0000000000677177

AUTHOR

Pablo Rodríguez-belenguer

showing 3 related works from this author

SARS-CoV-2 vaccine response and rate of breakthrough infection in patients with hematological disorders

2022

Abstract Background The clinical efficacy of SARS-CoV-2 vaccines according to antibody response in immunosuppressed patients such as hematological patients has not yet been established. Patients and methods A prospective multicenter registry-based cohort study conducted from December 2020 to December 2021 by the Spanish transplant and cell therapy group was used to analyze the relationship of antibody response at 3–6 weeks after full vaccination (2 doses) with breakthrough SARS-CoV-2 infection in 1394 patients with hematological disorders. Results At a median follow-up of 165 days after complete immunization, 37 out of 1394 (2.6%) developed breakthrough SARS-CoV-2 infection at median of 77 …

*Pfizer-BioNTech BNT162b2Cancer ResearchCOVID-19 Vaccines*Hematological malignanciesAutologous stem cell transplantationAntibodies ViralBreakthrough SARS-CoV-2 infectionModerna mRNA-1273Cohort StudiesHematological malignancies*Moderna mRNA-1273Correlates of protection*VaccineHumansProspective StudiesVacunacióPfizer-BioNTech BNT162b2Molecular BiologyBNT162 Vaccine*Immunocompromised patients*Correlates of protectionSARS-CoV-2VaccinationHematologic diseasesCOVID-19Hematology*Breakthrough SARS-CoV-2 infectionHematologic DiseasesSARS-CoV-2 vaccinesAllogeneic stem cell transplantationVirusOncologyMalalties hematològiquesImmunocompromised patients*SARS-CoV-2 vaccines*Autologous stem cell transplantation*COVID-19Vaccine*Allogeneic stem cell transplantationJournal of Hematology & Oncology
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Machine learning for mortality analysis in patients with COVID-19

2020

This paper analyzes a sample of patients hospitalized with COVID-19 in the region of Madrid (Spain). Survival analysis, logistic regression, and machine learning techniques (both supervised and unsupervised) are applied to carry out the analysis where the endpoint variable is the reason for hospital discharge (home or deceased). The different methods applied show the importance of variables such as age, O2 saturation at Emergency Rooms (ER), and whether the patient comes from a nursing home. In addition, biclustering is used to globally analyze the patient-drug dataset, extracting segments of patients. We highlight the validity of the classifiers developed to predict the mortality, reaching…

feature importanceComputer scienceHealth Toxicology and MutagenesisPneumonia ViralDecision treelcsh:MedicineSample (statistics)Machine learningcomputer.software_genreLogistic regressionArticlesurvival analysisBiclustering03 medical and health sciencesBetacoronavirus0302 clinical medicineMachine learningRisk of mortalitygraphical modelsHumans030212 general & internal medicineGraphical modelPandemicsSurvival analysisInformática0303 health sciences030306 microbiologybusiness.industrySARS-CoV-2Decision Treeslcsh:RPublic Health Environmental and Occupational HealthCOVID-19Decision ruleSurvival analysisFeature importancemachine learningSpainArtificial intelligenceGraphical modelsbusinessCoronavirus Infectionscomputer
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Additional file 1 of SARS-CoV-2 vaccine response and rate of breakthrough infection in patients with hematological disorders

2022

Additional file 1: Table S1. Characteristics of serological assays used in the study. Table S2. Commercial PCR test available in participating centers.

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