Preoperative body mass index and physical function are associated with length of stay and facility discharge after total knee arthroplasty

The Investigation of Preoperative Factors Associated With Postoperative Outcomes Following Total Knee Arthroplasty for Osteoarthritis: A Scoping Review

This study aimed to investigate preoperative factors associated with non-home discharges from acute care hospitals in patients undergoing total knee arthroplasty (TKA) due to osteoarthritis. It was a scoping review focused on patients who received their first unilateral TKA for osteoarthritis. The research targeted observational studies that examined the destinations of patients post-surgery based on preoperative factors, with a literature search conducted in April 2023. Out of 3,255 identified papers, 28 met the eligibility criteria. A total of 26 preoperative factors were identified as potentially related to discharge destinations, including age, gender, comorbidities, and obesity. By selecting an appropriate discharge destination based on preoperative factors, there may be potential for more efficient use of medical resources. Future studies should consider preoperative factors in the context of national healthcare systems and lengths of hospital stay.

Preoperative and Postoperative Weight Change has Minimal Influence on Health Care Utilization and Patient-Reported Outcomes Following Total Knee Arthroplasty

As obesity becomes more prevalent, more patients are at risk of lower extremity osteoarthritis and subsequent total knee arthroplasty (TKA). This study aimed to test (1) the association of preoperative weight change with health care utilization and (2) the association of pre- and postoperative weight changes with failure to achieve satisfaction and minimal clinically important difference (MCID) in Knee injury and Osteoarthritis Outcome Score for pain (KOOS-Pain) and function (KOOS-PS) 1 year after TKA. Prospectively collected monocentric data on patients who underwent primary TKA were retrospectively reviewed. Multivariable logistic regression assessed the influence of BMI and weight change on outcomes while controlling for confounding variables. Outcomes included prolonged length of stay (LOS >3 days), nonhome discharge, 90-day readmission rate, satisfaction, and achievement of MCID for KOOS-Pain and KOOS-PS. Preoperative weight change had no impact on prolonged LOS (gain, p = 0.173; loss, p = 0.599). Preoperative weight loss was associated with increased risk of nonhome discharge (odds ratio [OR]: 1.47, p = 0.003). There was also increased risk of 90-day readmission with preoperative weight gain (OR: 1.27, p = 0.047) and decreased risk with weight loss (OR: 0.73, p = 0.033). There was increased risk of nonhome discharge with obesity class II (OR: 1.6, p = 0.016) and III (OR: 2.21, p < 0.001). Weight change was not associated with failure to achieve satisfaction, MCID in KOOS-Pain, or MCID in KOOS-PS. Obesity class III patients had decreased risk of failure to reach MCID in KOOS-Pain (OR: 0.43, p = 0.005) and KOOS-PS (OR: 0.7, p = 0.007). Overall, pre- and postoperative weight change has little impact on the achievement of satisfaction and clinically relevant differences in pain and function at 1 year. However, preoperative weight gain was associated with a higher risk of 90-day readmissions after TKA. Furthermore, patients categorized in Class III obesity were at increased risk of nonhome discharge but experienced a greater likelihood of achieving MCID in KOOS-Pain and KOOS-PS. Our results raise awareness of the dangers of using weight changes and BMI alone as a measure of TKA eligibility.

The Impact of Preoperative Medical Evaluation in an Orthopaedic Perioperative Medical Clinic on Total Joint Arthroplasty Outcomes: An Observational Study

BACKGROUND

A preoperative medical evaluation (PME) in total joint arthroplasty (TJA) is routine despite considerable variation and uncertainty regarding its benefits. The orthopaedic department in our academic health system established a perioperative medical clinic (PMC) to standardize perioperative management and to study the effect of this intervention on total hip arthroplasty (THA) and total knee arthroplasty (TKA) outcomes. This observational study compared the impact of a PME within 30 days prior to surgery at the PMC (Periop30) versus elsewhere ("Usual Care") on postoperative length of stay (LOS), extended LOS (i.e., a stay of >3 days), and Patient-Reported Outcomes Measurement Information System-10 (PROMIS-10) Global Physical Health (GPH) score improvement in TJA.

