Physical Therapy for Gait, Balance, and Cognition in Individuals with Cognitive Impairment: A Retrospective Analysis
Bibliographic record
Abstract
OBJECTIVES: The purpose of this study was to determine if a pragmatic physical therapy (PT) program was associated with improved cognition, gait, and balance in individuals with cognitive impairment. This study investigated these associations for individuals with Alzheimer disease (AD), vascular dementia (VaD), dementia with Lewy bodies (DLB), and mild cognitive impairment (MCI) in order to better characterize outcomes to PT for each diagnostic group. METHODS: Data before and after one month of physical therapy were extracted from patient records (67 with AD, 34 with VaD, 35 with DLB, and 37 with MCI). The mean number of PT sessions over a month was 3.4 (±1.8). Outcomes covered the domains of gait, balance, and cognition with multiple outcomes used to measure different constructs within the balance and gait domains. RESULTS: All groups showed improvements in balance and at least one gait outcome measure. Those with MCI improved in every measure of gait and balance performance. Lastly, cognition as measured by Montreal Cognitive Assessment improved in individuals in the AD, VaD, and MCI groups. CONCLUSION: . While physical therapy is not typically a primary treatment strategy for individuals with cognitive impairment, the results of this study are consistent with the literature that demonstrates improvement from physical therapy for other neurodegenerative diseases. Further clinical and research exploration for physical therapy as a primary treatment strategy in these populations is warranted.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".