Postsurgical deep musculoskeletal infections are a major clinical problem in Orthopaedic Surgery. A serum-based nomogram, which can objectively risk-stratify patients, and aid surgeons in delineating infection risk associated with orthopedic surgical interventions, would be immensely helpful. Here, we constructed a multi-parametric nomogram based on serum anti-Staphylococcus aureus antibody responses, patient characteristics including demographics and standard clinical tests. This nomogram was formally tested in a prospective cohort study comparing 303 hospitalized patients with culture-confirmed S. aureus infection compared with a cohort of 223 healthy screened preoperative patients. Serum anti-S. aureus antibody responses, standard of care clinical tests, and patient demographic data were utilized to perform multivariate logistic regression analysis to quantify the presence of infection and adverse outcome using odds ratios (OR) and to assess predictive ability via area under the ROC curve (AUC). At enrollment, high anti-S. aureus IgG titers were predictive of infection. Remarkably, low serum albumin was found to be significantly associated with infection (OR = 479.963, 95% CI 61.59 - 3740.33, p < 0.0001) and this finding was surprisingly higher than BMI or HbA1c-associations. Combining all risk factors in the nomogram yielded a diagnostic AUC of 0.949 for predicting S. aureus infection. Our results indicate that a serum-based multi-parametric nomogram can be useful in diagnosing S. aureus infections, and importantly, malnourishment is significantly associated with these infections.
Keywords: Staphylococcus aureus; albumin; antibiotics; immunoassay; orthopaedic infections; osteomyelitis; serum anti-Staphylococcal antibodies.
© 2020 The Authors. Journal of Orthopaedic Research® published by Wiley Periodicals LLC on behalf of Orthopaedic Research Society.