesis that a structured, risk-stratified nursing model can create a positive feedback loop for patient empowerment. Specifically, we posited a causal pathway where (1) accurate risk stratification allows for (2) the targeted allocation of nursing resources, which directly enhances (3) patient knowledge, self-management skills, and treatment adherence. These intermediate behavioral improvements are, in turn, hypothesized to lead to (4) better clinical outcomes and (5) an improved overall quality of life (Grady & Gough, 2014). While the Triangle model has shown efficacy in other chronic conditions, a significant research gap remains regarding its application in MHD settings, particularly within mainland China where nurse-to-patient ratios can be high. This study aimed to address this gap by assessing the impact of a nurse-led, Triangle-based hierarchical management model on the quality of life, disease-related knowledge, self-management ability, and treatment adherence of MHD patients.