Acute Compartment Syndrome Modeling with Sequential Infusion Shows the Deep Posterior Compartment Is Not Functionally Discrete

Evaluation of obesity and age as a predictive factor of lower extremity compartment syndrome: A national trauma data bank analysis

BACKGROUND

Risk factors of acute compartment syndrome (ACS) of the leg include tibial fractures followed by soft tissue injuries.

METHODS

Data collected from the National Trauma Data Bank (NTDB) between 2017 and 2019 were analyzed for adult patients with lower extremity fractures, including proximal tibia, tibial shaft, and distal tibia. The primary outcome was a diagnosis of ACS.

RESULTS

There were 1052/220,868 patients with lower extremity fractures with a concomitant diagnosis of compartment syndrome. Our study has shown that patients with a BMI of ≥30 had a lower incidence of compartment syndrome when compared with patients with a BMI of 25-29 and controlled for fracture type. Increased age ≥55 in males, and females between 65 and 84, also demonstrated a decreased risk. Proximal tibial fractures (n ​= ​54,696) were significantly associated with ACS compared to midshaft (n ​= ​42,153) and distal (n ​= ​100,432), p ​< ​0.0001.

CONCLUSION

We found that being overweight decreases risk for development of compartment syndrome in patients with lower extremity fractures. This big data study aids in establishing risk factors for development of ACS in adult trauma patients.

Continuous Compartment Pressure Monitoring Allows the Early Detection of Compartment Syndrome After Arterial Revascularization

Compartment syndrome (CS) occurs in several clinical scenarios. Reperfusion injury and tissue swelling are common causes. This can occur after trauma but also is seen post revascularization of extremities. CS is a difficult diagnosis to make in a timely fashion that avoids permanent tissue damage. The treatment for CS is immediate fasciotomy, but fasciotomy is not a complication-free procedure. Previous care pathways usually resulted in fasciotomy being performed in a disproportionate number of normal legs. These false positives and prophylactic releases are costly to the health system because of protracted hospital stays and increased surgery numbers. The desirable tool for surgeons would be one that decreases false positives and negatives while ensuring a diagnosis in a timely fashion with true positives. A new technology that allows continuous pressure monitoring seems to be the best aid to make a diagnosis. We present our experience in decreasing the time to diagnosis in a CS case post revascularization despite the neurological blockade.

Acute compartment syndrome of the lower limbs: Fasciotomy or dermofasciotomy? A cadaver study of compartment pressures

BACKGROUND

Acute compartment syndrome (ACS) of the lower limbs is a function-threatening event usually managed by extended dermofasciotomy. Closure of the skin may be delayed, creating a risk of complications when there is an underlying fracture. Early treatment at the pre-ACS stage might allow isolated fasciotomy with no skin incision. The primary objective of this study was to compare intracompartmental pressure (ICP) changes after fasciotomy and after dermofasciotomy. The secondary objectives were to evaluate potential associations linking the starting ICP to achievement of an ICP below the physiological cut-off of 10mm Hg and to determine whether the ICP changes after fasciotomy and dermofasciotomy varied across muscle compartments.

HYPOTHESIS

Fasciotomy with no skin incision may not provide a sufficient ICP decrease, depending on the initial ICP value.

MATERIAL AND METHODS

A previously validated model of cadaver ACS of the lower limbs was used. Saline was injected gradually to raise the ICP to>15mmHg (ICP15), >30mmHg (ICP30), and >50mmHg (ICP50). We studied 70 leg compartments (anterior, lateral, and superficial posterior) in 13 cadavers (mean age, 89.1±4.6years). ICP was monitored continuously. Percutaneous, minimally invasive fasciotomy consisting in one to three 1-cm incisions was performed in each compartment. ICP was measured before and after fasciotomy then after subsequent skin incision. The objective was to decrease the ICP below 10mmHg after fasciotomy or dermofasciotomy.

RESULTS

Overall, mean ICP was 37.8±19.1mmHg after the injection of 184.0±133.01mL of saline. In the ICP15 group, the mean ICP of 16.1mmHg fell to 1.4mmHg after fasciotomy (ΔF=14.7) and 0.3mmHg after dermofasciotomy (ΔDF=1.1). Corresponding values in the ICP30 group were 33.9mmHg, 4.7mmHg (ΔF=29.2), and 1.2mmHg (ΔDF=3.5); and in the ICP50 group, 63.7mmHg, 17.0mmHg (ΔF=46.7), and 1.2mmHg (ΔDF=15.8). Thus, in the group with initial pressures >50mmHg, the ICP decrease was greater after both procedures, but fasciotomy alone nonetheless failed to achieve physiological values (<10mmHg). The pressure changes were not significantly associated with the compartment involved (anterior, lateral, or superficial posterior) (p<0.05).

CONCLUSION

Under the conditions of this study, higher baseline ICPs were associated with larger ICP drops after fasciotomy and dermofasciotomy. Nevertheless, when the baseline ICP exceeded 50mmHg, fasciotomy alone failed to decrease the ICP below 10mmHg. Adding a skin incision achieved this goal.

LEVEL OF EVIDENCE

IV, experimental study.

Sensor technology usage in orthopedic trauma

Medicine in general is quickly transitioning to a digital presence. Orthopaedic surgery is also being impacted by the tenets of digital health but there are also direct efforts with trauma surgery. Sensors are the pen and paper of the next wave of data acquisition. Orthopaedic trauma can and will be part of this new wave of medicine. Early sensor products that are now coming to market, or are in early development, will directly change the way we think about surgical diagnosis and outcomes. Sensor development for biometrics is already here. Wellness devices, pressure, temperature, and other parameters are already being measured. Data acquisition and analysis is going to be a fruitful addition to our research armamentarium with the volume of information now available. A combination of broadband internet, micro electrical machine systems (MEMS), and new wireless communication standards is driving this new wave of medicine. The Internet of Things (IoT) [1] now has a subset which is the Internet of Medical Devices [2-5] permitting a much more in-depth dive into patient procedures and outcomes. IoT devices are now being used to enable remote health monitoring, in hospital treatment, and guide therapies. This article reviews current sensor technology that looks to impact trauma care.