Prediction of Early Periprosthetic Joint Infection After Total Hip Arthroplasty

Bülow, Erik; Hahn, Ute; Andersen, Ib; Rolfson, Ola; Pedersen, Alma B; Hailer, Nils P.

doi:10.2147/clep.s347968

Cited by 9 publications

(17 citation statements)

References 51 publications

(48 reference statements)

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“…The 10 database-based studies, with a combined population of 1,892609, cover 4 continents (North America, Oceania, Europe, and Asia) and 9 countries (including the USA, Australia, Korea, Sweden, Denmark, Canada, Finland, France, and Norway). In addition, because Bulow [ 11 ] grouped the populations from Sweden and Denmark separately, we conducted the two data sources in this article in separate Table 1 . For Dale.…”

Section: Resultsmentioning

confidence: 99%

“…2 and 3 . Estimates for the medical database-base studies [ 11 – 15 , 19 – 22 , 26 ] ranged from 0.34 to 2.45% (Fig. 2 ), and the random-effects overall pooled estimated incidence of PJI was 1.05% (95% CI 0.75–1.46%), with very high heterogeneity ( I 2 = 99.6%; heterogeneity test P = 0).…”

Section: Resultsmentioning

confidence: 99%

“…1). 5 studies [ 11 , 13 , 15 , 19 , 20 ] (6 data sources, n = 385,802) used patient information extracted from ICD code searches by regional statistical agencies of the medical nature, and the combined incidence estimate of PJI was 1.58% (95% CI 1.54–1.62%), also with very high heterogeneity ( I 2 = 99.5%; heterogeneity test P < 0.01) (Additional file 1 : Fig. 1).…”

Section: Resultsmentioning

confidence: 99%

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Incidence of periprosthetic joint infection after primary total hip arthroplasty is underestimated: a synthesis of meta-analysis and bibliometric analysis

Zeng,

Yao,

et al. 2023

J Orthop Surg Res

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The American Musculoskeletal Society updated the diagnostic criteria for periprosthetic joint infection (PJI) in 2011 and 2018. However, the overall incidence of PJI since the introduction of these new standards has not been assessed. In order to fill this knowledge gap, a single-group meta-analysis was conducted using articles obtained from several databases, focusing on the incidence of PJI after primary total hip arthroplasty (THA). Our study revealed a significant difference in the incidence of PJI reported by different national or regional databases. Moreover, most cases of PJI were found to be underestimated. This highlights the crucial need for standardized diagnostic criteria and monitoring methods to accurately identify and track cases of PJI. Furthermore, a bibliometric analysis was conducted to provide a comprehensive overview of the current state of research on PJI after THA. This analysis explored the most productive countries, organizations, journals, and individuals in this research area. Additionally, it identified the research trends and hotspots of the last decade, highlighting the advancements and areas of focus in this field. By conducting these analyses, the study aims to contribute to the understanding of PJI after THA and provide valuable insights for clinicians, researchers, and policymakers involved in the management of this condition.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Incidence of periprosthetic joint infection after primary total hip arthroplasty is underestimated: a synthesis of meta-analysis and bibliometric analysis

Zeng,

Yao,

et al. 2023

J Orthop Surg Res

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“…In general, the risk prediction of PJI has been extensively discussed in the literature. A recent prediction model for early PJI, which was applied in Sweden and Denmark, consisted of the parameters diagnosis leading to endoprosthesis insertion, BMI, American Society for Anesthesiologists (ASA) class, sex, age, and the presence of five defined comorbidities [ 21 ]. A large-scale German study found BMI to be an important risk factor for PJI after hip replacement [ 22 ].…”

Section: Discussionmentioning

confidence: 99%

Preoperative dental screening can reduce periprosthetic infections of hip and knee endoprostheses in the first month after surgery: results of a cohort study

