Risk calculators predict failures of knee and hip arthroplasties: findings from a large health maintenance organization

Prediction of Early Adverse Events After THA: A Comparison of Different Machine-Learning Strategies Based on 262,356 Observations From the Nordic Arthroplasty Register Association (NARA) Dataset

OBJECTIVE

Preoperative risk prediction models can support shared decision-making before total hip arthroplasties (THAs). Here, we compare different machine-learning (ML) approaches to predict the six-month risk of adverse events following primary THA to obtain accurate yet simple-to-use risk prediction models.

METHODS

We extracted data on primary THAs (N = 262,356) between 2010 and 2018 from the Nordic Arthroplasty Register Association dataset. We benchmarked a variety of ML algorithms in terms of the area under the receiver operating characteristic curve (AUROC) for predicting the risk of revision caused by periprosthetic joint infection (PJI), dislocation or periprosthetic fracture (PPF), and death. All models were internally validated against a randomly selected test cohort (one-third of the data) that was not used for training the models.

RESULTS

The incidences of revisions because of PJI, dislocation, and PPF were 0.8%, 0.4%, and 0.3%, respectively, and the incidence of death was 1.2%. Overall, Lasso regression with stable iterative variable selection (SIVS) produced models using only four to five input variables but with AUROC comparable to more complex models using all 32 variables available. The SIVS-based Lasso models based on age, sex, preoperative diagnosis, bearing couple, fixation, and surgical approach predicted the risk of revisions caused by PJI, dislocations, and PPF, as well as death, with AUROCs of 0.61, 0.67, 0.76, and 0.86, respectively.

CONCLUSION

Our study demonstrates that satisfactory predictive potential for adverse events following THA can be reached with parsimonious modeling strategies. The SIVS-based Lasso models may serve as simple-to-use tools for clinical risk assessment in the future.

External Validation of Prediction Models for Surgical Complications in People Considering Total Hip or Knee Arthroplasty Was Successful for Delirium but Not for Surgical Site Infection, Postoperative Bleeding, and Nerve Damage: A Retrospective Cohort Study

Although several models for the prediction of surgical complications after primary total hip or total knee replacement (THA and TKA, respectively) are available, only a few models have been externally validated. The aim of this study was to externally validate four previously developed models for the prediction of surgical complications in people considering primary THA or TKA. We included 2614 patients who underwent primary THA or TKA in secondary care between 2017 and 2020. Individual predicted probabilities of the risk for surgical complication per outcome (i.e., surgical site infection, postoperative bleeding, delirium, and nerve damage) were calculated for each model. The discriminative performance of patients with and without the outcome was assessed with the area under the receiver operating characteristic curve (AUC), and predictive performance was assessed with calibration plots. The predicted risk for all models varied between <0.01 and 33.5%. Good discriminative performance was found for the model for delirium with an AUC of 84% (95% CI of 0.82-0.87). For all other outcomes, poor discriminative performance was found; 55% (95% CI of 0.52-0.58) for the model for surgical site infection, 61% (95% CI of 0.59-0.64) for the model for postoperative bleeding, and 57% (95% CI of 0.53-0.61) for the model for nerve damage. Calibration of the model for delirium was moderate, resulting in an underestimation of the actual probability between 2 and 6%, and exceeding 8%. Calibration of all other models was poor. Our external validation of four internally validated prediction models for surgical complications after THA and TKA demonstrated a lack of predictive accuracy when applied in another Dutch hospital population, with the exception of the model for delirium. This model included age, the presence of a heart disease, and the presence of a disease of the central nervous system as predictor variables. We recommend that clinicians use this simple and straightforward delirium model during preoperative counselling, shared decision-making, and early delirium precautionary interventions.

Evaluating methodological quality of prognostic prediction models on patient reported outcome measurements after total hip replacement and total knee replacement surgery: a systematic review protocol

BACKGROUND

Prediction models for poor patient-reported surgical outcomes after total hip replacement (THR) and total knee replacement (TKR) may provide a method for improving appropriate surgical care for hip and knee osteoarthritis. There are concerns about methodological issues and the risk of bias of studies producing prediction models. A critical evaluation of the methodological quality of prediction modelling studies in THR and TKR is needed to ensure their clinical usefulness. This systematic review aims to (1) evaluate and report the quality of risk stratification and prediction modelling studies that predict patient-reported outcomes after THR and TKR; (2) identify areas of methodological deficit and provide recommendations for future research; and (3) synthesise the evidence on prediction models associated with post-operative patient-reported outcomes after THR and TKR surgeries.

METHODS

MEDLINE, EMBASE, and CINAHL electronic databases will be searched to identify relevant studies. Title and abstract and full-text screening will be performed by two independent reviewers. We will include (1) prediction model development studies without external validation; (2) prediction model development studies with external validation of independent data; (3) external model validation studies; and (4) studies updating a previously developed prediction model. Data extraction spreadsheets will be developed based on the CHARMS checklist and TRIPOD statement and piloted on two relevant studies. Study quality and risk of bias will be assessed using the PROBAST tool. Prediction models will be summarised qualitatively. Meta-analyses on the predictive performance of included models will be conducted if appropriate. A narrative review will be used to synthesis the evidence if there are insufficient data to perform meta-analyses.

DISCUSSION

This systematic review will evaluate the methodological quality and usefulness of prediction models for poor outcomes after THR or TKR. This information is essential to provide evidence-based healthcare for end-stage hip and knee osteoarthritis. Findings of this review will contribute to the identification of key areas for improvement in conducting prognostic research in this field and facilitate the progress in evidence-based tailored treatments for hip and knee osteoarthritis.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration number CRD42021271828.

