Are Accelerometer-based Functional Outcome Assessments Feasible and Valid After Treatment for Lower Extremity Sarcomas?
Bibliographic record
Abstract
BACKGROUND: Aspects of physical functioning, including balance and gait, are affected after surgery for lower limb musculoskeletal tumors. These are not routinely measured but likely are related to how well patients function after resection or amputation for a bone or soft tissue sarcoma. Small, inexpensive portable accelerometers are available that might be clinically useful to assess balance and gait in these patients, but they have not been well studied. QUESTIONS/PURPOSES: In patients treated for lower extremity musculoskeletal tumors, we asked: (1) Are accelerometer-based body-worn monitor assessments of balance, gait, and timed up-and-go tests (TUG) feasible and acceptable? (2) Do these accelerometer-based body-worn monitor assessments produce clinically useful data (face validity), distinguish between patients and controls (discriminant validity), reflect findings obtained using existing clinical measures (convergent validity) and standard manual techniques in clinic (concurrent validity)? METHODS: This was a prospective cross-sectional study. Out of 97 patients approached, 34 adult patients treated for tumors in the femur/thigh (19), pelvis/hip (3), tibia/leg (9), or ankle/foot (3) were included in this study. Twenty-seven had limb-sparing surgery and seven underwent amputation. Patients performed standard activities while wearing a body-worn monitor on the lower back, including standing, walking, and TUG tests. Summary measures of balance (area [ellipsis], magnitude [root mean square {RMS}], jerkiness [jerk], frequency of postural sway below which 95% of power of acceleration power spectrum is observed [f95 of postural sway]), gait [temporal outcomes, step length and velocity], and TUG time were derived. Body-worn monitor assessments were evaluated for feasibility by investigating data loss and patient-reported acceptability and comfort. In addition, outcomes in patients were compared with datasets of healthy participants collected in parallel studies using identical methods as in this study to assess discriminant validity. Body-worn monitor assessments were also investigated for their relationships with routine clinical scales (the Musculoskeletal Tumour Society Scoring system [MSTS], the Toronto Extremity Salvage Score [TESS], and the Quality of life-Cancer survivors [QoL-CS)] to assess convergent validity and their agreement with standard manual techniques (video and stopwatch) to assess concurrent validity. RESULTS: Although this was a small patient group, there were initial indications that body-worn monitor assessments were well-tolerated, feasible to perform, acceptable to patients who responded (95% [19 of 20] of patients found the body-worn monitor acceptable and comfortable and 85% [17 of 20] found it user-friendly), and produced clinically useful data comparable with the evidence. Balance and gait measures distinguished patients and controls (discriminant validity), for instance balance outcome (ellipsis) in patients (0.0475 m/s [95% confidence interval 0.0251 to 0.0810]) was affected compared with controls (0.0007 m/s [95% CI 0.0003 to 0.0502]; p = 0.001). Similarly gait outcome (step time) was affected in patients (0.483 seconds [95% CI 0.451 to 0.512]) compared with controls (0.541 seconds [95% CI 0.496 to 0.573]; p < 0.001). Moreover, body-worn monitor assessments showed relationships with existing clinical scales (convergent validity), for instance ellipsis with MSTS (r = -0.393; p = 0.024). Similarly, manual techniques showed excellent agreement with body-worn monitor assessments (concurrent validity), for instance stopwatch time 22.28 +/- 6.93 seconds with iTUG time 21.18 +/- 6.23 seconds (intraclass correlation coefficient agreement = 0.933; p < 0.001). P < 0.05 was considered statistically significant. CONCLUSIONS: Although we had a small, heterogeneous patient population, this pilot study suggests that body-worn monitors might be useful clinically to quantify physical functioning in patients treated for lower extremity tumors. Balance and gait relate to disability and quality of life. These measurements could provide clinicians with useful novel information on balance and gait, which in turn could guide rehabilitation strategies. LEVEL OF EVIDENCE: Level III, diagnostic study.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".