Fenske,

Kujat,

Krause

et al. 2023

Infection

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Purpose The oral cavity and, in particular, potential oral foci might pose a risk of periprosthetic joint infection (PJI). The aim of this cohort study was to determine whether practical preoperative dental screening would reduce the prevalence of early PJI in the first month after surgery. Methods Patients attending a specialized endoprosthesis implantation clinic between 2018 and 2022 were recruited. Two groups were examined. The test group consisted of patients attending the clinic between 2020 and 2022 and who were referred to their family dentist using a standardized form. The comparison group consisted of patients who were treated in the clinic between 2018 and 2020. They were not referred to their family dentist. The two groups were compared for the prevalence of PJI. Univariate analysis followed by multiple logistic regression was performed to confirm risk factors for PJI in this cohort. Results 2560 individuals (test group: 1227, comparison group: 1333) were included. The prevalence of PJI was significantly lower in the test group (0.8% vs. 1.8%, p = 0.04). Multiple logistic regression with PJI as the dependent variable showed that a dental referral was a strong predictor of a lower prevalence of PJI (OR: 0.43, CI95 0.205–0.917, p = 0.03). Male gender was also strongly associated with a higher frequency of PJI (OR: 2.68, CI95 1.32–5.42, p = 0.01). Age (OR: 1.06, CI95 1.01–1.10, p = 0.01) and BMI (OR: 1.11, CI95 1.05–1.17, p < 0.01) had little effect on the risk of PJI. Conclusion Dental referral using a standardized form can reduce the prevalence of early PJI. Accordingly, orthopedists and dentists should collaborate in this practical way.

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“…However, the tool was not specifically tailored to infections and would underestimate the risk of SSI when with a predicted probability >0.10. Recently, Bülow et al 11 developed and validated a risk prediction model for periprosthetic joint infection (PJI) within 90 days following total hip arthroplasty (THA), and confirmed its superior discriminatory ability compared to traditional models. Nevertheless, the inflammatory biomarkers with high predictive value for infections were not incorporated and the area under the curve (AUC) <0.7 suggested relatively inadequate accuracy of the model in their study.…”

mentioning

confidence: 99%

Preoperative Risk Factor Analysis and Dynamic Online Nomogram Development for Early Infections Following Primary Hip Arthroplasty in Geriatric Patients with Hip Fracture

Cheng¹,

Liu²,

Wang³

et al. 2022

CIA

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Background Hip arthroplasty is in increasing demand with the aging of the world population, and early infections, such as pneumonia, surgical site infection (SSI), and urinary tract infection (UTI), are uncommon but fatal complications following hip arthroplasty. This study aimed to identify preoperative risk factors independently associated with early infections following primary arthroplasty in geriatric hip fracture patients, and to develop a prediction nomogram. Methods Univariate and multivariate logistical analyses were performed to identify the independent risk factors for early infections, which were combined and transformed into a nomogram model. The prediction model was evaluated by using the area under the receiver operating characteristic curve (AUC), Hosmer–Lemeshow test, concordance index (C-index), 1000 bootstrap replications, decision curve analysis (DCA), and calibration curve. Results One thousand eighty-four eligible patients got included and 7 preoperative variables were identified to be independently associated with early infections, including heart disease (odds ratio (OR): 2.17; P: 0.026), cerebrovascular disease (OR: 2.25; P: 0.019), liver disease (OR: 8.99; P: <0.001), time to surgery (OR: 1.10; P: 0.012), hematocrit (44.52; OR: 2.73; P: 0.047), and high-sensitivity C-reactive protein (HCRP; >78.64mg/L; OR: 3.71; P: <0.001). For the nomogram model, AUC was 0.807 (95% confidence interval (CI): 0.742–0.873), the Hosmer-Lemeshow test demonstrated no overfitting (P = 0.522), and C-index was 0.807 (95% CI: 0.742–0.872) with corrected value of 0.784 after 1000 bootstrapping validations. Moreover, the calibration curve and DCA exhibited the tools’ good prediction consistency and clinical practicability. Conclusion Heart disease, cerebrovascular disease, liver disease, time to surgery, hematocrit, PMR, and HCRP were significant preoperative predictors for early infections following primary arthroplasty in elderly hip fracture patients, and the converted nomogram model had strong discriminatory ability and translatability to clinical application.

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Prediction of Early Periprosthetic Joint Infection After Total Hip Arthroplasty

Cited by 9 publications

References 51 publications

Incidence of periprosthetic joint infection after primary total hip arthroplasty is underestimated: a synthesis of meta-analysis and bibliometric analysis

Incidence of periprosthetic joint infection after primary total hip arthroplasty is underestimated: a synthesis of meta-analysis and bibliometric analysis

Preoperative dental screening can reduce periprosthetic infections of hip and knee endoprostheses in the first month after surgery: results of a cohort study

Preoperative Risk Factor Analysis and Dynamic Online Nomogram Development for Early Infections Following Primary Hip Arthroplasty in Geriatric Patients with Hip Fracture

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