METHODS

We stratified adult patients (≥18 years of age) who underwent primary TJA between January 2015 and December 2020 into Periop30 or Usual Care. We utilized univariate tests (a chi-square test for categorical variables and a t test for continuous variables) to assess for differences in patient characteristics. For both TKA and THA, LOS was assessed with use of multivariable negative binomial regression models; extended LOS, with use of binary logistic regression; and PROMIS-10 GPH score, with use of mixed-effects models with random intercept and slope. Interaction terms between the focal predictor (Periop30, yes or no) and year of surgery were included in all models.

RESULTS

Periop30 comprised 82.3% of TKAs (1,911 of 2,322 ) and 73.8% of THAs (1,876 of 2,541). For THA, the Periop30 group tended to be male (p = 0.005) and had a higher body mass index (p = 0.001) than the Usual Care group. The Periop30 group had a higher rate of staged bilateral THA (10.6% versus 7.5%; p = 0.028) and a lower rate of simultaneous bilateral TKA (5.1% versus 12.2%; p < 0.001) than the Usual Care group. Periop30 was associated with a lower mean LOS for both TKA (43.46 versus 54.15 hours; p < 0.001) and THA (41.07 versus 57.94 hours; p < 0.001). The rate of extended LOS was lower in the Periop30 group than in the Usual Care group for both TKA (15% versus 26.5%; p < 0.001) and THA (13.3% versus 27.4%; p < 0.001). There was no significant difference in GPH score improvement between Periop30 and Usual Care for either TKA or THA.

CONCLUSIONS

Periop30 decreased mean LOS and the rate of extended LOS for TJA without an adverse effect on PROMIS-10 GPH scores.

LEVEL OF EVIDENCE

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

The five times sit-to-stand test predicts same-day discharge for outpatients undergoing total joint arthroplasty

PURPOSE

To examine whether a patient's pre-operatively administered five times sit-to-stand (FTSTS) test score, when used alone or when combined with previously established predictors, relates to same-day discharge (SDD) after total knee or hip arthroplasty.

METHODS

This study utilized a multivariate, retrospective, observational design. Electronic medical record data for included participants were used to analyze the relationship between the patient factors (including the novel FTSTS variable) and the SDD outcome. Univariate and multiple variable regression modeling was undertaken to understand the strength of the relationship between the independent variables with the dependent variable. Receiver operating curve (ROC) analysis was performed to determine the area under the curve (AUC) for the novel model. Cut score analysis was performed to establish the score which has the greatest utility for stratifying patients based upon their likelihood of achieving SDD.

RESULTS

All independent variables related to the SDD outcome with varying effect sizes. The dichotomized FTSTS score related to the SDD outcome with medium effect (Exp(B) = 2.56). The score of 13.6 s was established as the point where the test was most highly sensitive and specific. The combined model including all included patient characteristics had a classification accuracy of 64.7% and an area under the curve score of .724.

CONCLUSION

The FTSTS score had higher predictive accuracy than all other stand-alone patient characteristics for the SDD outcome.

Preoperative Prediction and Risk Factor Identification of Hospital Length of Stay for Total Joint Arthroplasty Patients Using Machine Learning

Background

The aim of this study was to improve understanding of hospital length of stay (LOS) in patients undergoing total joint arthroplasty (TJA) in a high-efficiency, hospital-based pathway.

Methods

We retrospectively reviewed 1401 consecutive primary and revision TJA patients across 67 patient and preoperative care characteristics from 2016 to 2019 from the institutional electronic health records. A machine learning approach, testing multiple models, was used to assess predictors of LOS.

