External Validity of a New Prediction Model for Patient Satisfaction After Total Knee Arthroplasty

Instruments to assess appropriateness of hip and knee arthroplasty: a systematic review

OBJECTIVE

To assess criteria and psychometric properties of instruments for assessing appropriateness of elective joint arthroplasty (JA) for adults with primary hip and knee osteoarthritis (OA).

METHODS

A systematic review guided by Cochrane methods and PRISMA guidelines. Studies were searched in five databases. Eligible articles include all study designs developing, testing, and/or using an instrument to assess JA appropriateness. Two independent reviewers screened and extracted data. Instruments were compared with Hawker et al. JA consensus criteria. Psychometric properties of instruments were described and appraised guided by Fitzpatrick's and COSMIN approaches.

RESULTS

Of 55 instruments included, none met all Hawker et al. JA consensus criteria. Criteria the most met were pain (n = 50), function (n = 49), quality of life (n = 33), and radiography (n = 24). Criteria the least met were clinical evidence of OA (n = 18), expectations (n = 15), readiness for surgery (n = 11), conservative treatments (n = 8), and patient/surgeon agree benefits outweigh risks (n = 0). Instrument by Arden et al. met the most criteria (6 of 9). The most tested psychometric properties were appropriateness (n = 55), face/content validity (n = 55), predictive validity (n = 29), construct validity and feasibility (n = 24). The least tested psychometric properties were intra-rater reliability (n = 3), internal consistency (n = 5), and inter-rater reliability (n = 13). Instruments by Gutacker et al. and Osborne et al. met the most psychometric properties (4 of 10).

CONCLUSION

Most instruments included traditional criteria for assessing JA appropriateness but did not include a trial of conservative treatments or shared decision-making elements. There was limited evidence on psychometric properties.

Artificial intelligence in knee arthroplasty: current concept of the available clinical applications

Background

Artificial intelligence (AI) is defined as the study of algorithms that allow machines to reason and perform cognitive functions such as problem-solving, objects, images, word recognition, and decision-making. This study aimed to review the published articles and the comprehensive clinical relevance of AI-based tools used before, during, and after knee arthroplasty.

Methods

The search was conducted through PubMed, EMBASE, and MEDLINE databases from 2000 to 2021 using the 2009 Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol (PRISMA).

Results

A total of 731 potential articles were reviewed, and 132 were included based on the inclusion criteria and exclusion criteria. Some steps of the knee arthroplasty procedure were assisted and improved by using AI-based tools. Before surgery, machine learning was used to aid surgeons in optimizing decision-making. During surgery, the robotic-assisted systems improved the accuracy of knee alignment, implant positioning, and ligamentous balance. After surgery, remote patient monitoring platforms helped to capture patients’ functional data.

Conclusion

In knee arthroplasty, the AI-based tools improve the decision-making process, surgical planning, accuracy, and repeatability of surgical procedures.

A qualitative study to understand patients’ experiences of their post-operative outcomes following forefoot surgery

Background

Hallux valgus and hallux rigidus are two common forefoot conditions causing deformity, pain, functional limitations, disability and deteriorating health status resulting in the requirement for surgery. Even when surgery is performed by an experienced surgeon, there remains a potential for patients to experience dissatisfaction and unfavourable outcomes. Adverse results are moderated by psychosocial variables; however, there is a paucity of qualitative research providing insight into how patients perceive their outcomes and the factors affecting their recovery.

Objective

The study aimed to qualitatively explore patients’ experiences of their surgical outcomes following forefoot surgery and factors associated with their recovery. Semi-structured interviews with 15 patients who received surgery for hallux valgus and/or hallux rigidus were conducted.

Results

Thematic analysis generated five themes: physical limitations, the psychosocial impact of surgical recovery, regaining normality, patients’ expectations for physical recovery and an altered body-image. Physical and psychosocial factors were inter-related. Patients experiencing problematic outcomes were functionally limited, had low mood and were unable to return to a normal life post-surgery. The women reported weight related issues and were limited in their footwear and clothing choices, negatively impacting on their self-esteem.

Conclusion

A forefoot condition is multifaceted, with patients experiencing a range of physical and psychological factors that may influence their outcomes and recovery from surgery. Patients need to be supported holistically with the use of a biopsychosocial model. A multidisciplinary approach to care and treatment within the forefoot surgical pathway with the inclusion of allied health professionals will enable to better support patients to enhance their outcomes.

