A novel mixed reality system to manage phantom pain in-home: results of a pilot clinical trial
Bibliographic record
Abstract
Introduction Mirror therapy for phantom limb pain (PLP) is a well-accepted treatment method that allows participants to use a mirror to visually perceive the missing limb. Mixed reality options are now becoming increasingly available, but an in-home virtual mirror therapy option has yet to be adequately investigated. Methods We had previously developed a mixed reality system for Managing Phantom Pain (Mr. MAPP) that registers the intact limb and mirrors it onto the amputated limb with the system's visual field, allowing the user to engage with interactive games targeting different large lower limb movements. Feasibility and pilot outcomes of treating patients with lower extremity PLP by using Mr. MAPP at home for 1 month were evaluated in this study. Pain intensity and interference were assessed using the McGill Pain Questionnaire, Brief Pain Inventory, and a daily exercise diary. Function was assessed using the Patient Specific Functional Scale (PSFS). The clinical trial registry number for this study is NCT04529083. Results This pilot study showed that it was feasible for patients with PLP to use Mr. MAPP at home. Among pilot clinical outcomes, statistically significant differences were noted in mean current pain intensity [1.75 (SD = 0.46) to 1.125 (SD = 0.35) out of 5, P = .011] and PSFS goal scores [4.28 (SD = 2.27) to 6.22 (SD = 2.58) out of 10, P = .006], with other outcome measures showing non-significant trends towards improvement. Discussion This pilot study revealed that in-home use of Mr. MAPP has potential to provide pain relief and improve function in patients with lower extremity PLP and is feasible. Each scale used provided unique perspective on the functional impact of PLP. Further expanded studies and investigation, including a fully powered clinical trial, with these scales are warranted. Clinical Trial Registration https://www.clinicaltrials.gov/ct2/show/NCT04529083, Identifier: NCT04529083 .
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".