Population-based 10-year cumulative revision risks after hip and knee arthroplasty for osteoarthritis to inform patients in clinical practice: a competing risk analysis from the Dutch Arthroplasty Register

Background and purpose - A lifetime perspective on revision risks is needed for optimal timing of arthroplasty in osteoarthritis (OA) patients, weighing the benefit of total hip arthroplasty/total knee arthroplasty (THA/TKA) against the risk of revision, after which outcomes are less favorable. Therefore, we provide population-based 10-year cumulative revision risks stratified by joint, sex, fixation type, and age.Patients and methods - Data from the Dutch Arthroplasty Register (LROI) was used. Primary THAs and TKAs for OA between 2007 and 2018 were included, except metal-on-metal prostheses or hybrid/reversed hybrid fixation. Revision surgery was defined as any change of 1 or more prosthesis components. The 10-year cumulative revision risks were calculated stratified by joint, age, sex, at primary arthroplasty, and fixation type (cemented/uncemented), taking into account mortality as a competing risk. We estimated the percentage of potentially avoidable revisions assuming all OA patients aged < 75 received primary THA/TKA 5 years later while keeping age-specific 10-year revision risks constant.Results - 214,638 primary THAs and 211,099 TKAs were included, of which 31% of THAs and 95% of TKAs were cemented. The 10-year cumulative revision risk varied between 1.6% and 13%, with higher risks in younger age categories. Delaying prosthesis placement by 5 years could potentially avoid 23 (3%) THA and 162 (17%) TKA revisions.Interpretation - Cumulative 10- year revision risk varied considerably by age in both fixation groups, which may be communicated to patients and used to guide timing of surgery.

What Is the Effect of Using a Competing-risks Estimator when Predicting Survivorship After Joint Arthroplasty: A Comparison of Approaches to Survivorship Estimation in a Large Registry

BACKGROUND

There is increasing interest in the development of statistical models that can be used to estimate risk of adverse patient outcomes after joint arthroplasty. Competing risk approaches have been recommended to estimate risk of longer-term revision, which is often likely to be precluded by the competing risk of death. However, a common approach is to ignore the competing risk by treating death as a censoring event and using standard survival models such as Cox regression. It is well-known that this approach can overestimate the event risk for population-level estimates, but the impact on the estimation of a patient's individualized risk after joint arthroplasty has not been explored.

QUESTIONS/PURPOSES

We performed this study to (1) determine whether using a competing risk or noncompeting risk method affects the accuracy of predictive models for joint arthroplasty revision and (2) determine the magnitude of difference that using a competing risks versus noncompeting risks approach will make to predicted risks for individual patients.

METHODS

The predictive performance of a standard Cox model, with competing risks treated as censoring events, was compared with the performance of two competing risks approaches, the cause-specific Cox model and Fine-Gray model. Models were trained and tested using data pertaining to 531,304 TKAs and 274,618 THAs recorded in the Australian Orthopaedic Association National Joint Replacement Registry between January 1, 2003 and December 31, 2017. The registry is a large database with near-complete capture and follow-up of all hip and knee joint arthroplasty in Australia from 2003 onwards, making it an ideal setting for this study. The performance of the three modeling approaches was compared in two different prediction settings: prediction of the 10-year risk of all-cause revision after TKA and prediction of revision for periprosthetic fracture after THA. The calibration and discrimination of each approach were compared using the concordance index, integrated Brier scores, and calibration plots. Calibration of 10-year risk estimates was further assessed within subgroups of age by comparing the observed and predicted proportion of events. Estimated 10-year risks from each model were also compared in three hypothetical patients with different risk profiles to determine whether differences in population-level performance metrics would translate into a meaningful difference for individual patient predictions.

RESULTS

The standard Cox and two competing risks models showed near-identical ability to distinguish between high-risk and low-risk patients (c-index 0.64 [95% CI, 0.64 to 0.64] for all three modeling approaches for TKAs and 0.66 [95% CI 0.66 to 0.66] for THA). All models performed similarly in patients younger than 75 years, but for patients aged 75 years and older, the standard Cox model overestimated the risk of revision more than the cause-specific Cox and Fine-Gray model did. These results were echoed when predictions were made for hypothetical individual patients. For patients with a low competing risk of mortality, the 10-year predicted risks from the standard Cox, cause-specific Cox, and Fine-Gray models were similar for TKAs and THAs. However, a larger difference was observed for hypothetical 89-year-old patients with increased mortality risk. In TKAs, the revision risk for an 89-year-old patient was so low that this difference was negligible (0.83% from the cause-specific Cox model versus 1.1% from the standard Cox model). However, for THAs, where older age is a risk factor for both death and revision for periprosthetic fracture, a larger difference was observed in the 10-year predicted risks for a hypothetical 89-year-old patient (3.4% from the cause-specific Cox model versus 5.2% from the standard Cox model).

CONCLUSION

When developing models to predict longer-term revision of joint arthroplasty, failing to use a competing risks modeling approach will result in overestimating the revision risk for patients with a high risk of mortality during the surveillance period. However, even in an extreme instance, where both the frequency of the event of interest and the competing risk of death are high, the largest absolute difference in predicted 10-year risk for an individual patient was just 1.8%, which may not be of consequence to an individual. Despite these findings, when developing or using risk prediction models, researchers and clinicians should be aware of how competing risks were handled in the modeling process, particularly if the model is intended for use populations where the mortality risk is high.

LEVEL OF EVIDENCE

Level III, therapeutic study.

Preoperative Risk Prediction Models for Short-Term Revision and Death After Total Hip Arthroplasty: Data from the Finnish Arthroplasty Register

Because of the increasing number of total hip arthroplasties (THAs), even a small proportion of complications after the operation can lead to substantial individual difficulties and health-care costs. The aim of this study was to develop simple-to-use risk prediction models to assess the risk of the most common reasons for implant failure to facilitate clinical decision-making and to ensure long-term survival of primary THAs.

What Factors Are Associated With Implant Failure?

PURPOSE

Recognition of patient-specific risk factors should reduce implant failure. The purpose of this study was to identify risk factors associated with implant failure and to determine if these factors differ over time after implant placement.

METHODS

The investigators implemented a retrospective case-controlled study and enrolled a sample composed of patients who had 1 or more implants removed from December 1, 2007 to February 29, 2020. Risk factors were grouped into demographic, medical history, and treatment-related variables. The primary outcome variable was whether the patient's implant failed, with control patients including those without implant failure. The duration was recorded for follow-up from the time of implant placement to the last visit or implant removal. Backward variable selection was used to predict whether an implant failed within 1 year, 1 to 4 years, or after 4 years in 3 multivariable logistic regressions.

