Estimating risk in Medicare patients with THA: an electronic risk calculator for periprosthetic joint infection and mortality

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.

Is asymptomatic bacteriuria a noticeable risk factor for periprosthetic joint infection following total joint arthroplasty? A systematic review and meta-analysis

INTRODUCTION

Total joint arthroplasty (TJA) is a common procedure that improves the quality of life for severe arthritis patients. The rising demand for TJA places enormous financial strain on the world's healthcare systems, which is exacerbated by postoperative readmissions for complications such as periprosthetic joint infections (PJIs). We conducted a systematic review and meta-analysis to determine if asymptomatic bacteriuria (ASB) increases infection risk.

METHODS

We conducted searches in three databases: PubMed, Scopus, and Web of Science. Screening steps have been carried out according to PRISMA guidelines. The study focused on patients who had undergone TJA and exhibited ASB. Two reviewers independently screened, assessed quality, and extracted data. Meta-analysis used Mantel-Haenszel method.

RESULTS

Following full-text screening, 12 studies were deemed eligible for inclusion in the systematic review, encompassing a total of 42,592 patients. A heightened occurrence of PJI was observed among TJA patients with ASB in comparison to controls (OR [95%CI] = 3.47 [1.42-8.44]). However, microorganisms responsible for the PJIs differed from those identified in the urine cultures of ASB. Additionally, analyses indicate that preoperative antibiotic treatment for ASB does not significantly affect the subsequent risk of PJI (OR [95% CI] = 1.00 [0.42-2.39]). Unlike surgical site infection (SSI), which did not show a difference in the rate of occurrence between the two groups, TJA patients with ASB were more likely to experience superficial wound infection (OR [95%CI] = 3.81 [2.02-7.21]).

CONCLUSION

This review and meta-analysis confirm that ASB correlate with heightened risks of PJI and superficial infection in TJA patients. However, no relationship was found between ASB and PJI microorganisms which raise doubts about the role of ASB microorganisms as the direct cause of infection following TJA.

Identifying Critical Evidence Gaps in Wound Closure and Incision Management After Total Knee Arthroplasty: Delphi Panel Insights

BACKGROUND

Effective surgical wound management in total knee arthroplasty (TKA) is crucial for optimal healing and patient outcomes. Despite surgical advances, managing wounds to prevent complications remains challenging. This study aimed to identify and address evidence gaps in TKA wound management, including preoperative optimization, intraoperative options, and postoperative complication avoidance. Addressing these issues is vital for patient recovery and surgical success.

METHODS

This study used the Delphi method with 20 experienced orthopedic surgeons from Europe and North America. Conducted from April to September 2023, the process involved three stages: an initial electronic survey, a virtual meeting, and a concluding electronic survey. The panel reviewed and reached a consensus on 26 statements about TKA wound management based on a comprehensive literature review. Additionally, the panel aimed to identify critical evidence gaps in wound management practices.

RESULTS

The panel achieved consensus on various wound management practices but highlighted significant evidence gaps. Consensus was reached on wound closure methods, including mesh-adhesive dressings, skin glue, staples, barbed sutures, and negative pressure wound therapy. However, further evidence is needed to address the cost-effectiveness of these methods and develop best practices for patient outcomes. Identifying these gaps highlights the need for more research to improve TKA wound care.

CONCLUSIONS

Identifying major evidence gaps underscores the need for targeted research in TKA wound management. Addressing these gaps is crucial for developing effective, efficient, and patient-friendly wound care strategies. Future research should focus on comparative effectiveness studies and developing guidelines for emerging technologies. Bridging these gaps could improve patient outcomes, reduce complications, and enhance TKA surgery success.

Early Readmission and Revision After Total Joint Arthroplasty: An Analysis of Cause and Cost

Background: Bundled payments for total joint arthroplasty (TJA) were instituted by the Centers for Medicare and Medicaid Services (CMS) to reimburse providers a lump sum for operative and 90-day postoperative costs. Gaining a better understanding of which TJA patients are at risk for early return to the operating room (OR) is critical in preoperative optimization of those with modifiable risks, which could improve bundled-payment performance. Purpose: We sought to identify the most common reason for readmissions, as well as patient characteristics and costs, associated with early return to the OR among TJA patients. Methods: This was a retrospective cohort study of Medicare patients who had undergone primary total hip or knee arthroplasty (THA or TKA) between 2013 and 2018 at a tertiary care hospital. We used the CMS research identifiable files database to identify the most common reasons for readmissions and revisions within 90 days of surgery. Total billing claims were used to determine the cost of early readmissions and revisions. Multivariate regression analysis was used to determine the characteristics associated with early readmission or revision. Results: Out of 20 166 primary TJA patients identified, we found 1349 readmissions (5.6%) and 163 (0.8%) revisions within 90 days of surgery. Dislocation was the most common indication for readmission, and periprosthetic joint infection was the most common indication for revision. Early return to the OR was associated with a mean $105,988 (standard deviation [SD] = $76,865) in CMS claims for the inpatient stay. Factors associated with a higher risk of early reoperation were female sex, THA, longer length of stay, and discharge to long-term care facility. Conclusions: This retrospective cohort study found that early return to the OR after TJA increased overall 90-day costs by 260%, suggesting that early reoperation might have a significant impact on bundled payments. Further study is warranted.

Chronic kidney disease increases cost of care and readmission risk after shoulder arthroplasty

BACKGROUND

Chronic kidney disease (CKD) is associated with adverse outcomes and higher costs after lower extremity arthroplasty from higher rates of infection, aseptic loosening, and transfusion and longer hospital length of stay (LOS). The purpose of this study was to compare health care utilization and 90-day encounter charges after shoulder arthroplasty (SA) in patients with and without renal disease. A secondary aim was to define the characteristics of patients with renal disease.

METHODS

We conducted a retrospective cohort study of all patients who underwent primary SA from January 2015 to December 2019 by a single surgeon at a single institution. Patients without a baseline glomerular filtration rate (GFR) were excluded. We evaluated results for patients with CKD (GFR ≤59 mL/min/1.73 m2) and without CKD (GFR ≥60 mL/min/1.73 m2). Univariate regression was performed to assess the influence of CKD on health care utilization, including LOS, transfusion, and risk for emergency department (ED) revisit or readmission during the 90-day postoperative period. In addition, 90-day encounter charges, revisit charges, and ED charges for patients with CKD were compared with those for patients with normal renal function. Last, multivariable linear regression models were used to assess the effect of estimated GFR on total 90-day encounter charges.

RESULTS

A total of 514 patients met the study inclusion criteria, with 125 having CKD and 389 having normal GFR. Patients with CKD were more likely to require transfusion (odds ratio: 16.2 [confidence interval: 1.9, 139.7], P = .011) despite similar intraoperative estimated blood loss (156.9 ± 132.5 mL vs. 153.8 ± 89.7 mL; P = .768). In addition, patients with CKD had longer LOS (2.8 ± 1.3 days vs. 2.3 ± 1.0 days; P < .001), had higher 90-day readmission rates (P = .001), were more likely to visit the ED within 90 days after SA (P = .018), and had higher total 90-day encounter charges ($37,769 ± $6901 vs. $35,684 ± $5312; P = .001). Each unit increase in eGFR independently reduced total encounter charges by $67 (-$132, -$2; P = .043); dialysis patients incurred higher total 90-day encounter charges compared with patients with less severe renal disease ($42,733 ± $8985 vs. $37,531 ± $6749; P = .002). Also, patients with CKD were older (73.2 ± 8.9 vs. 68.1 ± 9.4 years; P < .001); had a lower preoperative hemoglobin level (12.4 ± 1.5 g/dL vs. 13.4 ± 1.5 g/dL; P < .001), higher American Society of Anesthesiologists score (P < .001), and more preoperative comorbidities (5.9 ± 2.9 vs. 5.0 ± 3.1; P < .001); and were more likely to use opioids preoperatively (P = .043).

CONCLUSION

Patients with CKD have a higher risk for blood transfusion, ED visits, and readmission after SA, with higher total 90-day encounter charges. Identifying and optimizing this patient population before surgery can reduce costs and improve outcomes, which benefits patients, physicians, institutions, and payors.

International Delphi Study on Wound Closure and Dressing Management in Joint Arthroplasty: Part 1: Total Knee Arthroplasty

BACKGROUND

The purpose of this modified Delphi study was to obtain consensus on wound closure and dressing management in total knee arthroplasty (TKA).

METHODS

The Delphi panel included 20 orthopaedic surgeons from Europe and North America. There were 26 statements identified using a targeted literature review. Consensus was developed for the statements with up to three rounds of anonymous voting per topic. Panelists ranked their agreement with each statement on a five-point Likert scale. An a priori threshold of ≥ 75% was required for consensus.

RESULTS

All 26 statements achieved consensus after three rounds of anonymous voting. Wound closure-related interventions that were recommended for use in TKA included: 1) closing in semi-flexion versus extension (superior range of motion); 2) using aspirin for venous thromboembolism prophylaxis over other agents (reduces wound complications); 3) barbed sutures over non-barbed sutures (lower wound complications, better cosmetic appearances, shorter closing times, and overall cost savings); 4) mesh-adhesives over other skin closure methods (lower wound complications, higher patient satisfaction scores, lower rates of readmission); 5) silver-impregnated dressings over standard dressings (lower wound complications, decreased infections, fewer dressing changes); 6) in high-risk patients, negative pressure wound therapy over other dressings (lower wound complications, decreased reoperations, fewer dressing changes); and 7) using triclosan-coated over non-antimicrobial-coated sutures (lower risks of surgical site infection).