Results

The median LOS was 1 day; outpatients accounted for 16.5%, 1-day inpatient stays for 38.0%, 2-day stays for 26.4%, and 3-days or more for 19.1%. Patients characteristically fell into 1 of 3 broad categories that contained relatively similar characteristics: outpatient (0-day LOS), short stay (1- to 2-day LOS), and prolonged stay (3 days or greater). The random forest models suggested that a lower Risk Assessment and Prediction Tool score, unplanned admission or hospital transfer, and a medical history of cardiovascular disease were associated with an increased LOS. Documented narcotic use for surgery preparation prior to hospitalization and preoperative corticosteroid use were factors independently associated with a decreased LOS.

Conclusions

After TJA, most patients have either an outpatient or short-stay hospital episode. Patients who stay 2 days do not differ substantially from patients who stay 1 day, while there is a distinct group that requires prolonged admission. Our machine learning models support a better understanding of the patient factors associated with different hospital LOS categories for TJA, demonstrating the potential for improved health policy decisions and risk stratification for centers caring for complex patients.

Establishment and evaluation of a predictive model for length of hospital stay after total knee arthroplasty: A single-center retrospective study in China

Background

Total knee arthroplasty (TKA) is the ultimate option for end-stage osteoarthritis, and the demand of this procedure are increasing every year. The length of hospital stay (LOS) greatly affects the overall cost of joint arthroplasty. The purpose of this study was to develop and validate a predictive model using perioperative data to estimate the risk of prolonged LOS in patients undergoing TKA.

Methods

Data for 694 patients after TKA collected retrospectively in our department were analyzed by logistic regression models. Multi-variable logistic regression modeling with forward stepwise elimination was used to determine reduced parameters and establish a prediction model. The discrimination efficacy, calibration efficacy, and clinical utility of the prediction model were evaluated.

Results

Eight independent predictors were identified: non-medical insurance payment, Charlson Comorbidity Index (CCI) ≥ 3, body mass index (BMI) &gt; 25.2, surgery on Monday, age &gt; 67.5, postoperative complications, blood transfusion, and operation time &gt; 120.5 min had a higher probability of hospitalization for ≥6 days. The model had good discrimination [area under the curve (AUC), 0.802 95% CI, 0.754–0.850]] and good calibration (p = 0.929). A decision curve analysis proved that the nomogram was clinically effective.

Conclusion

This study identified risk factors for prolonged hospital stay in patients after TKA. It is important to recognize all the factors that affect hospital LOS to try to maximize the use of medical resources, optimize hospital LOS and ultimately optimize the care of our patients.

Predicting Length of Stay using machine learning for total joint replacements performed at a rural community hospital

BACKGROUND

Predicting patient's Length of Stay (LOS) before total joint replacement (TJR) surgery is vital for hospitals to optimally manage costs and resources. Many hospitals including in rural areas use publicly available models such as National Surgical Quality Improvement Program (NSQIP) calculator which, unfortunately, performs suboptimally when predicting LOS for TJR procedures.

OBJECTIVE

The objective of this research was to develop a Machine Learning (ML) model to predict LOS for TJR procedures performed at a Perioperative Surgical Home implemented rural community hospital for better accuracy and interpretation than the NSQIP calculator.

METHODS

A total of 158 TJR patients were collected and analyzed from a rural community hospital located in Montana. A random forest (RF) model was used to predict patient's LOS. For interpretation, permuted feature importance and partial dependence plot methods were used to identify the important variables and their relationship with the LOS.

RESULTS

The root mean square error for the RF model (0.7) was lower than the NSQIP calculator (1.21). The five most important variables for predicting LOS were BMI, Duke Activity Status-Index, diabetes, patient's household income, and patient's age.

CONCLUSION

This pilot study is the first of its kind to develop an ML model to predict LOS for TJR procedures that were performed at a small-scale rural community hospital. This pilot study contributes an approach for rural hospitals, making them more independent by developing their own predictions instead of relying on public models.

