Tibial shaft fractures - to monitor or not? a multi-centre 2 year comparative study assessing the diagnosis of compartment syndrome in patients with tibial diaphyseal fractures
Bibliographic record
Abstract
AIMS: The aim of this study was to compare the outcome in patients who did and did not undergo continuous compartment pressure monitoring (CCPM) following a tibial diaphyseal fracture. PATIENTS AND METHODS: We performed a retrospective cohort study of 287 patients with an acute tibial diaphyseal fractures who presented to three centres over a two-year period. Demographic data, diagnosis, management, wound closure, complications, and subsequent surgeries were recorded. The primary outcome measure was the rate of short-term complications. Secondary outcomes were time to fasciotomy and split-skin grafting rates. RESULTS: Of the 287 patients in the study cohort, 171 patients underwent CCPM (monitored group; MG) and 116 did not (non-monitored group; NMG). There were 21 patients who developed ACS and underwent fasciotomy, with comparable rates in both groups (n=13 in the MG vs n=8 in NMG; p=0.82). There was no difference in the rate of complications between groups (all p>0.05). The mean time from admission to fasciotomy was 22.1hrs, with a mean time of 19.8hrs in the MG and 25.8hrs in the NMG (mean difference, 6hrs; p=0.301). One patient in the NMG required a below-knee amputation. There was a trend towards a reduced requirement for split-skin grafting post decompression in the MG (15% vs 50%; p=0.14). CONCLUSION: This study found no difference in the short-term complication rates in those patients that underwent CCPM and those that did not following a fracture of the tibial diaphysis. CCPM does appear to be safe with no increase in the rate of fasciotomies performed. There was a trend towards a reduced time to fasciotomy and a reduced rate of split skin grafting for wound closure with CCPM. LEVEL OF EVIDENCE: Level III (Diagnostic: Retrospective cohort study).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".