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Adriana Lopez-Pineda
Researcher at Universidad Miguel Hernández de Elche
Publications - 68
Citations - 777
Adriana Lopez-Pineda is an academic researcher from Universidad Miguel Hernández de Elche. The author has contributed to research in topics: Medicine & Population. The author has an hindex of 11, co-authored 50 publications receiving 420 citations.
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Journal ArticleDOI
Maternal periodontitis and preterm birth: Systematic review and meta-analysis.
Edwar J. Manrique‐Corredor,Domingo Orozco-Beltrán,Adriana Lopez-Pineda,Jose A. Quesada,Vicente Francisco Gil-Guillén,Concepción Carratalá-Munuera +5 more
TL;DR: Pregnant mothers with periodontitis double the risk of preterm birth and there is a lack of international consensus for diagnosing maternalperiodontitis.
Journal ArticleDOI
Inappropriate Use of Medication by Elderly, Polymedicated, or Multipathological Patients with Chronic Diseases.
Virtudes Pérez-Jover,José Joaquín Mira,Concepción Carratalá-Munuera,Vicente Francisco Gil-Guillén,Josep Basora,Adriana Lopez-Pineda,Domingo Orozco-Beltrán +6 more
TL;DR: A literature review found that half of patients know what their prescribed treatment is, that most of elderly people take five or more medications a day, and that in elderly, polymedicated people, the probability of a medication error occurring is higher, so strategies based on the evidence should be applied in order to reduce medication errors.
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Trends in respiratory syncytial virus bronchiolitis hospitalizations in children less than 1 year: 2004-2012.
Manuel Sánchez-Luna,Francisco J. Elola,Cristina Fernández-Pérez,José L. Bernal,Adriana Lopez-Pineda +4 more
TL;DR: RSV bronchiolitis is a leading cause of hospitalizations for infants under 1 year and has not shown incidence reduction over a 9 year period.
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Machine learning to predict cardiovascular risk.
Jose A. Quesada,Adriana Lopez-Pineda,Vicente Francisco Gil-Guillén,Ramon Durazo-Arvizu,Domingo Orozco-Beltrán,Angela Lopez-Domenech,Concepción Carratalá-Munuera +6 more
TL;DR: To analyse the predictive capacity of 15 machine learning methods for estimating cardiovascular risk in a cohort and to compare them with other risk scales, a large number of methods were used.
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Incubation period of COVID-19: A systematic review and meta-analysis
Jose A. Quesada,Adriana Lopez-Pineda,Vicente Francisco Gil-Guillén,J.M. Arriero-Marín,Félix Gutiérrez,Concepción Carratalá-Munuera +5 more
TL;DR: Based on the published data reporting the incubation period of COVID-19, the mean time between exposure and onset of clinical symptoms depended on the statistical model used, and the 95th percentile depended onThe mean age of the patients.