The Clinical Diagnosis and Treatment of an Anterior Calcaneal Process Fracture Overlooked on Imaging: A Case Study
Bibliographic record
Abstract
BACKGROUND: Anterior calcaneal process fractures are often overlooked on radiographs. Given a similar clinical presentation, these fractures are frequently misdiagnosed as lateral ankle sprains. CASE DESCRIPTION: A 43-year-old male was referred to physical therapy following an inversion ankle injury. Sites of interest identified on initial radiography were asymptomatic, including an os trigonum and possible dorsal talar avulsion fracture. Screening with the Ottawa ankle rules was negative. His clinical presentation was similar to an inversion ankle sprain with concordant swelling and pain. OUTCOME: Subsequent ankle imaging was completed following a lack of expected clinical progression, revealing a subtle calcaneal fracture overlooked on initial imaging. The patient was referred to orthopedics and managed in a boot with partial weight-bearing. He was released to full weight-bearing 6 weeks later with resolution of pain and gradual recovery of normalized range of motion and strength. DISCUSSION: Improving proficiency of interpreting radiograph images as physical therapists, application of the four-eyes principle when reading images, and awareness of potential fractures with negative Ottawa ankle rules screening are beneficial to early and accurate diagnosis and treatment of foot fractures. JOSPT Cases 2025;5(1):12-17. Epub 20 December 2024. doi:10.2519/josptcases.2024.0086
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".