RESULTS

Of 224 patients in this cohort, 82 experienced an implant failure. The mean age was 58.6 ± 15.3 years, and 53.1% were females. Patients with osteoporosis had an increased risk of failure in each period. Alcohol use, smoking, depression, and penicillin allergy were all associated with an increased probability of failure within 1 or more of the periods considered.

CONCLUSIONS

This study has identified multiple discrete risk factors for implant failure and has demonstrated that these factors are associated with implant failure at different periods after placement.

Developing a personalized outcome prediction tool for knee arthroplasty

AIMS

The purpose of this study was to develop a personalized outcome prediction tool, to be used with knee arthroplasty patients, that predicts outcomes (lengths of stay (LOS), 90 day readmission, and one-year patient-reported outcome measures (PROMs) on an individual basis and allows for dynamic modifiable risk factors.

METHODS

Data were prospectively collected on all patients who underwent total or unicompartmental knee arthroplasty at a between July 2015 and June 2018. Cohort 1 (n = 5,958) was utilized to develop models for LOS and 90 day readmission. Cohort 2 (n = 2,391, surgery date 2015 to 2017) was utilized to develop models for one-year improvements in Knee Injury and Osteoarthritis Outcome Score (KOOS) pain score, KOOS function score, and KOOS quality of life (QOL) score. Model accuracies within the imputed data set were assessed through cross-validation with root mean square errors (RMSEs) and mean absolute errors (MAEs) for the LOS and PROMs models, and the index of prediction accuracy (IPA), and area under the curve (AUC) for the readmission models. Model accuracies in new patient data sets were assessed with AUC.

RESULTS

Within the imputed datasets, the LOS (RMSE 1.161) and PROMs models (RMSE 15.775, 11.056, 21.680 for KOOS pain, function, and QOL, respectively) demonstrated good accuracy. For all models, the accuracy of predicting outcomes in a new set of patients were consistent with the cross-validation accuracy overall. Upon validation with a new patient dataset, the LOS and readmission models demonstrated high accuracy (71.5% and 65.0%, respectively). Similarly, the one-year PROMs improvement models demonstrated high accuracy in predicting ten-point improvements in KOOS pain (72.1%), function (72.9%), and QOL (70.8%) scores.

CONCLUSION

The data-driven models developed in this study offer scalable predictive tools that can accurately estimate the likelihood of improved pain, function, and quality of life one year after knee arthroplasty as well as LOS and 90 day readmission. Cite this article: Bone Joint J 2020;102-B(9):1183-1193.

Preoperative vitamin D level does not affect the short-term functional outcome after total knee arthroplasty in elderly women

Background

We aimed to evaluate the effect of vitamin D levels on the functional outcome of elderly women who underwent total knee arthroplasty (TKA).

Methods

Seven hundred and four patients (1013 knees) who underwent primary TKA were included in our retrospective study. Preoperative vitamin D levels were measured and the relationship analyzed between these and age, weight, height, body mass index, and bone mineral density. Two hundred and twenty patients (220 knees) who received unilateral TKA and were followed up for more than 1 year after operation were divided into two groups: Group 1, serum 25-hydroxyvitamin D3 (25(OH)D3) level < 20 ng/ml; and Group 2, 25(OH)D3 level ≥ 20 ng/ml. Both groups were evaluated for the relationship between vitamin D levels and postoperative Visual Analogue Scale (VAS) score, Knee Society Knee Score (KSKS), Knee Society Function Score (KSFS), and Western Ontario and McMaster Universities Arthritis Index (WOMAC) score.

Results

The number of vitamin D-deficient patients (< 20 ng/ml of serum 25(OH)D3 level) was 556 (79.0%). In the correlation analysis, the vitamin D level was negatively correlated with weight only (p = 0.033). No significant differences were observed between the groups in terms of postoperative VAS score, KSKS, KSFS, and WOMAC score.

Conclusions

Vitamin D deficiency was highly prevalent in patients who underwent TKA. Vitamin D levels negatively correlated with weight. Low vitamin D level was not a risk factor for unsatisfactory TKA outcome in elderly women.

Analysis and Review of Automated Risk Calculators Used to Predict Postoperative Complications After Orthopedic Surgery

PURPOSE OF REVIEW

To discuss the automated risk calculators that have been developed and evaluated in orthopedic surgery.

RECENT FINDINGS

Identifying predictors of adverse outcomes following orthopedic surgery is vital in the decision-making process for surgeons and patients. Recently, automated risk calculators have been developed to quantify patient-specific preoperative risk associated with certain orthopedic procedures. Automated risk calculators may provide the orthopedic surgeon with a valuable tool for clinical decision-making, informed consent, and the shared decision-making process with the patient. Understanding how an automated risk calculator was developed is arguably as important as the performance of the calculator. Additionally, conveying and interpreting the results of these risk calculators with the patient and its influence on surgical decision-making are paramount. The most abundant research on automated risk calculators has been conducted in the spine, total hip and knee arthroplasty, and trauma literature. Currently, many risk calculators show promise, but much research is still needed to improve them. We recommend they be used only as adjuncts to clinical decision-making. Understanding how a calculator was developed, and accurate communication of results to the patient, is paramount.

Impact of diabetes mellitus on surgical complications in patients undergoing revision total knee arthroplasty: Insulin dependence makes a difference

OBJECTIVES

Assessing the effects of diabetes mellitus (DM), non-insulin-dependent diabetes mellitus (NIDDM), and insulin-dependent diabetes mellitus (IDDM) on revision TKA (rTKA) has become increasingly imperative due to the increased rates of revisions associated with DM. This study sought to identify complications in rTKA that were independently associated with NIDDM/IDDM compared to non-diabetic (Non-DM) patients and whether IDDM was associated with specific postoperative complications compared to NIDDM.

