Hip disarticulation and hemipelvectomy prostheses: A review of the literature
Bibliographic record
Abstract
BACKGROUND: Although the global population of people with a hip disarticulation (HD) or hemipelvectomy (HP) amputation is small, the degree of disability is high, affecting function and independence. A comprehensive literature review is needed to examine the evidence for prostheses in these amputation levels. METHOD: A scoping literature review was conducted to examine related research documents from 1950 to September 2020, found using Scopus, Web of Science, PubMed, and Google Scholar databases. Studies evaluated (retrospectively or prospectively) HD or HP prostheses and were written in English. Study design and protocol, research instrument, sample size, and outcome measures were reviewed. RESULTS: In the past 70 years, 53 articles that evaluated HD or HP prostheses were published. Most research was conducted in the United States (24 articles) and Japan (nine articles). In 42 articles, authors prospectively evaluated the effects of prostheses in these amputation levels. On average, prospective studies had four (SD = 5) participants. Since 1950, only five prospective studies evaluated HD or HP prostheses with 10 or more participants. Moreover, sufficient information was often unavailable for research replication. CONCLUSION: More evidence is needed regarding the effects of HD or HP prosthetic components (i.e. hip, knee, ankle, socket type, and suspension system) on gait, patient satisfaction, prosthetic use, interface pressure, and energy expenditure. Articles mostly have small sample sizes that reduce confidence in the reliability of their findings and limit generalizability. Future investigations are needed with vigorous methodology and larger sample sizes to provide strong statistical conclusions.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".