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 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.