dc.contributor
Institut Català de la Salut
dc.contributor
[Carpio JD] Department of Nephrology, Arnau de Vilanova University Hospital, 25198 Lleida, Spain. Departament de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain. Institute of Biomedical Research (IRBLleida), 25198 Lleida, Spain. [Marco MP, Martin ML] Department of Nephrology, Arnau de Vilanova University Hospital, 25198 Lleida, Spain. Institute of Biomedical Research (IRBLleida), 25198 Lleida, Spain. [Ramos N] Servei de Nefrologia, Vall d’Hebron Hospital Universitari, Barcelona, Spain. [de la Torre J] Servei de Nefrologia, Vall d’Hebron Hospital Universitari, Barcelona, Spain. Department of Nephrology, Althaia Foundation, 08243 Manresa, Spain. [Prat J] Servei d’Informàtica, Vall d’Hebron Hospital Universitari, Barcelona, Spain. Department of Development, Parc Salut Hospital, 08019 Barcelona, Spain. [Torres MJ, Nieto N] Servei d’Informàtica, Vall d’Hebron Hospital Universitari, Barcelona, Spain. Department of Information, Southern Metropolitan Territorial Management, 08028 Barcelona, Spain. [Montoro B] Servei de Farmàcia, Vall d’Hebron Hospital Universitari, Barcelona, Spain. [Segarra A] Department of Nephrology, Arnau de Vilanova University Hospital, 25198 Lleida, Spain. Servei de Nefrologia, Vall d’Hebron Hospital Universitari, Barcelona, Spain
dc.contributor
Vall d'Hebron Barcelona Hospital Campus
dc.contributor.author
Marco, Maria Paz
dc.contributor.author
Martin, Maria Luisa
dc.contributor.author
Torre McKinney, Judith de la
dc.contributor.author
Prat Dopazo, Joana
dc.contributor.author
Torres Francin, Maria Jesus
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Montoro Ronsano, J. Bruno
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Nieto, Nacho
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Segarra Medrano, Alfons
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Ramos Terrades, Natalia
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Del Carpio, Jacqueline
dc.date.accessioned
2025-10-24T10:42:40Z
dc.date.available
2025-10-24T10:42:40Z
dc.date.issued
2022-05-02T12:43:10Z
dc.date.issued
2022-05-02T12:43:10Z
dc.identifier
Carpio JD, Marco MP, Martin ML, Ramos N, de la Torre J, Prat J, et al. Development and Validation of a Model to Predict Severe Hospital-Acquired Acute Kidney Injury in Non-Critically Ill Patients. J Clin Med. 2021 Sep;10(17):3959.
dc.identifier
https://hdl.handle.net/11351/7432
dc.identifier
10.3390/jcm10173959
dc.identifier
000694293100001
dc.identifier.uri
https://hdl.handle.net/11351/7432
dc.description.abstract
Lesión renal aguda; Registros electrónicos de datos de salud; Adquirido en el hospital
dc.description.abstract
Lesió renal aguda; Registres electrònics de dades de salut; Adquirit a l'Hospital
dc.description.abstract
Acute kidney injury; Electronic health data records; Hospital-acquired
dc.description.abstract
Background. The current models developed to predict hospital-acquired AKI (HA-AKI) in non-critically ill fail to identify the patients at risk of severe HA-AKI stage 3. Objective. To develop and externally validate a model to predict the individual probability of developing HA-AKI stage 3 through the integration of electronic health databases. Methods. Study set: 165,893 non-critically ill hospitalized patients. Using stepwise logistic regression analyses, including demography, chronic comorbidities, and exposure to risk factors prior to AKI detection, we developed a multivariate model to predict HA-AKI stage 3. This model was then externally validated in 43,569 non-critical patients admitted to the validation center. Results. The incidence of HA-AKI stage 3 in the study set was 0.6%. Among chronic comorbidities, the highest odds ratios were conferred by ischemic heart disease, ischemic cerebrovascular disease, chronic congestive heart failure, chronic obstructive pulmonary disease, chronic kidney disease and liver disease. Among acute complications, the highest odd ratios were associated with acute respiratory failure, major surgery and exposure to nephrotoxic drugs. The model showed an AUC of 0.906 (95% CI 0.904 to 0.908), a sensitivity of 89.1 (95% CI 87.0–91.0) and a specificity of 80.5 (95% CI 80.2–80.7) to predict HA-AKI stage 3, but tended to overestimate the risk at low-risk categories with an adequate goodness-of-fit for all risk categories (Chi2: 16.4, p: 0.034). In the validation set, incidence of HA-AKI stage 3 was 0.62%. The model showed an AUC of 0.861 (95% CI 0.859–0.863), a sensitivity of 83.0 (95% CI 80.5–85.3) and a specificity of 76.5 (95% CI 76.2–76.8) to predict HA-AKI stage 3 with an adequate goodness of fit for all risk categories (Chi2: 15.42, p: 0.052). Conclusions. Our study provides a model that can be used in clinical practice to obtain an accurate dynamic assessment of the individual risk of HA-AKI stage 3 along the hospital stay period in non-critically ill patients.
dc.description.abstract
This research received no external funding.
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application/pdf
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application/pdf
dc.relation
Journal of Clinical Medicine;10(17)
dc.relation
https://doi.org/10.3390/jcm10173959
dc.rights
Attribution 4.0 International
dc.rights
http://creativecommons.org/licenses/by/4.0/
dc.rights
info:eu-repo/semantics/openAccess
dc.subject
Ronyons - Malalties - Diagnòstic
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Riscos per a la salut - Avaluació
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Ronyons - Malalties - Prognosi
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DISEASES::Male Urogenital Diseases::Urologic Diseases::Kidney Diseases::Renal Insufficiency::Acute Kidney Injury
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Other subheadings::Other subheadings::/diagnosis
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ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT::Investigative Techniques::Epidemiologic Methods::Statistics as Topic::Probability::Risk::Risk Assessment
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ENFERMEDADES::enfermedades urogenitales masculinas::enfermedades urológicas::enfermedades renales::insuficiencia renal::lesión renal aguda
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Otros calificadores::Otros calificadores::/diagnóstico
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TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS::técnicas de investigación::métodos epidemiológicos::estadística como asunto::probabilidad::riesgo::evaluación de riesgos
dc.title
Development and Validation of a Model to Predict Severe Hospital-Acquired Acute Kidney Injury in Non-Critically Ill Patients
dc.type
info:eu-repo/semantics/article
dc.type
info:eu-repo/semantics/publishedVersion
