A Validated Model for Sudden Cardiac Death Risk Prediction in Pediatric Hypertrophic Cardiomyopathy.
cardiomyopathies
cardiomyopathy, hypertrophic
death, sudden, heart
defibrillators, implantable
hypertrophy
pediatrics
Journal
Circulation
ISSN: 1524-4539
Titre abrégé: Circulation
Pays: United States
ID NLM: 0147763
Informations de publication
Date de publication:
21 07 2020
21 07 2020
Historique:
pubmed:
19
5
2020
medline:
31
8
2021
entrez:
19
5
2020
Statut:
ppublish
Résumé
Hypertrophic cardiomyopathy is the leading cause of sudden cardiac death (SCD) in children and young adults. Our objective was to develop and validate a SCD risk prediction model in pediatric hypertrophic cardiomyopathy to guide SCD prevention strategies. In an international multicenter observational cohort study, phenotype-positive patients with isolated hypertrophic cardiomyopathy <18 years of age at diagnosis were eligible. The primary outcome variable was the time from diagnosis to a composite of SCD events at 5-year follow-up: SCD, resuscitated sudden cardiac arrest, and aborted SCD, that is, appropriate shock following primary prevention implantable cardioverter defibrillators. Competing risk models with cause-specific hazard regression were used to identify and quantify clinical and genetic factors associated with SCD. The cause-specific regression model was implemented using boosting, and tuned with 10 repeated 4-fold cross-validations. The final model was fitted using all data with the tuned hyperparameter value that maximizes the c-statistic, and its performance was characterized by using the c-statistic for competing risk models. The final model was validated in an independent external cohort (SHaRe [Sarcomeric Human Cardiomyopathy Registry], n=285). Overall, 572 patients met eligibility criteria with 2855 patient-years of follow-up. The 5-year cumulative proportion of SCD events was 9.1% (14 SCD, 25 resuscitated sudden cardiac arrests, and 14 aborted SCD). Risk predictors included age at diagnosis, documented nonsustained ventricular tachycardia, unexplained syncope, septal diameter Our study provides a validated SCD risk prediction model with >70% prediction accuracy and incorporates risk factors that are unique to pediatric hypertrophic cardiomyopathy. An individualized risk prediction model has the potential to improve the application of clinical practice guidelines and shared decision making for implantable cardioverter defibrillator insertion. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT0403679.
Sections du résumé
BACKGROUND
Hypertrophic cardiomyopathy is the leading cause of sudden cardiac death (SCD) in children and young adults. Our objective was to develop and validate a SCD risk prediction model in pediatric hypertrophic cardiomyopathy to guide SCD prevention strategies.
METHODS
In an international multicenter observational cohort study, phenotype-positive patients with isolated hypertrophic cardiomyopathy <18 years of age at diagnosis were eligible. The primary outcome variable was the time from diagnosis to a composite of SCD events at 5-year follow-up: SCD, resuscitated sudden cardiac arrest, and aborted SCD, that is, appropriate shock following primary prevention implantable cardioverter defibrillators. Competing risk models with cause-specific hazard regression were used to identify and quantify clinical and genetic factors associated with SCD. The cause-specific regression model was implemented using boosting, and tuned with 10 repeated 4-fold cross-validations. The final model was fitted using all data with the tuned hyperparameter value that maximizes the c-statistic, and its performance was characterized by using the c-statistic for competing risk models. The final model was validated in an independent external cohort (SHaRe [Sarcomeric Human Cardiomyopathy Registry], n=285).
RESULTS
Overall, 572 patients met eligibility criteria with 2855 patient-years of follow-up. The 5-year cumulative proportion of SCD events was 9.1% (14 SCD, 25 resuscitated sudden cardiac arrests, and 14 aborted SCD). Risk predictors included age at diagnosis, documented nonsustained ventricular tachycardia, unexplained syncope, septal diameter
CONCLUSION
Our study provides a validated SCD risk prediction model with >70% prediction accuracy and incorporates risk factors that are unique to pediatric hypertrophic cardiomyopathy. An individualized risk prediction model has the potential to improve the application of clinical practice guidelines and shared decision making for implantable cardioverter defibrillator insertion. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT0403679.
