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. 2023 May 20;13(1):8192.
doi: 10.1038/s41598-023-35384-1.

Early postoperative laboratory parameters are predictive of initial treatment failure in acute septic arthritis of the knee and shoulder joint

Affiliations

Early postoperative laboratory parameters are predictive of initial treatment failure in acute septic arthritis of the knee and shoulder joint

Jennifer Straub et al. Sci Rep. .

Abstract

Septic arthritis is an orthopedic emergency potentially causing irreversible joint damage. However, the predictive value of potential risk factors such as early postoperative laboratory parameters remains uncertain. We investigated risk factors for initial surgical treatment failure using data from 249 patients (194 knees, 55 shoulders) treated for acute septic arthritis between 2003 and 2018. Necessity for further surgical intervention was defined as primary outcome. Demographic data, medical history, initial and postoperative laboratory parameters, Charlson Comorbidity Index (CCI), and Kellgren and Lawrence classification were collected. Two scoring systems were developed as tools for failure risk estimation after initial surgical irrigation and debridement. More than one intervention was necessary in 26.1% of cases. Treatment failure occurred significantly more often for those with longer symptom duration (p = 0.003), higher CCI grades (p = 0.027), Kellgren-Lawrence grade IV (p = 0.013), shoulder arthroscopy (p = 0.010), positive bacterial culture results (p < 0.001), slow postoperative CRP decline until day three (p = 0.032) and five (p = 0.015), reduced WBC-decline (p = 0.008), and lower hemoglobin (p < 0.001). Scores for third and fifth postoperative day achieved AUCs of 0.80 and 0.85, respectively. This study identified risk factors for treatment failure in patients with septic arthritis, suggesting that early postoperative laboratory parameters can guide further treatment.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Flow-chart diagram of the exclusion process.
Figure 2
Figure 2
Distribution of Kellgren-Lawrence classes in the success and failure group.
Figure 3
Figure 3
Distribution of pathogens over a total of 112 positive bacterial cultures.
Figure 4
Figure 4
Absolute (abs) and relative (rel) CRP changes compared to admission values.
Figure 5
Figure 5
ROCs from the two prediction models. The first includes information on CRP and neutrophilic granulocytes up to day 3 post surgery, symptom duration, CCI, and bacterial culture result. The second model additionally includes information on CRP change from admission to day 5 post-OP.
Figure 6
Figure 6
Low, intermediate, and high risk of failure depending on score points on the 3rd and 5th postoperative day.

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