Patient Satisfaction Following Primary Total Knee Arthroplasty: Contributing Factors

The reported dissatisfaction rate after primary total knee arthroplasty (TKA) ranges between 15% and 25%. The purpose of this article is to perform a narrative review of the literature with the aim of answering the following question: What are the main factors contributing to patient dissatisfaction after TKA? A review of the literature was performed on patient satisfaction after TKA. The search engines used were MedLine (PubMed) and the Cochrane Library. The keywords used were "TKA" and "satisfaction". The main reported preoperative factors positively contributing to patient satisfaction were the following: fulfilment of preoperative expectations, preoperative complete joint space collapse, increasing patellar and lateral compartment osteophyte size, and TKA communication checklist. The principal preoperative factors negatively contributing to patient satisfaction included female sex, comorbidities, and Hispanic race. The chief perioperative factor positively contributing to patient satisfaction was cosmetic closure, whereas the fundamental perioperative factors negatively contributing to patient satisfaction included joint laxity, anterior tibial component slope, and greater femoral component valgus angle. The principal postoperative factors positively contributing to patient satisfaction were the following: ameliorated walking distance, improved range of motion, and improvements in pain. The most important postoperative factors negatively contributing to patient satisfaction included poor postoperative knee stability and soft-tissue balance, functional limitation, surgical complication and reoperation, staff or quality of care issues, and increased stiffness.

Patient Factors That Matter in Predicting Hip Arthroplasty Outcomes: A Machine-Learning Approach

BACKGROUND

Despite the success of total hip arthroplasty (THA), approximately 10%-15% of patients will be dissatisfied with their outcome. Identifying patients at risk of not achieving meaningful gains postoperatively is critical to pre-surgical counseling and clinical decision support. Machine learning has shown promise in creating predictive models. This study used a machine-learning model to identify patient-specific variables that predict the postoperative functional outcome in THA.

METHODS

A prospective longitudinal cohort of 160 consecutive patients undergoing total hip replacement for the treatment of degenerative arthritis completed self-reported measures preoperatively and at 3 months postoperatively. Using four types of independent variables (patient demographics, patient-reported health, cognitive appraisal processes and surgical approach), a machine-learning model utilizing Least Absolute Shrinkage Selection Operator (LASSO) was constructed to predict postoperative Hip Disability and Osteoarthritis Outcome Score (HOOS) at 3 months.

RESULTS

The most predictive independent variables of postoperative HOOS were cognitive appraisal processes. Variables that predicted a worse HOOS consisted of frequent thoughts of work (β = -0.34), frequent comparison to healthier peers (β = -0.26), increased body mass index (β = -0.17), increased medical comorbidities (β = -0.19), and the anterior surgical approach (β = -0.15). Variables that predicted a better HOOS consisted of employment at the time of surgery (β = 0.17), and thoughts related to family interaction (β = 0.12), trying not to complain (β = 0.13), and helping others (β = 0.22).

CONCLUSIONS

This clinical prediction model in THA revealed that the factors most predictive of outcome were cognitive appraisal processes, demonstrating their importance to outcome-based research.

LEVEL OF EVIDENCE

Prognostic Level 1.

Clinical Decision Support Tools for Predicting Outcomes in Patients Undergoing Total Knee Arthroplasty: A Systematic Review

BACKGROUND

Total knee arthroplasty is the standard surgical treatment for end-stage osteoarthritis. Although widely accepted as a successful procedure, approximately 30% of patients are not satisfied due to non-optimal postoperative outcomes. Clinical decision support tools that are able to accurately predict post-surgery outcomes would assist in providing individualized advice or services to help alleviate possible issues, resulting in significant benefits to both the healthcare system and individuals.

METHODS

Five databases (Ovid Medline, Ovid EMBASE, CINAHL complete, Cochrane Library, and Scopus) were searched for the key phrases "knee replacement" or "knee arthroplasty" and "decision support tool," "decision tool," "predict∗ tool," "predict∗ model," "algorithm" or "nomogram." Searches were limited to peer-reviewed journal articles published between January 2000 and June 2019. Reference lists of included articles were examined. Authors came to a consensus on the final list of included articles.

RESULTS

Eighteen articles were included for review. Most models reported low predictive success and inability to externally validate. Both candidate and final predictor variables were inconsistent between studies. Only 1 model was considered strongly predictive (AUROC >0.8), and only 2 studies were able to externally validate their developed model. In general, models that performed well used large patient numbers, were tested on similar demographics, and used either nonlinear input transformations or a completely nonlinear model.

CONCLUSION

Some models do show promise; however, there remains the question of whether the reported predictive success can continue to be replicated. Furthermore, clinical applicability and interpretation of predictive tools should be considered during development.

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

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 – Level III.

Perioperative predictability of unsatisfactory functional outcomes 6 months after hip arthroplasty

Background

Aiming at an early identification of patients with an unsatisfactory outcome after hip arthroplasty we investigated the pre-, intra- and early postoperative predictability.

Methods

Using logistic regression models at nine different time points we calculated the area under the curve of the receiver operating characteristic (ROC-AUC) to compare the predictability of an unsatisfactory outcome.

Results

The predictability of unsatisfactory outcomes increased significantly from a ROC-AUC (95% CI) of 0.73 (0.62-0.84) in the preoperative setting to 0.85 (0.77-0.94) on day 2 after surgery.

Conclusion

Most of the patients with unsatisfactory outcomes can be identified during the first days after surgery.

Outpatient physiotherapy versus home-based rehabilitation for patients at risk of poor outcomes after knee arthroplasty: CORKA RCT

BACKGROUND

Over 100,000 primary knee arthroplasty operations are undertaken annually in the UK. Around 15-30% of patients do not report a good outcome. Better rehabilitation strategies may improve patient-reported outcomes.

