Latent class analysis for exploring distribution patterns of primary superficial venous insufficiency.

Background: This study aims to identify specific segmental distribution patterns of lower extremity chronic venous disease based on latent class analysis of Doppler mapping results. Methods: A total of 1,871 lower extremities of 1,218 treatment-naive patients (536 males, 682 females; mean age 45.4 years; range, 21 to 87 years) with chronic venous disease referred for Doppler examination between September 2009 and August 2018 were included. Refluxing superficial venous segments of the lower extremities were mapped and recorded in database in 10 distinct anatomic locations as follows: saphenofemoral junction and proximal greater saphenous vein, mid and distal thigh greater saphenous vein, anterior and posterior accessory saphenous veins, proximal and distal calf greater saphenous vein, saphenopopliteal junction and proximal lesser saphenous vein, distal lesser saphenous vein, and intersaphenous veins including Giacomini's vein. Repeated examinations were excluded. The latent class analysis was applied to identify any possible anatomic distribution patterns of chronic venous disease. Results: Bayesian information criteria revealed three latent class models fit for refluxing segment distribution as follows: 58.2% (n=1,089) were above-the-knee greater saphenous vein segments including saphenofemoral junction (pattern 1); 29.3% (n=548) were below-the-knee greater saphenous vein segments (pattern 2); and 12.5% (n=234) were lesser saphenous vein segments and intersaphenous veins including Giacomini's vein (pattern 3). There was no age- or sex-specific differences in the chronic venous disease distribution patterns. Conclusion: The latent class analysis, by identifying previously unseen subgroups within the sampled population, provides a new approach to classification of reflux patterns in chronic venous disease. Identification of latent classes may provide understanding of different pathophysiological bases of venous reflux and more optimal planning for interventions.