Purpose
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 IRB-approved retrospective review of patients from two large hospitals (2010 to 2022) was conducted. Spontaneous sternoclavicular joint infection 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, orthopedic 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 analyzed 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 spontaneous sternoclavicular joint infection 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 (central image).