Predicting whether patients will achieve minimal clinically important differences following hip or knee arthroplasty

High Expectations Among Patients Who Have Undergone TKA Do Not Correlate With Satisfaction

BACKGROUND

One of five patients is dissatisfied with the outcome of TKA. With the increasing number of TKAs, this affects many patients. It has been suggested that high expectations may influence satisfaction, but the relationship between preoperative patient expectations and postoperative patient satisfaction remains poorly understood.

QUESTIONS/PURPOSES

(1) Are preoperative patient expectations correlated with postoperative satisfaction? (2) Are expectations correlated with patient characteristics or patient-reported outcome measures (PROMs)? (3) Is satisfaction correlated with patient characteristics or PROMs? (4) Do patients report specific items as more relevant to their expectations?

METHODS

This was a single-center, observational, retrospective, comparative study involving patients who underwent TKA. Between December 2020 and June 2022, three senior surgeons performed 306 TKAs. Of these, 76% (234) had the preoperative PROMs required for this study, and of these, 82% (193) had completed PROMs at the 12-month follow-up interval and were analyzed. Of the 193 included patients, 53% (102) were women; the mean age was 68 ± 9 years. Data were collected at baseline, 4 months, and 12 months. Twelve months of follow-up has been shown to be adequate in studies with PROMs. Patient expectations were measured using the validated Hospital for Special Surgery Knee Replacement Expectation Survey on a scale from 0 to 100, with higher scores indicating higher expectations. We also assessed patient satisfaction, the Knee injury and Osteoarthritis Outcome Score, Forgotten Joint Score, High-Activity Arthroplasty Score, EQ-5D-3L, and the objective Knee Society Score. Bivariate linear correlations were analyzed using the Pearson or Spearman test.

RESULTS

Preoperative patient expectations did not correlate with postoperative satisfaction. The mean Hospital for Special Surgery Knee Replacement Expectation Survey score was 82 ±16 points and did not correlate with satisfaction at either 4 months (r = -0.061; p = 0.42) or 12 months (r = -0.126; p = 0.11). Expectations did not correlate with patient characteristics or any of the preoperative or postoperative PROMs or the Knee Society Score. Patient satisfaction was 88% (158 of 179) at 4 months and 83% (160 of 193) at 12 months and did not correlate with patient characteristics or any of the preoperative PROMs or Knee Society Score. Patient satisfaction was medium to strongly correlated with postoperative PROMs and Knee Society Score. The Hospital for Special Surgery Knee Replacement Expectation Survey items with the most frequent expected improvement were "ability to walk" (99% [192 of 193]), "go downstairs" (99% [191 of 192]), and "go upstairs" (99% [192 of 193]).

CONCLUSION

Preoperative expectations were not correlated with postoperative satisfaction or PROMs. Surgeons should be aware that patients have high expectations. However, these expectations appear to be less relevant in determining postoperative satisfaction.

LEVEL OF EVIDENCE

Level III, therapeutic study.

Who Benefits From Hip Arthroplasty or Knee Arthroplasty? Preoperative Patient-reported Outcome Thresholds Predict Meaningful Improvement

BACKGROUND

Hip arthroplasty (HA) and knee arthroplasty (KA) are high-volume procedures. However, there is a debate about the quality of indication; that is, whether surgery is truly indicated in all patients. Patient-reported outcome measures (PROMs) may be used to determine preoperative thresholds to differentiate patients who will likely benefit from surgery from those who will not.

QUESTIONS/PURPOSES

(1) What were the minimum clinically important differences (MCIDs) for three commonly used PROMs in a large population of patients undergoing HA or KA treated in a general orthopaedic practice? (2) Do patients who reach the MCID differ in important ways from those who do not? (3) What preoperative PROM score thresholds best distinguish patients who achieve a meaningful improvement 12 months postsurgery from those who do not? (4) Do patients with preoperative PROM scores below thresholds still experience gains after surgery?