Clinical Pathways of Patients Denied Total Knee Arthroplasty Due to an Institutional BMI Cutoff

Out of concern for the increased risk of complications with morbid obesity, institutional body mass index (BMI) cutoffs for total knee arthroplasty (TKA) have become commonplace. We sought to answer the questions: what percentage of morbidly obese patients with knee osteoarthritis who present to an arthroplasty clinic will, within 2 years, undergo TKA at (1) a BMI less than 40 kg/m² or (2) at a BMI greater than 40 kg/m²? Of those who do not undergo surgery, (3) what percentage lose enough weight to become TKA-eligible, and (4) what percentage do not? We performed an observational study of 288 patients, of which 256 had complete follow-up. Institutional electronic medical record review and patient follow-up by telephone were conducted to determine which patients underwent surgery, and at what BMI. For those that did not undergo TKA, BMI was examined to see if the patient ever lost enough weight to become TKA eligible. Twelve of 256 patients (4.7%) underwent TKA at a BMI less than 40 kg/m², 64 patients (25%) underwent TKA at a BMI greater than 40 kg/m², and 7 patients (2.7%) underwent surgery at an outside hospital. The average BMI at the time of surgery was 42.3 kg/m². Thirty-seven of 256 patients (14.4%) lost enough weight to become TKA-eligible within 2 years of the initial visit but did not undergo surgery, while 136 patients (53.1%) neither underwent TKA nor became eligible. Strict enforcement of a BMI cutoff for TKA is variable among surgeons. In the absence of weight loss protocols, 19.1% of morbidly obese patients may be expected to reach the sub-40 kg/m² BMI milestone.

Patterns and Predictors of Weight Change Before and After Total Hip Arthroplasty in Class 2 and 3 Obese Patients

BACKGROUND

This study aimed to better understand body mass index (BMI) change patterns and factors associated with BMI change before and after total hip arthroplasty (THA) in Class 2 and 3 obese patients, and assess if preoperative or postoperative BMI change affects postoperative clinical outcomes.

METHODS

We retrospectively reviewed World Health Organization Class 2 and 3 obese patients (BMI > 35.0 at surgery) who underwent THA at a tertiary medical center from 2010 to 2020. BMI was recorded at 1 year preoperatively (mean 11.6 months), and at most recent postoperative visit (mean 29.0 months). Baseline demographics and postoperative clinical outcomes were recorded.

RESULTS

We reviewed 436 THAs with a mean age of 59.9 (11.5) years. Leading up to surgery 55.5% had unchanged BMI, and postoperatively 48.2% had unchanged BMI. Multivariate logistic regression revealed that those who lost BMI preoperatively were more likely to gain BMI postoperatively (odds ratio [OR] 3.28, confidence interval [CI] 1.83-5.97, P = .005), but those who gained >5% BMI preoperatively had no association with BMI change postoperatively. Those in a higher BMI class preoperatively were less likely to gain BMI preoperatively (Class 3 obese patients: OR 0.001, CI 0.0002-0.004, P < .001). African American patients were more likely to gain BMI preoperatively (OR 2.32, CI 1.16-4.66, P = .017). We did not detect an association between BMI change and postoperative clinical outcomes.

CONCLUSION

In World Health Organization Class 2 or 3 obese patients, most maintained BMI between their first preoperative and final postoperative visit. Preoperatively, Class 3 obese patients were less likely to gain weight than Class 2 obese patients. The primary predictor of postoperative weight gain was preoperative weight loss. Weight change preoperatively and postoperatively were not associated with worse clinical outcomes.

Do TKAs in Patients with Higher BMI Take Longer, and is the Difference Associated with Surgeon Volume? A Large-database Study from a National Arthroplasty Registry

BACKGROUND

Increased surgical time in TKA may impact economic costs and clinical outcomes. Prior work has found that TKAs in patients with high BMI take longer, and these patients may be at greater risk for postoperative complications like infection. However, these studies included small numbers of patients and surgeons from single institutions and they did not consider surgeon volume.

