Implementing Vancomycin Population Pharmacokinetic Models: An App for Individualized Antibiotic Therapy in Critically Ill Patients
13 páginas
- Autores:
-
Mena, Manuel
Garcia, Julio Cesar
Bustos, Rosa Helena
- Tipo de recurso:
- Trabajo de grado de pregrado
- Fecha de publicación:
- 2023
- Institución:
- Universidad de la Sabana
- Repositorio:
- Repositorio Universidad de la Sabana
- Idioma:
- eng
- OAI Identifier:
- oai:intellectum.unisabana.edu.co:10818/59036
- Acceso en línea:
- https://hdl.handle.net/10818/59036
- Palabra clave:
- Vancomycin
Bayesian prediction
Population pharmacokinetics
Personalized dosing
Individualized therapy
Critical ill patients
Therapeutic drug management
Shiny application
- Rights
- License
- Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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Implementing Vancomycin Population Pharmacokinetic Models: An App for Individualized Antibiotic Therapy in Critically Ill Patients |
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Implementing Vancomycin Population Pharmacokinetic Models: An App for Individualized Antibiotic Therapy in Critically Ill Patients |
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Implementing Vancomycin Population Pharmacokinetic Models: An App for Individualized Antibiotic Therapy in Critically Ill Patients Vancomycin Bayesian prediction Population pharmacokinetics Personalized dosing Individualized therapy Critical ill patients Therapeutic drug management Shiny application |
| title_short |
Implementing Vancomycin Population Pharmacokinetic Models: An App for Individualized Antibiotic Therapy in Critically Ill Patients |
| title_full |
Implementing Vancomycin Population Pharmacokinetic Models: An App for Individualized Antibiotic Therapy in Critically Ill Patients |
| title_fullStr |
Implementing Vancomycin Population Pharmacokinetic Models: An App for Individualized Antibiotic Therapy in Critically Ill Patients |
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Implementing Vancomycin Population Pharmacokinetic Models: An App for Individualized Antibiotic Therapy in Critically Ill Patients |
| title_sort |
Implementing Vancomycin Population Pharmacokinetic Models: An App for Individualized Antibiotic Therapy in Critically Ill Patients |
| dc.creator.fl_str_mv |
Mena, Manuel Garcia, Julio Cesar Bustos, Rosa Helena |
| dc.contributor.author.none.fl_str_mv |
Mena, Manuel Garcia, Julio Cesar Bustos, Rosa Helena |
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Vancomycin Bayesian prediction Population pharmacokinetics Personalized dosing Individualized therapy Critical ill patients Therapeutic drug management Shiny application |
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Vancomycin Bayesian prediction Population pharmacokinetics Personalized dosing Individualized therapy Critical ill patients Therapeutic drug management Shiny application |
| description |
13 páginas |
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2023 |
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2023-08-09 |
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2024-01-12T13:17:10Z |
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2024-01-12T13:17:10Z |
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Tesis/Trabajo de grado - Especialización |
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10.3390/antibiotics12020301 |
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eng |
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Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
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Mena, ManuelGarcia, Julio CesarBustos, Rosa Helena2024-01-12T13:17:10Z2024-01-12T13:17:10Z2023-08-09https://hdl.handle.net/10818/5903610.3390/antibiotics1202030113 páginasIn individualized therapy, the Bayesian approach integrated with population pharmacokinetic models (PopPK) for predictions together with therapeutic drug monitoring (TDM) to maintain adequate objectives is useful to maximize the efficacy and minimize the probability of toxicity of vancomycin in critically ill patients. Although there are limitations to implementation, model-informed precision dosing (MIPD) is an approach to integrate these elements, which has the potential to optimize the