Using Wearable Inertial Sensors to Assess Mobility of Patients With Hematologic Cancer and Associations With Chemotherapy-Related Symptoms Before Autologous Hematopoietic Stem Cell Transplant: Cross-sectional Study
Bibliographic record
Abstract
BACKGROUND: Wearable sensors could be a simple way to quantify and characterize mobility in patients with hematologic cancer scheduled to receive autologous hematopoietic stem cell transplant (autoHSCT) and how they may be related to common treatment-related symptoms and side effects of induction chemotherapy. OBJECTIVE: We aimed to conduct a cross-sectional study comparing mobility in patients scheduled to receive autoHSCT with that in healthy, age-matched adult controls and determine the relationships between patient mobility and chemotherapy-related symptoms. METHODS: Patients scheduled to receive autoHSCT (78/156, 50%) and controls (78/156, 50%) completed the prescribed performance tests using wearable inertial sensors to quantify mobility including turning (turn duration and number of steps), gait (gait speed, stride time, stride time variability, double support time, coronal trunk range of motion, heel strike angle, and distance traveled), and balance (coronal sway, coronal range, coronal velocity, coronal centroidal frequency, sagittal sway, sagittal range, sagittal velocity, and sagittal centroidal frequency). Patients completed the validated patient-reported questionnaires to assess symptoms common to chemotherapy: chemotherapy-induced peripheral neuropathy (Functional Assessment of Cancer Therapy/Gynecologic Oncology Group-Neurotoxicity subscale), nausea and pain (European Organization for Research and Treatment of Cancer Quality of Life Questionnaire), fatigue (Patient-Reported Outcomes Measurement Information System Fatigue Short Form 8a), vertigo (Vertigo Symptom Scale-short form), and depression (Center for Epidemiological Studies-Depression). Paired, 2-sided t tests were used to compare mobility between patients and controls. Stepwise multivariable linear regression models were used to evaluate associations between patient mobility and symptoms. RESULTS: Patients aged 60.3 (SD 10.3) years had significantly worse turning (turn duration; P<.001), gait (gait speed, stride time, stride time variability, double support time, heel strike angle, stride length, and distance traveled; all P<.001), and balance (coronal sway; P<.001, range; P<.001, velocity; P=.02, and frequency; P=.02; and sagittal range; P=.008) than controls. In patients, high nausea was associated with worse stride time variability (ß=.001; P=.005) and heel strike angle (ß=-.088; P=.02). Pain was associated with worse gait speed (ß=-.003; P=.003), stride time variability (ß=.012; P=.02), stride length (ß=-.002; P=.004), and distance traveled (ß=-.786; P=.005). Nausea and pain explained 17% to 33% and 14% to 36% of gait variance measured in patients, respectively. CONCLUSIONS: Patients scheduled to receive autoHSCT demonstrated worse mobility in multiple turning, gait, and balance domains compared with controls, potentially related in part to nausea and pain. Wearable inertial sensors used in the clinic setting could provide granular information about mobility before further treatment, which may in turn benefit from rehabilitation or symptom management. Future longitudinal studies are needed to better understand temporal changes in mobility and symptoms across the treatment trajectory to optimally time, design, and implement strategies, to preserve functioning in patients with hematologic cancer in the long term.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".