Can Near-Infrared Spectroscopy (NIRS) or Intramuscular Glucose Levels Detect Impaired Leg Compartment' Perfusion?

Inclusion criteria: * Patient's age: 18 - 75 years old * Diagnosis of tibial fracture or fracture-dislocation with diagnosis of acute compartment syndrome AND/OR diagnosis of concomitant vascular injury with documented loss of pulses in the leg below the knee * Unilateral injury (i.e. only one leg is affected) * Depth of anterior compartment of the leg \< 2.5 cm (as measured by ultrasound) Study size - 7-10 patients Procedure of enrollment: When diagnosis of tibial fracture with vascular compromise or established ACS is made by the ED physician and confirmed by the Orthopedic surgeon, study team will be notified immediately (by the orthopedic service). Study team member will approach the study candidate, explain the purpose of the study and obtain the informed consent. After obtaining the consent, pre-scanning of the anterior compartment of the leg will be performed at bedside to measure the depth between the surface of the skin and the muscle. If depth of the anterior muscular compartment found to be \<2.5 cm, NIRS sensors will be applied to the skin of the broken leg at that location, and to the corresponding location on the uninjured leg. Sensors will be connected to the monitor and readings will be obtained until patient enters the OR. Sensor will be removed from the skin of the injured extremity, but will stay in place on uninjured leg to describe tissue perfusion changed which occur during anesthesia. When incision is made by the surgeon, upon entering the anterior muscular-fascial compartment, blood sample will be obtained from the cut surface of the muscle for glucose concentration measurement. At the same time fingerstick will be performed and capillary glucose will be measured. Both glucose readings will be recorded. Before entering the anterior compartment, intracompartmental pressure measurement will be performed by the surgeon using a sterile arterial line catheter attached to the transducer connected to the anesthesia monitor, or with the Striker device - at surgeon discretion. At completion of the surgery, sensor will be re-applied on the anterior compartment of the injured leg before dressing application. Monitoring of both extremities will continue for 72 hrs following surgery, (if condition of the operative extremity permits presence of the sensor). All available data stored in the monitor then will be downloaded and analyzed. (Please see more specific time points below). Data analysis: NIRS readings will be collected at the following time=points: * "time 0" (after sensors' application) - both legs * "Time in the OR - surgery" - for uninjured leg only - 1 hr after induction of general anesthesia * "Time in the OR - post surgery", after emergence from anesthesia - both legs * Every 6 hrs thereafter for the first 24 hrs, * Every 12 hrs for subsequent 48 hrs. Graphic analysis: Superimposed graphs (trajectories) of all patients in each group (with vascular injury and without vascular injury). Means will be calculated for the injured and uninjured leg for all time points as mentioned above. Graphs for means will be also created and analyzed. Additionally, the following data will be collected: demographic data ( patient's age, gender), fracture diagnosis, time from admission to surgery, type of surgery performed (external temporary fixation, internal fixation with intramedullary nail vs with plate(s)). Data will be downloaded to the encrypted thumb-drive and transferred to a password-protected electronic file on HSC server. Only HRRC-approved investigators will have access to the files. After completion of the study all electronic data will be destroyed. Temporary data sheets will be used to facilitate data collection. They will be stored in the locked cabinet in the Anesthesiology department offices, away from patient areas. Upon enrollment patients will be given numbers from 1 to 10. After complete set of data is obtained, each patient will be de-identified. Should need arise to refer back to the electronic data, patients will be only identified by their numbers (from 1 to 10) and their respective sets of data.