Compartment Pressure Curves Predict Surgical Outcome in Chronic Deep Posterior Compartment Syndrome

Background: Results of surgery for chronic exertional compartment syndrome (CECS) of the lower leg deep posterior compartment are inferior compared with other types of CECS. Factors predicting success after surgery are unknown. Purpose: To study the prognostic value of preoperative compartmental pressure curves in patients receiving surgery for deep posterior compartment CECS. Study Design: Case series; Level of evidence, 4. Methods: Intracompartmental pressures (ICPs) of patients with deep posterior lower leg CECS were obtained at 4 time points (ie, before, immediately after, and 1 and 5 minutes after a standard exercise challenge test). Area under the 4-point pressure curve was calculated. Patients received a questionnaire investigating residual symptoms after surgery. Results: A complete data set was available for 52 patients (men, n = 23; age, 33 ± 14 years). They rated their 3-month postoperative clinical outcome as excellent (14%), good (38%), fair (35%), or poor (13%). Outcome at 3 months was related to the area under the preoperative 4-point pressure curve (excellent, 127 ± 28; good, 113 ± 25; fair, 100 ± 22; and poor, 88 ± 15; P = .005; odds ratio [OR], 1.04; 95% confidence interval [CI], 1.01-1.08). At the long-term follow-up (39 ± 24 months), all 5 cardinal symptoms (pain, tight feeling, cramps, weakness, and diminished sensibility) were greatly attenuated (P < .001) in the successfully operated group. Long-term success was 48%. Delay in diagnosis was related to poor outcome (P = .04). Correlations between pressures/area under the 4-point pressure curve and long-term outcome were not significant, however. Conclusion: Preoperative measured intracompartmental pressures obtained in rest and after a standard exercise test may predict success of surgery for deep posterior compartment CECS of the lower limb. Further standardizing of preoperative pressure protocols may confirm that compartmental pressure analysis has diagnostic as well as predictive properties.