METHODS AND MATERIALS

16,428 rTKA patients were identified from the ACS-NSQIP database from 2005 to 2016 and stratified into three separate cohorts. 12,922 (78.66%) were Non-DM, 2335 (14.21%) had NIDDM, and 1171 (7.13%) had IDDM. Univariate analyses were utilized to assess for differences in demographics, preoperative comorbidities, and postoperative complication rates. Multivariate logistic regression analyses were then employed to control for significant differences in patients characteristics to assess NIDDM and IDDM as independent risk factors for complications in comparison to Non-DM. IDDM was further analyzed as a risk factor in comparison to NIDDM for the purpose of elucidating the impact of insulin dependence on risk for postoperative complications.

RESULTS

NIDDM was an independent risk factor for deep incisional surgical site infections (Odds Ratio (OR): 2.477) and urinary tract infections (UTI) (OR 1.862) (p < 0.05). Compared to NIDDM, IDDM was independently associated with greater risk for pneumonia (OR 2.603), septic shock (OR 6.597), blood transfusions (OR 1.326), and an extended length of stay (OR: 1.331) (p < 0.05). IDDM additionally increased the risk for acute renal failure (OR 3.269) and cardiac arrest (OR 3.268) (p < 0.05) when compared to Non-DM. DM patients overall had increased rates of worse outcomes and infectious complications.

CONCLUSION

Although differences between diabetes and non-diabetes rTKA patients were seen, differences in complication rates between diabetes patients further divided based on insulin dependence status were also noted. Future work examining whether targeting perioperative glucose levels <200 mg/dL in DM rTKA patients decreases infectious complications is warranted. Future work analyzing the role of tranexamic acid administration and 24-h postoperative antibiotics in rTKA IDDM patients may be warranted given the elevated risk of pneumonia, septic shock, and blood transfusions.

Homogeneity in prediction of survival probabilities for subcategories of hipprosthesis data: the Nordic Arthroplasty Register Association, 2000-2013

Introduction: The four countries in the Nordic Arthroplasty Register Association (NARA) share geographic proximity, culture, and ethnicity. Pooling data from different sources in order to obtain higher precision and accuracy of survival-probability estimates is appealing. Nevertheless, survival probabilities of hip replacements vary between the countries. As such, risk prediction for individual patients within countries may be problematic if data are merged. In this study, our primary question was to address when data merging for estimating prosthesis survival in subcategories of patients is advantageous for survival prediction of individual patients, and at what sample sizes this may be advised.

Methods: Patients undergoing total hip replacements for osteoarthritis between January 1, 2000 and December 31, 2013 in the four Nordic countries were studied. A total of 184,507 patients were stratified into 360 patient subcategories based on country, age-group, sex, fixation, head size, and articulation. For each patient category, we determined the sample size needed from a single country to obtain a more accurate and precise estimate of prosthesis-survival probability at 5 and 10 years compared to an estimate using data from all countries. The comparison was done using mean-square error.

Results: We found large variations in the sample size needed, ranging from 40 to 2,060 hips, before an estimate from a single Nordic country was more accurate and precise than estimates based on the NARA data.

Conclusion: Using pooled survival-probability estimates for individual risk prediction may be imprecise if there is heterogeneity in the pooled data sources. By applying mean-square error, we demonstrate that for small sample sizes, applying the larger NARA database may provide a more accurate and precise estimate; however, this effect is not consistent and varies with the characteristics of the subcategory.

An international comparison of THA patients, implants, techniques, and survivorship in Sweden, Australia, and the United States

Background and purpose - International comparisons of total hip arthroplasty (THA) practices and outcomes provide an opportunity to enhance the quality of care worldwide. We compared THA patients, implants, techniques, and survivorship in Sweden, Australia, and the United States. Patients and methods - Primary THAs due to osteoarthritis were identified using Swedish (n = 159,695), Australian (n = 279,693), and US registries (n = 69,641) (2003-2015). We compared patients, practices, and implant usage across the countries using descriptive statistics. We evaluated time to all-cause revision using Kaplan-Meier survival curves. We assessed differences in countries' THA survival using chi-square tests of survival probabilities. Results - Sweden had fewer comorbidities than the United States and Australia. Cement fixation was used predominantly in Sweden and cementless in the United States and Australia. The direct anterior approach was used more frequently in the United States and Australia. Smaller head sizes (≤ 32 mm vs. ≥ 36 mm) were used more often in Sweden than the United States and Australia. Metal-on-highly cross-linked polyethylene was used more frequently in the United States and Australia than in Sweden. Sweden's 5- (97.8%) and 10-year THA survival (95.8%) was higher than the United States' (5-year: 97.0%; 10-year: 95.2%) and Australia (5-year: 96.3%; 10-year: 93.5%). Interpretation - Patient characteristics, surgical techniques, and implants differed across the 3 countries, emphasizing the need to adjust for demographics, surgical techniques, and implants and the need for global standardized definitions to compare THA survivorship internationally.

Age, gender, functional KSS, reason for revision and type of bone defect predict functional outcome 5 years after revision total knee arthroplasty: a multivariable prediction model

PURPOSE

The number of revision total knee arthroplasties (rTKA) is increasing. Unfortunately, not all patients benefit from revision surgery. The aim of this study was to develop a clinical prediction model that can be used to predict the functional outcome 5 years after rTKA.

METHODS

Data of patients receiving rTKA at Sint Maartenskliniek, Nijmegen, The Netherlands, from 2004 onwards were prospectively collected. Demographic and clinical variables and patient-reported outcome scores were collected and considered as potential predictors. Beneficial outcome was defined as an increase of ≥ 20 points on the functional knee society scores (fKSS) or an absolute fKSS ≥ 80 points 5 years after surgery. The prediction model was developed using backward logistic regression. Regression coefficients were converted into an easy to use prediction rule.

RESULTS

Overall, 295 rTKA patients were included of whom 157 (53%) had beneficial fKSS 5 years later. Age, gender, femoral bone defects, preoperative fKSS, and stiffness as reason for revision were included in the model. Men had a higher chance of beneficial fKSS than women (OR 1.59, 95% CI 0.91-2.78). Patients with major bone defects (OR 0.44, 95% CI 0.22-0.85), higher age (IQR OR 0.39, 95% CI 0.26-0.58), higher preoperative fKSS (IQR OR 0.42, 95% CI 0.30-0.59), and severe stiffness (OR 0.48, 95% CI 0.20-1.15) had a lower chance of successful outcome. The model's AUC was 0.76, 95% CI 0.70-0.81.