Identifiants
pubmed: 32418493
doi: 10.1161/CIRCULATIONAHA.120.047235
pmc: PMC7365676
doi:
Banques de données
ClinicalTrials.gov
['NCT04036799']
Types de publication
Journal Article
Multicenter Study
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
217-229Commentaires et corrections
Type : CommentIn
Type : CommentIn
Références
Heart. 2019 Apr;105(8):623-631
pubmed: 30366935
Am J Cardiol. 2018 Feb 1;121(3):349-355
pubmed: 29203036
Heart. 2013 Apr;99(8):534-41
pubmed: 23339826
Circulation. 2018 Jul 3;138(1):29-36
pubmed: 29490994
Heart Rhythm. 2019 Oct;16(10):1462-1467
pubmed: 31026510
JAMA Cardiol. 2018 Jun 1;3(6):520-525
pubmed: 29710196
Heart. 2019 Dec;105(24):1850-1851
pubmed: 31551293
JAMA Cardiol. 2019 Jul 1;4(7):644-657
pubmed: 31116360
Heart. 2007 Mar;93(3):372-4
pubmed: 16940391
Eur Heart J. 2017 Jun 7;38(22):1728-1737
pubmed: 27371714
J Am Coll Cardiol. 2015 May 12;65(18):1915-28
pubmed: 25953744
Prog Pediatr Cardiol. 2018 Jun;49:31-37
pubmed: 31097901
J Am Coll Cardiol. 2013 Apr 9;61(14):1527-35
pubmed: 23500286
Acta Cardiol. 2010 Oct;65(5):521-5
pubmed: 21125973
Circulation. 2018 Mar 6;137(10):1015-1023
pubmed: 29191938
Circ Arrhythm Electrophysiol. 2014 Dec;7(6):1057-63
pubmed: 25262116
Genet Med. 2015 May;17(5):405-24
pubmed: 25741868
Can J Cardiol. 2019 Dec;35(12):1626-1628
pubmed: 31703825
BMC Med Res Methodol. 2007 Jul 13;7:33
pubmed: 17629912
Circulation. 2008 Oct 28;118(18):1854-63
pubmed: 18955676
J Am Coll Cardiol. 2015 Mar 31;65(12):1249-1254
pubmed: 25814232
J Clin Med. 2017 Dec 12;6(12):
pubmed: 29231893
Europace. 2019 Oct 1;21(10):1559-1565
pubmed: 31155643
Circulation. 1995 Aug 15;92(4):785-9
pubmed: 7641357
Circulation. 2018 Oct 2;138(14):1387-1398
pubmed: 30297972
J Am Coll Cardiol. 2008 Apr 29;51(17):1685-91
pubmed: 18436121
Europace. 2019 Jan 01;21(1):106-113
pubmed: 30339209
Eur Heart J. 2014 Aug 7;35(30):2010-20
pubmed: 24126876
JAMA Cardiol. 2019 Sep 1;4(9):918-927
pubmed: 31411652
Arq Bras Cardiol. 2019 Mar;112(3):281-289
pubmed: 30916191
Open Heart. 2019 Jun 27;6(1):e000963
pubmed: 31328003
Circ Cardiovasc Genet. 2009 Oct;2(5):436-41
pubmed: 20031618
Clin Genet. 2018 Feb;93(2):310-319
pubmed: 29053178
JAMA. 2007 Jul 25;298(4):405-12
pubmed: 17652294
Circ Cardiovasc Genet. 2009 Apr;2(2):182-90
pubmed: 20031583
J Am Coll Cardiol. 2016 Dec 27;68(25):2871-2886
pubmed: 28007147
Biostatistics. 2014 Jul;15(3):526-39
pubmed: 24493091
J Am Coll Cardiol. 2011 Dec 13;58(25):e212-60
pubmed: 22075469
Cardiol Clin. 2019 Feb;37(1):63-72
pubmed: 30447717
Circ Arrhythm Electrophysiol. 2018 Apr;11(4):e005820
pubmed: 29625970
Arrhythm Electrophysiol Rev. 2016;5(3):188-196
pubmed: 28116084