{"doi":"10.3233/shti230979","title":"Construction of a Prediction Model for Voriconazole-Induced Hepatotoxicity Based on Mixed-Effects Random Forest","abstract":"<jats:p>Voriconazole is a second-generation triazole antifungal agent with strong antifungal activity against a variety of clinically significant pathogens. Controlling blood concentrations within guideline limits through blood concentration monitoring can reduce the probability of hepatotoxicity in patients with voriconazole. However, statistical analysis based on real-world data found that there were still several patients who had blood concentration monitoring developed voriconazole induced hepatotoxicity. Therefore, it has important clinical significance to predict whether hepatotoxicity will occur in patients who meet the guidelines for voriconazole plasma concentration requirements. In this study, based on real-world data, the mixed-effects random forest was used to analyze the electronic medical record data of patients who met the guidelines for voriconazole blood concentration requirements during hospitalization, and a predictive model was constructed to predict whether patients would develop hepatotoxicity within 30 days after using voriconazole.</jats:p>","journal":"Studies in Health Technology and Informatics","year":2024,"id":672146,"datarank":0.16479184330021646,"base_score":1.0986122886681096,"endowment":1.0986122886681096,"self_citation_contribution":0.16479184330021646,"citation_network_contribution":0.0,"self_endowment_contribution":0.16479184330021646,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1204114,"name":"Yu Wang","orcid":"0000-0002-8683-6196","position":1,"is_corresponding":false},{"id":1004368,"name":"Jing Ma","orcid":"0000-0002-0510-4744","position":2,"is_corresponding":false},{"id":139768,"name":"Jiaqi Wang","orcid":"0009-0009-8847-9194","position":3,"is_corresponding":false},{"id":354185,"name":"Jingsong Li","orcid":"0000-0002-1064-637X","position":4,"is_corresponding":false},{"id":1756103,"name":"Danyang Tong","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Construction of a Prediction Model for Voriconazole-Induced Hepatotoxicity Based on Mixed-Effects Random Forest","abstract":"<jats:p>Voriconazole is a second-generation triazole antifungal agent with strong antifungal activity against a variety of clinically significant pathogens. Controlling blood concentrations within guideline limits through blood concentration monitoring can reduce the probability of hepatotoxicity in patients with voriconazole. However, statistical analysis based on real-world data found that there were still several patients who had blood concentration monitoring developed voriconazole induced hepatotoxicity. Therefore, it has important clinical significance to predict whether hepatotoxicity will occur in patients who meet the guidelines for voriconazole plasma concentration requirements. In this study, based on real-world data, the mixed-effects random forest was used to analyze the electronic medical record data of patients who met the guidelines for voriconazole blood concentration requirements during hospitalization, and a predictive model was constructed to predict whether patients would develop hepatotoxicity within 30 days after using voriconazole.</jats:p>","is_dataset_classified":null,"base_score":1.0986122886681096,"endowment":1.0986122886681096,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"38269817","pmcid":null,"openalex_id":"https://openalex.org/W4391224441","authors":[],"funders":[],"total_grants":0,"fwci":4.041,"citation_percentile":0.91010665,"influential_citations":0,"citation_trend":[{"year":2026,"count":2}],"oa_status":"hybrid","license":"cc-by-nc","oa_locations":[{"url":"https://ebooks.iospress.nl/pdf/doi/10.3233/SHTI230979","host_type":"book series"},{"url":"https://ebooks.iospress.nl/pdf/doi/10.3233/SHTI230979","host_type":"publisher"},{"url":"http://dx.doi.org/10.3233/shti230979","host_type":"book series"},{"url":"https://pubmed.ncbi.nlm.nih.gov/38269817","host_type":"repository"}],"fields_of_study":["Antifungal resistance and susceptibility","Antibiotic Resistance in Bacteria","Oral microbiology and periodontitis research","Humans","Voriconazole","Random Forest","Electronic Health Records","Hospitalization","Chemical and Drug Induced Liver Injury"],"mesh_terms":["Random Forest","Hospitalization","Humans","Chemical and Drug Induced Liver Injury","Electronic Health Records","Voriconazole"],"keywords":["Voriconazole","Antifungal","Guideline","Medicine","Statistical analysis","Blood concentration","Intensive care medicine","Internal medicine","Pharmacology","Pathology","Statistics","Dermatology","Prediction model","Hepatotoxicity","Real-world Study","Mixed-effect Random Forest"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Life in Land"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-16T06:48:35.897417Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}