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The Aggregate Index of Systemic Inflammation (AISI) demonstrates superior prognostic value for predicting mortality and critical care interventions compared to conventional inflammatory markers in palliative care patients. Novelty: ClaimNovelty.NOVEL_FINDING. Consensus alignment: ConsensusAlignment.NEUTRAL.

June 3, 2026Open Access

Prognostic value of the aggregate index of systemic inflammation in palliative care patients

Puntos clave

This study aims to evaluate the prognostic value of the Aggregate Index of Systemic Inflammation (AISI) in palliative care patients.
Retrospective cohort study of 144 palliative care patients admitted between January 2020 and December 2024.
Prognostic performance of AISI, SIRI, SII, and NLR was assessed for predicting mortality and critical care needs.
Statistical analyses included receiver operating characteristic curve, multivariable Cox regression, and Kaplan-Meier survival analysis.
AISI had the highest discriminatory capacity for mortality prediction (AUC 0.826, 95% CI 0.754–0.898), significantly superior to NLR and SII (p < 0.042).
Patients with AISI > 1850 had a median survival of 9 days compared to 35 days for those with AISI ≤ 1850 (log-rank p < 0.001).
AISI also predicted ICU admission (adjusted OR 3.96, 95% CI 1.89–8.28, p < 0.001) and mechanical ventilation requirement (adjusted OR 4.15, 95% CI 1.98–8.69, p < 0.001).

Resumen

Abstract Accurate prognostication remains essential for appropriate care planning in palliative care settings. The Aggregate Index of Systemic Inflammation (AISI) represents a comprehensive integration of four inflammatory cell populations, but its comparative prognostic value in palliative care has not been established. This retrospective cohort study analyzed 144 consecutive patients admitted to a palliative care unit between January 2020 and December 2024. We evaluated the prognostic performance of AISI, Systemic Inflammation Response Index (SIRI), Systemic Immune-Inflammation Index (SII), and Neutrophil-to-Lymphocyte Ratio (NLR) for predicting in-hospital mortality, intensive care unit admission, and mechanical ventilation requirement. Receiver operating characteristic curve analysis, multivariable Cox regression, and Kaplan-Meier survival analysis were performed. A total of 144 patients (mean age 75.4 ± 11.8 years; 85 male 59.0%) were included. In-hospital mortality occurred in 99 patients (68.8%). AISI demonstrated the highest discriminatory capacity for mortality prediction with area under the curve 0.826 (95% CI: 0.754–0.898), significantly superior to NLR (0.734, p = 0.003) and SII (0.768, p = 0.042). Optimal AISI cutoff of 1850 yielded sensitivity 79.8% and specificity 77.8%. In multivariable analysis, AISI > 1850 remained the strongest independent mortality predictor (adjusted HR 4.38, 95% CI: 2.41–7.96, p 1850 versus ≤ 1850 (log-rank p < 0.001). AISI also independently predicted intensive care unit admission (adjusted OR 3.96, 95% CI: 1.89–8.28, p < 0.001) and mechanical ventilation requirement (adjusted OR 4.15, 95% CI: 1.98–8.69, p < 0.001). AISI demonstrates superior prognostic value compared to conventional inflammatory markers in palliative care patients. This readily available, cost-effective biomarker enables robust risk stratification for mortality and critical care interventions. Integration of AISI into comprehensive prognostic assessments could enhance individualized care planning and optimize resource allocation in palliative care settings.

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