Development and Validation of a Nomogram for Predicting Sepsis-Associated Acute Respiratory Distress Syndrome

Area of Science:

• Critical care medicine
• Respiratory medicine
• Biostatistics

Background:

• Sepsis-associated acute respiratory distress syndrome (ARDS) presents a significant challenge due to high morbidity and mortality.
• Early identification of sepsis patients at high risk for ARDS is crucial for timely and effective interventions.

Purpose of the Study:

• To develop and validate a nomogram for predicting the risk of ARDS in patients diagnosed with sepsis.
• To provide clinicians with a practical tool for early risk stratification of sepsis patients.

Main Methods:

• Retrospective enrollment of 308 patients in a development cohort and 132 in a validation cohort.
• Logistic regression analysis to identify independent risk factors for ARDS.
• Performance evaluation using Area Under the Receiver Operating Characteristic Curve (AUC), calibration curves, and Decision Curve Analysis (DCA).

Main Results:

• The nomogram identified pulmonary infection, procalcitonin (PCT), tumor necrosis factor-alpha (TNF-α), oxygenation index, and APACHE II score as independent predictors of ARDS.
• The nomogram demonstrated excellent predictive performance with AUCs of 0.862 (development) and 0.881 (validation).
• Good calibration and clinical utility were confirmed by calibration curves, non-significant Hosmer-Lemeshow tests, and DCA.

Conclusions:

• The developed nomogram is a reliable and practical tool for predicting ARDS risk in sepsis patients.
• This model aids clinicians in identifying high-risk individuals for early preventive strategies and personalized management.
• The nomogram incorporates five accessible variables, facilitating its widespread clinical application.