CONCLUSIONS

Using a modified Delphi approach, the panel achieved consensus on 26 statements pertaining to wound closure and dressing management in TKA. This study forms the basis for identifying critical evidence supported by clinical practice for wound management to help reduce variability, advance standardization, and ultimately improve outcomes during TKA. The results presented here can serve as the foundation for knowledge, education, and improved clinical outcomes for surgeons performing TKAs.

International Delphi Study on Wound Closure and Incision Management in Joint Arthroplasty Part 2: Total Hip Arthroplasty

BACKGROUND

This modified Delphi study aimed to develop a consensus on optimal wound closure and incision management strategies for total hip arthroplasty (THA). Given the critical nature of wound care and incision management in influencing patient outcomes, this study sought to synthesize evidence-based best practices for wound care in THA procedures.

METHODS

An international panel of 20 orthopedic surgeons from Europe, Canada, and the United States evaluated a targeted literature review of 18 statements (14 specific to THA and 4 related to both THA and total knee arthroplasty). There were 3 rounds of anonymous voting per topic using a modified 5-point Likert scale with a predetermined consensus threshold of ≥ 75% agreement necessary for a statement to be accepted.

RESULTS

After 3 rounds of voting, consensus was achieved for all 18 statements. Notable recommendations for THA wound management included (1) the use of barbed sutures over non-barbed sutures (shorter closing times and overall cost savings); (2) the use of subcuticular sutures over skin staples (lower risk of superficial infections and higher patient preferences, but longer closing times); (3) the use of mesh-adhesives over silver-impregnated dressings (lower rate of wound complications); (4) for at-risk patients, the use of negative pressure wound therapy over other dressings (lower wound complications and reoperations, as well as fewer dressing changes); and (5) the use of triclosan-coated sutures (lower risk of surgical site infection) over standard sutures.

CONCLUSIONS

Through a structured modified Delphi approach, a panel of 20 orthopedic surgeons reached consensus on all 18 statements pertaining to wound closure and incision management in THA. This study provides a foundational framework for establishing evidence-based best practices, aiming to reduce variability in patient outcomes and to enhance the overall quality of care in THA procedures.

What enhances the in-hospital mortality following total hip arthroplasty? A national inpatient sample-based study

PURPOSE

With prolonged life expectancy and advancements in prosthetic designs, the proportion of patients belonging to diverse age groups undergoing total hip arthroplasty (THA) has progressively increased. In this context, the details regarding risk factors associated with mortality after THA, and its prevalence need to be clearly understood. This study sought to identify the possible co-morbidities associated with post-THA mortality.

METHODS

Based on Nationwide Inpatient Sample (NIS) database, patients undergoing THA from 2016 to 2019 (using ICD-10CMP) were identified. The included cohort was stratified into two groups: "early mortality" and "no mortality" groups. The data regarding patients' demographics, co-morbidities, and associated complications were compared between the groups.

RESULTS

Overall, 337,249 patients underwent THA, among whom, 332 (0.1%) died during their hospital admission ("early mortality" group). The remaining patients were included under "no mortality" group (336,917 patients). There was significantly higher mortality in the patients, who underwent emergent THA (as compared with elective THA: odd's ratio 0.075; p < 0.001). Based on multivariate analysis, presence of liver cirrhosis, chronic kidney disease (CKD) and previous history of organ transplant increased the odds of mortality {odds ratio [Exp (B)]} after THA by 4.66- (p < 0.001), 2.37-fold (p < 0.001) and 1.91-fold (p = 0.04), respectively. Among post-THA complications, acute renal failure (ARF), pulmonary embolism (PE), pneumonia, myocardial infarction (MI), and prosthetic dislocation increased the odds of post-THA mortality by 20.64-fold (p < 0.001), 19.35-fold (p < 0.001), 8.21-fold (p < 0.001), 2.71-fold (p = 0.05) and 2.54-fold (p < 0.001), respectively.

CONCLUSION

THA is a safe surgery with low mortality rate during early post-operative period. Cirrhosis, CKD, and previous history of organ transplant were the most common co-morbidities associated with post-THA mortality. Among post-operative complications, ARF, PE, pneumonia, MI, and prosthetic dislocation substantially enhanced the odds of post-THA mortality.

An Update on the Management and Optimization of the Patient with Morbid Obesity Undergoing Hip or Knee Arthroplasty

The prevalence of obesity in the United States is at a record high of 42%. In 1999, the Centers for Disease Control and Prevention recognized the obesity epidemic as a national problem, spurring the first generation of interventions for obesity prevention and control. Despite billions of dollars in funding, legislative changes, and public health initiatives, the trajectory of American obesity has not waivered. Obesity is also strongly associated with the development of osteoarthritis. The growing population of young, obese, and sick patients presents a unique dilemma for orthopedic surgeons performing joint replacement, as obesity levels and the demand for joint replacement are only expected to rise further.

Effect of documented and undocumented psychiatric conditions on length of stay and discharge destination after total knee arthroplasty

INTRODUCTION

Length of stay (LOS) and readmissions are quality metrics linked to physician payments and substantially impact the cost of care. This study aims to evaluate the effect of documented and undocumented psychiatric conditions on LOS, discharge location, and readmission following total knee arthroplasty (TKA).

METHODS

Retrospective review of all primary, unilateral TKA from 2015 to 2020 at a high-volume, academic orthopedic hospital was conducted. Patients were separated into three cohorts: patients with a documented psychiatric diagnosis (+Dx), patients without a documented psychiatric diagnosis but with an actively prescribed psychiatric medication (-Dx), and patients without a psychiatric diagnosis or medication (control). Patient demographics, LOS, discharge location, and 90 days readmissions were assessed.

RESULTS

A total of 2935 patients were included; 1051 patients had no recorded psychiatric medications (control); 1884 patients took at least one psychiatric medication, of which 1161 (61.6%) were in the-Dx and 723 (38.4%) were in the +Dx cohort. Operative time (+Dx, 103.4 ± 29.1 and -Dx, 103.1 ± 28.5 vs. 93.6 ± 26.2 min, p < 0.001 for both comparisons) and hospital LOS stay (+ Dx, 3.00 ± 1.70 and -Dx, 3.01 ± 1.83 vs. 2.82 ± 1.40 days, p = 0.021 and p = 0.006, respectively) were greater for patients taking psychiatric medications when compared to the control group. Patients taking psychiatric medication with or without associated diagnosis were significantly more likely to be discharged to a secondary facility-22.8% and 20.9%, respectively-compared to controls, at 12.5% (p < 0.001). Ninety-day readmission rates did not differ between the control and both psychiatric groups (p = 0.693 and p = 0.432, respectively).

CONCLUSION

TKA patients taking psychiatric medications with or without a documented psychiatric diagnosis have increased hospital LOS and higher chances of discharge to a secondary facility. Most patients taking psychiatric medication also had no associated diagnosis. Payment models should consider the presence of undocumented psychiatric diagnoses when constructing metrics. Surgeons and institutions should also direct their attention to identifying, recording, and managing these patients to improve outcomes.

LEVEL III EVIDENCE

Retrospective Cohort Study.

Prevention Techniques Have Had Minimal Impact on the Population Rate of Prosthetic Joint Infection for Primary Total Hip and Knee Arthroplasty: A National Database Study

BACKGROUND

Several studies over the years have offered modalities that may greatly decrease the rate of periprosthetic joint infection when implemented. As a result, one would expect a drastic decrease in infection rate among the implementing population with its widespread use. The purpose of this study was to assess whether there exists a decrease in infection rate over time, after accounting for available confounding variables, within a large national database.

METHODS

A large national database from 2005 to 2019 was queried for primary total hip arthroplasty (THA) and total knee arthroplasty (TKA). In total, 221,416 THAs and 354,049 TKAs were performed over the study period. Differences in 30-day infection rate were assessed with time and available preoperative risk factors using multinominal logistic regressions.

RESULTS

Rate of infection overall trended downward for both THA and TKA. After accounting for confounding variables, odds of THA infection marginally decreased over time (odds ratio 0.968 [0.952-0.985], P < .0001), while the odds of a TKA infection marginally increased with time (odds ratio 1.037 [1.020-1.054], P < .0001).

CONCLUSION

Individual peer-reviewed publications have presented infection control modalities demonstrating dramatic decreases in infection rate while analysis at a population level shows almost no changes in infection rate over a 15-year time period. This study supports continued investigation for influential modalities in preventing periprosthetic joint infection and care in patient selection for primary hip and knee arthroplasty.

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.

The Utility of Chlorhexidine Cloth Use for the Prevention of Surgical Site Infections in Total Hip Arthroplasty and Surgical as well as Basic Science Applications: A Meta-Analysis and Systematic Review

Skin antisepsis, such as ready-to-use, no-rinse, 2% chlorhexidine-impregnated cloths, is one of the fundamental cornerstones for reducing periprosthetic infections after primary lower extremity total joint arthroplasties. This systematic review presents background material concerning the problem and methods to deal with and then describes the use of chlorhexidine cloth prophylaxis related to various surgical applications. The authors found an almost universal benefit of the cloths. In the meta-analysis, the total pooled effect showed a reduction in infection rates. The use of chlorhexidine cloths is appropriate for prophylaxis for knee arthroplasty, hip arthroplasty, and a variety of other surgeries.

Prosthetic Joint Infections of the Hip and Knee Among the Elderly: A Retrospective Study

BACKGROUND

As the population ages and demand for total joint arthroplasty increases, rates of periprosthetic joint infection are expected to increase in the geriatric population. Studies comparing prevalence of risk factors, etiology, management, and mortality of prosthetic joint infection in older patients are lacking.

