Integrated Pulmonary Index as a Predictor of Respiratory Compromise in Critically Ill Patients: A Prospective, Observational Study
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- Category: Vol. 93, March 2025
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Integrated Pulmonary Index as a Predictor of Respiratory Compromise in Critically Ill Patients: A Prospective, Observational Study, DOAA M. KAMAL EL-DIN, ABDELRAHMAN A.M. EL HAWEY, HANAA M. ABD ALLAH EL GENDY and SARAH A. SALEM AHMED
Abstract
Background: Recent developments in detecting ARDS focus on using multiple physiological parameters, integrating them into a single index to improve accuracy while reducing false alarms and alarm fatigue. The Integrated Pulmonary Index (IPITM) is one such multi-parameter tool, combining oxygen saturation, respiratory rate, ETCO2, and pulse rate into a 1-10 scale. Scores ≥8 indicate normal conditions, while ≤4 suggest intervention is needed. Aim of Study: In this study, we prospectively investigated the effectiveness and usefulness of integrated pulmonary in dex as a predictor of respiratory compromise in critically ill patients. Patients and Methods: This prospective observational study was conducted at Ain Shams University Hospitals from June 2023 to December 2023, involving 70 critically ill patients aged 18 or older, admitted to the ICU. IPI measurements were recorded for all patients at (2, 6, 12, 18, and 24 hours). Pa tients were then categorized into respiratory compromise (RC) defined as development of hypoxemia, hypercapnia, bronchos pasm, tachypnea, and any other events that required interven tion, and non-respiratory compromise (NRC). The values were then correlated with the need for oxygen support, onset of me chanical ventilation, duration of mechanical ventilation, length of ICU, duration of hospital stay and 28-day mortality rate. Results: Among the 70 patients included in the study 41 pa tients (58.6%) developed respiratory compromise (RC), while 29 patients (41.4%) did not develop any respiratory compro mise (NRC). Analysis of the Integrated Pulmonary Index (IPI) showed significant differences between patients with respira tory compromise (RC) and those without. At all-time intervals (2, 6, 12, 18, and 24 hours), median and interquartile ranges for IPI values were lower in the RC group (p<0.001), highlight- ing IPI’s reliability in predicting respiratory status. The RC group required longer duration of mechanical ventilation, had longer ICU and hospital stays and exhibited a higher mortality rate (19.5%) compared to 0% in the non-compromised group (p=0.011). Correlation analysis showed strong negative associ ations between IPI and various clinical parameters, such as res piratory compromise (r=–0.812), the need for oxygen support (r=–0.812), and the need for mechanical ventilation (r=–0.542), as well as ICU stay (r=–0.814) and hospital stay (r=–0.809), as well as 28-day mortality rate (r=–0.477). These correlations emphasize IPI’s value in predicting adverse clinical outcomes. ROC curve analysis demonstrated that IPI, with a cut-off val ue of <6, had excellent predictive accuracy for oxygen support (AUC=0.906, sensitivity 90%, PPV 98.7%). SpO2 also showed good predictive performance (AUC=0.839, sensitivity 86.7%, PPV 94.3%). Overall, IPI was the superior predictor, emphasiz ing its clinical utility in identifying patients at risk for respira tory deterioration. Conclusion: The findings of this study highlight the Inte grated Pulmonary Index (IPI) as a reliable and dynamic predic tor of respiratory compromise and oxygen support requirements in critically ill patients, outperforming SpO2 in overall accura cy. The IPI demonstrated strong correlations with adverse clini cal outcomes, including the duration of mechanical ventilation, length of ICU, length of hospital stay, and mortality rate. Its high sensitivity and predictive values emphasize its utility in early detection of respiratory compromise, aiding timely inter ventions to improve patient outcomes. These results underscore the importance of incorporating IPI into routine monitoring protocols in intensive care settings to enhance patient care and prognosis.