Factors Explaining the Severity of Acute Achilles Tendinopathy Among Runners: A Comprehensive Cross-Sectional Analysis
Bibliographic record
Abstract
Background: Achilles tendinopathy (AT) is a prevalent musculoskeletal injury among runners, accounting for approximately 10% of all running-related injuries. AT can result in persistent symptoms and impact the quality of life of runners. The Victorian Institute of Sport Assessment questionnaire (VISA-A) is a widely used self-reported tool for assessing severity of AT. However, the anatomic, biomechanical, psychological, and social factors that influence its score are still poorly understood. The aim of this study is to identify the factors that explain the severity of AT based on the VISA-A score in runners experiencing acute AT. Hypothesis: The VISA-A score will be explained by both biological and psychosocial factors. Study Design: Cross-sectional study. Level of Evidence: Level 4. Methods: Runners with AT were assessed within 3 months of symptoms onset. The potential explanatory factors assessed included sociodemographic characteristics and medical history, as well as psychosocial, physical, and anatomic (ultrasound imaging) variables. Results: Participants with AT (n = 84) demonstrated moderate impairments, with a mean VISA-A score of 62.8 (SD, 15.1). Three variables emerged as significant factors explaining AT severity: higher level of kinesiophobia and pain catastrophizing, pain during single-leg jumps, and increased cross-sectional Achilles tendon area on ultrasound imaging. These 3 variables had a moderate capacity ( R 2 = 0.47) to explain the VISA-A score. Conclusion: Pain during single-leg jumps, an increased cross-sectional tendon area assessed by ultrasound, and a high score on kinesiophobia and pain catastrophizing questions are associated with higher VISA scores. Clinical Relevance: These findings provide the basis for the development of more tailored interventions to improve the quality of life and function of runners with acute AT.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".