The 4th Annual Kentucky Appalachian Rural Rehabilitation Network Conference on Spinal Cord Injury and Stroke Across the Lifespan
Bibliographic record
Abstract
The 4th annual Kentucky Appalachian Rural Rehabilitation Network conference featured four speakers and two panel discussions focused on current evidence-based practice important to individuals with spinal cord injury (SCI) or stroke living in rural communities as well as the healthcare providers serving them. Specially, the aims to this year’s conference were to: 1) discuss special issues related to spinal cord injury in the pediatric population; 2) discuss the long-term issues related to aging in the spinal cord injured population; 3) discuss the use of telehealth for the evaluation and treatment of individuals with stroke living in rural communities; 4) discuss communication difficulties after stroke; 5) demonstrate wheelchair set up, positioning and pressure mapping; and 6) discuss technology that is available to enhance patient/client communication in stroke rehabilitation. On September 19th over 215 attendees from across Kentucky and the U.S. took part in this event. The conference welcomed individuals from the community, particularly those personally affected by SCI or stroke and their caregivers. Healthcare professionals in attendance included physicians, physical and occupational therapists, speech and language pathologists, nurses, social workers, researchers, and university professors. In addition, physical therapy students from the University of Kentucky and occupational therapy students from Eastern Kentucky University, our future healthcare providers, attended to network and learn about their future clients. The morning session included two keynote presentations. Dr. Therese Johnston PT, PhD from the University of the Sciences in Philadelphia opened the conference with a presentation about SCI rehabilitation in the pediatric population. Dr. Greg Jicha M.D., Ph.D. from the University of Kentucky’s Department of Neurology followed with a presentation on vascular dementia and the use of telehealth to reach rural communities. During the extended lunch break, attendees had the chance to view research posters covering a diverse array of topics including adaptive farming equipment, crafting for ventilator-dependent patients, and peripheral nerve stimulation in stroke patients. In the afternoon, two breakout sessions focused on either stroke or SCI. The SCI breakout session began with a presentation from Dr. Susan Charlifue Ph.D. of Craig Hospital in Englewood, CO regarding aging in individuals with SCI, which was followed by a demonstration of the use of pressure mapping to ensure proper wheelchair setup for the prevention of secondary complications. The stroke breakout session began with Dr. Bob Marshall Ph.D., FASHA, CCC-SLP of the University of Kentucky, who discussed ways to reveal the competence and independence of individuals who have communication difficulties following a stroke, which was followed by therapists from Cardinal Hill Rehabilitation Hospital shared cutting-edge technology, such as computer programs and mobile apps, being used to help people who have had a stroke with communication difficulties. As always, the most popular sessions of the afternoon were the panel discussions. A panel of individuals with SCI offered a candid discussion about their experiences with aging with SCI, and a panel of caregivers discussed strategies they have used to facilitate communication with their loved ones with aphasia. The conference provided an open and interactive forum for all interested individuals to discuss the real issues of concern for individuals with stroke and SCI.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.066 | 0.012 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".