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Record W4415439103 · doi:10.1302/1358-992x.2025.10.127

MULTICENTRE CLINICAL TRIAL OF A CONTINUOUS COMPARTMENTAL PRESSURE DEVICE IN PATIENTS WITH LONG BONE FRACTURES

2025· article· en· W4415439103 on OpenAlexaffabout
Ross Leighton, M. Balhareth, Kelly Trask, Job N. Doornberg, Pierre Guy, Jason Hall, A-R. Lawendy, Aaron Liew, P. Schneider

Bibliographic record

VenueOrthopaedic Proceedings · 2025
Typearticle
Languageen
FieldMedicine
TopicMuscle and Compartmental Disorders
Canadian institutionsQueen Elizabeth II Health Sciences Centre
Fundersnot available
KeywordsClinical trialProspective cohort studyBlood pressureCompartment (ship)Orthopedic surgeryPerfusion

Abstract

fetched live from OpenAlex

Acute compartment syndrome (ACS) is an orthopaedic emergency that can develop after a wide array of etiologies. Continuous pressure monitoring may contribute to the early diagnosis of ACS. This multicenter prospective study evaluated a new compartmental pressure monitor that reports continuous pressures in real-time. Patients with acute long bone fractures were prospectively enrolled from six Canadian academic centers after obtaining informed consent. The study device was inserted in the compartment deemed by the attending surgeon most likely to develop ACS. Intracompartmental pressure (ICP) was continuously measured for up to 18 hours. Patients were simultaneously monitored for clinical signs of ACS and their vitals and pain levels were recorded. Compartment pressures were plotted along with perfusion pressures for the duration of the device measurements. Patients were grouped by timing of device insertion (pre-operative or post-operative) and by AO/OTA fracture classification to look for trends in ICP over time and correlations with clinical data. One hundred patients were enrolled between November 2020 and November 2022. There were 68 males and 32 females. The mean age was 41 years (range, 17–80). Eighty-nine patients received the device post-operatively and eleven received it pre-operatively. There were no complications related to the use of the device. Consistent with previously published literature (McQueen et al. J Bone Joint Surg Br. 1990;72(3):395–7), the post-operative ICPs were found to be considerably higher than pre-operative ICPs (as shown in Table 1) but trended downwards very quickly if the ICP was not clinically significant. One patient developed ACS post-operatively; their pressures exhibited the same higher initial baseline measurements, but instead of steadily decreasing, the pressure plateaued at a relatively high level and then stayed consistently above the perfusion pressure (Figure 1). These data suggest that the trend of the curve in continuous pressure monitoring appears to be more significant than absolute pressure – which is a distinct change in understanding from the standard literature on diagnosing ACS. One patient with a fractured tibia illustrated a steep trend upwards in ICP pre-operatively, which pre-dated clinical symptoms by four hours. The patient underwent fasciotomy for ACS at the time of fracture fixation. Our results suggest that this device is a reliable and easy to use commercially available option for continuous pressure monitoring. We found that post-operative ICP can be higher than would have been acceptable in the literature, but usually dropped rapidly. These findings agree with the current understanding on the difference between pre-operative and post-operative ICPs. Further examination of the continuous upwards or downwards trends in compartmental pressure monitoring and the accompanying perfusion pressures should allow us to diagnose elevated ICP many hours earlier than would be clinically possible with the usual symptom complex of ACS. This could reduce the chance of a false positive or a false negative in dealing with patients at high risk of ACS, thus preventing unnecessary fasciotomies and drastically reducing the chance of muscle necrosis during the management of these difficult long bone fractures. For any figures or tables, please contact the authors directly.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.313
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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