{"doi":"10.1101/2023.02.20.23286194","title":"Training parameters and longitudinal adaptations that most strongly mediate walking capacity gains from high-intensity interval training post-stroke","abstract":"Background: Locomotor high-intensity interval training (HIIT) has been shown to improve walking capacity more than moderate-intensity aerobic training (MAT) after stroke, but it is unclear which training parameter(s) should be prioritized (e.g. speed, heart rate, blood lactate, step count) and to what extent walking capacity gains are the result of neuromotor versus cardiorespiratory adaptations. Objective: Assess which training parameters and longitudinal adaptations most strongly mediate 6-minute walk distance (6MWD) gains from post-stroke HIIT. Methods: The HIT-Stroke Trial randomized 55 persons with chronic stroke and persistent walking limitations to HIIT or MAT and collected detailed training data. Blinded outcomes included 6MWD, plus measures of neuromotor gait function (e.g. fastest 10-meter gait speed) and aerobic capacity (e.g. ventilatory threshold). This ancillary analysis used structural equation models to compare mediating effects of different training parameters and longitudinal adaptations on 6MWD. Results: Net gains in 6MWD from HIIT versus MAT were primarily mediated by faster training speeds and longitudinal adaptations in neuromotor gait function. Training step count was also positively associated with 6MWD gains, but was lower with HIIT versus MAT, which decreased the net 6MWD gain. HIIT generated higher training heart rate and lactate than MAT, but aerobic capacity gains were similar between groups, and 6MWD changes were not associated with training heart rate, training lactate, or aerobic adaptations. Conclusions: To increase walking capacity with post-stroke HIIT, training speed and step count appear to be the most important parameters to prioritize.","journal":"medRxiv","year":2023,"id":390937,"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":8,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9624,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":687530,"name":"Allison Miller","orcid":"0000-0003-3043-6852","position":1,"is_corresponding":false},{"id":727344,"name":"Sarah M. Schwab","orcid":"0000-0002-3835-5718","position":2,"is_corresponding":false},{"id":548700,"name":"Heidi Sucharew","orcid":"0000-0002-3933-1574","position":3,"is_corresponding":false},{"id":458870,"name":"Daniel Carl","orcid":"0000-0002-7807-7417","position":4,"is_corresponding":false},{"id":364111,"name":"Sandra A. Billinger","orcid":"0000-0002-1618-7207","position":5,"is_corresponding":false},{"id":408286,"name":"Darcy S. Reisman","orcid":null,"position":6,"is_corresponding":false},{"id":360847,"name":"Pierce Boyne","orcid":"0000-0003-3611-9057","position":0,"is_corresponding":true}],"reference_count":48,"raw_metadata":null,"created_at":"2026-07-19T01:18:42.653719Z","pmid":"36865178","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":[]}