A Novel Scoring System for the Administration of an IgM- and IgA-Enriched Intravenous Immunoglobulin Preparation: The SORRISO Score
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background/Objectives: The use of intravenous immunoglobulins enriched with IgA and IgM (eIg) in patients with septic shock remains controversial due to a lack of robust, standardized criteria for patient selection and timing of treatment. This study in-troduces the SORRISO Score, a novel, evidence-informed scoring system designed to guide clinical decision-making for eIg administration. Methods: Based on data from the Italian multicentric SORRISO registry, involving 248 patients across seven ICUs from 2015 to 2022, the score integrates patient-related and therapy-related variables. These were deri-ved through an enhanced version of the TO-PIRO score and include factors such as im-munosuppressive status, infection type, timing of treatment, and adequacy of antibiotic therapy. Results: Statistical analyses, including Kaplan-Meier curves and regression mo-dels, identified key predictors of survival and validated the score’s ability to stratify pa-tients by outcome. A cutoff of 13.7 showed significant prognostic value (AUC = 0.731), with lower scores correlating with increased mortality. Conclusions: The SORRISO Score thus offers a practical, bedside tool to improve patient selection for eIg therapy, potentially optimizing outcomes in septic shock treatment.
Source: Journal of Clinical Medicine
DOI: 10.3390/jcm14175950
Institutions: Ospedale Policlinico San Martino, University of Trieste, Azienda sanitaria universitaria Giuliano Isontina, Azienda Ospedaliera Santa Maria Degli Angeli, University of Messina, University of Foggia, Azienda Ospedaliero Universitaria Policlinico "G.Rodolico - San Marco", University of Pisa, Azienda Ospedaliera Universitaria Pisana, Azienda Ospedaliera Nazionale SS. Antonio e Biagio e Cesare Arrigo, Azienda Ospedaliera Universitaria Policlinico "Paolo Giaccone" di Palermo, University of Palermo
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,137
OpenAlex ID: W4413426453