METHODS

We compared clinical characteristics, management, and mortality of patients <75 vs ≥75 years of age with first prosthetic joint infection of the hip or knee admitted to a tertiary medical center between September 2017 and December 2019.

RESULTS

Ninety-eight patients (<75 years of age [n = 63]; ≥75 years of age (n = 35) were studied. Groups were similar in terms of etiology, culture-directed therapy, antibiotic suppression, and length of stay. There was no difference in surgical management, performed in almost 97% of cases in both groups. Arrhythmia and heart failure were more prevalent in those aged ≥75 years. Readmission related to prosthetic joint infection occurred less often in older individuals (P = .005). Deaths within 1 year of diagnosis were rare (n = 4; 4.1%), occurring in older patients and resulting mostly from sepsis.

CONCLUSION

In our single-center study, patients with first prosthetic joint infection had similar management, regardless of age. We identified cardiac history as one of the host factors for prosthetic joint infection most seen in patients ≥75 years of age. Although deaths were rare, 1-year mortality was higher in patients aged ≥75. Prospective, multicenter studies are needed to explore risk factors and management strategies of prosthetic joint infection among elderly populations.

One-Year Readmissions Following Total Joint Arthroplasty May Be Associated With Failure to Achieve the Minimal Clinically Important Difference of Patient-Reported Outcomes Measurement Information System Physical, Mental, and Physical-Short Form-10a

The primary aims of our study were to determine if hospital readmissions within one year following primary total joint arthroplasty (TJA) and their relative timing influence patients' ability to achieve the two-year Patient-Reported Outcomes Measurement Information System (PROMIS) physical, PROMIS mental, and PROMIS Physical-Function-Short-Form-10a (SF-10a) minimal clinically important difference (MCID). This is a retrospective study conducted using data from a multi-institutional, arthroplasty registry. Only patients with paired patient-reported outcome measure (PROM) assessments (preoperatively and two years postoperatively) were included. Five separate readmission cohorts were formed: (1) any-cause readmission within one year, (2) any-cause readmission within 90 days, (3) non-index-surgery-related readmission within 90 days, (4) index-surgery-related readmission within one year, and (5) index-surgery-related readmission within 90 days. A propensity score match was used to match each of the patients to one of the 972 patients (1:1 basis) in the non-readmission group. The association between failure to achieve each of the three two-year MCIDs and Readmission status was analyzed using logistic regression. We found that all readmissions within one year and index-surgery-related readmissions within one year resulted in an increased risk of failure to achieve the two-year MCID across all three collected PROMs. Index surgery-related readmissions within 90 days (OR 3.24; 95% CI 1.05-11.05; p=0.048) sustained significantly different rates of two-year PROMIS physical MCID achievement compared to matched controls. Postoperative complications requiring readmission, particularly those related to the joint arthroplasty and those within 90 days of index surgery, significantly impact the ability to achieve the two-year MCID of PROMs.

Development of prediction models for complications after primary total hip and knee arthroplasty: a single-centre retrospective cohort study in the Netherlands

OBJECTIVE

The aim of this study was to develop prediction models for patients with total hip arthroplasty (THA) and total knee arthroplasty (TKA) to predict the risk for surgical complications based on personal factors, comorbidities and medication use.

DESIGN

Retrospective cohort study.

SETTING

Tertiary care in outpatient clinic of university medical centre.

PARTICIPANTS

3776 patients with a primary THA or TKA between 2004 and 2018.

PRIMARY AND SECONDARY OUTCOME MEASURES

Multivariable logistic regression models were developed for primary outcome surgical site infection (SSI), and secondary outcomes venous thromboembolism (VTE), postoperative bleeding (POB), luxation, delirium and nerve damage (NER).

RESULTS

For SSI, age, smoking status, body mass index, presence of immunological disorder, diabetes mellitus, liver disease and use of non-steroidal anti-inflammatory drugs were included. An area under the receiver operating characteristic curve (AUC) of 71.9% (95% CI=69.4% to 74.4%) was found. For this model, liver disease showed to be the strongest predictor with an OR of 10.7 (95% CI=2.4 to 46.6). The models for POB and NER showed AUCs of 73.0% (95% CI=70.7% to 75.4%) and 76.6% (95% CI=73.2% to 80.0%), respectively. For delirium an AUC of 85.9% (95% CI=83.8% to 87.9%) was found, and for the predictive algorithms for luxation and VTE we found least favourable results (AUC=58.4% (95% CI=55.0% to 61.8%) and AUC=66.3% (95% CI=62.7% to 69.9%)).

CONCLUSIONS

Discriminative ability was reasonable for SSI and predicted probabilities ranged from 0.01% to 51.0%. We expect this to enhance shared decision-making in considering THA or TKA since current counselling is predicated on population-based probability of risk, rather than using personalised prediction. We consider our models for SSI, delirium and NER appropriate for clinical use when taking underestimation and overestimation of predicted risk into account. For VTE and POB, caution concerning overestimation exceeding a predicted probability of 0.08 for VTE and 0.05 for POB should be taken into account. Furthermore, future studies should evaluate clinical impact and whether the models are feasible in an external population.

A waterproof, low-cost dressing system reduces postoperative wound dressing changes in primary total hip arthroplasty: An efficacy study

Backgrounds

Postoperative wound complication is a major risk factor for the development of Periprosthetic joint infection. We innovatively invented a new dressing system to reduce the occurrence of postoperative wound complications and improve the quality of life of patients after total hip arthroplasty.

Methods

A total of 120 patients who underwent primary unilateral total hip arthroplasty were enrolled in this study. The data collected included the number of dressing changes, costs of the dressings, postoperative hospital stay, The Visual Analogue Scale (VAS) score, The Harris Hip Score (HHS), ASEPSIS score, The Stony Brook Scar Evaluation Scale (SBSES), wound complications, the frequency of showers and satisfaction. Data were statistically analyzed.

Results

The average number of dressing changes was 0.74 ± 0.46, while the average postoperative hospital stay was 3.67 ± 0.97 days. The average cost of the new dressings throughout a treatment cycle was 57.42 ± 15.18 dollars. The VAS score decreased from 5.63 ± 1.09 before the operation to 0.88 ± 0.54 one month after the operation. The HHS score increased from 70.18 ± 7.84 before the operation to 80.36 ± 4.08 one month after the operation. The results of the four indexes of the ASEPSIS score were all 0. The SBSES score was 3.55 ± 0.61 at two weeks after the operation, and 4.38 ± 0.71 at one month after the operation. No wound complications were recorded until one month after the operation when the satisfaction rate was 92.53 ± 3.62%.

Conclusion

In this study, we have invented a new dressing system for surgical wounds after total hip arthroplasty and confirmed its efficacy.

Chinese Clinical Trial Registry

ChiCTR2000033822, Registered 13/ June/2020

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.

Machine learning models accurately predict recurrent infection following revision total knee arthroplasty for periprosthetic joint infection

PURPOSE

This study aimed to develop and validate machine-learning models for the prediction of recurrent infection in patients following revision total knee arthroplasty for periprosthetic joint infection.

METHODS

A total of 618 consecutive patients underwent revision total knee arthroplasty for periprosthetic joint infection. The patient cohort included 165 patients with confirmed recurrent periprosthetic joint infection (PJI). Potential risk factors including patient demographics and surgical characteristics served as input to three machine-learning models which were developed to predict recurrent periprosthetic joint. The machine-learning models were assessed by discrimination, calibration and decision curve analysis.

RESULTS

The factors most significantly associated with recurrent PJI in patients following revision total knee arthroplasty for PJI included irrigation and debridement with/without modular component exchange (p < 0.001), > 4 prior open surgeries (p < 0.001), metastatic disease (p < 0.001), drug abuse (p < 0.001), HIV/AIDS (p < 0.01), presence of Enterococcus species (p < 0.01) and obesity (p < 0.01). The machine-learning models all achieved excellent performance across discrimination (AUC range 0.81-0.84).

CONCLUSION

This study developed three machine-learning models for the prediction of recurrent infections in patients following revision total knee arthroplasty for periprosthetic joint infection. The strongest predictors were previous irrigation and debridement with or without modular component exchange and prior open surgeries. The study findings show excellent model performance, highlighting the potential of these computational tools in quantifying increased risks of recurrent PJI to optimize patient outcomes.

LEVEL OF EVIDENCE

IV.

Chlorhexidine gluconate lavage during total joint arthroplasty may improve wound healing compared to dilute betadine

PURPOSE

Intraoperative wound irrigation prior to closure during total joint arthroplasty (TJA) is an essential component of preventing infections and limiting health care system costs. While studies have shown the efficacy of dilute betadine in reducing infection risk, there remains concerns over its safety profile and theoretical inactivation by blood and serum. This study aims to compare infection and wound complications between chlorhexidine gluconate (CHG) and betadine lavage during TJA.

METHODS

All primary TJA between 2019-2021 were analyzed at a single institution, and periprosthetic joint infection (PJI), wound drainage, 30 and 90-day emergency room (ER) readmission due to wound complications, aseptic loosening, and revision surgery rate were compared between patients undergoing intraoperative CHG versus betadine lavage prior to closure. Baseline demographics were controlled, and multivariate logistic regression was performed to compare complication rates.

