RESUMO
OBJECTIVES: Spontaneous sternoclavicular joint infection (SSCJI) is a rare and poorly understood disease process. This study aims to identify factors guiding effective management strategies for SSCJI by using data mining. METHODS: An Institutional Review Board-approved retrospective review of patients from 2 large hospitals (2010-2022) was conducted. SSCJI is defined as a joint infection without direct trauma or radiation, direct instrumentation or contiguous spread. An interdisciplinary team consisting of thoracic surgeons, radiologists, infectious disease specialists, orthopaedic surgeons, hospital information experts and systems engineers selected relevant variables. Small set data mining algorithms, utilizing systems engineering, were employed to assess the impact of variables on patient outcomes. RESULTS: A total of 73 variables were chosen and 54 analysed against 11 different outcomes. Forty-seven patients [mean age 51 (22-82); 77% male] met criteria. Among them, 34 underwent early joint surgical resection (<14 days), 5 patients received delayed surgical intervention (>14 days) and 8 had antibiotic-only management. The antibiotic-only group had comparable outcomes. Indicators of poor outcomes were soft tissue fluid >4.5 cm, previous SSCJI, moderate/significant bony fragments, HgbA1c >13.9% and moderate/significant bony sclerosis. CONCLUSIONS: This study suggests that targeted antibiotic-only therapy should be considered initially for SSCJI cases while concurrently managing comorbidities. Patients displaying indicators of poor outcomes or no symptomatic improvement after antibiotic-only therapy should be considered for surgical joint resection.
