Investigating the incidence and magnitude of heterotopic ossification with and without joints involvement in patients with a limb fracture and mild traumatic brain injury
Bibliographic record
Abstract
Objectives This study seeks to evaluate the incidence rate of heterotopic ossification (HO) formation in patients afflicted by an isolated limb fracture (ILF) and a concomitant mild traumatic brain injury (mTBI). Methods The current study is an observational study including ILF patients with or without a concomitant mTBI recruited from an orthopedic clinic of a Level 1 Trauma Hospital. Patients were diagnosed with a mTBI according to the American Congress of Rehabilitation Medicine (ACRM) criteria. Radiographs taken on average 3 months post-trauma were analyzed separately by two distinct specialists for the presence of HO proximally to the fracture site (joints or extra joints). Both raters referred to Brooker's and Della's Valle's classification to establish signs of HO. First, analyses were conducted for the full sample. Secondly, a matched cohort was used in order to control for specific factors, namely age, sex, type of injury, and time elapsed between the accident and the analyzed radiograph. Results The full sample included a total of 183 patients with an ILF (94 females; 47.5 years old), of which 50 had a concomitant mTBI and 133 without. Radiographic evidence of HO was significantly higher in patients with an ILF and a mTBI compared to ILF patients (X 2 = 6.50; p = 0.01). The matched cohort consisted of 94 participants (i.e.; 47 patients from the ILF + mTBI group and 47 patients from the ILF group). Again, ILF + mTBI patients presented significantly higher rates of HO signs in comparison to ILF patients (X 2 = 3.69; p = 0.04). Presence of HO was associated with prolonged delays to return to work (RTW) only in ILF + mTBI patients (F = 4.055; p = 0.05) but not in ILF patients (F = 0.823; p = 0.37). Conclusions Study findings suggest that rates of HO are significantly higher proximally to fracture sites when ILF patients sustain a concomitant mTBI, even after controlling for factors known to influence HO. Moreover, results show that HO is associated with a prolonged RTW only in ILF patients with a concomitant mTBI but not in ILF-only patients. The impact of mTBI on HO formation warrants further attention to detect early signs of HO, to identify shared physiopathological mechanisms and, ultimately, to design targeted therapies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".