Stress fractures: diagnosis and management in the primary care setting
Bibliographic record
Abstract
Stress fractures or fatigue fractures are common overuse injuries that occur following repetitive bouts of mechanical loading to bones. They most often occur in the weight-bearing bones of the lower limbs. Their diagnosis can be challenging due to their insidious onset and requirement for imaging to confirm a diagnosis. The risk factors for such injuries include an increase in load, which can be from an increase in volume, intensity, or duration of exercise, abnormal biomechanical factors, and reduced bone mineral density. Their management can be relatively straightforward, but symptoms can persist for many months if load management is not adhered to. If missed, the clinical consequences can be substantial, particularly when involving the femoral neck. Stress fractures occur when bones undergo repetitive stress at a rate greater than their ability to remodel. The initial microtrauma can cause symptoms, such as a pain and swelling, without the presence of a fracture on X-rays. This phenomenon is known as a ‘stress reaction’ and cannot be detected on X-rays in the early stages. If the causative factor continues, this can cause the cortex of the bone to weaken, leading to crack initiation. If this crack propagates across the bone then a complete fracture can occur. Stress fractures should not be confused with insufficiency fractures, which occur when physiological abnormal bone fractures under normal load (that is, secondary to osteoporosis). The incidence of stress fractures in the general population is not clear and most research has studied their incidence in the athletic …
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".