CONCLUSION

Easily determinable characteristics of patients who need rTKA can be used to predict future functional outcome. Young men with low preoperative fKSS without severe stiffness are more likely to achieve a beneficial outcome.

LEVEL OF EVIDENCE

IV.

A risk-stratification algorithm to reduce superficial surgical site complications in primary hip and knee arthroplasty

BACKGROUND

Surgical site complications (SSCs) are the most common cause for readmission after total joint arthroplasty (TJA), increasing costs while predisposing to inferior long-term outcomes. Prophylactic use of closed-incision negative pressure therapy (ciNPT) may lower the risk of these complications, especially in high-risk populations, but appropriate-use guidelines are lacking for patients undergoing primary TJA. We sought to develop a risk-stratification algorithm to guide use of ciNPT dressings and test its use in normalizing the rate of superficial SSCs among high-risk groups.

METHODS

We reviewed 323 consecutive primary TJAs, where 38% of those patients considered at elevated risk were risk-stratified to receive ciNPT dressings. An individual risk score was developed, assigning points based on patient-specific risk factors. We identified a historical control population of 643 patients who all received the same postoperative dressing to test the impact of this risk score.

RESULTS

Compared with historical controls, we observed a modest but significant improvement in superficial SSCs after implementation of risk-stratification (12.0% vs 6.8%; P = .013). Among high-risk patients, there was a marked improvement in SSCs when treated prophylactically with ciNPT dressings as compared with historical controls (26.2% vs 7.3%; P < .001). Low-risk patients, who continued to be treated with standard postoperative dressings, demonstrated no significant improvement (8.6% vs 6.5%; P = .344).

CONCLUSIONS

ciNPT dressings are effective at reducing and normalizing risks of superficial SSCs among high-risk primary arthroplasty patients. The proposed risk-stratification algorithm may help identify those patients who benefit most from these dressings.

The Michigan Arthroplasty Registry Collaborative Quality Initiative Experience: Improving the Quality of Care in Michigan

The Michigan Arthroplasty Registry Collaborative Quality Initiative (MARCQI) is a regional quality improvement effort that is focused on hip and knee arthroplasty. From its inception in 2012, MARCQI has grown to include data from 66 hospitals and surgery centers, and contains over 209,000 fully abstracted cases in its database. Using high-quality risk-standardized outcomes data, MARCQI drives quality improvement through a collaborative and nonpunitive structure. Quality improvement initiatives have included transfusion reduction, infection prevention, venous thromboembolism reduction, and reduction of discharge to nursing homes. In addition, MARCQI focuses on postmarket surveillance of implants by computing revision-risk estimates based on the cases that were registered prior to the end of 2016. This paper describes the impact of MARCQI on the quality of hip and knee arthroplasty care in the state of Michigan since its inception in 2012, and it briefly summarizes the recently released 5-year report.

Influence of diabetes on tissue healing in orthopaedic injuries

Diabetes is a group of metabolic diseases characterized by hyperglycaemia resulting from the defective action or secretion of insulin. Chronic hyperglycaemia can lead to the damage, dysfunction and failure of various organs. In the context of complications of healing and orthopaedic rehabilitation, vascular (microangiopathy) and nerve (neuropathy) disorders deserve particular attention. About 12% of the patients admitted to orthopaedic departments have diabetes. Studies indicate that there is an indisputable link between diabetes and: an increased risk of fractures, the difficult healing of injuries of bones, ligaments and musculotendinous. It appears that one of the main reasons for this is non-enzymatic glycosylation (glycation) of collagen molecules, a phenomenon observed in the elderly and diabetic populations, as it leads to the formation of advanced glycation end products (AGEs). Collagen is one of the major connective tissue components, and is therefore part of ligaments, tendons and bones. AGEs affect the weakening of its structure and biomechanical properties, and thus also affects the weakening of the structure and properties of the above-mentioned tissues. The aim of the study is to undertake an overview of the current knowledge of the impact of diabetes on the risk of some injuries and subsequent healing and rehabilitation of patients following orthopaedic injuries.

On a learning curve for shared decision making: Interviews with clinicians using the knee osteoarthritis Option Grid

RATIONAL

Tools used in clinical encounters to illustrate to patients the risks and benefits of treatment options have been shown to increase shared decision making. However, we do not have good information about how these tools are viewed by clinicians and how clinicians think patients would react to their use.

OBJECTIVE

Our aim was to examine clinicians' views about the possible and actual use of tools designed to support patients and clinicians to collaborate and deliberate about treatment options, namely, Option Grid decision aids.

METHOD

We conducted a thematic analysis of qualitative interviews embedded in the intervention phase of a trial of an Option Grid decision aid for osteoarthritis of the knee. Interviews were conducted with 6 participating clinicians before they used the tool and again after clinicians had used the tool with 6 patients.

RESULTS

In the first interview, clinicians voiced concerns that the tool would lead to an increase in encounter duration, patient resistance regarding involvement in decision making, and potential information overload. At the second interview, after minimal training, the clinicians reported that the tool had changed their usual way of communicating, and it was generally acceptable and helpful to integrate it into practice.

DISCUSSION AND CONCLUSIONS

After experiencing the use of Option Grids, clinicians became more willing to use the tools in their clinical encounters with patients. How best to introduce Option Grids to clinicians and adopt their use into practice will need careful consideration of context, workflow, and clinical pathways.

The Influence of Radiological Severity and Symptom Duration of Osteoarthritis on Postoperative Outcome After Total Hip Arthroplasty: A Prospective Cohort Study

BACKGROUND

We aimed to investigate the influence of preoperative radiological severity and symptom duration of hip osteoarthritis (OA) on the postoperative functional outcome, quality of life, as well as abductor muscle strength after total hip arthroplasty (THA).

METHODS

In this prospective cohort study, we studied 250 patients. Preoperatively, we evaluated the function with the Western Ontario and McMaster Universities Osteoarthritis (WOMAC) index and quality of life with euroqol-5D (EQ-5D). At 1 year after THA, the same scores and also hip abductor muscle strength were measured in 222 patients. We divided the cohort twice, first according to the radiological OA severity [Kellgren-Lawrence classification (KL)] and then according to the OA symptom duration. We investigated whether the preoperative KL class and symptom duration influenced the 1-year WOMAC (primary outcome measure) or EQ-5D and abductor muscle strength (secondary outcome measures).

