Meet the 2025 IFFAS Award Winner: Predictive Model for AOS Response in Total Ankle Replacement

Summary

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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.

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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.

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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."

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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 |

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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.

Transcript

[Podcast Host]

Welcome to AOFAS Ortho Podcast where leaders in foot and ankle orthopedic surgery discuss the issues that affect you and your practice. Please note that the views expressed on this podcast do not necessarily represent the views of the AOFAS or its members.

[Pam Luke]

Welcome. This is Pam Luke and as part of our Ortho podcast recording live at the 2025 AFAS annual meeting, I'm here with the IFAS award winner finalists, Drs. Carlos Alran and Dr. Marianne Kulin, who are the winners for their paper titled predictive model for AOS response in total ankle replacement. Dr. Will My symptoms get better after the ankle replacement?

[Dr. Carlos Alran]

Thank you, Pam.

[Pam Luke]

Congratulations on the award. As for our listeners who didn't have the pleasure of being in the paper session and getting to hear your abstract presentation, my first question is if you can help us summarize the background for your paper and what your findings were regarding total ankle replacement.

[Dr. Carlos Alran]

Okay, so this is like two papers to be honest. So it was too much to put in one paper, so we divided it into two. We started with the trends of the pros, which is the title of the paper, Analysis of variation of the Problems in Total Anchor Prosthesis over Time. So we were analyzing in this paper how the Pros behave in 15 year time and we saw that the AOS score doesn't change after one year. That's all that patients improve up to one year. And that's when we realized if we know that we can do a predictive model of it, we can know which are the patients will benefit the most of the ankle replacement. So what we did after that, we calculated, we looked for the evidence and looked for the MCID of the AOS score. That way we categorized the patients whether they were doing good or bad based on the MCID of the AOS score. And then we built a predictive model with all the variables that are in the cohort study. We're doing the other cohort study. So we take advantage of that data in order to do this study. So basically we did a lot of multivariable logistic regression with a lot of different analysis and our final results were 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. But we didn't stop there. We knew that we needed something a little bit more precise. So we calculated like a threshold for the AOS score at the beginning, at the enrollment to know which patients from the beginning to which point they will benefit, who were the ones. So we calculated it Based on. We prioritized the specificity to know where the patients were benefited the most and try to include only patients who have a meaningful improvement. We calculated threshold. It was an AOS score of equally or more than 63 points. And we also saw that patient with instability etiology had a lot of improvement as well.

[Pam Luke]

Great. And so you've already done that part where you've taken the cohort that you thought would benefit the most and then applied it to them and they did demonstrate that they were benefiting the most.

[Dr. Carlos Alran]

Yes, maybe.

[Dr. Marianne Kulin]

I think it's good to add that we also, we really. I think once you're a foot and ankle surgeon, you really want to know what you can tell your patients. And by that, if you have those values, it's nice that you can tell them a little bit more information about what their outcomes will be after one year.

[Pam Luke]

And that's great. This is all really helpful information. These are kind of the studies that we want to hear at these meetings to really bring back research to clinical application. So thank you for sharing all that. And I think these are really important studies. That is good work. And it's sharing to our surgeons for, I guess, for the population, for the cohort that, you know, you definitely want to include the ones that would benefit from the most. But for maybe the people who are beneath or just below or just miss that mark, what would you say to, based on your data and your information that you found from the study, how would you guide clinicians about using that information?

[Dr. Carlos Alran]

So thank you for that question. We did an extra analysis also, and we also show it here in the meeting. So we also analyzed patients who were like, poor responders, so to speak. And we saw, and we subdivided the AOS score, the 18 different levels it has, and we compare it from the beginning and compare it to one or two years. And we saw that they improved in all of their scores meaningfully. The effect size was pretty high in between 0.46 to 0.74. That's quite a lot. Early responders did it even better. But we can see here, and one of our final conclusions is that 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. But the message is who will benefit the most. So it's not like if you get an ankle replacement, it's not going to work for you. Probably it will if you have the end stage ankle arthritis, but if you are not, if you're doing not that bad, you should probably wait a little until your symptoms get worse. Great.

[Pam Luke]

Thank you guys so much and thank you for listening.

[Podcast Host]

Thank you for listening to the AOFAS Ortho Podcast, a Convey Med production. To learn more about joining our dynamic community of highly skilled orthopedic specialists, visit aofas.org.