Brazilian journal of anesthesiology (Elsevier) · 2026
Artificial intelligence in the prediction of intraoperative red blood cell transfusion in cardiac surgery: a systematic review and diagnostic test accuracy meta-analysis.
СтатьяСистематический обзорМетаанализНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Valério Filipe Giordano, Rodrigues Amanda Carneiro, de Amorim Davi Ricardo Soares Gama, Cantarino Roberta Esterque, de Araujo Glauco Martins, Yusuf Jimmy, Bessa Lecticia Vianna Leal Soares, Leme Millena Mendonça Andrade Paes, Euzebio Marcella Freire de Campos, Seixas Flávio Luiz, Assad Alexandra Rezende, Diego Luis Antonio Dos Santos
Аннотация
BACKGROUND: Red Blood Cell (RBC) transfusion in cardiac surgery is associated with risks. Conventional prediction scores lack accuracy, conflicting with Patient Blood Management (PBM) principles. Artificial Intelligence (AI) offers a potential avenue for developing precise, data-driven predictive models to enhance clinical decision-making and optimize patient outcomes.
METHODS: A systematic review and meta-analysis of diagnostic test accuracy studies was conducted following PRISMA guidelines, searching PubMed, Embase, and Cochrane Library databases until April 2025. Studies developing AI models to predict intraoperative Red Blood Cell (RBC) transfusions in adult cardiac surgery were included. Pooled sensitivity, specificity, and Area Under the receiver operating Characteristic Curve (AUC) were calculated using a bivariate random-effects model. To summarize overall diagnostic performance, Summary Receiver Operating Characteristic curves were generated.
RESULTS: Five studies encompassing 3,063 patients were analyzed in the meta-analysis. AI models demonstrated high pooled specificity, ranging from 86.3% (95% CI 82.8%‒89.1%) to 93.6% (95% CI 84.3%‒97.6%), whereas pooled sensitivity ranged from 50.3% (95% CI 20.9%‒79.6%) to 55.7% (95% CI 33.8%‒75.6%). AUC values ranged between 0.793 (95% CI 0.634‒0.899) and 0.892 (95% CI 0.740‒0.943). Preoperative hemoglobin levels and patient age were consistently identified as clinical predictors for intraoperative RBC transfusion.
CONCLUSION: This systematic review and meta-analysis suggests that AI models may have potential for predicting intraoperative RBC transfusion in cardiac surgery, with consistently high specificity but only moderate sensitivity. However, given the low certainty of evidence, substantial heterogeneity, and reliance on non-standardized transfusion practices, these findings should be interpreted cautiously.
METHODS: A systematic review and meta-analysis of diagnostic test accuracy studies was conducted following PRISMA guidelines, searching PubMed, Embase, and Cochrane Library databases until April 2025. Studies developing AI models to predict intraoperative Red Blood Cell (RBC) transfusions in adult cardiac surgery were included. Pooled sensitivity, specificity, and Area Under the receiver operating Characteristic Curve (AUC) were calculated using a bivariate random-effects model. To summarize overall diagnostic performance, Summary Receiver Operating Characteristic curves were generated.
RESULTS: Five studies encompassing 3,063 patients were analyzed in the meta-analysis. AI models demonstrated high pooled specificity, ranging from 86.3% (95% CI 82.8%‒89.1%) to 93.6% (95% CI 84.3%‒97.6%), whereas pooled sensitivity ranged from 50.3% (95% CI 20.9%‒79.6%) to 55.7% (95% CI 33.8%‒75.6%). AUC values ranged between 0.793 (95% CI 0.634‒0.899) and 0.892 (95% CI 0.740‒0.943). Preoperative hemoglobin levels and patient age were consistently identified as clinical predictors for intraoperative RBC transfusion.
CONCLUSION: This systematic review and meta-analysis suggests that AI models may have potential for predicting intraoperative RBC transfusion in cardiac surgery, with consistently high specificity but only moderate sensitivity. However, given the low certainty of evidence, substantial heterogeneity, and reliance on non-standardized transfusion practices, these findings should be interpreted cautiously.