From KDIGO Staging Toward Dynamic AKI Phenotyping: A Function–Biology–Reserve–Duration Framework Across the AKI–AKD Continuum

The 2012 KDIGO staging system standardized acute kidney injury (AKI) diagnosis; however, its reliance on serum creatinine and urine output primarily captures established functional impairment and incompletely reflects early biological injury, patient susceptibility, and temporal trajectories. The March 2026 KDIGO Public-Review Draft substantially expands this paradigm by incorporating biomarkers, susceptibility and kidney functional reserve, and temporal phenotyping, although these dimensions remain only partially integrated into a unified longitudinal phenotype architecture. This narrative review introduces a pragmatic, bedside-oriented extension of this emerging framework, integrating function, biology, susceptibility, and trajectory to support anticipatory risk stratification across the AKI–acute kidney disease (AKD) continuum. We developed a modular taxonomy based on an analytical review of stress and damage biomarkers, renal functional reserve (RFR) assessment, including emerging ultrasound-based renal stress testing, and temporal disease mapping. These elements were integrated into a multidimensional phenotyping framework (F–B–R–D) and a structured clinical pathway. Function (F) remains anchored to KDIGO serum creatinine and urine output criteria; Biology (B) captures kidney stress or structural damage using context-appropriate biomarkers; Reserve (R) describes preserved or reduced RFR as a proposed operational descriptor of reserve-related vulnerability; and Duration (D) captures persistence, recovery, and progression toward AKD. AKI risk is conceptualized as a qualitative interaction between susceptibility and exposure load (E), allowing candidate multidimensional phenotypes to be mapped to proposed action bundles for prevention, diagnostic escalation, and structured follow-up. The F–B–R–D taxonomy is intended to complement, rather than replace, KDIGO classification. If prospectively validated, it could support more proactive monitoring, individualized prevention, and longitudinal risk assessment.