METHODS

Between October 1, 2019, and December 31, 2020, 4182 patients undergoing HA and 3645 patients undergoing KA agreed to be part of the PROMoting Quality study and were hence included by study nurses in one of nine participating German hospitals. From a selected group of 1843 patients with HA and 1546 with KA, we derived MCIDs using the anchor-based change difference method to determine meaningful improvements. Second, we estimated which preoperative PROM score thresholds best distinguish patients who achieve an MCID from those who do not, using the preoperative PROM scores that maximized the Youden index. PROMs were Hip Disability and Osteoarthritis Outcome Score-Physical Function short form (HOOS-PS) (scored 0 to 100 points; lower indicates better health), Knee Injury and Osteoarthritis Outcome Score-Physical Function short form (KOOS-PS) (scored 0 to 100 points; lower indicates better health), EuroQol 5-Dimension 5-level (EQ-5D-5L) (scored -0.661 to 1 points; higher indicates better health), and a 10-point VAS for pain (perceived pain in the joint under consideration for surgery within the past 7 days) (scored 0 to 10 points; lower indicates better health). The performance of derived thresholds is reported using the Youden index, sensitivity, specificity, F1 score, geometric mean as a measure of central tendency, and area under the receiver operating characteristic curve.

RESULTS

MCIDs for the EQ-5D-5L were 0.2 for HA and 0.2 for KA, with a maximum of 1 point, where higher values represented better health-related quality of life. For the pain scale, they were -0.9 for HA and -0.7 for KA, of 10 points (maximum), where lower scores represent lower pain. For the HOOS-PS, the MCID was -10, and for the KOOS-PS it was -5 of 100 points, where lower scores represent better functioning. Patients who reached the MCID differed from patients who did not reach the MCID with respect to baseline PROM scores across the evaluated PROMs and for both HA and KA. Patients who reached an MCID versus those who did not also differed regarding other aspects including education and comorbidities, but this was not consistent across PROMs and arthroplasty type. Preoperative PROM score thresholds for HA were 0.7 for EQ-5D-5L (Youden index: 0.55), 42 for HOOS-PS (Youden index: 0.27), and 3.5 for the pain scale (Youden index: 0.47). For KA, the thresholds were 0.6 for EQ-5D-5L (Youden index: 0.57), 39 for KOOS-PS (Youden index: 0.25), and 6.5 for the pain scale (Youden index: 0.40). A higher Youden index for EQ-5D-5L than for the other PROMs indicates that the thresholds for EQ-5D-5L were better for distinguishing patients who reached a meaningful improvement from those who did not. Patients who did not reach the thresholds could still achieve MCIDs, especially for functionality and the pain scale.

CONCLUSION

We found that patients who experienced meaningful improvements (MCIDs) mainly differed from those who did not regarding their preoperative PROM scores. We further identified that patients undergoing HA or KA with a score above 0.7 or 0.6, respectively, on the EQ-5D-5L, below 42 or 39 on the HOOS-PS or KOOS-PS, or below 3.5 or 6.5 on a 10-point joint-specific pain scale presurgery had no meaningful benefit from surgery. The thresholds can support clinical decision-making. For example, when thresholds indicate that a meaningful improvement is not likely to be achieved after surgery, other treatment options may be prioritized. Although the thresholds can be used as support, patient preferences and medical expertise must supplement the decision. Future studies might evaluate the utility of using these thresholds in practice, examine how different thresholds can be combined as a multidimensional decision tool, and derive presurgery thresholds based on additional PROMs used in practice.

CLINICAL RELEVANCE

Preoperative PROM score thresholds in this study will support clinicians in decision-making through objective measures that can improve the quality of the recommendation for surgery.

Preoperative prediction for periprosthetic bone loss and individual evaluation of bisphosphonate effect after total hip arthroplasty using artificial intelligence

Aims

This study was designed to develop a model for predicting bone mineral density (BMD) loss of the femur after total hip arthroplasty (THA) using artificial intelligence (AI), and to identify factors that influence the prediction. Additionally, we virtually examined the efficacy of administration of bisphosphonate for cases with severe BMD loss based on the predictive model.

Methods

The study included 538 joints that underwent primary THA. The patients were divided into groups using unsupervised time series clustering for five-year BMD loss of Gruen zone 7 postoperatively, and a machine-learning model to predict the BMD loss was developed. Additionally, the predictor for BMD loss was extracted using SHapley Additive exPlanations (SHAP). The patient-specific efficacy of bisphosphonate, which is the most important categorical predictor for BMD loss, was examined by calculating the change in predictive probability when hypothetically switching between the inclusion and exclusion of bisphosphonate.

Results

Time series clustering allowed us to divide the patients into two groups, and the predictive factors were identified including patient- and operation-related factors. The area under the receiver operating characteristic (ROC) curve (AUC) for the BMD loss prediction averaged 0.734. Virtual administration of bisphosphonate showed on average 14% efficacy in preventing BMD loss of zone 7. Additionally, stem types and preoperative triglyceride (TG), creatinine (Cr), estimated glomerular filtration rate (eGFR), and creatine kinase (CK) showed significant association with the estimated patient-specific efficacy of bisphosphonate.

