دورية أكاديمية
A machine-learning model for reducing misdiagnosis in heparin-induced thrombocytopenia: A prospective, multicenter, observational study
| العنوان: | A machine-learning model for reducing misdiagnosis in heparin-induced thrombocytopenia: A prospective, multicenter, observational study |
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| المؤلفون: | Nilius, Henning, Cuker, Adam, Haug, Sigve, Nakas, Christos, Studt, Jan-Dirk, Tsakiris, Dimitrios A, Greinacher, Andreas, Mendez, Adriana, Schmidt, Adrian, Wuillemin, Walter A, Gerber, Bernhard, Kremer Hovinga, Johanna A, Vishnu, Prakash, Graf, Lukas, Kashev, Alexander, Sznitman, Raphael, Bakchoul, Tamam, Nagler, Michael |
| المصدر: | Nilius, Henning; Cuker, Adam; Haug, Sigve; Nakas, Christos; Studt, Jan-Dirk; Tsakiris, Dimitrios A; Greinacher, Andreas; Mendez, Adriana; Schmidt, Adrian; Wuillemin, Walter A; Gerber, Bernhard; Kremer Hovinga, Johanna A; Vishnu, Prakash; Graf, Lukas; Kashev, Alexander; Sznitman, Raphael; Bakchoul, Tamam; Nagler, Michael (2023). A machine-learning model for reducing misdiagnosis in heparin-induced thrombocytopenia: A prospective, multicenter, observational study. eClinicalMedicine, 55:101745. |
| بيانات النشر: | Elsevier |
| سنة النشر: | 2023 |
| المجموعة: | University of Zurich (UZH): ZORA (Zurich Open Repository and Archive |
| مصطلحات موضوعية: | Clinic for Oncology and Hematology, 610 Medicine & health |
| الوصف: | Background: Diagnosing heparin-induced thrombocytopenia (HIT) at the bedside remains challenging, exposing a significant number of patients at risk of delayed diagnosis or overtreatment. We hypothesized that machine-learning algorithms could be utilized to develop a more accurate and user-friendly diagnostic tool that integrates diverse clinical and laboratory information and accounts for complex interactions. Methods: We conducted a prospective cohort study including 1393 patients with suspected HIT between 2018 and 2021 from 10 study centers. Detailed clinical information and laboratory data were collected, and various immunoassays were conducted. The washed platelet heparin-induced platelet activation assay (HIPA) served as the reference standard. Findings: HIPA diagnosed HIT in 119 patients (prevalence 8.5%). The feature selection process in the training dataset (75% of patients) yielded the following predictor variables: (1) immunoassay test result, (2) platelet nadir, (3) unfractionated heparin use, (4) CRP, (5) timing of thrombocytopenia, and (6) other causes of thrombocytopenia. The best performing models were a support vector machine in case of the chemiluminescent immunoassay (CLIA) and the ELISA, as well as a gradient boosting machine in particle-gel immunoassay (PaGIA). In the validation dataset (25% of patients), the AUROC of all models was 0.99 (95% CI: 0.97, 1.00). Compared to the currently recommended diagnostic algorithm (4Ts score, immunoassay), the numbers of false-negative patients were reduced from 12 to 6 (-50.0%; ELISA), 9 to 3 (-66.7%, PaGIA) and 14 to 5 (-64.3%; CLIA). The numbers of false-positive individuals were reduced from 87 to 61 (-29.8%; ELISA), 200 to 63 (-68.5%; PaGIA) and increased from 50 to 63 (+29.0%) for the CLIA. Interpretation: Our user-friendly machine-learning algorithm for the diagnosis of HIT (https://toradi-hit.orgTest) was substantially more accurate than the currently recommended diagnostic algorithm. It has the potential to reduce delayed diagnosis and overtreatment ... |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | application/pdf |
| اللغة: | English |
| تدمد: | 2589-5370 |
| العلاقة: | https://www.zora.uzh.ch/id/eprint/224136/1/PIIS2589537022004746.pdfTest; info:pmid/36457646; urn:issn:2589-5370 |
| DOI: | 10.5167/uzh-224136 |
| DOI: | 10.1016/j.eclinm.2022.101745 |
| الإتاحة: | https://doi.org/10.5167/uzh-22413610.1016/j.eclinm.2022.101745Test https://www.zora.uzh.ch/id/eprint/224136Test/ https://www.zora.uzh.ch/id/eprint/224136/1/PIIS2589537022004746.pdfTest |
| حقوق: | info:eu-repo/semantics/openAccess ; Creative Commons: Attribution 4.0 International (CC BY 4.0) ; http://creativecommons.org/licenses/by/4.0Test/ |
| رقم الانضمام: | edsbas.4A639E4C |
| قاعدة البيانات: | BASE |
Full Text Finder | تدمد: | 25895370 |
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| DOI: | 10.5167/uzh-224136 |