Purpose: To advance the understanding of the epidemiology and treatment outcomes of congenital upper limb differences, a multicenter registry for Congenital Upper Limb Differences (CoULD) was established. After 4 years of recruitment, we sought to examine whether the relative frequency of congenital conditions compares with prior cross-sectional research and how the data have matured over time by (1) comparing our registry population with previous studies in similar populations and (2) evaluating the change over time of relative frequencies of selected conditions within the CoULD registry cohort, specifically to investigate for registry inclusion effects.
Methods: Data from the 2 founding centers in the CoULD registry were analyzed over a 4-year period. We compared patients included in the CoULD registry against 2 prior studies by matching each condition according to the Oberg-Manske-Tonkin classification system. The relative frequency of 4 representative conditions was calculated to evaluate change over time and to determine when the inception cohort effect diminished.
Results: The CoULD cohort of 1,381 patients was found to have notable differences compared with a 1-year cross-sectional cohort from the U.S. Midwest and a Swedish birth registry. Each of these registries had differences from the CoULD population in prevalence for approximately 33% of the diagnosis categories. The CoULD registry identified and included more pathologies of late presentation and those that do not commonly require surgical care. Changes in relative frequencies of incident and prevalent conditions, the registry inclusion effect, occurred early and stabilized by the third year.
Conclusions: The CoULD registry captures a different relative frequency of conditions than prior studies in similar populations. The findings highlight the CoULD registry may be a more accurate representation of clinical practice in tertiary referral centers; however, it is important to note that there was a registry inclusion effect identified.
Clinical relevance: Inclusion criteria are an important consideration with any longitudinal data collection method and data should display stability prior to registry reporting.
Keywords: Congenital difference; database; inclusion effect; prevalence; relative frequency.
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