Characteristics of phantom limb pain in U.S. civilians and service members
Bibliographic record
Abstract
OBJECTIVES: The population of Americans with limb loss is on the rise, with a different profile than in previous generations (e.g., greater incidence of amputation due to diabetes). This study aimed to identify the key characteristics of phantom limb sensation (PLS) and pain (PLP) in a current sample of Americans with limb loss. METHODS: This cross-sectional study is the first large-scale (n=649) study on PLP in the current population of Americans with limb loss. A convenience sample of military and civilian persons missing one or more major limbs was surveyed regarding their health history and experience with phantom limb phenomena. RESULTS: Of the participants surveyed, 87% experienced PLS and 82% experienced PLP. PLS and PLP typically first occurred immediately after amputation (47% of cases), but for a small percentage (3-4%) onset did not occur until over a year after amputation. Recent PLP severity decreased over time (β=0.028, 95% CI: -0.05-0.11), but most participants reported PLP even 10 years after amputation. Higher levels of recent PLP were associated with telescoping (β=0.123, 95% CI: 0.04-0.21) and higher levels of pre-amputation pain (β=0.104, 95% CI: 0.03-0.18). Those with congenitally missing limbs experienced lower levels of recent PLP (t (37.93)=3.93, p<0.01) but there were no consistent differences in PLP between other amputation etiologies. CONCLUSIONS: Phantom limb phenomena are common and enduring. Telescoping and pre-amputation pain are associated with higher PLP. Persons with congenitally missing limbs experience lower levels of PLP than those with amputation(s), yet PLP is common even in this subpopulation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".