Single-Stage Revision of the Infected Total Knee Arthroplasty Is Associated With Improved Functional Outcomes: A Propensity Score–Matched Cohort Study

Klemt, Christian; Tirumala, Venkatsaiakhil; Oganesyan, Ruben; Xiong, Liang; Kieboom, Janna van den; Kwon, Young‐Min

doi:10.1016/j.arth.2020.07.012

Cited by 49 publications

(61 citation statements)

References 44 publications

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“…However, similar limitations were reported in prior retrospective studies on this topic. [34][35][36] In conclusion, this study developed and validated five ML models for the prediction of patient-specific SSI following primary TKA. The study findings show excellent model performance, with the best modeling accuracy of ANNs.…”

Section: Discussionmentioning

confidence: 99%

The Use of Artificial Neural Networks for the Prediction of Surgical Site Infection Following TKA

et al. 2022

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This is a retrospective study. Surgical site infection (SSI) is associated with adverse postoperative outcomes following total knee arthroplasty (TKA). However, accurately predicting SSI remains a clinical challenge due to the multitude of patient and surgical factors associated with SSI. This study aimed to develop and validate machine learning models for the prediction of SSI following primary TKA. This is a retrospective study for patients who underwent primary TKA. Chart review was performed to identify patients with superficial or deep SSIs, defined in concordance with the criteria of the Musculoskeletal Infection Society. All patients had a minimum follow-up of 2 years (range: 2.1–4.7 years). Five machine learning algorithms were developed to predict this outcome, and model assessment was performed by discrimination, calibration, and decision curve analysis. A total of 10,021 consecutive primary TKA patients was included in this study. At an average follow-up of 2.8 ± 1.1 years, SSIs were reported in 404 (4.0%) TKA patients, including 223 superficial SSIs and 181 deep SSIs. The neural network model achieved the best performance across discrimination (area under the receiver operating characteristic curve = 0.84), calibration, and decision curve analysis. The strongest predictors of the occurrence of SSI following primary TKA, in order, were Charlson comorbidity index, obesity (BMI >30 kg/m2), and smoking. The neural network model presented in this study represents an accurate method to predict patient-specific superficial and deep SSIs following primary TKA, which may be employed to assist in clinical decision-making to optimize outcomes in at-risk patients.

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Section: Discussionmentioning

confidence: 99%

The Use of Artificial Neural Networks for the Prediction of Surgical Site Infection Following TKA

et al. 2022

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“…This prompts us to favor single-stage revision surgery instead of the cumbersome two-stage revision surgery. There is now evidence from several comparative case series that complications and reinfection rates after single-stage revisions are similar to those in two-stage revisions [11][12][13][14]. Revision surgery protocols of PJI, designed to address the nature of these infections, were first introduced over three decades ago.…”

Section: Discussionmentioning

confidence: 99%

COVID-19 Collateral Damage: Management of Periprosthetic Joint Infection in Malaysia

Khan¹,

Kow²,

Ramalingam³

et al. 2021

Cureus

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Background and objectivePeriprosthetic joint infection (PJI) is one of the dreaded complications in patients after arthroplasty surgeries, owing to the risk of morbidity and arduous investigations and management associated with it. Nevertheless, as Malaysia is currently battling against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-induced coronavirus disease 2019 (COVID-19) pandemic head-on, the treatment for other non-life-threatening diseases including PJI has taken a backseat. In this study, we present a case series of 11 patients with PJI who were managed surgically at the largest tertiary hospital in Malaysia and we hope to shed some light on the difficulties we have encountered during this trying period. Patients and methodsPatients with PJIs who underwent surgical intervention during the ongoing COVID-19 pandemic (March 1, 2020, to June 30, 2021) were reviewed and included in this study. The demographic profile of the patients, presenting complaints, prosthesis topography, biochemical investigative findings, surgical interventions, and short-term outcomes were summarized. ResultsA total of 11 patients were treated surgically at Hospital Kuala Lumpur for PJI. Among them, five patients are still awaiting their second-stage surgeries despite the completion of their antibiotic regimes, and they are fit for the procedure. ConclusionThe COVID-19 pandemic has wreaked havoc on the treatment of patients with PJI. In a setting with scarce resources, surgeons should strongly consider single-stage revision surgeries for the treatment of patients with PJI.

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“…40 Reinfection rates and 90-day readmission rates are similar regardless of spacer configuration used. 38 Other debates exist regarding optimal antibiotic spacer design. The necessity of using intramedullary (IM) dowels has been discussed, given that literature exists showing that 40% of IM canals were culture-positive at time of resection for infected TKA, 41 which suggest an insidious nidus of infection.…”

Section: Two-stage Revisionmentioning

confidence: 99%

“…Articulating spacers are preferred when appropriate, as a growing body of literature supports that they result in increased range of motion (ROM) following reimplantation, decreased hospital length of stay, and increased patient satisfaction after both the first and second stages of treatment. [36][37][38] Improvement in ROM following articulating spacer versus static spacer has been cited as high as 10 to 13°. 36,37,39 Similarly, the need to use an extensile exposure at the time of reimplantation was found to be significantly less when articulating spacers were used.…”

Section: Two-stage Revisionmentioning

confidence: 99%

Current Insights in the Evaluation and Treatment of Infected Total Knee Arthroplasty

Ashley

Parvızı

2021

J Knee Surg

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Total knee arthroplasty is a widely successful procedure, but a small percentage of patients have a postoperative course complicated by periprosthetic joint infection (PJI). PJI is a difficult problem to diagnose and to treat, and the management of PJI differs, depending on the acuity of the infection. This paper discusses the established and newer technologies developed for the diagnosis of PJI as well as different treatment considerations and surgical solutions currently available.

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Single-Stage Revision of the Infected Total Knee Arthroplasty Is Associated With Improved Functional Outcomes: A Propensity Score–Matched Cohort Study

Cited by 49 publications

References 44 publications

The Use of Artificial Neural Networks for the Prediction of Surgical Site Infection Following TKA

The Use of Artificial Neural Networks for the Prediction of Surgical Site Infection Following TKA

COVID-19 Collateral Damage: Management of Periprosthetic Joint Infection in Malaysia

Current Insights in the Evaluation and Treatment of Infected Total Knee Arthroplasty

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