RESULTS

A total of 410 TJA, including 160 hip and 250 knee arthroplasties were included. Compared to the dilute betadine cohort, all TJA patients undergoing CHG lavage had a statistically significant lower 30 and 90-day emergency room readmission rate due to wound complications. Both hip and knee arthroplasty patients with CHG had a statistically significant lower rate of postoperative superficial drainage and dressing saturation at clinic follow-up, but only knee arthroplasty patients had significant decreased readmission rate for incisional wound vacuum placement and close inpatient monitoring of wound healing. Among all TJA, there was no significant association in the rate of PJI requiring return to the OR between groups.

CONCLUSIONS

Although betadine is cost-effective and has been shown to reduce PJI rates, there remains concerns in the literature over soft tissue toxicity and wound healing. This study suggests CHG may be as efficacious as dilute betadine in preventing PJI while also decreasing the risk of superficial drainage and wound complications needing unplanned ER visits during the acute postoperative period.

Development of a Machine Learning Algorithm for Prediction of Complications and Unplanned Readmission Following Primary Anatomic Total Shoulder Replacements

Background

The demand and incidence of anatomic total shoulder arthroplasty (aTSA) procedures is projected to increase substantially over the next decade. There is a paucity of accurate risk prediction models which would be of great utility in minimizing morbidity and costs associated with major post-operative complications. Machine learning is a powerful predictive modeling tool and has become increasingly popular, especially in orthopedics. We aimed to build a ML model for prediction of major complications and readmission following primary aTSA.

Methods

A large California administrative database was retrospectively reviewed for all adults undergoing primary aTSA between 2015 to 2017. The primary outcome was any major complication or readmission following aTSA. A wide scope of standard ML benchmarks, including Logistic regression (LR), XGBoost, Gradient boosting, AdaBoost and Random Forest were employed to determine their power to predict outcomes. Additionally, important patient features to the prediction models were indentified.

Results

There were a total of 10,302 aTSAs with 598 (5.8%) having at least one major post-operative complication or readmission. XGBoost had the highest discriminative power (area under receiver operating curve AUROC of 0.689) of the 5 ML benchmarks with an area under precision recall curve AURPC of 0.207. History of implant complication, severe chronic kidney disease, teaching hospital status, coronary artery disease and male sex were the most important features for the performance of XGBoost. In addition, XGBoost identified teaching hospital status and male sex as markedly more important predictors of outcomes compared to LR models.

Conclusion

We report a well calibrated XGBoost ML algorithm for predicting major complications and 30-day readmission following aTSA. History of prior implant complication was the most important patient feature for XGBoost performance, a novel patient feature that surgeons should consider when counseling patients.

Documented and Undocumented Psychiatric Conditions Affect the Length of Stay and Discharge Disposition Following Total Hip Arthroplasty

BACKGROUND

Despite increased efforts toward patient optimization, some patients have undocumented conditions that can affect costs and quality metrics for institutions and physicians. This study evaluates the effect of documented and undocumented psychiatric conditions on length of stay (LOS) and discharge disposition following total hip arthroplasty (THA).

METHODS

A retrospective review of all primary THAs from 2015 to 2020 at a high-volume academic orthopedic specialty hospital was conducted. Patients were separated into 3 cohorts: patients with a documented psychiatric diagnosis (+Dx), patients without a documented psychiatric diagnosis but with an actively prescribed psychiatric medication (-Dx), and patients without a psychiatric diagnosis or medication (control). Patient demographics, LOS, and discharge disposition were assessed.

RESULTS

A total of 5309 patients were included; 3048 patients had no recorded psychiatric medications (control); 2261 patients took at least 1 psychiatric medication, of which 1513 (65.9%) and 748 (34.1%) patients were put in the -Dx and +Dx cohorts, respectively. American Society of Anesthesiologists class differed between groups (P < .001). The -Dx and +Dx groups had increased LOS (3.15 ± 2.37 [75.6 ± 56.9] and 3.12 ± 2.27 [74.9 ± 54.5] vs 2.42 ± 1.70 [57.6 ± 40.8] days (hours), P < .001) and were more likely to be discharged to a secondary facility (23.0% and 21.7% vs 13.8%, P < .001) than the control group. Outcomes did not significantly differ between the -Dx and +Dx cohorts.

CONCLUSION

Most THA patients' psychiatric diagnoses were not documented. The presence of psychiatric medications was associated with longer LOS and a greater likelihood of discharge to secondary facilities. This has implications for both cost and quality metrics. Review of medications can help identify and optimize these patients before surgery.

LEVEL III EVIDENCE

Retrospective Cohort Study.

Prediction of Early Periprosthetic Joint Infection After Total Hip Arthroplasty

Purpose

To develop a parsimonious risk prediction model for periprosthetic joint infection (PJI) within 90 days after total hip arthroplasty (THA).

Patients and Methods

We used logistic LASSO regression with bootstrap ranking to develop a risk prediction model for PJI within 90 days based on a Swedish cohort of 88,830 patients with elective THA 2008–2015. The model was externally validated on a Danish cohort with 18,854 patients.

Results

Incidence of PJI was 2.45% in Sweden and 2.17% in Denmark. A model with the underlying diagnosis for THA, body mass index (BMI), American Society for Anesthesiologists (ASA) class, sex, age, and the presence of five defined comorbidities had an area under the curve (AUC) of 0.68 (95% CI: 0.66 to 0.69) in Sweden and 0.66 (95% CI: 0.64 to 0.69) in Denmark. This was superior to traditional models based on ASA class, Charlson, Elixhauser, or the Rx Risk V comorbidity indices. Internal calibration was good for predicted probabilities up to 10%.

Conclusion

A new PJI prediction model based on easily accessible data available before THA was developed and externally validated. The model had superior discriminatory ability compared to ASA class alone or more complex comorbidity indices and had good calibration. We provide a web-based calculator (https://erikbulow.shinyapps.io/thamortpred/) to facilitate shared decision making by patients and surgeons.

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

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

Preoperative bacteriuria positivity on urinalysis increases wound complications in primary total hip arthroplasty regardless of the urine culture result

BACKGROUND

Current evidence does not recommend screening urine culture and curing asymptomatic bacteriuria (ASB) before joint arthroplasty. The bacteriuria count on pre-operative urinalysis is a more common clinical parameter. We aimed to investigate whether the bacteriuria count on preoperative urinalysis can increase postoperative wound complications in primary total hip arthroplasty (THA).

METHODS

We conducted a retrospective study that included patients who underwent primary THA in our institution from 2012 to 2018. We obtained preoperative urinalysis results before THA during the same hospitalization and identified patients with abnormal urinalysis. Receiver operating characteristic (ROC) curves were first generated to evaluate the predicted value of leukocyte esterase (LE), nitrite, bacteriuria, and pyuria in the urinalysis for superficial wound infection. Then, all included patients were divided into two groups according to the preoperative urinalysis: a bacteriuria-positive group and a bacteriuria-negative group. The primary outcome was the superficial wound infection rate within 3 months postoperatively, and the secondary outcomes included wound leakage, prosthetic joint infection (PJI), pulmonary infection, urinary tract infection (UTI), readmission rate within 3 months postoperatively, and length of stay (LOS) during hospitalization. We utilized univariable analyses to compare the outcomes between the two groups. A multivariable logistic regression model was generated to explore the potential association between bacteriuria and the risk of superficial wound infection, wound leakage, and readmission rate controlling for baseline values.

RESULTS

A total of 963 patients were included in the study. One hundred sixty patients had abnormal urinalysis. The AUCs for LE, nitrite, bacteriuria, and pyuria were 0.507 (95% confidence interval (CI), 0.315 to 0.698), 0.551 (0.347 to 0.756), 0.675 (0.467 to 0.882), and 0.529 (0.331 to 0.728), respectively. Bacteriuria was diagnostically superior to LE, nitrite, and pyuria. Among the 963 patients, 95 had a positive bacteriuria on preoperative urinalysis, and only 9 (9.5%) had a positive urine culture. Compared with the bacteriuria-negative group, the bacteriuria-positive group had a higher superficial wound infection rate (4.2% vs. 0.6%, P = 0.008), higher wound leakage rate (11.6% vs. 4.5%, P = 0.007), higher readmission rate (5.3% vs. 1.3%, P = 0.015) within 3 months postoperatively and longer LOS (6.19 ± 2.89 days vs. 5.58 ± 2.14 days, P = 0.011). After adjustment, the bacteriuria-positive group had a significantly increased risk of superficial wound infection (OR = 7.587, 95%CI: 2.002 to 28.755, P = 0.003), wound leakage (OR = 3.044, 95%CI: 1.461 to 6.342, P = 0.003), and readmission (OR = 4.410, 95%CI: 1.485 to 13.097, P = 0.008).

CONCLUSION

Preoperative bacteriuria positivity on urinalysis significantly increased the risk of postoperative wound complications, readmission, and LOS in primary THA regardless of the result of the urine culture. Urinalysis is a fast and cost-acceptable test whose advantages have been underestimated.

LEVEL OF EVIDENCE

Level III, observational study.

Patients' risk factors for periprosthetic joint infection in primary total hip arthroplasty: a meta-analysis of 40 studies

BACKGROUND

Periprosthetic joint infection (PJI) is a catastrophic complication after total hip arthroplasty (THA). Our meta-analysis aimed to identify the individual-related risk factors that predispose patients to PJI following primary THA.

METHODS

Comprehensive literature retrieval from Pubmed, Web of Science, and the Cochrane Library was performed from inception to Feb 20th, 2021. Patient-related risk factors were compared as per the modifiable factors (BMI, smoke and alcohol abuse), non-modifiable factors (gender, age), and medical history characteristics, such as diabetes mellitus (DM), avascular necrosis (AVN) of femoral head, femoral neck fracture, rheumatoid arthritis (RA), cardiovascular disease (CVD), and osteoarthritis (OA) etc. The meta-analysis was applied by using risk ratios with 95% corresponding intervals. Sensitivity analysis and publication bias were performed to further assess the credibility of the results.

