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Frailty assessment in acute spinal cord injury surgery: Insights from the risk analysis index and broader neurosurgical context

J Spinal Cord Med. 2025 Sep 15:1-4. doi: 10.1080/10790268.2025.2554011. Online ahead of print.

ABSTRACT

Context: Frailty has emerged as a key determinant of surgical outcomes, surpassing chronological age and comorbidity indices in prognostic value. The Risk Analysis Index (RAI), a multidomain frailty assessment tool, has shown strong predictive utility in spine surgery. Recent analyses specifically evaluated RAI in urgent surgical intervention for acute traumatic spinal cord injury (SCI), where timely outcome prediction is critical.Findings: In 10,000 SCI patients, frailty demonstrated a graded association with adverse 30-day outcomes. Mortality increased from 1.5% in robust individuals (RAI 0-20) to 11.8% in very frail patients (RAI >41), paralleled by increased non-home discharge and complications. The RAI consistently outperformed the modified frailty index (mFI-5), achieving c-statistics >0.72 for mortality and discharge outcomes. These results align with broader spine surgery literature, where the RAI has demonstrated superior discrimination compared to mFI-5 across elective cases, degenerative conditions, spinal deformity, and tumor surgery. Predictive strength reflects incorporation of functional and nutritional domains, which comorbidity-based indices miss. Importantly, RAI-based analyses have identified high-risk subsets even in lower-risk cohorts, such as anterior cervical discectomy, underscoring its generalizability.Conclusion/Clinical Relevance: The RAI reliably predicts short-term outcomes after SCI and across diverse spine surgery populations, outperforming simpler frailty measures. Its integration into neurosurgical assessment enables more accurate risk stratification, informs perioperative management, and supports shared decision-making. Routine use of the RAI may guide multidisciplinary optimization and resource allocation, and future interventions targeting frail patients may leverage its predictive capacity to improve outcomes.

PMID:40952757 | DOI:10.1080/10790268.2025.2554011

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