Recurrent event survival analysis predicts future risk of hospitalization in patients with paroxysmal and persistent atrial fibrillation

Autor: Olivier Bouaziz, Dana Li, Per Lav Madsen, Jakob Schroder, Ulrik Dixen, Torben Martinussen, Bue Ross Agner
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Male
Epidemiology
030204 cardiovascular system & hematology
Electrocardiography
0302 clinical medicine
Mathematical and Statistical Techniques
Quality of life
Atrial Fibrillation
Medicine and Health Sciences
030212 general & internal medicine
Multidisciplinary
medicine.diagnostic_test
Statistical Models
Statistics
Atrial fibrillation
Middle Aged
Recurrent event
Hospitalization
Bioassays and Physiological Analysis
Research Design
Persistent atrial fibrillation
Physical Sciences
Cardiology
Disease Progression
Medicine
Female
Arrhythmia
Research Article
Risk
medicine.medical_specialty
Clinical Research Design
Future risk
Science
Surgical and Invasive Medical Procedures
Research and Analysis Methods
03 medical and health sciences
Internal medicine
medicine
Humans
In patient
Statistical Methods
Survival analysis
Aged
business.industry
Electrophysiological Techniques
medicine.disease
Survival Analysis
Medical Risk Factors
Quality of Life
Cardiac Electrophysiology
business
Mathematics
Forecasting
Zdroj: PLoS ONE, Vol 14, Iss 6, p e0217983 (2019)
PLoS ONE
Schroder, J, Bouaziz, O, Agner, B R, Martinussen, T, Madsen, P L, Li, D & Dixen, U 2019, ' Recurrent event survival analysis predicts future risk of hospitalization in patients with paroxysmal and persistent atrial fibrillation ', PLoS ONE, vol. 14, no. 6, e0217983 . https://doi.org/10.1371/journal.pone.0217983
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0217983
Popis: BackgroundIn patients with paroxysmal atrial fibrillation (PAF) or persistent atrial fibrillation (PeAF) symptom burden and fear of hospital readmission are major causes of reduced quality of life. We attempted to develop a prediction model for future atrial fibrillation hospitalization (AFH) risk in PAF and PeAF patients including all previously experienced AFHs in the analysis, as opposed to time to first event.MethodsRecurrent event survival analysis was used to model the impact of past AFHs on the risk of future AFHs. A recurrent event was defined as a hospitalization due to a new episode of AF. Death or progression to permanent AF were included as competing risks.ResultsWe enrolled 174 patients with PAF or PeAF, mean follow up duration was 1279 days, and 325 AFHs were observed. Median patient age was 63.0 (IQR 52.2-68.0), 29% had PAF, and 71% were male. Highly significant predictors of future AFH risk were PeAF (HR 3.20, CI 2.01-5.11) and number of past AFHs observed (HR for 1 event: 2.97, CI 2.04-4.32, HR for ≥2 events: 7.54, CI 5.47-10.40).ConclusionIn PAF and PeAF patients, AF type and observed AFH frequency are highly significant predictors of future AFH risk. The developed model enables risk prediction in individual patients based on AFH history and baseline characteristics, utilizing all events experienced by the patient. This is the first time recurrent event survival analysis has been used in AF patients.
Databáze: OpenAIRE
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