RESULTS

Overall, 40 studies with 3,561,446 hips were enrolled in our study. By implementing cumulative meta-analysis, higher BMI was found associated with markedly increased PJI risk after primary THA [2.40 (2.01-2.85)]. Meanwhile, medical characteristics including DM [1.64 (1.25-2.21)], AVN [1.65 (1.07-2.56)], femoral neck fracture [1.75 (1.39-2.20)], RA [1.37 (1.23-1.54)], CVD [1.34 (1.03-1.74)], chronic pulmonary disease (CPD) [1.22 (1.08-1.37)], neurological disease [1.19 (1.05-1.35)], opioid use [1.53 (1.35-1.73)] and iron-deficiency anemia (IDA) [1.15 (1.13-1.17)] were also significantly correlated with higher rate of PJI. Conversely, dysplasia or dislocation [0.65 (0.45-0.93)], and OA [0.70 (0.62-0.79)] were protective factors. Of Note, female gender was protective for PJI only after longer follow-up. Besides, age, smoking, alcohol abuse, previous joint surgery, renal disease, hypertension, cancer, steroid use and liver disease were not closely related with PJI risk.

CONCLUSION

Our finding suggested that the individual-related risk factors for PJI after primary THA included high BMI, DM, AVN, femoral neck fracture, RA, CVD, CPD, neurological disease, opioid use and IDA, while protective factors were female gender, dysplasia/ dislocation and OA.

A Novel, Potentially Universal Machine Learning Algorithm to Predict Complications in Total Knee Arthroplasty

BACKGROUND

There remains a lack of accurate and validated outcome-prediction models in total knee arthroplasty (TKA). While machine learning (ML) is a powerful predictive tool, determining the proper algorithm to apply across diverse data sets is challenging. AutoPrognosis (AP) is a novel method that uses automated ML framework to incorporate the best performing stages of prognostic modeling into a single well-calibrated algorithm. We aimed to compare various ML methods to AP in predictive performance of complications after TKA.

METHODS

Thirty-eight preoperative patient demographics and clinical features from all primary TKAs performed at California-licensed hospitals between 2015 and 2017 were evaluated as predictors of major complications after TKA. Traditional logistic regression (LR), various other ML methods (XGBoost, Gradient Boosting, AdaBoost, and Random Forest), and AP were used for model building to determine discriminative power (area under receiver operating curve), calibration (Brier score), and feature importance.

RESULTS

Between 2015 and 2017, there were a total of 156,750 TKAs with 1109 (0.7%) total major complications. AP had the highest discriminative performance with area under receiver operating curve 0.679 compared with LR, XGBoost, Gradient Boosting, AdaBoost, and Random Forest (0.617, 0.601, 0.662, 0.657, and 0.545, respectively). AP (Brier score 0.007) had similar calibration as the other ML methods (0.006, 0.006, 0.022, 0.007, and 0.008, respectively). The variables that are most important for AP differ from those that are most important for LR.

CONCLUSION

Compared to conventional ML algorithms, AP has superior discriminative ability with similar calibration and suggests nonlinear relationships between variables in outcomes of TKA.

External Validation Demonstrates Limited Clinical Utility of a Preoperative Prognostic Calculator for Periprosthetic Joint Infection

BACKGROUND

Preoperative calculation of treatment failure risk in patients undergoing surgery for periprosthetic joint infection (PJI) is imperative to allow for medical optimization and targeted prevention. A preoperative prognostic model for PJI treatment failure was previously developed, and this study sought to externally validate the model.

METHODS

A retrospective review was performed of 380 PJIs treated at two institutions. The model was used to calculate the risk of treatment failure, and receiver operating characteristic curves were generated to calculate the area under the curve (AUC) for each institution.

RESULTS

When applying this model to institution 1, an AUC of 0.795 (95% confidence interval [CI]: 0.693-0.897) was found, whereas institution 2 had an AUC of 0.592 (95% CI: 0.502-0.683). Comparing all institutions in which the model had been applied to, we found institution 2 represented a significantly sicker population and different infection profile.

CONCLUSION

In this cohort study, we externally validated the prior published model for institution 1. However, institution 2 had a decreased AUC using the prior model and represented a sicker and less homogenous cohort compared with institution 1. When matching for chronicity of the infection, the AUC of the model was not affected. This study highlights the impact of comorbidities and their distributions on PJI prognosis and brings to question the clinical utility of the algorithm which requires further external validation.

Development of a Novel, Potentially Universal Machine Learning Algorithm for Prediction of Complications After Total Hip Arthroplasty

BACKGROUND

As the prevalence of hip osteoarthritis increases, the number of total hip arthroplasty (THA) procedures performed is also projected to increase. Accurately risk-stratifying patients who undergo THA would be of great utility, given the significant cost and morbidity associated with developing perioperative complications. We aim to develop a novel machine learning (ML)-based ensemble algorithm for the prediction of major complications after THA, as well as compare its performance against standard benchmark ML methods.

METHODS

This is a retrospective cohort study of 89,986 adults who underwent primary THA at any California-licensed hospital between 2015 and 2017. The primary outcome was major complications (eg infection, venous thromboembolism, cardiac complication, pulmonary complication). We developed a model predicting complication risk using AutoPrognosis, an automated ML framework that configures the optimally performing ensemble of ML-based prognostic models. We compared our model with logistic regression and standard benchmark ML models, assessing discrimination and calibration.

RESULTS

There were 545 patients who had major complications (0.61%). Our novel algorithm was well-calibrated and improved risk prediction compared to logistic regression, as well as outperformed the other four standard benchmark ML algorithms. The variables most important for AutoPrognosis (eg malnutrition, dementia, cancer) differ from those that are most important for logistic regression (eg chronic atherosclerosis, renal failure, chronic obstructive pulmonary disease).

CONCLUSION

We report a novel ensemble ML algorithm for the prediction of major complications after THA. It demonstrates superior risk prediction compared to logistic regression and other standard ML benchmark algorithms. By providing accurate prognostic information, this algorithm may facilitate more informed preoperative shared decision-making.

Readmission, Complication, and Disposition Calculators in Total Joint Arthroplasty: A Systemic Review

BACKGROUND

Predictive tools are useful adjuncts in surgical planning. They help guide patient selection, candidacy for inpatient vs outpatient surgery, and discharge disposition as well as predict the probability of readmissions and complications after total joint arthroplasty (TJA). Surgeons may find it difficult due to significant variation among risk calculators to decide which tool is best suited for a specific patient for optimal decision-based care. Our aim is to perform a systematic review of the literature to determine the existing post-TJA readmission calculators and compare the specific elements that comprise their formula. Second, we intend to evaluate the pros and cons of each calculator.

METHODS

Using a Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols protocol, we conducted a systematic search through 3 major databases for publications addressing TJA risk stratification tools for readmission, discharge disposition, and early complications. We excluded those manuscripts that were not comprehensive for hips and knees, did not list discharge, readmission or complication as the primary outcome, or were published outside the North America.

RESULTS

Ten publications met our criteria and were compared on their sourced data, variable types, and overall algorithm quality. Seven of these were generated with single institution data and 3 from large administrative datasets. Three tools determined readmission risk, 5 calculated discharge disposition, and 2 predicted early complications. Only 4 prediction tools were validated by external studies. Seven studies utilized preoperative data points in their risk equations while 3 utilized intraoperative or postsurgical data to delineate risk.

CONCLUSION

The extensive variation among TJA risk calculators underscores the need for tools with more individualized stratification capabilities and verification. The transition to outpatient and same-day discharge TJA may preclude or change the need for many of these calculators. Further studies are needed to develop more streamlined risk calculator tools that predict readmission and surgical complications.

Prediction of 90-day mortality after total hip arthroplasty

AIMS

To develop and externally validate a parsimonious statistical prediction model of 90-day mortality after elective total hip arthroplasty (THA), and to provide a web calculator for clinical usage.

METHODS

We included 53,099 patients with cemented THA due to osteoarthritis from the Swedish Hip Arthroplasty Registry for model derivation and internal validation, as well as 125,428 patients from England and Wales recorded in the National Joint Register for England, Wales, Northern Ireland, the Isle of Man, and the States of Guernsey (NJR) for external model validation. A model was developed using a bootstrap ranking procedure with a least absolute shrinkage and selection operator (LASSO) logistic regression model combined with piecewise linear regression. Discriminative ability was evaluated by the area under the receiver operating characteristic curve (AUC). Calibration belt plots were used to assess model calibration.

RESULTS

A main effects model combining age, sex, American Society for Anesthesiologists (ASA) class, the presence of cancer, diseases of the central nervous system, kidney disease, and diagnosed obesity had good discrimination, both internally (AUC = 0.78, 95% confidence interval (CI) 0.75 to 0.81) and externally (AUC = 0.75, 95% CI 0.73 to 0.76). This model was superior to traditional models based on the Charlson (AUC = 0.66, 95% CI 0.62 to 0.70) and Elixhauser (AUC = 0.64, 95% CI 0.59 to 0.68) comorbidity indices. The model was well calibrated for predicted probabilities up to 5%.

CONCLUSION

We developed a parsimonious model that may facilitate individualized risk assessment prior to one of the most common surgical interventions. We have published a web calculator to aid clinical decision-making. Cite this article: Bone Joint J 2021;103-B(3):469-478.

