Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 2 de 2
Filtrar
Mais filtros

Base de dados
Ano de publicação
Tipo de documento
Intervalo de ano de publicação
1.
J Cardiothorac Vasc Anesth ; 37(8): 1487-1494, 2023 08.
Artigo em Inglês | MEDLINE | ID: mdl-37120321

RESUMO

TACROLIMUS, a mainstay of immunosuppression after orthotopic heart transplantation (OHT), is associated with a broad range of side effects. Vasoconstriction caused by tacrolimus has been proposed as a mechanism underlying common side effects such as hypertension and renal injury. Neurologic side effects attributed to tacrolimus include headaches, posterior reversible encephalopathy syndrome (PRES), or reversible cerebral vasospasm syndrome (RCVS). Six case reports have been published describing RCVS in the setting of tacrolimus administration after OHT. The authors report a case of perfusion-dependent focal neurologic deficits attributed to tacrolimus-induced RCVS in an OHT recipient.


Assuntos
Transplante de Coração , Síndrome da Leucoencefalopatia Posterior , Vasoespasmo Intracraniano , Humanos , Tacrolimo/efeitos adversos , Vasoespasmo Intracraniano/induzido quimicamente , Vasoespasmo Intracraniano/diagnóstico por imagem , Síndrome da Leucoencefalopatia Posterior/induzido quimicamente , Síndrome da Leucoencefalopatia Posterior/diagnóstico por imagem , Estado Terminal , Perfusão/efeitos adversos , Transplante de Coração/efeitos adversos
2.
J Med Internet Res ; 24(4): e33537, 2022 04 14.
Artigo em Inglês | MEDLINE | ID: mdl-35436221

RESUMO

BACKGROUND: Suboptimal adherence to data collection procedures or a study intervention is often the cause of a failed clinical trial. Data from connected sensors, including wearables, referred to here as biometric monitoring technologies (BioMeTs), are capable of capturing adherence to both digital therapeutics and digital data collection procedures, thereby providing the opportunity to identify the determinants of adherence and thereafter, methods to maximize adherence. OBJECTIVE: We aim to describe the methods and definitions by which adherence has been captured and reported using BioMeTs in recent years. Identifying key gaps allowed us to make recommendations regarding minimum reporting requirements and consistency of definitions for BioMeT-based adherence data. METHODS: We conducted a systematic review of studies published between 2014 and 2019, which deployed a BioMeT outside the clinical or laboratory setting for which a quantitative, nonsurrogate, sensor-based measurement of adherence was reported. After systematically screening the manuscripts for eligibility, we extracted details regarding study design, participants, the BioMeT or BioMeTs used, and the definition and units of adherence. The primary definitions of adherence were categorized as a continuous variable based on duration (highest resolution), a continuous variable based on the number of measurements completed, or a categorical variable (lowest resolution). RESULTS: Our PubMed search terms identified 940 manuscripts; 100 (10.6%) met our eligibility criteria and contained descriptions of 110 BioMeTs. During literature screening, we found that 30% (53/177) of the studies that used a BioMeT outside of the clinical or laboratory setting failed to report a sensor-based, nonsurrogate, quantitative measurement of adherence. We identified 37 unique definitions of adherence reported for the 110 BioMeTs and observed that uniformity of adherence definitions was associated with the resolution of the data reported. When adherence was reported as a continuous time-based variable, the same definition of adherence was adopted for 92% (46/50) of the tools. However, when adherence data were simplified to a categorical variable, we observed 25 unique definitions of adherence reported for 37 tools. CONCLUSIONS: We recommend that quantitative, nonsurrogate, sensor-based adherence data be reported for all BioMeTs when feasible; a clear description of the sensor or sensors used to capture adherence data, the algorithm or algorithms that convert sample-level measurements to a metric of adherence, and the analytic validation data demonstrating that BioMeT-generated adherence is an accurate and reliable measurement of actual use be provided when available; and primary adherence data be reported as a continuous variable followed by categorical definitions if needed, and that the categories adopted are supported by clinical validation data and/or consistent with previous reports.


Assuntos
Biometria , Cimetidina , Biometria/métodos , Coleta de Dados , Humanos , Projetos de Pesquisa , Tecnologia
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA