Abstract

Introduction: Fluid responsiveness assessment is crucial in managing critically ill patients. This study evaluates the correlation and efficacy of Inferior Vena Cava Collapsibility Index (IVCCI) and Perfusion Index (PI) in predicting fluid responsiveness.
 Objectives: The primary objective was to evaluate the correlation between the IVCCI and PI as predictors fluid responsiveness in critically ill patients. Secondary objectives involved studying the individual accuracy of the IVCCI and PI in predicting of fluid responsiveness and exploring whether their combined use improves overall accuracy in predicting fluid responsiveness in this patient population.
 Methodology: This prospective study enrolled 80 critically ill patients requiring hemodynamic monitoring and fluid resuscitation. IVCCI was measured using bedside ultrasonography, and PI was derived from pulseoximetry. Hemodynamic parameters were recorded before and after a standardized fluid bolus. Receiver Operating Characteristic (ROC) curves were generated to assess the predictive performance of IVCCI and PI.
 Results: Among 80 enrolled patients, responders (N=35) demonstrated significantly lower baseline cardiac output (4.5 ± 0.23 vs 4.76 ± 0.22, p<0.01) and higher IVCCI (35.13 ± 13.41 vs 28.53 ± 10.17, p=0.015) compared to non-responders. After a standardized fluid bolus, responders exhibited higher cardiac output (5.31 ± 0.24 vs 4.9 ± 0.27, p<0.01) and lower IVCCI (22.01 ± 15.84 vs 28.88 ± 11.71, p=0.029). IVCCI and PI before fluid bolus showed a very weak positive correlation (r = 0.080, p = 0.478). Moreover, IVCCI before fluid bolus had better sensitivity (0.745) and specificity (0.727) than PI before fluid bolus (sensitivity: 0.574, specificity: 0.485), with AUC values of 0.693 and 0.455, respectively.
 Conclusion: IVCCI demonstrates efficacy in predicting fluid responsiveness, with a very weak positive correlation to PI. Notably, IVCCI before fluid bolus outperforms PI before fluid bolus in sensitivity and specificity, highlighting its superior predictive accuracy in critically ill patients.

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