PMID- 36639191
OWN - NLM
STAT- MEDLINE
DCOM- 20230117
LR  - 20230215
IS  - 2053-3624 (Print)
IS  - 2053-3624 (Electronic)
IS  - 2053-3624 (Linking)
VI  - 10
IP  - 1
DP  - 2023 Jan
TI  - Development and validation of prediction models for incident atrial fibrillation 
      in heart failure.
LID - 10.1136/openhrt-2022-002169 [doi]
LID - e002169
AB  - OBJECTIVES: Accurate prediction of heart failure (HF) patients at high risk of 
      atrial fibrillation (AF) represents a potentially valuable tool to inform shared 
      decision making. No validated prediction model for AF in HF is currently 
      available. The objective was to develop clinical prediction models for 1-year 
      risk of AF. METHODS: Using the Danish Heart Failure Registry, we conducted a 
      nationwide registry-based cohort study of all incident HF patients diagnosed from 
      2008 to 2018 and without history of AF. Administrative data sources provided the 
      predictors. We used a cause-specific Cox regression model framework to predict 
      1-year risk of AF. Internal validity was examined using temporal validation. 
      RESULTS: The population included 27 947 HF patients (mean age 69 years; 34% 
      female). Clinical experts preselected sex, age at HF, NewYork Heart Association 
      (NYHA) class, hypertension, diabetes mellitus, chronic kidney disease, 
      obstructive sleep apnoea, chronic obstructive pulmonary disease and myocardial 
      infarction. Among patients aged 70 years at HF, the predicted 1-year risk was 
      9.3% (95% CI 7.1% to 11.8%) for males and 6.4% (95% CI 4.9% to 8.3%) for females 
      given all risk factors and NYHA III/IV, and 7.5% (95% CI 6.7% to 8.4%) and 5.1% 
      (95% CI 4.5% to 5.8%), respectively, given absence of risk factors and NYHA class 
      I. The area under the curve was 65.7% (95% CI 63.9% to 67.5%) and Brier score 
      7.0% (95% CI 5.2% to 8.9%). CONCLUSION: We developed a prediction model for the 
      1-year risk of AF. Application of the model in routine clinical settings is 
      necessary to determine the possibility of predicting AF risk among patients with 
      HF more accurately and if so, to quantify the clinical effects of implementing 
      the model in practice.
CI  - (c) Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No 
      commercial re-use. See rights and permissions. Published by BMJ.
FAU - Vinter, Nicklas
AU  - Vinter N
AUID- ORCID: 0000-0003-0558-8483
AD  - Silkeborg Regional Hospital, Silkeborg, Denmark nicvin@rm.dk.
AD  - Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
AD  - Danish Center for Clinical Health Services Research, Department of Clinical 
      Medicine, Aalborg University, Aalborg, Denmark.
FAU - Gerds, Thomas Alexander
AU  - Gerds TA
AD  - Section of Biostatistics, University of Copenhagen, Denmark, Copenhagen, Denmark.
FAU - Cordsen, Pia
AU  - Cordsen P
AD  - Danish Center for Clinical Health Services Research, Department of Clinical 
      Medicine, Aalborg University, Aalborg, Denmark.
FAU - Valentin, Jan Brink
AU  - Valentin JB
AD  - Danish Center for Clinical Health Services Research, Department of Clinical 
      Medicine, Aalborg University, Aalborg, Denmark.
FAU - Lip, Gregory Y H
AU  - Lip GYH
AD  - Liverpool Centre for Cardiovascular Science, University of Liverpool and 
      Liverpool Chest & Heart Hospital, Liverpool, UK.
AD  - Department of Clinical Medicine, Aalborg University, Aalborg, Denmark.
FAU - Benjamin, Emelia J J
AU  - Benjamin EJJ
AD  - Department of Medicine, Boston Medical Center, Boston University School of 
      Medicine and Department of Epidemiology, Boston University School of Public 
      Health, Framingham, Massachusetts, USA.
FAU - Johnsen, Soren Paaske
AU  - Johnsen SP
AD  - Danish Center for Clinical Health Services Research, Department of Clinical 
      Medicine, Aalborg University, Aalborg, Denmark.
FAU - Frost, Lars
AU  - Frost L
AUID- ORCID: 0000-0001-9215-9796
AD  - Silkeborg Regional Hospital, Silkeborg, Denmark.
AD  - Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
LA  - eng
GR  - R01 HL092577/HL/NHLBI NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
PT  - Research Support, Non-U.S. Gov't
PL  - England
TA  - Open Heart
JT  - Open heart
JID - 101631219
SB  - IM
MH  - Male
MH  - Humans
MH  - Female
MH  - Aged
MH  - *Atrial Fibrillation/diagnosis/epidemiology
MH  - Cohort Studies
MH  - *Heart Failure/diagnosis/epidemiology/etiology
MH  - Heart
MH  - Risk Factors
PMC - PMC9843222
OTO - NOTNLM
OT  - Atrial Fibrillation
OT  - Electronic Health Records
OT  - HEART FAILURE
COIS- Competing interests: GYHL: Consultant and speaker for BMS/Pfizer, Boehringer 
      Ingelheim and Daiichi-Sankyo. No fees are received personally. SPJ: Consultant 
      and speaker for BMS/Pfizer. Research grants from BMS/Pfizer and Novo Nordisk. LF: 
      Supported by a grant from Health Research Fund of Central Denmark Region. 
      Consultant for BMS and Pfizer.
EDAT- 2023/01/14 06:00
MHDA- 2023/01/18 06:00
PMCR- 2023/01/13
CRDT- 2023/01/13 21:02
PHST- 2022/10/09 00:00 [received]
PHST- 2023/01/04 00:00 [accepted]
PHST- 2023/01/13 21:02 [entrez]
PHST- 2023/01/14 06:00 [pubmed]
PHST- 2023/01/18 06:00 [medline]
PHST- 2023/01/13 00:00 [pmc-release]
AID - openhrt-2022-002169 [pii]
AID - 10.1136/openhrt-2022-002169 [doi]
PST - ppublish
SO  - Open Heart. 2023 Jan;10(1):e002169. doi: 10.1136/openhrt-2022-002169.