Internal Validation of a Predictive Model for Satisfaction After Primary Total Knee Arthroplasty

Kunze, Kyle N.; Akram, Faisal; Fuller, Brian C.; Zabawa, Luke; Sporer, Scott M.; Levine, Brett R.

doi:10.1016/j.arth.2018.12.020

Cited by 16 publications

(18 citation statements)

References 29 publications

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“…(2019) [ 14 ] Moderate Moderate Moderate Low Low Moderate Low Moderate Kunze et al. (2019) [ 39 ] Low Low Moderate Low Low Moderate Low Moderate Clement et al. (2019) [ 19 ] Moderate Low Low Low Moderate Moderate Moderate Moderate Ramkumar et al.…”

Section: Resultsmentioning

confidence: 99%

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Predictive Models for Clinical Outcomes in Total Knee Arthroplasty: A Systematic Analysis

Batailler

Lording²,

Massari

et al. 2021

Arthroplasty Today

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Background: Predictive modeling promises to improve our understanding of what variables influence patient satisfaction after total knee arthroplasty (TKA). The purpose of this article was to systematically review the relevant literature using predictive models of clinical outcomes after TKA. The aim was to identify the predictor strategies used for systematic data collection with the highest likelihood of success in predicting clinical outcomes. Methods: A Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol systematic review was conducted using 3 databases (MEDLINE, EMBASE, and PubMed) to identify all clinical studies that had used predictive models or that assessed predictive features for outcomes after TKA between 1996 and 2020. The ROBINS-I tool was used to evaluate the quality of the studies and the risk of bias. Results: A total of 75 studies were identified of which 48 met our inclusion criteria. Preoperative predictive factors strongly associated with postoperative clinical outcomes were knee pain, knee-specific Patient-Reported Outcome Measure (PROM) scores, and mental health scores. Demographic characteristics, pre-existing comorbidities, and knee alignment had an inconsistent association with outcomes. The outcome measures that correlated best with the predictive models were improvement of PROM scores, pain scores, and patient satisfaction. Conclusions: Several algorithms, based on PROM improvement, patient satisfaction, or pain after TKA, have been developed to improve decision-making regarding both indications for surgery and surgical strategy. Functional features such as preoperative pain and PROM scores were highly predictive for clinical outcomes after TKA. Some variables such as demographics data or knee alignment were less strongly correlated with TKA outcomes. Level of evidence: Systematic review e Level III.

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Section: Resultsmentioning

confidence: 99%

“…Several studies identified clinical comorbidities as significant predictive factors of poor outcomes after TKA [ 16 ]. Diabetes [ 20 , 39 ] or allergies [ 40 , 41 ] were singled out.…”

Section: Resultsmentioning

confidence: 99%

Predictive Models for Clinical Outcomes in Total Knee Arthroplasty: A Systematic Analysis

Batailler

Lording²,

Massari

et al. 2021

Arthroplasty Today

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“…The development of multivariate prediction models of patient postoperative recovery outcomes is gaining prominence. A number of existing models have examined predictors of patient-centered TKA outcomes, such as satisfaction (van Onsem et al, 2016;Kunze et al, 2019), pain (Dowsey et al, 2016;Sanchez-Santos et al, 2018), and function (Dowsey et al, 2016;Sanchez-Santos et al, 2018;Kunze et al, 2019), as well as discharge destination (Hansen et al, 2015) and outcomes of osteoarthritis rehabilitation interventions (Weigl et al, 2006). These models have been used to aid decisions regarding whether surgery will likely achieve the desired outcomes for particular individuals (Dowsey et al, 2016;van Onsem et al, 2016) and establish preoperative expectations for individual recovery outcomes (Sanchez-Santos et al, 2018).…”

Section: Interdisciplinary Precision Medicine and The Prediction Of Pmentioning

confidence: 99%

“…However, all of these TKA models have proposed a linear model, i.e., the outcome measure is assumed to be predicted by a weighted sum of the input factors. In some cases, the output is thresholded using a Logistic model (Weigl et al, 2006;Dowsey et al, 2016;Kunze et al, 2019) while in others a continuous output is predicted (van Onsem et al, 2016;Sanchez-Santos et al, 2018;Kunze et al, 2019). In either case, these linear models are not able to capture complex relationships between the predictors.…”

Section: Interdisciplinary Precision Medicine and The Prediction Of Pmentioning

confidence: 99%

“…Existing TKA prediction models (e.g., Tan et al, 2014 ; Dowsey et al, 2016 ; Sanchez-Santos et al, 2018 ; Kunze et al, 2019 ) have largely ignored psychological factors, focusing instead on medical and non-modifiable demographic predictors of adverse outcome. Models that have incorporated psychological factors have assessed “mental health” using general measures (e.g., Dowsey et al, 2016 ) or single-item measures that do not distinguish between depression and anxiety (e.g., van Onsem et al, 2016 ; Sanchez-Santos et al, 2018 ).…”

Section: The Role Of Modifiable Psychological Factorsmentioning

confidence: 99%

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Improving Patient Outcomes Following Total Knee Arthroplasty: Identifying Rehabilitation Pathways Based on Modifiable Psychological Risk and Resilience Factors

et al. 2020

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Improving Patient Outcomes Following TKA interdisciplinary domains outside their usual purview. The proposed approach could facilitate the development and provision of more targeted rehabilitative interventions on the basis of identified individual needs. The roles of several modifiable psychological risk and resilience factors in recovery are summarized, and intervention options are briefly presented. While focusing on rehabilitation following TKA, we advocate for the broader utilization of multivariate prediction models to inform individually tailored interventions targeting a range of health conditions.

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Key Factors for Achieving Expectations in Patient Satisfaction and Quality of Life After Knee Arthroplasty

Barber-Westin¹,

Noyes

2021

Critical Rehabilitation for Partial and Total Knee Arthroplasty

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Internal Validation of a Predictive Model for Satisfaction After Primary Total Knee Arthroplasty

Cited by 16 publications

References 29 publications

Predictive Models for Clinical Outcomes in Total Knee Arthroplasty: A Systematic Analysis

Predictive Models for Clinical Outcomes in Total Knee Arthroplasty: A Systematic Analysis

Improving Patient Outcomes Following Total Knee Arthroplasty: Identifying Rehabilitation Pathways Based on Modifiable Psychological Risk and Resilience Factors

Key Factors for Achieving Expectations in Patient Satisfaction and Quality of Life After Knee Arthroplasty

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