Predicting early mobility after hip or knee replacement using a machine learning model

Is this trial a fit for you?

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This observational study develops and pre-validates a predictive model using retrospective data from 2020-2023 and prospective data from 2026-2027. It combines clinical and perioperative information to forecast early mobility recovery and length of hospital stay after elective arthroplasty. The model will be trained on past data and prospectively tested in routine care, using multiple algorithms and standard performance metrics. Predictors include demographics, surgery and anesthesia details, physiotherapy timing, pain, catheter use, and orthostatic intolerance. Outcomes focus on ability to climb stairs in the first four days and discharge by day five.

Why it matters

Who can join: the full rules

Inclusion Criteria:

* Adults aged 18 years or older
* Patients underwent elective hip or knee arthroplasty.
* Patients for whom postoperative physiotherapy was initiated.

Exclusion Criteria:

* Patients who underwent surgery for oncologic disease, femoral fracture, or revision joint arthroplasty.
* Patients for whom postoperative physiotherapy was not provided due to postoperative complications
* clinical data are unavailable.

Where it's running

• SAITeR IRCCS Istituto Ortopedico Rizzoli
  Bologna, Italy Recruiting
• Azienda U.S.L. - IRCCS di Reggio Emilia
  Reggio Emilia, Italy Not yet recruiting

Study contacts

• Principal investigator: Mattia Morri — IRCCS Istotuto Ortopedico Rizzoli
• Study coordinator: Mattia Morri
• Email: mattia.morri@ior.it
• Phone: +390516366694

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How to take part

1. Review the eligibility criteria above with your treating physician.
2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.