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Published on: September 16, 2022
[Value of a model based on PIRO conception in predicting the prognosis in critical patients]
Tao Wang1, Yun-liang Cui, Zhi-xiang Chu
1Department of Emergency, Hainan Branch of PLA General Hospital, Sanya 572000, Hainan, China. Corresponding author: Ban Yu,
Insights
The PIRO system, incorporating predisposition, injury, response, and organ dysfunction, effectively predicts 28-day mortality in critical patients. Key factors include underlying disease scores, severe sepsis/septic shock, and Sequential Organ Failure Assessment (SOFA) scores.
Area of Science:
- Critical care medicine
- Prognostic modeling
- Clinical epidemiology
Context:
- Critical illness presents a significant challenge in predicting patient outcomes.
- Existing prognostic models may not fully capture the complexity of critical patient trajectories.
- The PIRO (Predisposition, Injury, Response, Organ dysfunction) concept offers a framework for assessing critical illness severity.
Purpose:
- To evaluate the predictive value of factors derived from the PIRO concept for 28-day mortality in critically ill patients.
- To identify independent predictors of mortality within the PIRO framework using multivariate logistic regression.
- To assess the performance of a PIRO-based prognostic model compared to individual clinical variables.
Summary:
- A retrospective analysis of 187 critical patients identified underlying disease scores, severe sepsis/septic shock, and Sequential Organ Failure Assessment (SOFA) scores as independent predictors of 28-day mortality.
- The PIRO model, utilizing these factors, demonstrated a high area under the receiver operating characteristic curve (AUC) of 0.871, indicating strong prognostic value.
- The developed PIRO-based model showed superior predictive accuracy for mortality compared to individual components like SOFA, APS, underlying disease scores, PCT, and age.
Impact:
- The findings suggest that a PIRO-based multivariate regression model can significantly enhance the prediction of 28-day mortality in critical care settings.
- This prognostic tool can aid clinicians in risk stratification and timely intervention for critically ill patients.
- The study validates the utility of the PIRO concept in developing robust clinical prediction models for critical illness outcomes.
Objective:
To investigate the values of factors based on PIRO conception in predicting the prognosis of critical patients.
Methods:
The clinical data of critical patients admitted to Hainan Branch of PLA General Hospital from December 2011 to August 2013 were retrospectively analyzed. The patients were randomly divided into non-survivors and survivors groups according to 28-day outcome. Predisposition (P), injury (I), response (R) and organ dysfunction induced by injury (O) were compared between two groups. The indexes with statistical significance (P<0.2) by univariate analysis were included in multivariate logistic regression analysis, and the receiver operating characteristic curve (ROC curve) was plotted to evaluate the values of factors based on PIRO conception in predicting the prognosis of critical patients.
Results:
One hundred and eighty-seven critical patients were enrolled, and among them 75 (40.1%) patients died. Univariate analysis showed that the age, underlying disease scores, history of cardiovascular disease, diabetes mellitus, and cerebrovascular disease, positive blood culture, whether or not complicated with acute respiratory distress syndrome (ARDS) or severe sepsis/septic shock, procalcitonin (PCT), acute physiology and chronic health evaluation II (APACHE II), acute pathophysiology score (APS) and sequential organ failure assessment (SOFA) were found to be the factors related with the prognosis (all P<0.2). Multivariate logistic regression analysis showed that the underlying disease scores [odds ratio (OR)=1.874, 95% confidence interval (95%CI) 1.138-3.084, P=0.014], whether patients occurrence of severe sepsis/septic shock (OR=0.167, 95%CI 0.064-0.435, P=0.000) and SOFA scores (OR=1.498, 95%CI 1.283-1.750, P=0.000) were independent factors for predicting 28-day mortality. The new model combined with above factors had more prognostic value in predicting the mortality than a single variable. The area under ROC curve (AUC) for PIRO model based on indexes with statistical significance by univariate analysis was 0.877 (0.821-0.934), P=0.000. AUC for PIRO model based on underlying disease scores, severe sepsis/septic shock, SOFA scores was 0.871 (0.814-0.928), P=0.000. AUC for SOFA was 0.762 (0.687-0.837), P=0.000. AUC for APS was 0.726 (0.647-0.805), P=0.000. AUC for underlying disease scores was 0.678 (0.593-0.763), P=0.000. AUC for PCT was 0.636 (0.548-0.724), P=0.004. AUC for age was 0.618 (0.532-0.705), P=0.013].
Conclusions:
The multivariate regression analysis based on PIRO system may help to predict 28 days mortality in critical patients.
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