QUESTIONS/PURPOSES

Using the New Zealand Joint Registry (NZJR), we asked: (1) Is there a relationship between increasing patient BMI and TKA operative time? (2) Is the effect of BMI on surgical time less pronounced among surgeons who perform more TKAs per year than those who perform fewer?

METHODS

Data were collected from the NZJR between January 2010 and December 2018 as it is the only national registry that records both BMI and surgical time. Primary TKA performed for osteoarthritis by surgeons with more than 50 TKAs over the period of the study were identified. BMI and operative time (skin incision to closure in minutes) were recorded. Patients with the following were excluded: lateral parapatellar or minimally invasive approaches; navigated, patient-specific instrumentation, or robot-assisted TKA; uncemented or hybrid fixation; those with procedures performed by a trainee (all or part); or a nonosteoarthritic indication. Of 64,108 TKAs performed during the study period, a total of 42% (27,057) met our inclusion criteria. The primary outcome was the effect of BMI on operative time. Operative time is expressed in minutes as a mean for each single-unit BMI increase across all surgeons, controlled for other variables that might influence operative time such as patella resurfacing and cruciate-retaining versus posterior-stabilized designs. Overall, the mean operative time (skin incision to closure) was 79 ± 22 minutes. Surgical experience was assessed by subdividing surgeons into six groups according to the number of TKAs performed annually (< 10, 10 to 24, 25 to 49, 50 to 74, 75 to 99, and > 100). Statistical analyses were performed including a general linear model to assess the independent association between BMI and operative time, allowing for the effects of other patient and surgical features. In addition, linear regression analyses explored the associations between BMI and operative time in the whole group and within surgical volume groups.

RESULTS

There was an association between increasing BMI and increasing surgical duration. The mean operative time increased from 75 ± 22 minutes in patients with a normal BMI of 25 kg/m2 to 87 ± 24 minutes in patients with a BMI of 40 kg/m2 to 94 ± 28 minutes in patients with a BMI > 50 kg/m2 (p < 0.001). Surgeons performing fewer than 25 TKAs per year took 14% longer to perform a TKA on a patient with a BMI of 40 kg/m2 than on a patient with a normal BMI of 25 kg/m2. However, surgeons performing greater than 25 TKAs per year took 10% longer.

CONCLUSION

In this study, an increase BMI was associated with increased surgical time in TKA. Surgical duration for high-volume surgeons appears less influenced by increases in BMI than lower volume surgeons. Although the absolute increase in duration was small, prolonged surgical time may reduce theater productivity. Even though the issues around managing patients with high BMI are multifactorial and complex, considerations from these findings include ensuring appropriate theater scheduling and possibly referring patients with high BMI to specialist centers. Further studies should focus on assessing the effectiveness of such measures in reducing complications and improving outcomes in patients with elevated BMI.

LEVEL OF EVIDENCE

Level III, therapeutic study.

Obesity, Comorbidities, and the Associated Risk among Patients Who Underwent Total Knee Arthroplasty in Alberta

Obesity, a common risk factor for osteoarthritis (OA), accelerates joint deterioration resulting in the need for early total knee arthroplasty (TKA). The role of obesity in the management of OA remains a controversial topic. In this study, we examined whether obesity along with other comorbidities is associated with peri/postoperative complications in patients who underwent primary unilateral TKA in Alberta, Canada. A retrospective secondary analysis was performed on data extracted from data repository of patients (n = 15,151) who underwent TKA between 2012 and 2016. The sample was divided into five groups based on body mass index (BMI) classification developed by the World Health Organization. The associations between dependent variable (presence or absence of a complication or comorbidity) with the independent variables (year of surgery, age, sex, length of surgery, and BMI groups) were examined using binomial logistic regression. Results showed that obese classes I, II, and III, irrespective of other covariates, were more likely to have diabetes and pulmonary embolism (p < 0.001) compared with the normal BMI group. Patients with obese class III compared with the patients in normal BMI group were more likely to have deep wound infection (p = 0.04). Patients with comorbidities were more likely to have a blood transfusion, infection, pulmonary embolism, and readmission. Patients in higher BMI groups or with comorbidities were more likely to experience peri/postoperative complications following TKA, though the level of risk depends on the severity of obesity. These findings may be used by health care providers to educate patients in higher BMI groups about the risks of TKA and optimize comorbidities prior to the surgery.

