Acute Respiratory Distress Syndrome (ARDS) is a severe respiratory condition characterized by hypoxemia, bilateral pulmonary infiltrates, and non-cardiac pulmonary edema. In pediatric patients, ARDS is associated with high mortality and long-term morbidity. Early identification of at-risk patients is critical for timely intervention, but current risk assessment tools are either adult-specific or lack validation in pediatric populations. This study aims to develop and validate a pediatric-specific ARDS risk assessment tool to improve early diagnosis and management in PICU patients.

Study Design: A prospective cohort study was conducted in a tertiary care PICU over two years.

Participants: The development cohort included 500 consecutive PICU patients aged 1 month to 18 years. The validation cohort included 300 patients from a different time period. Exclusion criteria included pre-existing chronic lung disease or congenital heart disease.

Data Collection: Clinical, laboratory, and respiratory parameters were collected within 24 hours of PICU admission. ARDS was diagnosed according to the Pediatric Acute Lung Injury Consensus Conference (PALICC) criteria.

Predictor Variables: Candidate predictors included hypoxia index (PaO₂/FiO₂ ratio), presence of pneumonia, sepsis, immunocompromised status, history of aspiration, lactate levels, and mechanical ventilation parameters.

Statistical Analysis: Logistic regression was used to identify independent predictors of ARDS. The tool was developed using the development cohort and validated using the independent cohort. Discrimination was assessed using AUC, and calibration was evaluated using the Hosmer-Lemeshow test. Sensitivity, specificity, and optimal cutoff values were determined.

Table 1: Predictors of ARDS and Their Assigned Scores

Table 2: Performance of the PARRT Tool

Table 3: Distribution of Risk Scores and ARDS Incidence

Summary of Results

1. Predictors of ARDS: Six variables were independently associated with ARDS: hypoxia index, pneumonia, sepsis, immunocompromised status, history of aspiration, and elevated lactate levels. These predictors were used to develop the Pediatric ARDS Risk Assessment Tool (PARRT).
2. Tool Performance:
• Development Cohort: The tool demonstrated excellent discrimination (AUC=0.92) and good calibration (Hosmer-Lemeshow p=0.50). At the optimal cutoff (risk score ≥4), sensitivity was 85%, and specificity was 89%.
• Validation Cohort: The tool maintained good discrimination (AUC=0.88) and calibration (Hosmer-Lemeshow p=0.45), with sensitivity of 82% and specificity of 87%.
3. Risk Stratification:
• Low risk (score 0–3): ARDS incidence was 5–6%.
• Moderate risk (score 4–6): ARDS incidence was 32–35%.
• High risk (score 7–10): ARDS incidence was 75–78%.
4. Clinical Utility: The PARRT tool is simple, practical, and effective for identifying pediatric patients at high risk of ARDS. It can be used at PICU admission to guide early interventions, such as lung-protective ventilation and close monitoring.

The Pediatric ARDS Risk Assessment Tool (PARRT) demonstrated excellent predictive performance in both the development and validation cohorts, with an AUC of 0.92 and 0.88, respectively. This tool, which incorporates six easily measurable predictors—hypoxia index, pneumonia, sepsis, immunocompromised status, history of aspiration, and elevated lactate levels—provides a practical and reliable method for identifying pediatric patients at high risk of developing ARDS. The results of this study align with and expand upon existing literature, offering a pediatric-specific tool that addresses a critical gap in ARDS risk prediction.

Comparison with Existing Literature

1. Hypoxia Index:
   Hypoxia, as measured by the PaO₂/FiO₂ ratio, is a well-established predictor of ARDS. Khemani et al. [1] highlighted the importance of hypoxia in pediatric ARDS, noting that a PaO₂/FiO₂ ratio <200 is strongly associated with disease progression. Our findings are consistent with this, as hypoxia index was the strongest predictor in the PARRT tool, contributing 3 points to the risk score.
2. Pneumonia and Sepsis:
   Pneumonia and sepsis are common precipitating factors for ARDS. Wong et al. [2] found that infections, particularly pneumonia and sepsis, were present in over 70% of pediatric ARDS cases. Similarly, our study identified both pneumonia and sepsis as significant predictors, each contributing 2 points to the risk score. These findings underscore the importance of early recognition and management of infections in PICU patients.
3. Immunocompromised Status:
   Immunocompromised children are at higher risk for ARDS due to their susceptibility to infections and inflammatory complications. Flori et al. [3] reported that immunocompromised status was independently associated with increased ARDS mortality. Our tool includes immunocompromised status as a predictor, reflecting its relevance in pediatric populations.
4. History of Aspiration:
   Aspiration of gastric contents is a known risk factor for ARDS, particularly in children with impaired airway protection. Zimmerman et al. [4] identified aspiration as a significant contributor to pediatric ARDS, a finding supported by our study, which included history of aspiration as a predictor.
5. Elevated Lactate Levels:
   Elevated lactate levels, a marker of tissue hypoxia and poor perfusion, have been associated with worse outcomes in ARDS. Studies by Randolph et al. [5] and Sapru et al. [6] emphasized the role of lactate as a prognostic marker in pediatric critical care. Our tool incorporates elevated lactate levels as a predictor, further validating its utility in ARDS risk assessment.

Clinical Implications

The PARRT tool provides a simple and effective method for identifying pediatric patients at high risk of ARDS. By stratifying patients into low, moderate, and high-risk categories, the tool can guide clinical decision-making and facilitate early interventions, such as lung-protective ventilation, fluid management, and close monitoring. Early identification of high-risk patients may reduce ARDS incidence and improve outcomes, as suggested by studies on early intervention in ARDS [7, 8].

Comparison with Adult ARDS Prediction Models

The PARRT tool builds on the success of adult ARDS prediction models, such as the Lung Injury Prediction Score (LIPS) [9] and the Modified LIPS [10]. While these models have been validated in adult populations, they lack specificity for pediatric patients. The PARRT tool addresses this gap by incorporating pediatric-specific predictors, such as immunocompromised status and history of aspiration, which are less relevant in adult populations.

Strengths of the Study

1. Pediatric-Specific Tool: The PARRT tool is the first validated risk assessment tool specifically designed for pediatric ARDS.
2. Prospective Design: The study used a prospective cohort design, ensuring robust data collection and minimizing bias.
3. Validation Cohort: The tool was validated in an independent cohort, demonstrating its generalizability and reliability.

Limitations

1. Single-Center Study: The study was conducted at a single tertiary care PICU, which may limit generalizability to other settings.
2. Dynamic Risk Factors: The tool does not account for changes in patient condition over time, which may affect ARDS risk.
3. External Validation: Further validation in diverse PICU populations is needed to confirm the tool’s applicability.

Future Directions

1. Multicenter Validation: Future studies should validate the PARRT tool in diverse PICU settings to confirm its generalizability.
2. Incorporation of Dynamic Variables: The tool could be enhanced by incorporating dynamic variables, such as changes in respiratory and hemodynamic parameters over time.
3. Integration into Clinical Practice: The tool should be integrated into electronic health records to facilitate real-time risk assessment and decision support.

The Pediatric ARDS Risk Assessment Tool (PARRT) is a valid and reliable tool for predicting ARDS in PICU patients. Its use may facilitate early identification of at-risk patients, enabling timely interventions to improve outcomes. Further multicenter studies are recommended to validate the tool in diverse populations and explore its impact on clinical practice.

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