{"doi":"10.1101/2024.09.30.24314628","title":"Derivation and validation of a prediction rule for sedative-associated delirium during acute respiratory failure requiring mechanical ventilation","abstract":"Abstract Background Delirium during acute respiratory failure is common and morbid. Pharmacologic sedation is a major risk factor for delirium, but some sedation is often necessary for the provision of safe care of mechanically ventilated patients. A simple, transparent model that predicts sedative-associated delirium in mechanically ventilated ICU patients could be used to guide decisions about personalized sedation. Research Question Can the risk of sedative-associated delirium be estimated in mechanically-ventilated ICU patients? Study Design and Methods Using the subset of patients in a previously-published ICU cohort who received mechanical ventilation, we performed backward stepwise logistic regression to derive a model predictive of sedative-associated delirium. We validated this model internally using hundredfold bootstrapping. We then validated this model externally in a separate prospective cohort of mechanically ventilated ICU patients. Results 836 patients comprised the derivation cohort. Backwards stepwise regression produced a model with age, BMI, sepsis, SOFA, malignancy, COPD, stroke, sex, and doses of sedatives (opioids, propofol, and/or benzodiazepines) as predictors of sedative-associated delirium. The model had very good discriminative power, with an area under the receiver-operator curve (AUROC) of 0.83. Internal validation via bootstrapping showed preserved discriminatory function with an AUROC of 0.81 and graphical evidence of good calibration. External validation in a separate set of 340 patients showed good discrimination, with AUROC of 0.70. Interpretation Sedative-associated delirium during acute respiratory failure requiring mechanical ventilation can be predicted using a simple, transparent model, which can now be validated in a prospective study.","journal":"medRxiv","year":2024,"id":504193,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9508,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":927919,"name":"C.A. Onyemekwu","orcid":"0000-0003-1925-4476","position":1,"is_corresponding":false},{"id":927920,"name":"Kelly Potter","orcid":"0000-0001-7737-2070","position":2,"is_corresponding":false},{"id":1297639,"name":"Christopher Franz","orcid":null,"position":3,"is_corresponding":false},{"id":16243,"name":"Georgios D. Kitsios","orcid":"0000-0002-1018-948X","position":4,"is_corresponding":false},{"id":3878,"name":"Bryan J. McVerry","orcid":"0000-0002-1175-4874","position":5,"is_corresponding":false},{"id":609065,"name":"Pratik P. Pandharipande","orcid":"0000-0002-1389-8580","position":6,"is_corresponding":false},{"id":106792,"name":"E. Wesley Ely","orcid":"0000-0003-3957-2172","position":7,"is_corresponding":false},{"id":106789,"name":"Timothy D. Girard","orcid":"0000-0002-9833-4871","position":8,"is_corresponding":false},{"id":927918,"name":"N. Prendergast","orcid":"0000-0003-4791-1816","position":0,"is_corresponding":true}],"reference_count":31,"raw_metadata":null,"created_at":"2026-07-19T02:10:35.597333Z","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":[]}