Development of a Preoperative Risk Calculator for Reinfection Following Revision Surgery for Periprosthetic Joint Infection

BACKGROUND

A recent systematic review demonstrated that reinfection rates following eradication of hip and knee periprosthetic joint infection (PJI) may be as high as 29%. This study aimed to develop a preoperative risk calculator for assessing patient's individual risk associated with reinfection following treatment of PJI in total joint arthroplasty (TJA).

METHODS

A total of 1081 consecutive patients who underwent revision TJA for PJI were evaluated. In total, 293 patients were diagnosed with TJA reinfection. A total of 56 risk factors, including patient characteristics and surgical variables, were evaluated with multivariate regression analysis. Analysis of the area under the receiver operating characteristics curve was performed to evaluate the strength of the predictive model.

RESULTS

Of the 56 risk factors studied, 19 were found to have a significant effect as risk factor for TJA reinfection. The strongest predictors for TJA reinfection included previous PJI treatment techniques such as irrigation and debridement, the number of previous surgical interventions, medical comorbidities such as obesity, drug abuse, depression and smoking, as well as microbiology including the presence of Enterococcus species. The combined area under the receiver operating characteristics curve of the risk calculator for periprosthetic hip and knee joint reinfection was 0.75.

CONCLUSIONS

The study findings demonstrate that surgical factors, including previous PJI surgical treatment techniques as well as the number of previous surgeries, alongside microbiology including the presence of Enterococcus species have the strongest effect on the risk for periprosthetic THA and TKA joint reinfection, suggesting the limited applicability of the existing risk calculators for the development of PJI following primary TJA in predicting the risk of periprosthetic joint reinfection.

Preoperative Risk Factors for Postoperative Urinary Tract Infection After Primary Total Hip and Knee Arthroplasties

BACKGROUND

Establishing clear risk factors for complications such as urinary tract infection (UTI) after arthroplasty procedures helps guide clinical practice and provides more information to both surgeons and patients. This study aims to assess selected preoperative patient characteristics as risk factors for postoperative UTI after primary total hip and knee arthroplasties (THA and TKA).

METHODS

This was a retrospective analysis using current procedural terminology codes to investigate the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database for patients who underwent THA or TKA from 2010 to 2017. Patients were classified for UTI by NSQIP guidelines. Patient samples with all possible covariates were included for multivariate logistic regression analysis and assessed for independent associations.

RESULTS

In a cohort of 983 identified patients (983 of 119,096; 0.83%): ages 57+ years, preoperative red blood cell (RBC) transfusion, perioperative RBC transfusion, bleeding disorders, operative time 110+ minutes, preoperative steroid use, diabetes, pulmonary comorbidities, body mass index 30+ kg/m² were independent risk factors for postoperative UTI after THA. In a cohort of 1503 identified patients (1503 of 189,327; 0.8%): ages 60+ years, preoperative RBC transfusion, perioperative RBC transfusion, anemia, platelets less than 150k, preoperative steroid use, diabetes, and body mass index 30+ kg/m² were independent risk factors for postoperative UTI after TKA. Male sex was associated with a decreased risk of UTI in both THA and TKA.

CONCLUSION

This study provides novel evidence on risk factors associated with the development of UTI after THA or TKA. Clinicians should be aware of risk factors in the manifestation of postoperative UTI after primary THA or TKA procedures.

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.

Can Machine Learning Methods Produce Accurate and Easy-to-Use Preoperative Prediction Models of One-Year Improvements in Pain and Functioning After Knee Arthroplasty?

BACKGROUND

Approximately 15%-20% of total knee arthroplasty (TKA) patients do not experience clinically meaningful improvements. We sought to compare the accuracy and parsimony of several machine learning strategies for developing predictive models of failing to experience minimal clinically important differences in patient-reported outcome measures (PROMs) 1 year after TKA.

METHODS

Patients (N = 587) in 3 large Veteran Health Administration facilities completed PROMs before and 1 year after TKA (92% follow-up). Preoperative PROMs and electronic health record data were used to develop and validate models to predict failing to experience at least a minimal clinically important difference in Knee Injury and Osteoarthritis Outcome Score (KOOS) Total, KOOS JR, and KOOS subscales (Pain, Symptoms, Activities of Daily Living, Quality of Life, and recreation). Several machine learning strategies were used for model development. Ten-fold cross-validation and bootstrapping were used to produce measures of overall accuracy (C-statistic, Brier Score). The sensitivity and specificity of various predicted probability cut-points were examined.

RESULTS

The most accurate models produced were for the Activities of Daily Living, Pain, Symptoms, and Quality of Life subscales of the KOOS (C-statistics 0.76, 0.72, 0.72, and 0.71, respectively). Strategies varied substantially in terms of the numbers of inputs required to achieve similar accuracy, with none being superior for all outcomes.

CONCLUSION

Models produced in this project provide estimates of patient-specific improvements in major outcomes 1 year after TKA. Integrating these models into clinical decision support, informed consent and shared decision making could improve patient selection, education, and satisfaction.

LEVEL OF EVIDENCE

Level III, diagnostic study.

Higher age, female gender, osteoarthritis and blood transfusion protect against periprosthetic joint infection in total hip or knee arthroplasties: a systematic review and meta-analysis

PURPOSE

The goal of this systematic review and meta-analysis was to identify the main risk factors for periprosthetic joint infection (PJI) in patients undergoing total hip or knee arthroplasties.

METHODS

A systematic review was conducted of the potential risk factors for PJI in total hip or total knee arthroplasty. Risk factors were compared and grouped according to demographics, comorbidities, behavior, infections, native joint diseases and other patient-related and procedure-related factors. Meta-analysis (random-effects models) was conducted using odds ratio (OR) and mean difference (MD). Risk of bias (ROBBINS-I) and strength of the evidence (GRADE) were assessed.

RESULTS

The study included 37 studies (2,470,827 patients). Older age was a protective factor (MD = - 1.18). Male gender (OR 1.34), coagulopathy (3.05), congestive heart failure (2.36), diabetes mellitus (1.80), obesity (1.61), systemic neoplasia (1.57), chronic lung disease (1.52), and hypertension (1.21) increased the risk for PJI. Behavioral risk factors comprised alcohol abuse (2.95), immunosuppressive therapy (2.81), steroid therapies (1.88), and tobacco (1.82). Infectious risk factors included surgical site infections (6.14), postoperative urinary tract infections (2.85), and prior joint infections (2.15). Rheumatoid arthritis, posttraumatic native joint disease, high National Nosocomial Infections Surveillance (NNIS) system surgical patient index score, prior joint operation, American Society of Anesthesiologists score ≥ 3 and obesity were also significantly associated with higher risk of PJI. Osteoarthritis and blood transfusion were protective factors.

CONCLUSIONS

The main risk factors for PJI in each category were male gender, coagulopathy, alcohol abuse, surgical site infection (highest score) and high NNIS system surgical patient index score. Protective factors were age, female gender in TKA, osteoarthritis and blood transfusion. Optimization of modifiable risk factors for PJI should be attempted in clinical practice.

LEVEL OF EVIDENCE

II.

Class III Obesity Increases Risk of Failure to Achieve the 1-Year Hip Disability and Osteoarthritis Outcome Score-Physical Function Short Form Minimal Clinically Important Difference Following Total Hip Arthroplasty

BACKGROUND

The relationship between obesity and failure to achieve a minimal clinically important difference (MCID) following total hip arthroplasty (THA) has not been well defined. The aims of this study are to determine whether increasing body mass index (BMI) is associated with failure to achieve the 1-year Hip Disability and Osteoarthritis Outcome Score-Physical Function Short Form (HOOS-PS) MCID and to determine a threshold BMI beyond which this risk is significantly increased.

METHODS

A multi-institutional arthroplasty registry was queried for THA patients from 2016 to 2018 with completion of preoperative and 1-year postoperative HOOS-PS. A previously defined anchor-based MCID threshold of 23 was used. Variables collected included demographics and patient-reported outcome measures. BMI was analyzed continuously and categorically. The association was analyzed via logistic regression. A BMI threshold was determined using the Youden index and receiver operating characteristic curve.

RESULTS

A total of 1256 THAs were included. The average HOOS-PS improvement was 27.6 ± 18 points. The area under the receiver operating characteristic curve for BMI and risk of failure to achieve HOOS-PS MCID was 0.54 (95% confidence interval [CI], 0.50-0.57). Increasing BMI assessed continuously was a significant risk factor (odds ratio [OR], 1.03; 95% CI, 1.01-1.05; P value = .010). When BMI was analyzed categorically, this association was only observed for obese class III patients (>40 kg/m²) (OR, 2.5; 95% CI, 1.21-5.3; P value = .010).

CONCLUSION

This study found an association between increasing BMI and failure to achieve the 1-year HOOS-PS MCID. Obese class III patients (>40 kg/m²) face a near 3-fold increased risk of suffering this adverse outcome.

Efficacy and safety of intrawound vancomycin in primary hip and knee arthroplasty

Aims

The efficacy and safety of intrawound vancomycin for preventing surgical site infection in primary hip and knee arthroplasty is uncertain.

Methods

A systematic review of the literature was conducted, indexed from inception to March 2020 in PubMed, Web of Science, Cochrane Library, Embase, and Google Scholar databases. All studies evaluating the efficacy and/or safety of intrawound vancomycin in patients who underwent primary hip and knee arthroplasty were included. Incidence of periprosthetic joint infection (PJI), superficial infection, aseptic wound complications, acute kidney injury, anaphylactic reaction, and ototoxicity were meta-analyzed. Results were reported as odds ratios (ORs) and 95% confidence intervals (CIs). The quality of included studies was assessed using the risk of bias in non-randomized studies of interventions (ROBINS-I) assessment tool.

