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1.
Genet Med ; 17(4): 319, 2015 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-25835197

RESUMO

Genet Med advance online publication, January 22, 2015; doi:10.1038/gim.2014.205. In the Advance Online Publication version, of this article, there is a mistake on page 2 in the first paragraph of the Materials and Methods section. The sentence beginning "Among 3,459 probands initially referred for HCM genetic testing …" the correct number of probands is 3,473 not 3,459. The authors regret the error.

2.
Genet Med ; 17(11): 880-8, 2015 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-25611685

RESUMO

PURPOSE: Hypertrophic cardiomyopathy (HCM) is caused primarily by pathogenic variants in genes encoding sarcomere proteins. We report genetic testing results for HCM in 2,912 unrelated individuals with nonsyndromic presentations from a broad referral population over 10 years. METHODS: Genetic testing was performed by Sanger sequencing for 10 genes from 2004 to 2007, by HCM CardioChip for 11 genes from 2007 to 2011 and by next-generation sequencing for 18, 46, or 51 genes from 2011 onward. RESULTS: The detection rate is ~32% among unselected probands, with inconclusive results in an additional 15%. Detection rates were not significantly different between adult and pediatric probands but were higher in females compared with males. An expanded gene panel encompassing more than 50 genes identified only a very small number of additional pathogenic variants beyond those identifiable in our original panels, which examined 11 genes. Familial genetic testing in at-risk family members eliminated the need for longitudinal cardiac evaluations in 691 individuals. Based on the projected costs derived from Medicare fee schedules for the recommended clinical evaluations of HCM family members by the American College of Cardiology Foundation/American Heart Association, our data indicate that genetic testing resulted in a minimum cost savings of about $0.7 million. CONCLUSION: Clinical HCM genetic testing provides a definitive molecular diagnosis for many patients and provides cost savings to families. Expanded gene panels have not substantively increased the clinical sensitivity of HCM testing, suggesting major additional causes of HCM still remain to be identified.


Assuntos
Cardiomiopatia Hipertrófica/diagnóstico , Cardiomiopatia Hipertrófica/genética , Testes Genéticos , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Cardiomiopatia Hipertrófica/epidemiologia , Criança , Pré-Escolar , Custos e Análise de Custo , Feminino , Predisposição Genética para Doença , Testes Genéticos/economia , Testes Genéticos/métodos , Testes Genéticos/normas , Variação Genética , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Masculino , Pessoa de Meia-Idade , Análise de Sequência com Séries de Oligonucleotídeos/economia , Análise de Sequência com Séries de Oligonucleotídeos/métodos , Análise de Sequência com Séries de Oligonucleotídeos/normas , Sensibilidade e Especificidade , Adulto Jovem
3.
Genet Med ; 14(8): 713-719, 2012.
Artigo em Inglês | MEDLINE | ID: mdl-22481129

RESUMO

Genetic tests often identify variants whose significance cannot be determined at the time they are reported. In many situations, it is critical that clinicians be informed when new information emerges on these variants. It is already extremely challenging for laboratories to provide these updates. These challenges will grow rapidly as an increasing number of clinical genetic tests are ordered and as the amount of patient DNA assayed per test expands; the challenges will need to be addressed before whole-genome sequencing is used on a widespread basis.Information technology infrastructure can be useful in this context. We have deployed an infrastructure enabling clinicians to receive knowledge updates when a laboratory changes the classification of a variant. We have gathered statistics from this deployment regarding the frequency of both variant classification changes and the effects of these classification changes on patients. We report on the system's functionality as well as the statistics derived from its use.Genet Med advance online publication 5 April 2012.

4.
Hum Mutat ; 32(5): 532-6, 2011 May.
Artigo em Inglês | MEDLINE | ID: mdl-21432942

RESUMO

The future of personalized medicine will hinge on effective management of patient genetic profiles. Molecular diagnostic testing laboratories need to track knowledge surrounding an increasingly large number of genetic variants, incorporate this knowledge into interpretative reports, and keep ordering clinicians up to date as this knowledge evolves. Treating clinicians need to track which variants have been identified in each of their patients along with the significance of these variants. The GeneInsight(SM) Suite assists in these areas. The suite also provides a basis for interconnecting laboratories and clinicians in a manner that increases the scalability of personalized medicine processes.


Assuntos
Testes Genéticos/métodos , Técnicas de Diagnóstico Molecular/métodos , Software , Sistemas Inteligentes , Variação Genética , Humanos , Bases de Conhecimento , Medicina de Precisão/métodos
5.
J Am Med Inform Assoc ; 21(e1): e117-21, 2014 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-24013137

RESUMO

OBJECTIVES: To understand the impact of GeneInsight Clinic (GIC), a web-based tool designed to manage genetic information and facilitate communication of test results and variant updates from the laboratory to the clinics, we measured the use of GIC and the time it took for new genetic knowledge to be available to clinicians. METHODS: Usage data were collected across four study sites for the GIC launch and post-GIC implementation time periods. The primary outcome measures were the time (average number of days) between variant change approval and notification of clinic staff, and the time between notification and viewing the patient record. RESULTS: Post-GIC, time between a variant change approval and provider notification was shorter than at launch (average days at launch 503.8, compared to 4.1 days post-GIC). After e-mail alerts were sent at launch, providers clicked into the patient record associated with 91% of these alerts. In the post period, clinic providers clicked into the patient record associated with 95% of the alerts, on average 12 days after the e-mail was sent. DISCUSSION: We found that GIC greatly increased the likelihood that a provider would receive updated variant information as well as reduced the time associated with distributing that variant information, thus providing a more efficient process for incorporating new genetic knowledge into clinical care. CONCLUSIONS: Our study results demonstrate that health information technology systems have the potential effectively to assist providers in utilizing genetic information in patient care.


Assuntos
Comunicação , Testes Genéticos , Internet , Correio Eletrônico , Humanos , Fatores de Tempo
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