Key result
Age ≥80 linked to ~22.9-fold higher risk of new-onset AF in critically ill patients.
Why the study?
AF occurrence represents clinical deterioration in acutely unwell patients and increases morbidity and mortality, whereas predicting AF development allows early intervention.
What are the primary risk factors for developing new episodes of atrial fibrillation in critically ill patients, and can they be modeled for risk prediction?
Observational (n=18,518)
No
What are the primary risk factors for developing new episodes of atrial fibrillation in critically ill patients, and can they be modeled for risk prediction?
Advanced age, mechanical ventilation, and elevated inflammatory markers are dominant risk factors for incident atrial fibrillation in critically ill patients, which can be accurately predicted using a machine learning-based logistic regression model.
Answers are grounded in this paper and cite their sources.
Age may guide AF monitoring in elderly ICU patients; leaves open whether prediction models improve outcomes.
The occurrence of atrial fibrillation (AF) represents clinical deterioration in acutely unwell patients and leads to increased morbidity and mortality. Prediction of the development of AF allows early intervention. Using the AmsterdamUMCdb, clinically relevant variables from patients admitted in sinus rhythm were extracted over the full duration of the ICU stay or until the first recorded AF episode occurred. Multiple logistic regression was performed to identify risk factors for AF. Input variables were automatically selected by a sequential forward search algorithm using cross-validation. We developed three different models: For the overall cohort, for ventilated patients and non-ventilated patients. 16,144 out of 23,106 admissions met the inclusion criteria. 2,374 (12.8%) patients had at least one AF episode during their ICU stay. Univariate analysis revealed that a higher percentage of AF patients were older than 70 years (60% versus 32%) and died in ICU (23.1% versus 7.1%) compared to non-AF patients. Multivariate analysis revealed age to be the dominant risk factor for developing AF with doubling of age leading to a 10-fold increased risk. Our logistic regression models showed excellent performance with AUC.ROC > 0.82 and > 0.91 in ventilated and non-ventilated cohorts, respectively. Increasing age was the dominant risk factor for the development of AF in both ventilated and non-ventilated critically ill patients. In non-ventilated patients, risk for development of AF was significantly higher than in ventilated patients. Further research is warranted to identify the role of ventilatory settings on risk for AF in critical illness and to optimise predictive models.
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Ortega‐Martorell et al. (2022) conducted an observational in Critically ill patients (medical-surgical ICU) admitted in sinus rhythm (n=18,518). Increasing age (80+ years) vs. Age 40-49 years was evaluated on First documented episode of atrial fibrillation during ICU stay (OR 22.909, 95% CI 15.363-34.163). Increasing age was the most dominant risk factor for developing new-onset atrial fibrillation in critically ill patients, with patients aged ≥80 years having an approximately 23-fold increased risk compared to those aged 40-49.
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