Peripheral Perfusion Index- Shock Index- Emergency Severity Index In Prediction Of Outcome Of Patient In Tertiary Care Hospital

Abstract

INTRODUCTION: The admissions in the Emergency Department are increasing day by day in recent years requiring the strong and effective triage systems. The goals of these triage systems are to differentiate the patients as high to low-risk patients and immediate attention to the high-risk patients. As increasing emergency care demand, it puts pressure on the ED hampering the patient care. Multiple systems are working on triaging of the patients worldwide. Emergency Severity Index is the most used system in western countries increasing the influence in other parts of the world also. It consists of five stage system. Certain indicators like peripheral perfusion index and shock index which can be easily obtained in triage can be added to the ESI grading to improve and to make the triage more effective and improving the patient care in the Emergency Department. OBJECTIVES To determine the combined effect of the Peripheral Perfusion Index and Shock Index with ESI to predict hospital outcomes in the form of need of ventilation and morbidity in acute critically ill patients coming to Emergency Department. To determine the individual effect of the Peripheral Perfusion Index, Shock Index and Emergency Severity Index. TYPE OF STUDY: Cross sectional study. STUDY PERIOD: Period of 21 months (August 2022 to April 2024). STUDY POPULATION: Patients coming to Emergency Department BLDE, Shri B.M Patil Medical College Hospital and Research Centre, Vijayapura from August 2022 to April 2024 consisting of patients aged older than 18 years who visited the Emergency Medicine department who met the inclusion Criteria. METHODOLOGY: A cross-sectional study was conducted by department of pediatrics at Shri BM Patil Medical College Hospital and Research Centre. The study included hospital-based patients coming in Emergency Department. Data was collected via triage examination of the patients and the in-hospital status of the patients. The triage included variables such as age, residence, sex, heart rate, systolic blood pressure, shock index, peripheral perfusion index and emergency severity index grading. STATISTICAL ANALYSIS: Statistical analyses were conducted using SPSS (Version 20). The Mann-Whitney U test was employed for non-normally distributed variables to compare medians accurately. Categorical variables were analyzed using the Chi-square test or Fisher's exact test to determine associations between different categorical outcomes and groups. For comparisons involving more than two groups, ANOVA was utilized for normally distributed variables, and the Kruskal-Wallis H test for non-normally distributed variables, ensuring appropriate analysis based on data distribution. The correlation between PPI, SI, and ESI was assessed using Pearson or Spearman correlation coefficients, depending on the normality of the data distribution. Logistic regression analysis was conducted to evaluate the association of PPI and SI measurements with hospital admission and mortality outcomes, providing insights into the predictive value of these indices. The prognostic value of PPI, SI, and ESI in predicting adverse outcomes was further assessed using receiver operating characteristic (ROC) curve analysis and the area under the curve (AUC). RESULTS: Among the 610 participants, Emergency Severity Index (ESI) score of less than 3, The PPI at admission shows a strong predictive accuracy with an AUC of 0.89 and a standard error of 0.01. At 12 hours, the PPI’s AUC slightly decreased to 0.86, and at 24 hours, it modestly increased to 0.87, indicating consistent predictive performance over time. The SI at admission had an AUC of 0.82, with a standard error of 0.02, reflecting moderate predictive accuracy. The SI's predictive power improved significantly, with an AUC of 0.93 at 12 hours and 0.95 at 48 hours, demonstrating high predictive accuracy. CONCLUSION: Peripheral Perfusion Index and Shock Index significantly enhance the predictive power of Emergency Severity Index, leading to better identification of high-risk patients and more timely interventions. The study suggests that incorporating these objective indices can optimize resource allocation and improve patient care. Future research should validate these results across multiple centers and explore additional variables. In conclusion, integrating PPI and SI with ESI can enhance triage effectiveness, ensuring better patient outcomes and more efficient emergency department operations.