Developing A Model to Predict Major Bleeding Among Hospitalized Patients Undergoing Therapeutic Plasma Exchange

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorFaculdade de Medicina de São José do Rio Preto-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorDuke University School of Medicine-
Autor(es): dc.contributorUniversity of North Carolina-
Autor(es): dc.creatorSoares Ferreira Junior, Alexandre-
Autor(es): dc.creatorLessa, Morgana Pinheiro Maux-
Autor(es): dc.creatorSanborn, Kate-
Autor(es): dc.creatorGordee, Alexander-
Autor(es): dc.creatorKuchibhatla, Maragatha-
Autor(es): dc.creatorKarafin, Matthew S.-
Autor(es): dc.creatorOnwuemene, Oluwatoyosi A.-
Data de aceite: dc.date.accessioned2025-08-21T21:24:30Z-
Data de disponibilização: dc.date.available2025-08-21T21:24:30Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2025-04-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1002/jca.70013-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/306050-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/306050-
Descrição: dc.descriptionAlthough therapeutic plasma exchange (TPE) can be associated with bleeding, there are currently no known strategies to reliably predict bleeding risk. This study developed a TPE bleeding risk prediction model for hospitalized patients. To develop the prediction model, we undertook a secondary analysis of public use files from the Recipient Epidemiology and Donor Evaluation Study-III. First, we used a literature review to identify potential predictors. Second, we used Multiple Imputation by Chained Equations to impute variables with < 30% missing data. Third, we performed a 10-fold Cross-Validated Least Absolute Shrinkage and Selection Operator to optimize variable selection. Finally, we fitted a logistic regression model. The model identified 10 unique predictors and seven interactions. Among those with the highest odds ratios (OR) were the following: > 10 TPE procedures and antiplatelet agents (OR 3.26); nephrogenic systemic sclerosis (OR 3.15); and intensive care unit stay (OR 3.08). Among those with the lowest OR were the following: albumin-only TPE (OR 0.50); male sex (OR 0.82); and heart failure (OR 0.85). The model indicated an acceptable performance with a C-statistic of 0.71 (95% CI 0.699-0.717). A model to predict bleeding risk among hospitalized patients undergoing TPE identified key predictors and interactions. Although the model achieved acceptable performance, future studies are needed to validate and operationalize it.-
Descrição: dc.descriptionAmerican Society of Hematology-
Descrição: dc.descriptionDepartment of Medicine Faculdade de Medicina de São José do Rio Preto-
Descrição: dc.descriptionGeneral and Applied Biology Program Institute of Biosciences (IBB) Sao Paulo State University (UNESP)-
Descrição: dc.descriptionDuke Biostatistics Epidemiology and Research Design Core Duke University School of Medicine-
Descrição: dc.descriptionDepartment of Biostatistics and Bioinformatics Duke University School of Medicine-
Descrição: dc.descriptionDepartment of Pathology and Laboratory Medicine University of North Carolina, Chapel Hill-
Descrição: dc.descriptionDivision of Hematology Department of Medicine Duke University School of Medicine-
Descrição: dc.descriptionGeneral and Applied Biology Program Institute of Biosciences (IBB) Sao Paulo State University (UNESP)-
Formato: dc.formate70013-
Idioma: dc.languageen-
Relação: dc.relationJournal of clinical apheresis-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectadverse effect-
Palavras-chave: dc.subjectblood coagulation-
Palavras-chave: dc.subjectblood transfusion-
Palavras-chave: dc.subjecthemorrhage-
Palavras-chave: dc.subjecthemostasis-
Palavras-chave: dc.subjectplasmapheresis-
Palavras-chave: dc.subjecttransfusion medicine-
Título: dc.titleDeveloping A Model to Predict Major Bleeding Among Hospitalized Patients Undergoing Therapeutic Plasma Exchange-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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