Results

Nine studies involving 4,607 patients were included. Intrawound vancomycin was associated with lower incidence of PJI (30 patients (1.20%) vs 58 control patients (2.75%); OR 0.44, 95% CI 0.28 to 0.69) and simultaneous acute kidney injury (four patients (0.28%) vs four control patients (0.35%), OR 0.71, 95% CI 0.19 to 2.55). However, it did not reduce risk of superficial infection (four patients (0.67%) vs six control patients (1.60%), OR 0.60, 95% CI 0.17 to 2.12) and was associated with higher incidence of aseptic wound complications (23 patients (2.15%) vs eight in control patients (0.96%), OR 2.39, 95% CI 1.09 to 5.23). Four studies reported no anaphylactic reactions and three studies reported no ototoxicity in any patient group.

Conclusion

The current literature suggests that intrawound vancomycin used in primary hip and knee arthroplasty may reduce incidence of PJI, but it may also increase risk of aseptic wound complications.

Cite this article: Bone Joint Res 2020;9(11):778–788.

Impact of Perioperative Urinary Tract Infection on Surgical Site Infection in Patients Undergoing Primary Hip and Knee Arthroplasty

BACKGROUND

The literature lacks clear consensus regarding the association between postoperative urinary tract infection (UTI) and surgical site infection (SSI). Additionally, in contrast to preoperative asymptomatic bacteriuria, SSI risk in patients with preoperative UTI has been incompletely studied. Therefore, our goal was to determine the effect of perioperative UTI on SSI in patients undergoing primary hip and knee arthroplasty.

METHODS

Using the National Surgical Quality Improvement Program database, all patients undergoing primary hip and knee arthroplasty were identified. Univariate and multivariate regressions, as well as propensity matching, were used to determine the independent risk of preoperative and postoperative UTI on SSI, reported as odds ratios (ORs) with 95% confidence intervals (CIs).

RESULTS

Postoperative UTI significantly increased the risk for superficial wound infection (OR 2.147, 95% CI 1.622-2.842), deep periprosthetic joint infection (PJI) (OR 2.288, 95% CI 1.579-3.316), and all SSIs (superficial and deep) (OR 2.193, 95% CI 1.741-2.763) (all P < .001). Preoperative UTI was not associated with a significantly increased risk of superficial infection (P = .636), PJI (P = .330), or all SSIs (P = .284). Further analysis of UTI present at the time of surgery using propensity matching showed no increased risk of superficial infection (P = 1.000), PJI (P = .624), or SSI (P = .546).

CONCLUSION

Postoperative UTI was associated with SSI, reinforcing the need to minimize factors which predispose patients to the risk of UTI after surgery. The lack of association between preoperative UTI and SSI suggests that hip and knee arthroplasty can proceed without delay, although initiating antibiotic treatment is prudent and future prospective investigations are warranted.

Modifiability of Depression's Impact on Early Revision, Narcotic Usage, and Outcomes After Total Hip Arthroplasty: The Impact of Psychotherapy

BACKGROUND

Depression is known to negatively influence functional recovery, patient satisfaction, narcotic requirements, implant survivorship, and perioperative resource utilization after total hip arthroplasty (THA). The degree to which this effect is modifiable is largely unknown, with mixed results on preoperative pharmacological intervention, and concomitant concerns over side effects. We aim to investigate the influence of psychotherapy before THA on surgical outcomes, medical complications, and resource utilization.

METHODS

A retrospective chart review of Truven MarketScan Databases was performed to generate 3 cohorts: patients without depression, patients with depression who did not receive preoperative psychotherapy, and patients with depression who received psychotherapy before surgery. Outcomes of interest were resource utilization, surgical and medical complications, narcotic requirements, and 1-year and 3-year revision rates.

RESULTS

On multivariate analysis, depressed patients who did not receive psychotherapy were more likely to be discharged to inpatient rehabilitation facility (odds ratio [OR] 1.28, 95% confidence interval [CI] 1.10-1.48, P < .001) and require 2 or more postoperative narcotic prescriptions (OR 1.20, 95% CI 1.06-1.37, P = .004) than depressed patients who received psychotherapy. Patients who did not receive psychotherapy were more likely to have continued narcotic requirements within 1 year after surgery (OR 1.23, 95% CI 1.08-1.39, P < .001) and undergo revision at 1 year (OR 1.74, 95% CI 1.17-2.58, P = .006) and 3 years (OR 1.92, 95% CI 1.10-3.34, P = .021) than depressed patients who received psychotherapy.

CONCLUSION

The negative influence of depression on narcotic requirements, resource utilization, and implant survivorship after THA appears to be modifiable with preoperative psychotherapy.

Novel Machine Learning Approach to Identify Preoperative Risk Factors Associated With Super-Utilization of Medicare Expenditure Following Surgery

Importance

Typically defined as the top 5% of health care users, super-utilizers are responsible for an estimated 40% to 55% of all health care costs. Little is known about which factors may be associated with increased risk of long-term postoperative super-utilization.

Objective

To identify clusters of patients with distinct constellations of clinical and comorbid patterns who may be associated with an elevated risk of super-utilization in the year following elective surgery.

Design, Setting, and Participants

A retrospective longitudinal cohort study of 1 049 160 patients who underwent abdominal aortic aneurysm repair, coronary artery bypass graft, colectomy, total hip arthroplasty, total knee arthroplasty, or lung resection were identified from the 100% Medicare inpatient and outpatient Standard Analytic Files at all inpatient facilities performing 1 or more of the evaluated surgical procedures from 2013 to 2015. Data from 2012 to 2016 were used to evaluate expenditures in the year preceding and following surgery. Using a machine learning approach known as Logic Forest, comorbidities and interactions of comorbidities that put patients at an increased chance of becoming a super-utilizer were identified. All comorbidities, as defined by the Charlson (range, 0-24) and Elixhauser (range, 0-29) comorbidity indices, were used in the analysis. Higher scores indicated higher comorbidity burden. Data analysis was completed on November 16, 2018.

Main Outcome and Measures

Super-utilization of health care in the year following surgery.

Results

In total, 1 049 160 patients met inclusion criteria and were included in the analytic cohort. Their median (interquartile range) age was 73 (69-78) years, and approximately 40% were male. Super-utilizers comprised 4.8% of the overall cohort (n = 79 746) yet incurred 31.7% of the expenditures. Although the difference in overall expenditures per person between super-utilizers ($4049) and low users ($2148) was relatively modest prior to surgery, the difference in expenditures between super-utilizers ($79 698) vs low users ($2977) was marked in the year following surgery. Risk factors associated with super-utilization of health care included hemiplegia/paraplegia (odds ratio, 5.2; 95% CI, 4.4-6.2), weight loss (odds ratio, 3.5; 95% CI, 2.9-4.2), and congestive heart failure with chronic kidney disease stages I to IV (odds ratio, 3.4; 95% CI, 3.0-3.9).

Conclusions and Relevance

Super-utilizers comprised only a small fraction of the surgical population yet were responsible for a disproportionate amount of Medicare expenditure. Certain subpopulations were associated with super-utilization of health care following surgical intervention despite having lower overall use in the preoperative period.

Are high-risk patient and revision arthroplasty effective indications for closed-incisional negative-pressure wound therapy after total hip or knee arthroplasty? A systematic review and meta-analysis

To determine the effective indications of closed-incisional negative-pressure wound therapy (ciNPWT) following total hip or knee arthroplasty, this systematic review and meta-analysis was conducted. The systematic search was performed on MEDLINE, Embase, and Cochrane Library, and 11 studies were included. The studies comparing between ciNPWT and conventional dressings were categorised into following subgroups based on patient risk and revision procedures: routine vs high-risk patient; primary vs revision arthroplasty. Pooled estimates were calculated for wound complication and surgical site infection (SSI) rates in the subgroup analyses using Review Manager. In high-risk patients, the overall rates of wound complication (odds ratio [OR] = 0.38; 95% confidence interval [CI] 0.15-0.93; P = .030) and SSI (OR = 0.24; 95% CI = 0.09-0.64; P = .005) were significantly lower in the ciNPWT; however, there were no differences in routine patients. In cases involving revision arthroplasties, the overall rates of wound complication (OR = 0.33; 95% CI = 0.18-0.62; P < .001) and SSI (OR = 0.26; 95% CI = 0.11-0.66; P = .004) were significantly lower in the ciNPWT; however, there were no differences in cases involving primary arthroplasties. In summary, ciNPWT showed a positive effect in decreasing the rates of wound complication and SSI in high-risk patients and in revision arthroplasties.

Tranexamic Acid Is Associated With Reduced Periprosthetic Joint Infection After Primary Total Joint Arthroplasty

BACKGROUND

Previous studies have demonstrated preoperative anemia to be a strong risk factor for periprosthetic joint infection (PJI) in total joint arthroplasty (TJA). Allogeneic blood transfusion can be associated with increased risk of PJI after primary and revision TJA. Tranexamic acid (TXA) is known to reduce blood loss and the need for allogeneic blood transfusion after TJA. The hypothesis of this study is that administration of intravenous TXA would result in a reduction in PJI after TJA.

METHODS

An institutional database was utilized to identify 6340 patients undergoing primary TJA between January 1, 2013 and June 31, 2017 with a minimum of 1-year follow-up. Patients were divided into 2 groups based on whether they received intravenous TXA prior to TJA or not. Patients who developed PJI were identified. All PJI patients met the 2018 International Consensus Meeting definition for PJI. A multivariate regression analysis was performed to identify variables independently associated with PJI.

