The Journal of Arthroplasty , Volume 33 , Issue 9 , 2971 - 2975

Malnutrition and the Development of Periprosthetic Joint Infection in Patients Undergoing Primary Elective Total Joint Arthroplasty

Blevins, Kier et al.
Hip Knee

Background

Although an abundance of literature exists linking malnutrition with infectious complications in surgical patients, there is little specifically examining the link between malnutrition and periprosthetic joint infection (PJI). This study evaluated the relationship between abnormal nutritional parameters and development of PJI in patients undergoing primary total joint arthroplasty (TJA).

Methods

We retrospectively reviewed TJA patients from 2000 to 2016 with preoperative nutritional screening at a single institution. Any development of PJI at 2 years was assessed as the primary outcome. The Musculoskeletal Infection society criteria were used to define PJI. The association between the aforementioned nutritional markers and PJI was evaluated in a bivariate analysis followed by multivariate logistic regression. Performance for markers was assessed using receiver operator characteristic curves. Sensitivity and specificity were also compared.

Results

Multivariate analysis demonstrated that low albumin (adjusted odds ratio [OR], 4.69; 95% confidence interval [CI], 2.428-9.085; P < .001) and low hemoglobin (adjusted OR, 2.718; 95% CI, 1.100-2.718; P = .018) were significantly associated with PJI. Albumin had the highest specificity and (95% CI, 97.8%-98.4%) and positive predictive value compared to all other markers. Platelet-to-white blood cell ratio had the highest sensitivity (95% CI, 29.5%-40.3%). The area under the curve was greatest for albumin (0.61; 95% CI, 0.55-0.67) followed by hemoglobin (0.57; 95% CI, 0.51-0.63), platelets (0.56; 95% CI, 0.50-0.62), and platelet-to-white blood cell ratio (0.54; 95% CI, 0.49-0.60).

Conclusion

The most valuable predictor of PJI following primary TJA, among nutritional parameters examined, was preoperative albumin with a very high specificity and positive predictive value.


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