Effect on Functional Outcome of Robotic Assisted Rehabilitation Versus Conventional Rehabilitation in Patients with Complete Spinal Cord Injury: A Prospective Comparative Study
Bibliographic record
Abstract
Abstract Study Design: Prospective Comparative Study Objective:This study aims to compare the functional outcomes of Robotic-assisted rehabilitation by Lokomat system Vs. Conventional rehabilitation in patients with Dorsolumbar complete spinal cord injury. Methods: 15 patients with Dorsolumbar spinal cord injury with ASIA A neurology were allocated to robotic rehabilitation and 15 patients to conventional rehabilitation after an operative procedure. Pre-rehabilitation parameters were noted in terms of ASIA Neurology, Motor, and sensory function scores, WISCI II score (Walking Index in Spinal Cord Injury score), LEMS (Lower Extremity Motor Score), SCIM III score (Spinal Cord Independence Measure III score), AO Spine PROST (AO Patient Reported Outcome Spine Trauma), McGill QOL score (Mc Gill Quality Of Life score), VAS score (Visual Analogue Scale) for pain and Modified Ashworth scale for spasticity in lower limbs. Results: On comparing of robotic group to conventional group there was a statistically significant improvement in group in terms of Motor score, WISCI II score, SCIM III score, AO PROST score, Mc GILL QOL score, Max velocity, and Step length. While LEMS score, ASIA neurology, VAS score, Sensory score, and Modified Ashworth scale for spasticity were not statically significant while comparing between two groups. Conclusion: Robot-assisted rehabilitation is superior than conventional rehabilitation in Spinal Cord Injury patients. Variations in results found in the literature for robotic assisted training are probably a result of factors such as differences in type and severity of lesion, time of onset to entry in rehab the devices used, application of the interventions and control interventions. Level of Evidence: III
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".