Clinical Trial of a New Continuous Compartment Pressure Monitoring to Aid in the Diagnosis of Acute Compartment Syndrome
Bibliographic record
Abstract
OBJECTIVES: To evaluate a new compartment pressure monitor reporting continuous pressures and its contribution to Acute Compartment Syndrome (ACS) diagnosis. METHODS: Design: Multicenter, non-randomized, prospective study. SETTING: Six Level-I Trauma Centers. PATIENT SELECTION CRITERIA: Enrolled were patients with acute long bone fractures (OTA 11-13, 2R, 2U, 31-33, and 41-43) where the Micro Electric Mechanical Sensor (MEMS) device was inserted either pre- or post-operatively into the compartment most likely to develop ACS, as deemed by the surgeon. Intracompartmental pressures (ICP) were continuously measured for up to 18 hours (as indicated by the FDA and Health Canada); clinical signs were simultaneously assessed for canonical compartment syndrome signs. OUTCOME MEASURES AND COMPARISONS: The primary measurement outcomes were ease of use, accuracy, and safety of the device across all participating sites. Ease of use was assessed through surveys completed by surgeons, which evaluated their confidence in the device's functionality and usability. Accuracy was determined by analyzing patient outcomes, using surgical findings and clinical resolution as the gold standards, to assess whether the device's results corresponded to true positive and true negative cases of compartment syndrome. Feasibility was defined as the device's ability to integrate into the clinical workflow, operate reliably under typical conditions, and provide actionable data for ACS diagnosis. The secondary outcomes included continuous intracompartmental pressure (ICP) measurements and their diagnostic value. Sensitivity and specificity were evaluated by comparing continuous ICP data with clinical assessments based on the "6 P's" (pain, pallor, paresthesia, pulselessness, poikilothermia, and paralysis) to determine their combined utility in diagnosing ACS. RESULTS: A total of 100 patients, 68 males and 32 females with an average age of 42 years old (17-80 years old), were enrolled. All of the patients had suffered a fracture, 25 proximal tibias (OTA/AO-41), 40 midshaft tibias (OTA/AO42), 13 distal tibias (OTA/AO43), 11 forearms (OTA/AO 2R.2U), 6 femurs (OTA/AO31-33), 5 humerus (OTA/AO 11-13). Eighty-nine patients received the MEMS device post-operatively and 11 patients pre-operatively. 93% of participating surgeons reported confidence in the device's function and ease of use. Pressures were measured on average for 16h36 (3h-18h). No complications were reported. Post-operative ICPs (25.4 mmHg) were higher (p =0.0462) on average than pre-operative ICPs (18.9 mmHg). Patients that did not develop Compartment Syndrome had their post-operative pressures trend down after 4 hours (23.8mmHg). Sensitivity and specificity analyses of ICP alone, delta P alone, pressure trends alone, or a combination of the three metrics were conducted using patient outcomes as the gold standard for diagnostic accuracy. The trend of the curve in continuous monitoring pressure measurements proved more reliable than a single absolute pressure value in aiding in the correct diagnosis of ACS deviating from standard ACS diagnosis literature The MEMS device allowed earlier diagnosis of ACS by 4 hours (. When continuous pressure measurement was combined with standard clinical examination, the sensitivity and specificity reached 100%. CONCLUSIONS: The MEMS-based device reliably enabled continuous compartment pressure monitoring in all the study institutions. Further examination of continuous trends and accompanying perfusion pressure could allow surgeons the clinical adjunct to diagnose ACS many hours earlier than clinical signs alone. LEVEL OF EVIDENCE: Level II - Prospective study.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".