Carpal Tunnel Syndrome (CTS), Cubital Tunnel Syndrome, DeQuervain's Tenosynovitis, Finger Injuries, Hand, Hand Arthritis, Hand Injuries, Hand Injuries and Disorders, Hand Therapy, Peripheral Nerve Injuries, Postoperative Rehabilitation, Prediction Models, Tendon Injuries, Trapeziometacarpal (TMC) Arthrosis, Trigger Finger, Upper Extremity, Upper Extremity Injuries, Wrist Fractures, Wrist Injuries
Conditions
Keywords
digital health monitoring, real-world evidence, clinical decision support, upper extremity rehabilitation, early response prediction
Brief summary
This study investigates whether early changes observed during the first weeks of hand and upper extremity rehabilitation can predict patient outcomes months later. In rehabilitation practice, clinicians make numerous decisions each session regarding exercise type, frequency, duration, and treatment approach. Most of these decisions are currently made without systematic longitudinal data. This study addresses three fundamental questions using data collected during routine clinical care: (1) Can the rate of improvement in the first weeks of treatment predict functional status months later, across both session-based and milestone-based time points? (2) Are there meaningfully different recovery profiles among hand rehabilitation patients? (3) Is there measurable variation in clinical decision-making among patients with similar profiles, and does this variation relate to outcomes? A digital patient monitoring platform developed by the principal investigator, a physiotherapist and academic researcher specializing in hand rehabilitation serves as the data collection infrastructure. The platform records standard clinical assessment measures in a structured format and has been in active clinical use at Hacettepe University prior to this study. For research purposes, the system has been expanded to include structured capture of patient-reported outcomes, patient global impression of change, treatment protocol coding, home exercise adherence, and automated calculation of early response metrics. This is a 12-month prospective observational cohort study enrolling a minimum of 60 patients. Data are stored securely on the university's institutional network. Patients are anonymized using identification codes. The study is subject to Hacettepe University Ethics Committee approval and participant informed consent. Findings are expected to generate evidence supporting data-driven clinical decision-making in rehabilitation and to provide a feasibility foundation for a larger multi-center study.
Detailed description
The study addresses three research questions: (1) predictive power of early functional response for later clinical outcomes across four cascaded models (M1-M4), (2) classification of patient recovery profiles, and (3) measurement of clinical decision variation. System and methodological details reported in study supplement.
Interventions
None listed
Sponsors
Hacettepe University
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Adults aged 18 years or older * Hand or upper extremity pathology requiring rehabilitation, including but not limited to: flexor or extensor tendon injuries, peripheral nerve injuries or compression syndromes (including carpal tunnel syndrome, cubital tunnel syndrome), distal radius fractures, metacarpal or phalangeal fractures, joint injuries and instabilities, arthropathy (osteoarthritis, rheumatoid arthritis), trapeziometacarpal osteoarthritis, trigger finger, Dupuytren's disease, DeQuervain tenosynovitis, lateral epicondylitis and post-surgical upper extremity conditions * Under clinical responsibility of the principal investigator at the Faculty of Physical Therapy and Rehabilitation, Hacettepe University * Expected to attend minimum 8 rehabilitation sessions * Able to provide written informed consent
Exclusion criteria
* • Active psychiatric illness precluding participation or completion of assessment tools * Severe cognitive impairment precluding understanding of patient-reported outcome measures * Literacy difficulties preventing self-completion of questionnaires * Concurrent enrollment in another interventional clinical study * Refusal to provide written informed consent
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Feasibility: PROM Data Completeness | Throughout the 12-month study period | Proportion of rehabilitation sessions with complete PROM data entries throughout the study period. Success criterion: ≥85% completeness rate. |
| Model M1: Session-Based Early Response → Session 12 | Baseline (session 1) to session 12 (approximately 4-8 weeks) | Predictive Power of Sessions 1-4 Functional Change (ΔS₁-₄) for Session 12 Outcome Association between the early response score (ΔS₁-₄ = mean change in primary PROM per session during sessions 1-4) and primary PROM score at session 12, assessed via linear regression and ROC curve analysis (AUC). Baseline PROM entered as covariate. |
| Model M2: Month 1 Change → Month 3 Outcome | Baseline to 3-month standardized assessment | Predictive Power of 1-Month Change (Δ₀→₁) for 3-Month Outcome Association between change in primary PROM from baseline to 1-month assessment and PROM score at 3 months, with covariate adjustment for baseline severity. Tests whether early-period change forecasts mid-term outcomes. |
| Model M4: Month 1 Change → Month 6 Outcome | Baseline to 6-month standardized assessment | Predictive Power of 1-Month Change (Δ₀→₁) for 6-Month Outcome Association between change in primary PROM from baseline to 1-month assessment and PROM score at 6 months. This is the primary cascaded prediction model: can a single early assessment predict medium-to-long-term functional outcomes? Findings will inform evidence-based treatment modification thresholds. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Model M3: Month 3 Change → Month 6 Outcome | Baseline to 6-month standardized assessment | Predictive Power of 3-Month Change (Δ₀→₃) for 6-Month Outcome Association between change in primary PROM from baseline to 3-month assessment and PROM score at 6 months, with baseline covariate adjustment. Completes the cascaded prediction chain (M1-M4). |
| Recovery Profile Classification | Baseline through session 12 (~4-8 weeks) | Number of Distinct Longitudinal Recovery Profiles Number of meaningfully different recovery trajectory clusters identified via K-means clustering of longitudinal PROM data (silhouette analysis for optimal cluster number) and individual growth curves from linear mixed models. |
| Clinical Decision Variation | Throughout the 12-month study period | Treatment Protocol Variation Coefficient (CV%) Coefficient of variation (CV%) of treatment protocol codes applied to patients with similar diagnostic and baseline profiles (IQR grouping), and Spearman correlation between protocol variation index and session 12 functional outcome. |
| Feasibility: Clinician Acceptance | At 3 months and 12 months | Clinician Acceptance Rate Proportion of clinicians a rating system usability as acceptable or above (≥4/5) on a structured 5-item Likert questionnaire. Success criterion: ≥80% acceptance rate. |
| MCID Responder Rate | Monthly from baseline to 12 months | Proportion Achieving MCID at Each Milestone Proportion of patients whose primary PROM change from baseline exceeds the established MCID threshold at each milestone (1, 2, 3, 6, 9, 12 months). Scale-specific MCID values: DASH=10.0; QuickDASH=15.9; PRWE=11.5; MHQ=12.8; Boston CTS=0.74; PSFS=2.0. |
| Feasibility: Milestone Completion Rate | Throughout the 12-month study period | Standardized Assessment Milestone Completion Rate Proportion of scheduled milestone assessments (baseline, 1, 2, 3, 6, 9, 12 months) completed within ±2 weeks of the target date. Success criterion: ≥80% completion rate. |
Countries
Turkey (Türkiye)
Contacts
CONTACTCigdem Ayhan Kuru, Professor
Outcome results
None listed