A dynamic online nomogram predicting post-traumatic arrhythmias: A retrospective cohort study

Area of Science:

• Trauma care
• Clinical prediction modeling
• Cardiac electrophysiology

Background:

• Clinical prediction models, known as nomograms, provide a scientific basis for decision-making.
• There is limited research on nomograms for predicting arrhythmias in trauma patients.
• This study addresses this gap by developing and validating a nomogram for this purpose.

Purpose of the Study:

• To develop and validate a straightforward nomogram for predicting the risk of arrhythmias in acute trauma patients.
• To identify independent risk factors associated with post-traumatic arrhythmias.

Main Methods:

• Retrospective collection of clinical data from 1119 trauma patients.
• Development of a nomogram based on independent risk factors identified in a training set (70% of data).
• Validation of the nomogram's predictive performance using a validation set (30% of data).

Main Results:

• Arrhythmias occurred in 29.1% of patients, associated with longer ICU/hospital stays and higher mortality.
• Independent risk factors included cardiovascular disease, catecholamine use, Glasgow Coma Scale score, Abbreviated Injury Scale score, Injury Severity Score, blood glucose, and international normalized ratio.
• The nomogram demonstrated strong discriminatory power (AUC > 0.7), good calibration, and high net benefit on decision curve analysis.

Conclusions:

• The developed nomogram is a valuable tool for accurately predicting post-traumatic arrhythmia risk.
• This novel approach enables physicians to tailor risk assessments for individual trauma patients.
• The nomogram facilitates improved clinical decision-making in trauma care.