Use of an innovative model to evaluate mobility in seniors with lower-limb amputations of vascular origin: a pilot study
Bibliographic record
Abstract
BACKGROUND: The mobility of older individuals has often been only partially assessed, without considering all important aspects such as potential (available) versus effective (used) mobilities and the physical and psychosocial factors that modulate them. This study proposes a new model for evaluating mobility that considers all important aspects, applied here to lower-limb amputees with vascular origin. This model integrates the concepts of potential mobility (e.g. balance, speed of movement), effective mobility (e.g. life habits, movements in living areas) and factors that modulate these two types of mobility (e.g. strength, sensitivity, social support, depression). The main objective was to characterize potential and effective mobility as well as mobility modulators in a small sample of people with lower-limb amputations of vascular origin with different characteristics. The second objective of this pilot study was to assess the feasibility of measuring all variables in the model in a residential context. METHODS: An observational and transversal design was used with a heterogeneous sample of 10 participants with a lower-limb amputation of vascular origin, aged 51 to 83, assessed between eight and 18 months after discharge from an acute care hospital. A questionnaire of participant characteristics and 16 reliable and valid measurements were used. RESULTS: The results show that the potential mobility indicators do not accurately predict effective mobility, i.e., participants who perform well on traditional measures done in the laboratory or clinic are not always those who perform well in the real world. The model generated 4 different profiles (categories) of participants ranging from reduced to excellent potential mobility and low to excellent effective mobility, and characterized the modulating factors. The evaluations were acceptable in terms of the time taken (three hours) and the overall measurements, with a few exceptions, which were modified to optimize the data collected and the classification of the participants. For the population assessed, the results showed that some of the negative modulators (particularly living alone, no rehabilitation, pain, limited social support, poor muscle strength) played an important role in reducing effective mobility. CONCLUSION: The first use of the model revealed interesting data that add to our understanding of important aspects linked to potential and effective mobility as well as modulators. The feasibility of measuring all variables in the model in a residential context was demonstrated. A study with a large number of participants is now warranted to rigorously characterize mobility levels of lower-limb amputees with vascular origin.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".