Publicación Artículo científico (article). 2017

Construction, internal validation and implementation in a mobile application of a scoring system to predict nonadherence to proton pump inhibitors

r-FISABIO. Repositorio Institucional de Producción Científica
oai:fundanet.fisabio.san.gva.es:p3572
r-FISABIO. Repositorio Institucional de Producción Científica
  • Mares-García E
  • PALAZON A
  • Folgado-de la Rosa DM
  • Pereira-Expósito A
  • Martínez-Martín Á
  • Cortés-Castell E
  • GIL V
Background. Other studies have assessed nonadherence to proton pump inhibitors (PPIs), but none has developed a screening test for its detection. Objectives. To construct and internally validate a predictive model for nonadherence to PPIs. Methods. This prospective observational study with a one-month follow-up was carried out in 2013 in Spain, and included 302 patients with a prescription for PPIs. The primary variable was nonadherence to PPIs (pill count). Secondary variables were gender, age, antidepressants, type of PPI, non-guideline-recommended prescription (NGRP) of PPIs, and total number of drugs. With the secondary variables, a binary logistic regression model to predict nonadherence was constructed and adapted to a points system. The ROC curve, with its area (AUC), was calculated and the optimal cut-off point was established. The points system was internally validated through 1,000 bootstrap samples and implemented in a mobile application (Android). Results. The points system had three prognostic variables: total number of drugs, NGRP of PPIs, and antidepressants. The AUC was 0.87 (95% CI [0.83-0.91], p < 0.001). The test yielded a sensitivity of 0.80 (95% CI [0.70-0.87]) and a specificity of 0.82 (95% CI [0.76-0.87]). The three parameters were very similar in the bootstrap validation. Conclusions. A points system to predict nonadherence to PPIs has been constructed, internally validated and implemented in a mobile application. Provided similar results are obtained in external validation studies, we will have a screening tool to detect nonadherence to PPIs.
 
DOI: https://fundanet.fisabio.san.gva.es/publicaciones/ProdCientif/PublicacionFrw.aspx?id=3572
r-FISABIO. Repositorio Institucional de Producción Científica
oai:fundanet.fisabio.san.gva.es:p3572

HANDLE: https://fundanet.fisabio.san.gva.es/publicaciones/ProdCientif/PublicacionFrw.aspx?id=3572
r-FISABIO. Repositorio Institucional de Producción Científica
oai:fundanet.fisabio.san.gva.es:p3572
 
Ver en: https://fundanet.fisabio.san.gva.es/publicaciones/ProdCientif/PublicacionFrw.aspx?id=3572
r-FISABIO. Repositorio Institucional de Producción Científica
oai:fundanet.fisabio.san.gva.es:p3572