Fifty-seven years ago, Freeman¹ first described chronic ankle instability (CAI) in a group of patients who had a previous lateral ankle sprain (LAS). Since then, the field of ankle injury research has uncovered evidence of dysfunction and impairment across many domains, whether it is patient-reported outcomes that reflect quality of life or biomechanical and neuromuscular changes in gait. Many of these studies compare outcomes between people with and without CAI or LAS. These studies remain important; however, a limitation which is not unique to this field is that small sample sizes are used to draw inferences about larger populations. This special section is a collection of 4 papers that aimed to provide a wider scope of insight into the injury patterns and outcomes of patients with CAI or LAS. The studies used several approaches including prospective epidemiology, practice classification, and merging common data elements for secondary analysis. The purpose of this special section is to leverage the strength of larger sample sizes to advance our understanding of injury patterns and treatment responses in CAI and LAS.

The 4 papers in this special section used a few different approaches toward leveraging the power of large sample sizes in LAS and CAI research. The first paper by Brown et al² is a prospective observational report of ankle injuries and health care utilization from the PAC-12 conference in the NCAA. Prospective studies of this nature often report from large sample sizes, but the novel aspect is how the data collection for this study was built into the point of care, wherein the health care providers were the ones reporting the injuries to a central database, allowing a better classification of both injury type and health care utilization. Similarly, a paper by Lam et al³ assessed the Foot and Ankle Ability Measure (FAAM) in the first 2 weeks following a LAS. This was a report from the Athletic Training Practice-Based Research Network which uses point-of-care data from health care providers to identify trends in patient outcomes using data from real patients rather than controlled laboratory studies. Both studies show that collecting data at the source can lead to novel insights and over time grow to larger sample sizes with minimal effort on the health care providers’ end due to the increased use of electronic medical records. The remaining 2 studies^4,5 were able to gain insight into LAS and CAI by leveraging common inclusion criteria endorsed by the International Ankle Consortium.⁶ These author groups pooled together data from previously published studies and performed participant-level analysis to identify trends in treatment response and links between injury severity and health-related quality of life. This approach led to sample sizes much larger than those reported by the individual studies and can generate an answer that is more broadly representative of these heterogeneous conditions.

The 4 papers in this special section highlight the benefits of larger samples of the CAI patient population by casting a wide net; however, there is still room to improve. There are 2 critical steps that can be taken that may facilitate long-term data collection and improve our understanding of the population of CAI and LAS. The first step to reinforce the bridge between clinical and laboratory research is the creation of common data elements that should be collected in CAI research. The last decade has seen this field benefit from the efforts of the International Ankle Consortium creating common definitions in the field as well as recommended minimum inclusion criteria for participants with CAI.^6,7 The significance of having a universal standard in research should not go unnoticed, as it allows for higher confidence and greater ease in synthesizing and appraising the collective knowledge from primary research studies (eg, meta-analysis). Creating a set of common data elements that represent outcomes which capture information important to stakeholders, including patients, clinicians, and researchers, could facilitate translation of laboratory-controlled clinical trials to clinics across the world. These efforts are in development for ankle osteoarthritis.⁸ The second critical step would be to establish minimal clinically important difference (MCID) cutoffs for these measures that reflect significant change or improvement for core outcome measures. These values are likely specific to these conditions, for example, how much of an improvement in dorsiflexion range of motion is important to a patient following an acute LAS? Some outcomes already have known values for a broad population; the FAAM has a published MCID of 8 and 9 points for the activities of daily living and sports scales, respectively.⁹ The MCID for the FAAM was established using a heterogeneous sample of various foot and ankle conditions,⁹ so it may not accurately represent clinically meaningful change in people with LAS or CAI. The studies by Lam et al³ and Powden et al⁴ may have reported different findings if there were LAS- or CAI-specific MCIDs for common outcome measures. Establishing these cutoffs could facilitate future studies investigating the overall effectiveness of therapeutic interventions in patients with LAS and CAI.

By establishing common data elements and MCIDs, we may be able to allow for easier synthesis of results and large-scale analyses that could advance our understanding of this heterogeneous condition. Such advances could lead to a new era where we are able to understand better collectively the short- and long-term prognosis of this injury and limit on the associated life-long consequences. These 4 papers in this special section have highlighted that ankle injuries often lead to time lost from participation, have early rapid but not full recovery, may be linked to worsened health status, and do not universally work in all patients.