TDM process and maximize the success of antibacterial therapy. The objective of this work was to present an app for individualized therapy and perform a validation of the implemented vancomycin PopPK models. A pragmatic approach was used for selecting the models of Llopis, Goti and Revilla for developing a Shiny app with R. Through ordinary differential equation (ODE)-based mixed effects models from the mlxR package, the app simulates the concentrations¿ behavior, estimates whether the model was simulated without variability and predicts whether the model was simulated with variability. Moreover, we evaluated the predictive performance with retrospective trough concentration data from patients admitted to the adult critical care unit. Although there were no significant differences in the performance of the estimates, the Llopis model showed better accuracy (mean 80.88%; SD 46.5%); however, it had greater bias (mean ¿34.47%, SD 63.38%) compared to the Revilla et al. (mean 10.61%, SD 66.37%) and Goti et al. (mean of 13.54%, SD 64.93%) models. With respect to the RMSE (root mean square error), the Llopis (mean of 10.69 mg/L, SD 12.23 mg/L) and Revilla models (mean of 10.65 mg/L, SD 12.81 mg/L) were comparable, and the lowest RMSE was found in the Goti model (mean 9.06 mg/L, SD 9 mg/L). Regarding the predictions, this behavior did not change, and the results varied relatively little. Although our results are satisfactory, the predictive performance in recent studies with vancomycin is heterogeneous, and although these three models have proven to be useful for clinical application, further research and adaptation of PopPK models is required, as well as implementation in the clinical practice of MIPD and TDM in real time.application/pdfengUniversidad de La SabanaAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/http://purl.org/coar/access_right/c_abf2VancomycinBayesian predictionPopulation pharmacokineticsPersonalized dosingIndividualized therapyCritical ill patientsTherapeutic drug managementShiny applicationImplementing Vancomycin Population Pharmacokinetic Models: An App for Individualized Antibiotic Therapy in Critically Ill PatientsTesis/Trabajo de grado - Especializaciónhttp://purl.org/coar/resource_type/c_7a1fTextoinfo:eu-repo/semantics/otherhttp://purl.org/redcol/resource_type/COtherinfo:eu-repo/semantics/acceptedVersionFacultad de MedicinaEspecialización en Farmacología ClínicaEspecialista en Farmacología ClínicaPublicationTEXTantibiotics-12-00301.pdf.txtantibiotics-12-00301.pdf.txtExtracted texttext/plain59470https://intellectum.unisabana.edu.co/bitstreams/36229f16-a50e-4a94-a1ec-b067b2e721f3/download5cccefcf0713eb3d340d73426ef74fdcMD55falseAnonymousREADORIGINALantibiotics-12-00301.pdfantibiotics-12-00301.pdfVer documento en PDFapplication/pdf1536463https://intellectum.unisabana.edu.co/bitstreams/36122a8e-352d-4d1d-86e3-13a25b711af4/download3e7ccdbaaf3d049f24158a88625e97c4MD51trueAnonymousREADCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805https://intellectum.unisabana.edu.co/bitstreams/c9e9bb99-08c5-4aef-b531-096216bf2915/download4460e5956bc1d1639be9ae6146a50347MD52falseAnonymousREADLICENSElicense.txtlicense.txttext/plain; charset=utf-8498https://intellectum.unisabana.edu.co/bitstreams/334a9053-a9a7-4a06-b53a-375246f45f25/downloadf52a2cfd4df262e08e9b300d62c85cabMD53falseAnonymousREADFormato de autorizacion de divulgacion RI trabajos de grado V2bk.pdfFormato de autorizacion de divulgacion RI trabajos de grado V2bk.pdfCartaapplication/pdf199072https://intellectum.unisabana.edu.co/bitstreams/af1cf558-5766-4f89-b2c7-6b3283ea27dc/download071f248a8bcce69d838bbe9532d93085MD54falseAdministratorREADTHUMBNAILantibiotics-12-00301.pdf.jpgantibiotics-12-00301.pdf.jpgGenerated Thumbnailimage/jpeg15727https://intellectum.unisabana.edu.co/bitstreams/add058e9-ef23-44b6-98db-fc91ccf7a47d/downloadee6e127086d694ae18df9fd1c8c49807MD56falseAnonymousREAD10818/59036oai:intellectum.unisabana.edu.co:10818/590362025-12-11 13:16:46.318http://creativecommons.org/licenses/by-nc-nd/4.0/Attribution-NonCommercial-NoDerivatives 4.0 Internacionalopen.accesshttps://intellectum.unisabana.edu.coIntellectum Repositorio Universidad de La Sabanacontactointellectum@unisabana.edu.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 |