Predictive Factors of Surgical Site Infection in Prosthetic Joint Surgery: A Prospective Study on 760 Arthroplasties

The success of total joint arthroplasty (TJA) has led to consistent growth in the use of arthroplasty in progressively younger patients. However, more than 10 percent of patients require revision surgery due to implant failure caused by aseptic or septic inflammation. Among the latter, surgical site infection (SSI) represents one of the worst complications of TJA, potentially resulting in the removal of the prosthesis. The aim of our study was to identify potential risk factors for SSIs in a population of patients undergoing TJA.

TJA were prospectively recruited at Casa di Cura Santa Maria Maddalena from February 2019 to April 2020. Age, sex, major comorbidities, American Society of Anesthesiologists (ASA) class, length of surgery, type of surgical suture, total hospital length of stay, and clinical laboratory data were collected. The study population was then divided into two groups: Group A, normal postoperative course, and Group B, patients who developed SSI at follow-up (17-25 days).

25/760 (3.3%) patients developed SSIs at follow-up. Clinical and demographic parameters were not different between the two groups. Total leucocyte and neutrophil values at discharge resulted to be significatively higher in Group B compared to Group A (p = 0.025 and p = 0.016, respectively). Values of 7860/μL for total leucocyte and 5185/μL for neutrophil count at discharge significantly predicted the future development of SSI (AUC 0.623 and AUC 0.641, respectively; p < 0.05) independently from confounding factors (total leukocytes: O.R. = 3, 69 [95% C.I. 1,63-8,32]; neutrophils: O.R. = 3, 98 [95% C.I. 1,76-8,97]). Deep SSIs has been diagnosed significantly before superficial SSIs (p = 0,008), with a median advance of 9 days.

Total leukocytes and neutrophils at discharge seem useful to identify a population at risk for the development of septic inflammation at the surgical site following TJA. Further studies with larger populations are needed to develop a predictive SSIs risk score that should include those variables.