Chronic Exertional Compartment Syndrome: A Review of Literature

Chronic exertional compartment syndrome (CECS) is a serious, yet underdiagnosed condition that can cause severe lower extremity pain in running athletes. CECS is a transient increase in compartment pressure leading to severe pain, paresthesia, and vascular compromise. Understanding the detailed anatomy is paramount to proper diagnosis and treatment. Diagnosis is made with measuring compartments pressures before and after exercise at certain time intervals. When properly diagnosed and treated, CECS can be appropriately managed and patients can return to their previous level of activity.

Predicting surgical outcomes for chronic exertional compartment syndrome using a machine learning framework with embedded trust by interrogation strategies

Chronic exertional compartment syndrome (CECS) is a condition occurring most frequently in the lower limbs and often requires corrective surgery to alleviate symptoms. Amongst military personnel, the success rates of this surgery can be as low as 20%, presenting a challenge in determining whether surgery is worthwhile. In this study, the data of 132 fasciotomies for CECS was analysed and using combinatorial feature selection methods, coupled with input from clinicians, identified a set of key clinical features contributing to the occupational outcomes of surgery. Features were utilised to develop a machine learning model for predicting return-to-work outcomes 12-months post-surgery. An AUC of 0.85 ± 0.08 was achieved using a linear-SVM, trained using 6 features (height, mean arterial pressure, pre-surgical score on the exercise-induced leg pain questionnaire, time from initial presentation to surgery, and whether a patient had received a prior surgery for CECS). To facilitate trust and transparency, interrogation strategies were used to identify reasons why certain patients were misclassified, using instance hardness measures. Model interrogation revealed that patient difficulty was associated with an overlap in the clinical characteristics of surgical outcomes, which was best handled by XGBoost and SVM-based models. The methodology was compiled into a machine learning framework, termed AITIA, which can be applied to other clinical problems. AITIA extends the typical machine learning pipeline, integrating the proposed interrogation strategy, allowing to user to reason and decide whether to trust the developed model based on the sensibility of its decision-making.

Comparison of 2 Fasciotomes for Treatment of Patients With Chronic Exertional Compartment Syndrome of the Anterior Leg

Background: Chronic exertional compartment syndrome (CECS) of the anterior leg compartment (ant-CECS) is frequently treated with a minimally invasive fasciotomy. Several operative techniques and operative devices exist, but none have been compared in a systematic and randomized manner. Purpose: To compare efficacy, safety, and postoperative pain of a novel operative device (FascioMax fasciotome) with a widely accepted device created by Due and Nordstrand (Due fasciotome) during a minimally invasive fasciotomy for ant-CECS. Study Design: Randomized controlled trial; Level of evidence, 2. Methods: Patients with bilateral isolated ant-CECS between October 2013 and April 2018 underwent a minimally invasive fasciotomy using the FascioMax fasciotome in 1 leg and the Due fasciotome in the contralateral leg in a single operative session. Symptom reduction at 3 to 6 months and >1 year, postoperative pain within the first 2 weeks, peri- and postoperative complications, and ability to regain sports were assessed using diaries, physical examination, and timed questionnaires. Results: Included in the study were 50 patients (66% female; median age, 22 years [range, 18-65 years]). No differences between the devices were found in terms of perioperative complications (both had none), minor postoperative complications including hematoma and superficial wound infection (overall complication rate: FascioMax, 8% vs Due, 6%), or reduction of CECS-associated symptoms at rest and during exercise. At long-term follow-up (>1 year), 82% of the patients were able to regain their desired type of sport, and 67% (33/49) were able to exercise at a level that was comparable with or higher than before their CECS-associated symptoms started. Conclusion: Both the FascioMax and the Due performed similarly in terms of efficacy, safety, and levels of pain within the first 2 weeks postoperatively. Registration: NL4274; Netherlands Trial Register.

Forearm compartment pressures and grip strength in elite motorbike racers with chronic exertional compartment syndrome

Background Remarkably little research has been published on chronic exertional compartment syndrome (CECS) of the forearm. This study investigated forearm flexor compartment pressure pre- and post-exercise in elite motorbike racers clinically diagnosed with CECS and assessed their grip strength before and after arm pump exercise. Methods Elite motorbike riders with a clinical diagnosis of CECS of the right forearm when racing were recruited during the opening rounds of a British Superbike season. Their grip strength and forearm flexor compartment pressures were measured before and after a set exercise programme. Results Of the 11 riders recruited to the study, 10 completed the full testing regime. The mean pre-exercise forearm compartment pressures [11.7 mmHg (range 7–17 mmHg)] significantly increased post-exercise [30.5 mmHg (range 15–45 mmHg)], with a mean increase of 18.80 mmHg (P < 0.0001). The mean pre-exercise grip strength [50.61 mmHg (range 37–66.7 mmHg)] decreased post-exercise to [35.62 mmHg (range 17.1–52.5 mmHg)], a mean decrease of 14.99 mmHg (P < 0.0001). Conclusion There is a statistically significant increase in the forearm flexor compartment pressures in elite motorbike racers with CECS, but with marked variability of these values. Grip strength decreases statistically significantly following onset of symptoms of CECS of the forearm.

MRI findings in chronic exertional compartment syndrome of the forearm: Using signal intensity ratio as a diagnostic tool

Background: Chronic exertional compartment syndrome (CECS) of the forearm is a rare but important cause of morbidity amongst athletes involved in strenuous upper limb activities. The diagnosis remains challenging due to the absence of objective, reproducible diagnostic studies.Objectives: To assess and quantify signal intensity (SI) changes of involved muscles in patients with CECS of the forearm compared to healthy control subjects competing in similar sporting disciplines. Also, to objectively measure MRI SIs within muscle compartments when using a pre- and post-exercise regime and calculating a signal intensity ratio (SIR) between post- and pre-exercise studies.Method: The study retrospectively examined MRI scans of patients treated for CECS of the forearm and compared these to the MRI scans of asymptomatic high-level rowers. A specific, reproducible pre- and post-exercise MRI scanning protocol was utilised in both patient and control subjects between 2011 and 2020. Signal intensities were evaluated pre- and post-exercise in involved muscle groups and ratios were calculated.Results: A total of 86 SIs were measured (43 pre- and 43 post-exercise) in nine study participants (five patients and four controls). After post:pre-exercise comparisons, a statistically significant difference was found between control and patient groups (p = 0.0010). The extensor carpi radialis, flexor digitorum profundus and flexor digitorum superficialis muscles were most commonly involved.Conclusion: This study confirms that significant SI changes are apparent in patients with CECS of the forearm when making use of a standardised pre- and post-exercise MRI protocol. Furthermore, SIR may be used to accurately diagnose CECS of the forearm.