Table 3.
Comparison of cohorts identified by algorithms for definite or probable pseudogout applied to the final datamart of 30,089 patients
≥1 billing code | Presence of CPP crystals | Combined algorithm: topic modeling approach and/or presence of CPP crystals | |
---|---|---|---|
Number of patients (n) | 12,035 | 1,630 | 2,490 |
Age at last medical visit, years | 72.8 (15.6) | 76.4 (13.0) | 76.3 (12.8) |
Female | 55.6 | 50.6 | 50.8 |
Race | |||
White | 84.7 | 79.5 | 81.0 |
African American | 4.8 | 8.8 | 7.8 |
Other | 10.5 | 11.7 | 11.2 |
≥1 pertinent billing code | 100.0 | 72.6 | 74.1 |
≥1 NLP concept “pseudogout” | 34.3 | 86.1 | 90.8 |
Synovial fluid crystal analysis performed, regardless of result | 18.9 | 100.0 | 86.0 |
Synovial fluid CPP crystals present | 9.8 | 100.0 | 65.5 |
Prescription medications in EHR | |||
Colchicine | 17.3 | 35.1 | 43.4 |
NSAID | 59.1 | 69.1 | 72.7 |
Oral glucocorticoids | 44.4 | 62.9 | 67.4 |
Presented as mean (SD) or percentage unless otherwise indicated