RESULTS

The crude results showed that KL class and symptom duration had no influence (P = .90 and P = .20, respectively) on the 1-year WOMAC. Younger age, male gender, and lower body mass index were associated with a better function. Regarding 1-year EQ-5D, the crude results showed that body mass index and KL class had no influence (P = .83 and P = .39, respectively). The adjusted results showed that only age and gender influenced the postoperative EQ-5D. No influence of the tested factors was found on the 1-year abductor muscle strength.

CONCLUSION

Preoperative radiological OA severity and symptom duration had no influence on the outcome of THA and should probably not affect the decision about timing the operative intervention.

Development and validation of a shared decision-making instrument for health-related quality of life one year after total hip replacement based on quality registries data

RATIONALE, AIMS AND OBJECTIVES

Clinicians considering improvements in health-related quality of life (HRQoL) after total hip replacement (THR) must account for multiple pieces of information. Evidence-based decisions are important to best assess the effect of THR on HRQoL. This work aims at constructing a shared decision-making tool that helps clinicians assessing the future benefits of THR by offering predictions of 1-year postoperative HRQoL of THR patients.

METHODS

We used data from the Swedish Hip Arthroplasty Register. Data from 2008 were used as training set and data from 2009 to 2012 as validation set. We adopted two approaches. First, we assumed a continuous distribution for the EQ-5D index and modelled the postoperative EQ-5D index with regression models. Second, we modelled the five dimensions of the EQ-5D and weighted together the predictions using the UK Time Trade-Off value set. As predictors, we used preoperative EQ-5D dimensions and the EQ-5D index, EQ visual analogue scale, visual analogue scale pain, Charnley classification, age, gender, body mass index, American Society of Anesthesiologists, surgical approach and prosthesis type. Additionally, the tested algorithms were combined in a single predictive tool by stacking.

RESULTS

Best predictive power was obtained by the multivariate adaptive regression splines (R²  = 0.158). However, this was not significantly better than the predictive power of linear regressions (R²  = 0.157). The stacked model had a predictive power of 17%.

CONCLUSIONS

Successful implementation of a shared decision-making tool that can aid clinicians and patients in understanding expected improvement in HRQoL following THR would require higher predictive power than we achieved. For a shared decision-making tool to succeed, further variables, such as socioeconomics, need to be considered.

Can patient-reported outcomes predict re-operations after total hip replacement?

PURPOSE

We investigated if patient-reported outcomes (PROMs) one year after total hip replacement (THR) can predict the risk of re-operation using data from the Swedish Hip Arthroplasty Register.

METHODS

A total of 75,899 patients with THR due to osteoarthritis operated in 2002-2014 were included. We used Kaplan-Meier and Cox regression to investigate the relationship between one-year post-operative PROMs and risk of re-operation (all types of further hip surgery). The predictive power of the model and post-operative PROMs were evaluated by concordance index (C).

RESULTS

Kaplan-Meier estimates for not being re-operated at eight years was 95.5% (95%CI; 95.3-95.8). Cox regression analyses showed that all PROMs, except for EQ-VAS, were associated with re-operation. The full model had a concordance index of 0.68. Satisfaction (C = 0.65) and pain (C = 0.65) in isolation had the highest predictive power.

CONCLUSIONS

Worse PROMs predicted higher risk of re-operation. Therefore, we believe PROMs may be helpful in identifying patients at risk for re-operation and timely address their problems.

Clinical Considerations for the Use Lower Extremity Arthroplasty in the Elderly

There is an increase in the aging population that has led to a surge of reported cases of osteoarthritis and a greater demand for lower extremity arthroplasty. This article aims to review the current treatment options and expectations when considering lower extremity arthroplasty in the elderly patient with an emphasis on the following subjects: (1) updated clinical guidelines for the management of osteoarthritis in the lower extremity, (2) comorbidities and risk factors in the surgical patient, (3) preoperative evaluation and optimization of the surgical patient, (4) surgical approach and implant selection, and (5) rehabilitation and life after lower extremity arthroplasty.

Comparison of Perioperative Adverse Event Rates After Total Knee Arthroplasty in Patients With Diabetes: Insulin Dependence Makes a Difference

BACKGROUND

Total knee arthroplasty (TKA) is an effective treatment option for patients with advanced osteoarthritis and has become one of the most frequently performed orthopedic procedures. With the increasing prevalence of diabetes mellitus (DM), the burden of its sequela and associated surgical complications has also increased. For these reasons, it is important to understand the association between DM and the rates of perioperative adverse events after TKA.

METHODS

A retrospective cohort study was conducted using the American College of Surgeons National Surgical Quality Improvement Program database. Patients who underwent TKA between 2005 and 2014 were identified and characterized as having insulin-dependent DM (IDDM), non-insulin-dependent DM (NIDDM), or not having DM. Multivariate Poisson regression was used to control for demographic and comorbid factors and to assess the relative risks of multiple adverse events in the initial 30 postoperative days.

RESULTS

A total of 114,102 patients who underwent TKA were selected (IDDM = 4881 [4.3%]; NIDDM = 15,367 [13.5%]; and no DM = 93,854 [82.2%]). Patients with NIDDM were found to be at greater risk for 2 of 17 adverse events studied relative to patients without DM. However, patients with IDDM were found to be at greater risk for 12 of 17 adverse events studied relative to patients without DM.

CONCLUSION

In comparison with patients with NIDDM, patients with IDDM are at greater risk for many more perioperative adverse outcomes relative to patients without DM. These findings have important implications for patient selection, preoperative risk stratification, and postoperative expectations.

Description of the rates, trends and surgical burden associated with revision for prosthetic joint infection following primary and revision knee replacements in England and Wales: an analysis of the National Joint Registry for England, Wales, Northern Ireland and the Isle of Man

OBJECTIVES

To describe the prevalence rates of revision surgery for the treatment of prosthetic joint infection (PJI) for patients undergoing knee replacement, their time trends, the cumulative incidence function of revision for PJI and estimate the burden of PJI at health service level.

