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Using Artificial Intelligence to Monitor and Predict Recovery after Anterior Cruciate Ligament Reconstruction.

Integration of Artificial Intelligence for Tracking and Predicting Post-Operative Recovery after Anterior Cruciate Ligament Reconstruction - NIL

Status
Active, not recruiting
Phases
Unknown
Study type
Interventional
Source
CTRI
Registry ID
CTRI/2026/01/101923
Enrollment
150
Registered
2026-01-23
Start date
Unknown
Completion date
Unknown
Last updated
2026-02-02

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Health Condition 1: M968- Other intraoperative and postprocedural complications and disorders of musculoskeletal system, not elsewhere classified

Interventions

Intervention1: Standardised ACL reconstruction rehabilitation program.: All enrolled participants will receive a standardized post operative rehabilitation program following anterior cruciate ligament

Sponsors

Galgotias University
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: 1. Age 18 - 40 years 2. Primary unilateral Anterior Cruciate Ligament reconstruction 3. Willingness and ability to attend scheduled visits 4. Specific graft type used 5. Adherence to post-operative rehabilitation 6. Owns a smartphone for monitoring and communication 7. Medically stable post-operatively - demonstrating stable cardiovascular, respiratory, and neurological function with no ongoing acute complications (e.g., bleeding, infection, or hemodynamic instability) and deemed fit by the attending surgeon to commence post-operative rehabilitation or study participation.

Exclusion criteria

Exclusion criteria: 1. Anterior Cruciate Ligament surgery performed more than1 year after injury 2. Previous lower-limb surgery or fracture fixation 3. Revision Anterior Cruciate Ligament surgery cases 4. Multi-ligament reconstruction 5. Anterior Cruciate Ligament reconstruction combined with High Tibial Osteotomy 6. Long-term hormone therapy with degenerative changes 7. Contralateral knee instability or knee injury 8. Neuromuscular disorders 9. Severe systemic comorbidities (Diabetes, Chronic kidney disease, cardiopulmonary disease) 10. History of cancer or currently in oncology rehabilitation 11. Autoimmune disease including rheumatoid arthritis

Design outcomes

Primary

MeasureTime frame
Artificial intelligence based models can accurately track and predict individual post-operative recovery trajectories in patients following anterior cruciate ligament reconstruction, with predictive performance comparable to or superior to conventional clinical assessment methods. Timepoint: thirty six weeks

Secondary

MeasureTime frame
Restoration of knee range of motion, hop limb symmetry index, pain reduction, improvement in IKDC and KOOS subscales, adherence indices, and time to return to running or return to sport clearance after ACL reconstruction. Timepoint: Baseline, 2 weeks, 6 weeks, 12 weeks, 24 weeks, 36 weeks and 6 months post surgery.

Countries

India

Contacts

Public ContactProfDr Nidhi SINGH

Galgotias University

singh.nidhi@galgotiasuniversity.edu.in7042627025

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Feb 7, 2026