OBJECTIVES

To compare the outcomes from a traditional outpatient physiotherapy model with those from a home-based rehabilitation programme for people assessed as being at risk of a poor outcome after knee arthroplasty.

DESIGN

An individually randomised, two-arm controlled trial with a blinded outcome assessment, a parallel health economic evaluation and a nested qualitative study.

SETTING

The trial took place in 14 NHS physiotherapy departments.

PARTICIPANTS

People identified as being at high risk of a poor outcome after knee arthroplasty.

INTERVENTIONS

A multicomponent home-based rehabilitation package delivered by rehabilitation assistants with supervision from qualified therapists compared with usual-care outpatient physiotherapy.

MAIN OUTCOME MEASURES

The primary outcome was the Late Life Function and Disability Instrument at 12 months. Secondary outcomes were the Oxford Knee Score (a disease-specific measure of function); Knee injury and Osteoarthritis Outcome Score; Quality of Life subscale; Physical Activity Scale for the Elderly; EuroQol-5 Dimensions, five-level version; and physical function assessed using the Figure-of-8 Walk Test, 30-Second Chair Stand Test and Single Leg Stance. Data on the use of health-care services, time off work and informal care were collected using participant diaries.

RESULTS

In total, 621 participants were randomised. A total of 309 participants were assigned to the COmmunity based Rehabilitation after Knee Arthroplasty (CORKA) home-based rehabilitation programme, receiving a median of five treatment sessions (interquartile range 4-7 sessions). A total of 312 participants were assigned to usual care, receiving a median of four sessions (interquartile range 2-6 sessions). The primary outcome, Late Life Function and Disability Instrument function total score at 12 months, was collected for 279 participants (89%) in the home-based CORKA group and 287 participants (92%) in the usual-care group. No clinically or statistically significant difference was found between the groups (intention-to-treat adjusted difference 0.49 points, 95% confidence interval -0.89 to 1.88 points; p = 0.48). There were no statistically significant differences between the groups in any of the patient-reported or physical secondary outcome measures at 6 or 12 months post randomisation. The health economic analysis found that the CORKA intervention was cheaper to provide than usual care (£66 less per participant). Total societal costs (combining health-care costs and other costs) were lower for the CORKA intervention than usual care (£316 less per participant). Adopting a societal perspective, CORKA had a 75% probability of being cost-effective at a threshold of £30,000 per quality-adjusted life-year. Adopting the narrower health and social care perspective, CORKA had a 43% probability of being cost-effective at the same threshold.

LIMITATIONS

The interventions were of short duration and were set within current commissioning guidance for UK physiotherapy. Participants and treating therapists could not be blinded.

CONCLUSIONS

This randomised controlled trial found no important differences in outcomes when post-arthroplasty rehabilitation was delivered using a home-based, rehabilitation assistant-delivered rehabilitation package or a traditional outpatient model. However, the health economic evaluation found that when adopting a societal perspective, the CORKA home-based intervention was cost-saving and more effective than, and thus dominant over, usual care, owing to reduced time away from paid employment for this group. Further research could look at identifying the risk of poor outcome and further evaluation of a cost-effective treatment, including the workforce model to deliver it.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN13517704.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 24, No. 65. See the NIHR Journals Library website for further project information.

Assessing the Validity of a New Prediction Model for Patient Satisfaction After Total Knee Arthroplasty: A Retrospective Cross-Sectional Study

Purpose

Previously, a simplified model using statistically selected questionnaires from various patients reported outcome measures (PROMs) was proposed to predict patient satisfaction after total knee arthroplasty (TKA). However, this simple and useful model needs to be validated across ethnic and cultural differences. The objective of this study was to evaluate the utility of this predictive model in Japanese patients.

Patients and Methods

Of all knees treated using primary TKA at our institution between August 2017 and June 2018, this study involved 50 knees of 48 patients (11 men, 37 women) to whom the predictive model was applied preoperatively and from whom PROMs were obtained at least 1 year postoperatively. To evaluate PROMs, patients completed the KSS and the Forgotten Joint Score-12. Correlations were analyzed between preoperatively predicted postoperative patient satisfaction and actual postoperative patient satisfaction, as well as each PROM.

Results

KSS satisfaction improved from 15.6 ± 6.1 preoperatively to 27.8 ± 8.3 postoperatively, with satisfaction reported for 41 knees (82%). The preoperatively predicted postoperative patient satisfaction score was 26.3 ± 4.6, with no significant correlation with actual postoperative score (r = 0.05, p = 0.72). The difference between preoperatively predicted patient satisfaction and actual postoperative patient satisfaction was positively correlated with the score for question 9 of the Pain Catastrophizing Scale, among other instruments constituting the predictive model.

Conclusion

Our data suggest that the predictive model had a low predictive value and that it had limited applicability to Japanese patients. The results also suggest that a tendency toward catastrophic thinking is associated with discrepancy between preoperatively predicted postoperative patient satisfaction and actual postoperative patient satisfaction. The predictive model has low utility and needs some modification.