DESIGN

We analysed revision knee replacements performed due to a diagnosis of PJI and the linked index procedures recorded in the National Joint Registry from 2003 to 2014 for England and Wales. The cohort analysed consisted of 679 010 index primary knee replacements, 33 920 index revision knee replacements and 8247 revision total knee replacements performed due to a diagnosis of PJI. The prevalence rates, their time trends investigated by time from index surgery to revision for PJI, cumulative incidence functions and the burden of PJI (total procedures) were calculated. Overall linear trends were investigated with log-linear regression.

RESULTS

The incidence of revision total knee replacement due to PJI at 2 years was 3.2/1000 following primary and 14.4/1000 following revision knee replacement, respectively. The prevalence of revision due to PJI in the 3 months following primary knee replacement has risen by 2.5-fold (95% CI 1.2 to 5.3) from 2005 to 2013 and 7.5-fold (95% CI 1.0 to 56.1) following revision knee replacement. Over 1000 procedures per year are performed as a consequence of knee PJI, an increase of 2.8 from 2005 to 2013. Overall, 75% of revisions were two-stage with an increase in use of single-stage from 7.9% in 2005 to 18.8% in 2014.

CONCLUSIONS

Although the risk of revision due to PJI following knee replacement is low, it is rising, and coupled with the established and further predicted increased incidence of both primary and revision knee replacements, this represents an increasing and substantial treatment burden for orthopaedic service delivery in England and Wales. This has implications for future service design and the funding of individual and specialist centres.

Revision for prosthetic joint infection following hip arthroplasty: Evidence from the National Joint Registry

Objectives

We used the National Joint Registry for England, Wales, Northern Ireland and the Isle of Man (NJR) to investigate the risk of revision due to prosthetic joint infection (PJI) for patients undergoing primary and revision hip arthroplasty, the changes in risk over time, and the overall burden created by PJI.

Methods

We analysed revision total hip arthroplasties (THAs) performed due to a diagnosis of PJI and the linked index procedures recorded in the NJR between 2003 and 2014. The cohort analysed consisted of 623 253 index primary hip arthroplasties, 63 222 index revision hip arthroplasties and 7585 revision THAs performed due to a diagnosis of PJI. The prevalence, cumulative incidence functions and the burden of PJI (total procedures) were calculated. Overall linear trends were investigated with log-linear regression.

Results

We demonstrated a prevalence of revision THA due to prosthetic joint infection of 0.4/100 procedures following primary and 1.6/100 procedures following revision hip arthroplasty. The prevalence of revision due to PJI in the three months following primary hip arthroplasty has risen 2.3-fold (95% confidence interval (CI) 1.3 to 4.1) between 2005 and 2013, and 3.0-fold (95% CI 1.1 to 8.5) following revision hip arthroplasty. Over 1000 procedures are performed annually as a consequence of hip PJI, an increase of 2.6-fold between 2005 and 2013.

Conclusions

Although the risk of revision due to PJI following hip arthroplasty is low, it is rising and, coupled with the established and further predicted increased incidence of both primary and revision hip arthroplasty, this represents a growing and substantial treatment burden.

Cite this article: E. Lenguerrand, M. R. Whitehouse, A. D. Beswick, S. A. Jones, M. L. Porter, A. W. Blom. Revision for prosthetic joint infection following hip arthroplasty: Evidence from the National Joint Registry. Bone Joint Res 2017;6:391–398. DOI: 10.1302/2046-3758.66.BJR-2017-0003.R1.

Arthroplasty registries around the world: valuable sources of hip implant revision risk data

PURPOSE OF REVIEW

National and regional arthroplasty registries have proliferated since the Swedish Knee Arthroplasty Register was started in 1975. Registry reports typically present implant-specific estimates of revision risk and patient- and technique-related factors that can inform clinical decision-making about implants and techniques. However, annual registry reports are long and it is difficult for clinicians to extract comparable revision risk data. Since implants may appear in multiple registry reports, it is even more difficult to gather relevant data for clinical decision-making about implant selection. The purpose of this paper is to briefly describe arthroplasty registry concepts, international registries around the world, US registries, and provide a parsimonious summary of total hip arthroplasty (THA) implant revision risk reports across registries.

RECENT FINDINGS

Revision risk data for conventional stem/cup combinations reported by the Australian, R.I.P.O. (Italian), Finnish, and Danish registries are summarized here. These registries were selected because they presented 10-year data on revision risk by stem/cup combination. Four tables of revision risk are presented based on fixation: cemented, uncemented, hybrid, and reverse hybrid. Review of these tables show there is wide variation in revision risk across conventional THA implants. It also demonstrates that some cemented implants have better 10-year risk than the best uncemented implants. Many arthroplasty registries prepare annual reports that include revision risk data for implants and they are posted on the registry websites. Arthroplasty surgeons should stay current with these registry reports on implant performance and potential outliers and keep them in mind when making implant decisions.

Annual revision rates of partial versus total knee arthroplasty: A comparative meta-analysis

BACKGROUND

Utilization of unicompartmental knee arthroplasty (UKA) and patellofemoral arthroplasty (PFA) as alternatives to total knee arthroplasty (TKA) for unicompartmental knee osteoarthritis (OA) has increased. However, no single resource consolidates survivorship data between TKA and partial resurfacing options for each variant of unicompartmental OA. This meta-analysis compared survivorship between TKA and medial UKA (MUKA), lateral UKA (LUKA) and PFA using annual revision rate as a standardized metric.

METHODS

A systematic literature search was performed for studies quantifying TKA, MUKA, LUKA and/or PFA implant survivorship. Studies were classified by evidence level and assessed for bias using the MINORS and PEDro instruments. Annual revision rates were calculated for each arthroplasty procedure as percentages/observed component-year, based on a Poisson-normal model with random effects using the R-statistical software package.