Conclusion

Periprosthetic BMD loss after THA is predictable based on patient- and operation-related factors, and optimal prescription of bisphosphonate based on the prediction may prevent BMD loss.

Artificial Intelligence for Clinically Meaningful Outcome Prediction in Orthopedic Research: Current Applications and Limitations

PURPOSE OF REVIEW

Patient-reported outcome measures (PROM) play a critical role in evaluating the success of treatment interventions for musculoskeletal conditions. However, predicting which patients will benefit from treatment interventions is complex and influenced by a multitude of factors. Artificial intelligence (AI) may better anticipate the propensity to achieve clinically meaningful outcomes through leveraging complex predictive analytics that allow for personalized medicine. This article provides a contemporary review of current applications of AI developed to predict clinically significant outcome (CSO) achievement after musculoskeletal treatment interventions.

RECENT FINDINGS

The highest volume of literature exists in the subspecialties of total joint arthroplasty, spine, and sports medicine, with only three studies identified in the remaining orthopedic subspecialties combined. Performance is widely variable across models, with most studies only reporting discrimination as a performance metric. Given the complexity inherent in predictive modeling for this task, including data availability, data handling, model architecture, and outcome selection, studies vary widely in their methodology and results. Importantly, the majority of studies have not been externally validated or demonstrate important methodological limitations, precluding their implementation into clinical settings. A substantial body of literature has accumulated demonstrating variable internal validity, limited scope, and low potential for clinical deployment. The majority of studies attempt to predict the MCID-the lowest bar of clinical achievement. Though a small proportion of models demonstrate promise and highlight the utility of AI, important methodological limitations need to be addressed moving forward to leverage AI-based applications for clinical deployment.

Use of a fluoroscopy-based robotic-assisted total hip arthroplasty system produced greater improvements in patient-reported outcomes at one year compared to manual, fluoroscopic-assisted technique

INTRODUCTION

The adoption of new technology should be supported by improvements in patient-reported outcomes (PROMs). The purpose of this study was to assess the one-year PROMs of patients who underwent total hip arthroplasty (THA) using a novel, fluoroscopy-based, robotic-assisted (RA-THA) system when compared to a manual, fluoroscopic-assisted technique (mTHA).

MATERIALS AND METHODS

A review of 91 consecutive mTHA and 85 consecutive RA-THA via a direct anterior approach was conducted. All cases were performed by the same surgeon at the same institution, for a pre-operative diagnosis of osteoarthritis, avascular necrosis, or rheumatoid arthritis. Outcomes included one-year Veterans RAND-12 (VR-12) Physical/Mental, Hip Disability and Osteoarthritis Outcome (HOOS) Pain/Physical Function/Joint Replacement, and University of California Los Angeles (UCLA) Activity scores, as well as the difference between pre-operative and one-year post-operative PROMs.

RESULTS

Patients in the RA-THA cohort had lower pre-operative HOOS-JR scores compared to patients in the mTHA cohort (37.0 vs. 43.1; p = 0.031). Cohorts experienced similar one-year post-operative VR-12, HOOS, and UCLA Activity scores. Patients in the RA-THA cohort experienced greater improvements across all pre- and post-operative HOOS scores compared to patients in the mTHA cohort: Pain (+ 54.7 vs. +42.1; p = 0.009), Physical Function (-41.6 vs. -28.7; p = 0.007), and Joint Replacement (+ 46.6 vs. +33.0; p = 0.002). These differences exceeded minimum clinically important difference (MCID).

CONCLUSIONS

Both manual and robotic cohorts experienced benefit from THA at one-year post-operative. Importantly, the use of a novel, fluoroscopy-based robotic assistance system for primary THA resulted in greater improvements in PROMs at one-year relative to manual technique.

Gender health gap pre- and post-joint arthroplasty: identifying affected patient-reported health domains

BACKGROUND

As patient-reported outcomes (PROs) gain prominence in hip and knee arthroplasty (HA and KA), studies indicate PRO variations between genders. Research on the specific health domains particularly impacted is lacking. Hence, we aim to quantify the gender health gap in PROs for HA/KA patients, differentiating between general health, health-related quality of life (HrQoL), physical functioning, pain, fatigue, and depression.