RESULTS

Of the patients included, 3683 (58.1%) received TXA and 2657 (41.9%) did not. The overall incidence of preoperative anemia was 16%, postoperative blood transfusion 1.8%, and PJI 2.4%. Bivariate analysis showed that patients who received TXA were significantly at lower odds of infection. After adjusting for all confounding variables, multivariate regression analysis showed that TXA is associated with reduced PJI after primary TJA.

CONCLUSION

TXA can help reduce the rate of PJI after primary TJA. This protective effect is likely interlinked to reduction in blood loss, lower need for allogeneic blood transfusion, and issues related to immunomodulation associated with blood transfusion.

Incidence of Corrective Procedures After Nonoperatively Managed Distal Radius Fractures in the Elderly

Although the majority distal radius fractures in the elderly are initially managed nonoperatively, the true incidence of subsequent corrective surgery is unknown. The purpose of this study was to determine the incidence and predictors of corrective surgery after conservative management.

Methods

ICD-9 and Current Procedural Terminology codes were queried from the Medicare 5% sample to select patients aged 65 years and older undergoing nonsurgical treatment of distal radius fractures with a minimum 5-year follow-up. Rates of subsequent ipsilateral wrist surgery were correlated against patient age, sex, geographic region, and initial closed reduction.

Results

Five thousand eighty patients with a mean age of 78.3 years were included. Fifty-five patients (1.1%) had undergone subsequent wrist surgery at a median time of 182 days after injury. The youngest cohort (65 to 69 years) had a significantly higher operation rate (1.9%, P = 0.007) than the oldest cohort (80+ years) (0.5%, P = 0.004). There was no notable difference in corrective procedures between sex, geographic region, and initial closed reduction.

Discussion

Once surgical intervention is deemed unnecessary per standard guidelines, the data support successful nonsurgical management in a large majority of patients but highlight a small subset of younger patients who remain at increased risk of requiring additional surgery.

Can We Improve Prediction of Adverse Surgical Outcomes? Development of a Surgical Complexity Score Using a Novel Machine Learning Technique

BACKGROUND

An optimal method to quantify surgical complexity using patient comorbidities derived from administrative billing data is lacking. We sought to develop a novel, easy-to-use surgical Complexity Score to accurately predict adverse outcomes among patients undergoing elective surgery.

STUDY DESIGN

A novel surgical Complexity Score was developed using 100% Medicare Inpatient and Outpatient Standard Analytic Files (SAFs) from years 2012 to 2016 (n = 1,049,160). Comorbid conditions were entered into a machine learning algorithm to assign weights to maximize the correlation with multiple postoperative outcomes including morbidity, readmission, mortality, and postoperative super-use. Predictive ability was compared against 3 of the most commonly used risk adjustment indices: the Charlson Comorbidity Index (CCI), Elixhauser Comorbidity Index (ECI), and the Centers for Medicare and Medicaid Service's Hierarchical Condition Category (CMS-HCC).

RESULTS

Patients underwent colectomy (12.6%), abdominal aortic aneurysm repair (4.4%), coronary artery bypass grafting (13.0%), total hip replacement (22.0%), total knee replacement (43.0%), or lung resection (5.0%). The Complexity Score had a good to very good predictive ability for all adverse outcomes. The Complexity Score had the highest accuracy in predicting perioperative morbidity (area under the curve [AUC]: 0.868, 95% CI 0.866 to 0.869); this performed better than the CCI (AUC: 0.717, 95% CI 0.715 to 0.719), ECI (AUC: 0.799, 95% CI 0.797 to 0.800), and similar to the CMS-HCC (AUC: 0.862, 95% CI 0.861 to 0.863). Similarly, the Complexity Score outperformed each of the 3 other comorbidity indices in predicting 90-day readmission (AUC: 0.707, 95% CI 0.705 to 0.709), 30-day readmission (AUC: 0.717, 95% CI 0.715 to 0.720), and postoperative super-use (AUC: 0.817, 95% CI 0.814 to 0.820).

CONCLUSIONS

Compared with the most commonly used comorbidity and surgical risk scores, the novel surgical Complexity Score outperformed the CCI, ECI, and CMS-HCC in predicting postoperative morbidity, 30-day readmission, 90-day readmission, and postoperative super-use.

The Impact of Running, Monofilament Barbed Suture for Subcutaneous Tissue Closure on Infection Rates in Total Hip Arthroplasty: A Retrospective Cohort Analysis

BACKGROUND

Recently, running, monofilament barbed suture has become more popular as an efficient and economical alternative to traditional braided interrupted suture for wound closure following total joint arthroplasty. Its overall association with wound complications following surgery remains unknown at this time. Several studies have investigated its use in total knee arthroplasty (TKA), but there is limited literature surrounding use in total hip arthroplasty (THA). In this retrospective cohort study, our primary objective was to determine whether the use of monofilament barbed suture in THA was associated with reduced rates of postoperative infection when compared to traditional braided suture.

METHODS

Patients who underwent primary unilateral THA between November 2011 and December 2017 by a single senior surgeon with closure using either monofilament barbed suture (162 patients) or braided interrupted suture (429 patients) were retrospectively reviewed for postoperative wound complications during the first 90 days after surgery. Demographics, comorbidities, and perioperative data were also included to assess for risk factors for infection.

RESULTS

There was no difference between braided and barbed suture in overall rates of major complication, including periprosthetic joint infection (PJI) (0.47% vs 0.62%, P = .82) or revisions (1.86% vs 1.23%, P = .60). The overall rate of minor, superficial wound complications was also similar between both groups (6.1% vs 3.1%, P = .15). However, when superficial complications were categorized by type (dehiscence vs infection), the use of barbed suture was associated with a decreased rate of superficial wound infection (0% vs 5.4%, P = .003) and an increased rate of wound dehiscence (3.1% vs 0.7%, P = .04).

CONCLUSION

The use of monofilament barbed suture for superficial skin closure in THA leads to similar overall rates of both major and minor wound complications when compared to traditional interrupted braided suture. However, while barbed suture was associated with fewer superficial infections, there was an increased incidence of wound dehiscence. Overall, barbed suture demonstrated a cumulatively equivalent rate of superficial wound complications compared to braided suture. Based on this investigation, barbed suture appears safe to use in THA and may represent an efficient and effective alternative to braided suture for wound closure.

LEVEL OF EVIDENCE

Level IV; retrospective cohort study.

Is Routine Urinary Screening Indicated Prior To Elective Total Joint Arthroplasty? A Systematic Review and Meta-Analysis

BACKGROUND

Prosthetic joint infection (PJI) is a serious complication after total joint arthroplasty, and prevention is of great importance. The genitourinary tract is a potential source of bacterial seeding and one that can be easily managed. Despite little supportive evidence, routine urine screening and subsequent treatment before elective surgery in patients without symptoms has found its way into clinical practice in many countries. This systematic review and meta-analysis aims to ascertain whether asymptomatic bacteriuria (ASB) is a risk factor for PJI and if so, whether preoperative antibiotic treatment is effective in reducing its risk.

METHODS

PubMed, Ovid Medline, and Cochrane databases were searched using a systematic strategy. Selection of papers was exclusive to include only those which offered information about PJI rate specifically in patients with or without asymptomatic abnormal urinalysis or bacteriuria and/or information on whether ASB patients were preoperatively treated with antibiotics or not to be included in the analysis.

RESULTS

Six-hundred sixty-three papers were screened, and 10 papers were ultimately included (28,588 patients). Results show an increased risk of developing PJI among ASB patients (odds ratio = 3.64, 95% confidence interval = 1.40-9.42). However, most PJI microorganisms are unrelated to those previously found in the urine and preoperative antibiotic therapy does not influence PJI risk (odds ratio = 0.98, 95% confidence interval = 0.39-2.44).

CONCLUSION

Routine urinary screening prior to elective total joint arthroplasty and treatment of asymptomatic patients is not recommended.

Sterile Parts of Operating Gown during Lower Limb Joint Replacement Surgery

BACKGROUND

The prevention of surgical site infection is one of the most concerning issues in operating rooms. Surgical gowns are worn as one of the intraoperative strategies for infection prevention. The present study investigated whether the gowns remained sterile during the surgical procedure. Furthermore, this study examined which parts of the surgical gown were more prone to contamination.

METHODS

The sterility of the gowns was investigated during eight total joint arthroplasties all of which were performed by four surgeons. The samples were taken from the arms and frontal part of the sterile gowns pre- and postoperatively. In the anterior surface of the gown, the sampling was initiated at a strip with 50 cm height from the ground followed by the strips with 15 cm distances from caudal to cephalad. Furthermore, the frontal part of the gown was divided into three parts in relation to the operating room table. Finally, the contamination rate was evaluated in each part. A semiquantitative method was used for the analysis of bacterial culture.

RESULTS

Before the operation, there were four samples tested positive for bacterial culture (1.06%). All of these samples were taken from the most proximal strip near the neckline. After the surgery, the rate of contamination in the strips on the frontal part of the gown was reported as 3.1% to 53%. Based on the operating table, the contamination rate was 35.9%, 8.9%, and 47.3% in the distal, middle, and proximal parts of the gown, respectively. The contamination rate at the elbow crease was 23%, and at 5 and 10 cm above the creases were 24% and 36%, respectively.

CONCLUSION

The high rate of gown contamination during the operation is concerning. However, part of the gown that was in contact with the operating room table remained clean most of the time. More safe strategies should be used for infection prevention in operating rooms.