RESULTS

One hundred and twenty-four studies (113 cohort and 11 registry-based studies) met inclusion/exclusion criteria, providing data for 374,934 arthroplasties and 14,991 revisions. The overall evidence level was low, with 96.7% of studies classified as level III-IV. Annual revision rates were lowest for TKA (0.49%, CI 0.41 to 0.58), followed by MUKA (1.07%, CI 0.87 to 1.31), LUKA (1.13%, CI 0.69 to 1.83) and PFA (1.75%, CI 1.19 to 2.57). No difference was detected between revision rates for MUKA and LUKA (p=0.222).

CONCLUSIONS

Revisions of MUKA, LUKA and PFA occur at an annual rate of 2.18, 2.31 and 3.57-fold that of TKA, respectively. These estimates may be used to inform clinical decision-making, guide patient expectations and evaluate the cost-effectiveness of total versus partial knee replacement in the setting of unicompartmental OA.

Calculating the Cost and Risk of Comorbidities in Total Joint Arthroplasty in the United States

BACKGROUND

With increased scrutiny regarding the cost and safety of health care delivery, there is increasing interest in judicious patient selection for total joint arthroplasty (TJA) procedures. It is unknown which comorbidities incur the greatest increase in risk to the patient and cost to the system after TJA. Therefore, this study sought to characterize the association of common preoperative comorbidities with both the risk for postoperative in-hospital complications and the total hospital cost in patients undergoing TJA.

METHODS

A retrospective cohort study was conducted using the National Inpatient Sample. All elective, unilateral, primary or revision total knee or hip arthroplasty procedures in patients aged 40-95 years from 2008 to 2012 were identified. Common preoperative comorbidities were identified with use of clinical comorbidity software. Risk of complication and cost were calculated for each comorbidity.

RESULTS

A total of 4,323,045 patients were identified. Patient comorbidities increased the risk of major postoperative complications, with the highest risk associated with congestive heart failure (CHF; relative risk [RR], 4.402), valvular heart disease (VHD; RR, 3.209), and chronic obstructive pulmonary disease (COPD; RR, 2.813). Likewise, comorbidities increased overall hospital costs, with the largest additional costs associated with coagulopathy (+$3787), CHF (+$3701), and electrolyte disorders (+$3179). The cumulative number of comorbidities was associated with increased risk (R² = 0.86) and cost (R² = 0.90).

CONCLUSION

The findings of our study suggest that greater comorbidity burden is associated with increased risk and cost in TJA. Specifically, this article identifies the patient comorbidities that incur the greatest increase in postoperative complications (CHF, VHD, COPD) and cost (coagulopathy, CHF, electrolyte disorders) after TJA.

Preoperative Opioid Use Is Associated with Early Revision After Total Knee Arthroplasty: A Study of Male Patients Treated in the Veterans Affairs System

BACKGROUND

Opioid use is endemic in the U.S. and is associated with morbidity and mortality. The impact of long-term opioid use on joint-replacement outcomes remains unknown. We tested the hypothesis that use of opioids is associated with adverse outcomes after total knee arthroplasty (TKA).

METHODS

We performed a retrospective analysis of patients who had had TKA within the U.S. Veterans Affairs (VA) system over a 6-year period and had been followed for 1 year postoperatively. The length of time for which an opioid had been prescribed and the morphine equivalent dose were calculated for each patient. Patients for whom opioids had been prescribed for >3 months in the year prior to the TKA were assigned to the long-term opioid group. A natural language processing-based machine-learning classifier was developed to classify revisions due to infectious and non-infectious causes on the basis of the postoperative note. Survival curves for the time to knee revision or manipulation were used to compare the long-term opioid group with the patients who did not take opioids long-term. Hazard and odds ratios for knee revision and manipulation were obtained as well.

RESULTS

Of 32,636 patients (94.4% male; mean age [and standard deviation], 64.45 ± 9.41 years) who underwent TKA, 12,772 (39.1%) were in the long-term opioid group and 734 (2.2%) had a revision within a year after the TKA. Chronic kidney disease, diabetes, and long-term opioid use were associated with revision within 1 year-with odds ratios (95% confidence intervals [CIs]) of 1.76 (1.37 to 2.22), 1.11 (0.93 to 1.31), and 1.40 (1.19 to 1.64), respectively-and were also the leading factors associated with a revision at any time after the index TKA-with odds ratios (95% CIs) of 1.61 (1.34 to 1.92), 1.21 (1.08 to 1.36), and 1.28 (1.15 to 1.43), respectively. Long-term opioid use had a hazard ratio of 1.19 (95% CI = 1.10 to 0.24) in the analysis of its relationship with knee revision, but the hazard was not significant in the analysis of its association with knee manipulation. The accuracy of the text classifier was 0.94, with the area under the receiver operating characteristic curve being 0.99. There was no association between long-term use of opioids and the specific cause for knee revision.

CONCLUSIONS

Long-term opioid use prior to TKA was associated with an increased risk of knee revision during the first year after TKA among predominantly male patients treated in the VA system.

LEVEL OF EVIDENCE

Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.

Preoperative Glycemic Control on Total Joint Arthroplasty Patient-Perceived Outcomes and Hospital Costs

BACKGROUND

The purpose of this study was to determine the influence of preoperative glycemic control in diabetic patients undergoing a primary total hip or knee arthroplasty. We wanted to study patient-perceived outcomes in the medium term, the length of stay, hospital costs, and rate of short-term postoperative complications.

METHODS

One hundred twenty consecutive primary total joint arthroplasties (TJAs) performed in type 2 diabetic patients were stratified into 2 groups representing optimal and suboptimal preoperative glycemic control, based on serum levels of glycated hemoglobin (HbA_1c), and those groups compared.

RESULTS

The mean follow-up time was 5.9 years (range, 2.1-10.7 years). Both groups demonstrated improvement in all patient-perceived outcome measures after TJA, with no significant difference detected in any change of a measure between the groups. No significant difference was detected in the length of stay, hospital costs, or rate of short-term postoperative complications between the groups.

CONCLUSION

Preoperative glycemic control in type 2 diabetic patients undergoing TJA did not affect patient-perceived outcomes in the medium term. Optimal vs suboptimal glycemic control in these patients also had no effect on the length of stay, hospital costs, or rate of short-term postoperative complications.