Episode Overview

Episode Title: Meet the 2025 IFFAS Award Winner: Predictive Model for AOS Response in Total Ankle Replacement
Podcast: The AOFAS Orthopod-Cast
Date: December 24, 2025
Host: Pam Luke, for the AOFAS Podcast Committee
Guests: Dr. Carlos Alran and Dr. Marianne Kulin (2025 IFAS Award winners)

Theme:
This episode spotlights a groundbreaking study by Drs. Alran and Kulin, which developed and validated a predictive model for patient outcomes—using the Ankle Osteoarthritis Scale (AOS)—after Total Ankle Replacement (TAR). The discussion dives into how this model can inform patient selection and surgeon-patient discussions about who benefits most from TAR.

Key Discussion Points

Background & Study Rationale

• [00:54] Pam Luke: Asks for a background and summary of the study’s findings regarding total ankle replacement.
• [01:09] Dr. Carlos Alran:
  • Explains the research evolved into two related studies:
    1. Trends of patient-reported outcomes (PROs) in ankle prosthesis over 15 years
    2. Development of a predictive model for AOS response after TAR
  • "[The] AOS score doesn't change after one year. That's all that patients improve up to one year."
  • Based on these patterns, the team used cohort data to examine which patients achieved a meaningful clinical improvement (using MCID—Minimal Clinically Important Difference).
  • Created a multivariable logistic regression model to determine predictors of the greatest benefit.

Study Findings & Predictive Model Details

• [01:45] Dr. Carlos Alran:
  • Main finding: Patients with the highest (worst) baseline AOS scores benefit the most from TAR.
  • Developed a threshold AOS score at enrollment (≥63 points) that defines which patients are most likely to have a meaningful improvement.
  • Patients with arthritis due to instability etiology showed especially notable improvement.
  • "We prioritized the specificity to know where the patients were benefited the most"
  • Emphasis on providing clinicians with a data-driven cutoff to help determine surgical candidacy.

Clinical Application & Communication With Patients

• [03:11] Dr. Marianne Kulin:
  • Stresses the importance of translating research so surgeons can better counsel patients:
    • "It's nice that you can tell them a little bit more information about what their outcomes will be after one year."
  • This predictive information empowers shared decision-making and clearer expectation setting.

Guidance for Borderline Cases & Universal Benefit

• [03:59] Dr. Carlos Alran:
  • Explains further analysis for “borderline” or “poor responder” patients:
    • Even those with lower (better) baseline AOS scores still experience meaningful improvements, though less dramatic than those with worse scores.
    • "All the patients will benefit, but the patients who will benefit the most are the ones who are doing the worst at the beginning."
  • Effect sizes for improvements range from 0.46 to 0.74 across AOS subscale domains.
  • Advises clinicians: For patients whose symptoms are not severe, it may be wise to wait until symptoms worsen to maximize the improvement from surgery.

Notable Quotes and Memorable Moments

• Dr. Carlos Alran [01:20]:
  "...the patients with the higher AOS score, that means patients who are doing the worst at the beginning, are the ones who benefit the most."

• Dr. Marianne Kulin [03:11]:
  "Once you're a foot and ankle surgeon, you really want to know what you can tell your patients... you can tell them a little bit more information about what their outcomes will be after one year."

• Dr. Carlos Alran [03:59]:
  "All the patients will benefit, but the patients who will benefit the most are the ones who are doing the worst at the beginning. So it doesn't mean that the patients will not, some patients will not benefit from the ankle replacement. Yes, they will. All the patients."

Timeline of Important Segments

| Timestamp | Segment & Content | |-----------|--------------------------------------------------------------------------------------------------------| | 00:27 | Host introduces guests Dr. Alran and Dr. Kulin, IFAS Award winners | | 01:09 | Dr. Alran summarizes the study’s rationale, design, and the creation of the predictive model | | 01:45 | Findings: Baseline AOS score predicts benefit; patients with instability etiology also do well | | 03:11 | Dr. Kulin on clinical significance: empowers conversations with patients | | 03:59 | Discussion on “borderline” patients: everyone benefits, but degree depends on pre-op severity | | 04:58 | Host thanks the guests and wraps up the content segment |

Summary & Takeaway Messages

• Predictive Model:
  The team developed and validated a predictive threshold (AOS score ≥63) to identify patients who will benefit most from total ankle replacement.
• Clinical Utility:
  Surgeons can use this model to better select candidates and set realistic expectations for TAR, helping patients understand their likely improvement after one year.
• Advice for Clinicians:
  While all patients with end-stage ankle arthritis benefit from TAR, those with the most severe symptoms at baseline see the largest improvements. For patients with milder symptoms, consider monitoring and waiting for surgery until symptom progression.
• Broader Impact:
  The research aims to move from statistical analysis to bedside decision-making, directly influencing patient conversations and surgical planning.

This episode gives a practical, evidence-backed framework for surgeons as they select TAR candidates and counsel patients—a clear example of AOFAS’s mission to connect clinical research to daily practice.