{"doi":"10.1002/dad2.70183","title":"Predicting cognitive status in stroke survivors from driving performance","abstract":"INTRODUCTION: This study aimed to determine whether simulated driving performance can reliably predict cognitive impairment in stroke survivors. METHODS: = 54) stroke survivors completed a simulated driving course with reactive, distracted, and route-planning sections. Performance was assessed using lane departures, average speed, brake reaction time, task completion time, and route accuracy. RESULTS: Logistic regression models correctly distinguished cognitive status in 77.5% of cases for reactive and distracted driving, and 80.9% for route planning. Notably, the route planning task also achieved the highest classification rate of cognitively impaired participants (∼70%). Receiver operating characteristic (ROC) analyses on the strongest predictors from each driving section revealed significant areas under the curve (AUCs), with optimal cutoffs identifying cognitively impaired participants at 70%-80% accuracy. DISCUSSION: These findings provide a critical foundation for developing simulator-based assessments as practical, functionally relevant screening tools for identifying cognitive impairment and determining driving readiness post-stroke. Highlights: Stroke survivors were tested on simulated driving tasks.Driving metrics were lane departures, speed, reaction time, and route accuracy.Cognitive status was predicted with greater than 75% accuracy.Simulators may be a clinical tool for assessing post-stroke driving readiness.","journal":"Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring","year":2025,"id":575129,"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":0.9496,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1483117,"name":"Anjali Tiwari","orcid":"0009-0009-1468-3504","position":1,"is_corresponding":false},{"id":759799,"name":"Sharon N. Poisson","orcid":"0000-0002-7162-4043","position":2,"is_corresponding":false},{"id":288057,"name":"Manfred Diehl","orcid":"0000-0002-2055-3839","position":3,"is_corresponding":false},{"id":724495,"name":"Neha Lodha","orcid":"0000-0003-4192-515X","position":4,"is_corresponding":false},{"id":374420,"name":"Stefan Delmas","orcid":"0000-0002-0054-3908","position":0,"is_corresponding":true}],"reference_count":35,"raw_metadata":null,"created_at":"2026-07-19T02:57:48.486077Z","pmid":"40970250","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":[]}