Symptoms-Based Clinical Algorithm for the Diagnosis and Treatment of Pelvic Congestion Syndrome

Background: Symptomatic Pelvic Congestion Syndrome (PCS) is often underdiagnosed and undertreated. We investigate a symptoms-based screening algorithm and treatment algorithm focused on position and location of pain for each type of PCS. Methods: This study is a retrospective, single-institution, multi-site review of 343 female patients who presented with pelvic pain. Results: Following a symptoms-based algorithm, 302 patients fulfilled criteria for inclusion; 299 patients had positional symptoms with a positive predictive value (PPV) of 97.99%, sensitivity of 98.99% and Odds Ratio (OR) of 48.83 (p=0.0003) while duplex ultrasonography (DUS) had a PPV of 98.84%, sensitivity of 86.49%, and OR of 6.4 (p=0.0396) confirmed by contrast venography. Patients with Type I PCS were treated with embolization and 87.5% reported total relief of anterior symptoms. Patients with Type II PCS were treated with embolization and/or vascular stenting based on their associated lesion, May-Thurner syndrome or Nutcracker syndrome, and 88.54% reported ≥50% symptom relief and 59.03% reported ≥80% symptom relief. Full treatment resulted in a mean “overall satisfaction” score of 96.07%. Conclusions: Algorithmic approaches are essential for PCS evaluation, diagnosis, and treatment. Patients with positional pelvic symptoms consistent with PCS should undergo diagnostic venography. Distinguishing between the types of PCS and using symptoms as a guide may be beneficial over a “one-size-fits-all” approach.