METHODS

The study included 3,693 HA patients (1,627 men, 2,066 women) and 3,110 KA patients (1,430 men, 1,680 women) receiving surgery between 2020 to 2021 in nine German hospitals, followed up until March 2022. Questionnaires used were: EQ-VAS, EQ-5D-5L, HOOS-PS, KOOS-PS, PROMIS-F-SF, PROMIS-D-SF, and a joint-specific numeric pain scale. PROs at admission, discharge, 12-months post-surgery, and the change from admission to 12-months (PRO-improvement) were compared by gender, tested for differences, and assessed using multivariate linear regressions. To enable comparability, PROs were transformed into z-scores (standard deviations from the mean).

RESULTS

Observed differences between genders were small in all health domains and differences reduced over time. Men reported significantly better health versus women pre-HA (KA), with a difference of 0.252 (0.224) standard deviations from the mean for pain, 0.353 (0.243) for fatigue (PROMIS-F-SF), 0.327 (0.310) for depression (PROMIS-D-SF), 0.336 (0.273) for functionality (H/KOOS-PS), 0.177 (0.186) for general health (EQ-VAS) and 0.266 (0.196) for HrQoL (EQ-5D-5L). At discharge, the gender health gap reduced and even disappeared for some health dimensions since women improved in health to a greater extent than men. No gender health gap was observed in most PRO-improvements and at month 12.

CONCLUSIONS

Men experiencing slightly better health than women in all health dimensions before surgery while experiencing similar health benefits 12-months post-surgery, might be an indicator of men receiving surgery inappropriately early, women unnecessarily late or both. As studies often investigate the PRO-improvement, they miss pre-surgery gender differences, which could be an important target for improvement initiatives in patient-centric care. Moreover, future research on cutoffs for meaningful between-group PRO differences per measurement time would aid the interpretation of gender health disparities.

TRIAL REGISTRATION

German Register for Clinical Trials, DRKS00019916, 26 November 2019.

Predicting Functional Outcomes of Total Hip Arthroplasty Using Machine Learning: A Systematic Review

The aim of this review was to assess the reliability of machine learning (ML) techniques to predict the functional outcome of total hip arthroplasty. The literature search was performed up to October 2023, using MEDLINE/PubMed, Embase, Web of Science, and NIH Clinical Trials. Level I to IV evidence was included. Seven studies were identified that included 44,121 patients. The time to follow-up varied from 3 months to more than 2 years. Each study employed one to six ML techniques. The best-performing models were for health-related quality of life (HRQoL) outcomes, with an area under the curve (AUC) of more than 84%. In contrast, predicting the outcome of hip-specific measures was less reliable, with an AUC of between 71% to 87%. Random forest and neural networks were generally the best-performing models. Three studies compared the reliability of ML with traditional regression analysis: one found in favour of ML, one was not clear and stated regression closely followed the best-performing ML model, and one showed a similar AUC for HRQoL outcomes but did show a greater reliability for ML to predict a clinically significant change in the hip-specific function. ML offers acceptable-to-excellent discrimination of predicting functional outcomes and may have a marginal advantage over traditional regression analysis, especially in relation to hip-specific hip functional outcomes.

Outcomes Vary by Pre-Operative Physical Activity Levels in Total Knee Arthroplasty Patients

Physical activity (PA) is suggested to reduce osteoarthritis pain; however, it may be avoided by patients requiring arthroplasty. Our goal was to investigate objective and patient-reported outcomes as a function of pre-operative PA levels in patients undergoing total knee arthroplasty (TKA). A total of 1941 patients enrolled in a multicenter prospective cohort study investigating a smartphone-based care management platform for self-directed rehabilitation underwent TKA and were included in the analysis. Activity was categorized based on the cohort's step count quartiles into low, moderate, and high pre-operative PA. Pre-operative and post-operative pain, EQ5D5L, KOOS JR, and step counts were compared by ANOVA according to activity group. Pre-operative pain scores increased with the decreasing activity level (all, p < 0.05) and were most improved post-operatively in the low PA group. High PA patients demonstrated the smallest improvements in EQ-5D-5L and KOOS JR. Low and moderate PA patients increased physical activity by three months, reaching 176% and 104% of pre-operative steps; high PA patients did not return to full step counts by one year post-operatively. Patients undergoing TKA who present with higher levels of physical activity report lower levels of pain and higher function pre-operatively but appreciate less improvement up to one year post-operatively. These results may be helpful in appropriate counseling of patient expectations before TKA.