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1.
J Asthma ; 57(12): 1316-1322, 2020 12.
Artículo en Inglés | MEDLINE | ID: mdl-31340703

RESUMEN

Objectives: The aim of this exploratory study was to assess the impact of caregiver health literacy (HL) on health care outcomes for their child with asthma.Methods: Caregiver dyads across two different healthcare delivery systems completed a battery of validated asthma outcome instruments, including the Newest Vital Sign™ as a measure of HL for the caregivers of children ages 7-18 y. Utilization history was obtained through the electronic medical record. Descriptive analysis with bivariate associations was conducted.Results: There was no direct relationship between HL and asthma outcomes in the 34 Hispanic and African American caregiver-child dyads. However, caregiver health literacy was significantly related to language (p = 0.02). African American English-speaking caregivers, seen in an urban emergency department, demonstrated adequate health literacy. Hispanic Spanish-speaking caregivers, seeking care in a mobile asthma van, showed limited health literacy. There was no significant association between caregivers' HL and routine asthma care visits when language and child age were controlled.Conclusions: Assessing patient factors can identify persons at risk who need additional support to negotiate the healthcare system when providing care for a child with asthma.


Asunto(s)
Asma/tratamiento farmacológico , Cuidadores/estadística & datos numéricos , Alfabetización en Salud/estadística & datos numéricos , Grupos Minoritarios/estadística & datos numéricos , Aceptación de la Atención de Salud/estadística & datos numéricos , Adolescente , Antiasmáticos/uso terapéutico , Asma/diagnóstico , Cuidadores/educación , Niño , Estudios Transversales , Escolaridad , Registros Electrónicos de Salud/estadística & datos numéricos , Femenino , Humanos , Masculino , Pobreza/estadística & datos numéricos , Medición de Riesgo/métodos , Resultado del Tratamiento
2.
Ann Allergy Asthma Immunol ; 123(2): 193-200, 2019 08.
Artículo en Inglés | MEDLINE | ID: mdl-31108180

RESUMEN

BACKGROUND: Despite potential value of identification of allergic inflammation with fractional exhaled nitric oxide (FeNO) in managing asthma, randomized clinical trials have not consistently shown better outcomes compared with guideline management alone. OBJECTIVE: To assess the effectiveness of FeNO vs non-FeNO-based therapeutic algorithms in managing asthma, and the phenotypic profile associated with FeNO >35 ppb yet well controlled by guidelines, as a potential model to predict better FeNO-based algorithm outcomes. METHODS: This is a randomized controlled study (RCT) in 88 high-risk children with asthma 7 to 18 years of age across 352 visits over a 1-year period. Generalized estimating equations analysis assessed algorithm group differences in outcomes and characteristics associated with higher odds uncontrolled by FeNO alone in the treatment decision algorithm. RESULTS: The FeNO treatment algorithm did not show superiority in reducing exacerbations and morbidity (P > .05). Phenotypes that more than doubled the odds FeNO alone identified uncontrolled asthma included adolescence, non-adherence, high atopy (>6+), and baseline FeNO >35 ppb, whereas obesity, FEF25-75% < 65% predicted, and bronchodilator response >10% decreased the odds. Uncontrolled asthma by FeNO alone (F) vs guidelines alone (G) showed overall F/G > 1.0 in adolescents, but <1.0 in younger patients unless the FeNO threshold was reduced to >20 ppb. CONCLUSION: Our study suggests that age and phenotypes play a key role in FeNO discordance compared with the conventional guideline-based uncontrolled asthma. The FeNO-based therapeutic algorithm, if confirmed further, could provide the clinician with an effective asthma management tool. The clinical implication could improve future FeNO-based RCTs and treatment decision algorithms in managing asthma by considering phenotypes and age-dependent FeNO thresholds.


Asunto(s)
Asma/diagnóstico , Pruebas Respiratorias/métodos , Óxido Nítrico/análisis , Adolescente , Factores de Edad , Algoritmos , Niño , Espiración , Femenino , Humanos , Masculino
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