Obesity, preoperative weight loss, and telemedicine before total joint arthroplasty: a review

The preoperative period prior to elective total joint arthroplasty (TJA) is a critical time for lifestyle interventions since a scheduled surgery may help motivate patients to lose weight. Weight loss may reduce complications associated with obesity following TJA and enable patients with severe obesity (body mass index [BMI] > 40 kg/m²) to become eligible for TJA, as many institutions use a 40 kg/m² cut-off for offering surgery. A comprehensive review was conducted to (1) provide background on complications associated with obesity following TJA, (2) synthesize prior research on the success rate of patients losing weight after being denied TJA for severe obesity, (3) discuss bariatric surgery before TJA, and (4) propose mobile health telemedicine weight loss interventions as potential weight loss methods for patients preoperatively. It is well established that obesity increases complications associated with TJA. In total knee arthroplasty (TKA), obesity increases operative time, length of stay, and hospitalization costs as well as the risk of deep infection, revision, and component malpositioning. Obesity may have an even larger impact on complications associated with total hip arthroplasty (THA), including wound complications and deep infection. Obesity also increases the risk of hip dislocation, aseptic loosening, and venous thromboembolism after THA. Synthesis of the only two studies (n = 417), to our knowledge, that followed patients denied TJA for severe obesity demonstrated that only 7% successfully reduced their BMI below 40 kg/m² via lifestyle modifications and ultimately underwent TJA. Unfortunately, bariatric surgery may only increase certain post-TKA complications including death, pneumonia, and implant failure, and there is limited research on preoperative weight loss via lifestyle modification. A review of short-term mobile health weight loss interventions that combined personalized counseling with self-monitoring via a smartphone app found about 5 kg of weight loss over 3-6 months. Patients with severe obesity have more weight to lose and may have additional motivation to do so before TJA, so weight loss results may differ by patient population. Research is needed to determine whether preoperative mobile health interventions can help patients become eligible for TJA and produce clinically significant weight loss sufficient to improve postoperative outcomes.

Morbid obesity is not a contraindication to lower limb arthroplasty

There are concerns that increased BMI is associated with a greater length of stay (LOS) and perioperative complications following total knee (TKR) and total hip replacements (THR). We analysed data from a six-month period to see if there was a correlation between BMI and LOS. We performed a subgroup analysis for patients with morbid obesity (BMI >40) looking at perioperative complications. 285 TKRs and 195 THRs were analysed. For TKRs, the average length of stay was 2.7 days. The average BMI was 32.4. There was no significant correlation between BMI and LOS (r=-0.0447, p=0.2267). The morbidly obese category (n=33) had the shortest LOS (2.5 days) compared to other BMI categories. 30- day readmission rate was 6%. 90-day re-admission rate was 12%. Six patients had minor wound issues requiring no intervention or antibiotics only. The was one prosthetic joint infection, one stitch abscess, one DVT and one patellar tendon injury. For THRs, the average LOS was 2.9 days. The average BMI was 29.9. There was no significant correlation between BMI and LOS (r=0.007, p=0.4613). The morbid obese category (n=9) had the shortest LOS (1.9 days) compared to other BMI categories. No patients were readmitted within 90 days or had documented complications. We have shown that for TKRs and THRs, increased BMI is not associated with increased LOS. The morbidly obese were found to have the shortest LOS. Re-admission rates and complications were commendable for patients with morbid obesity. BMI >40 is not a contraindication to TKR or THR.

Malnutrition in elective shoulder arthroplasty: a multi-institutional retrospective study of preoperative albumin and adverse outcomes

BACKGROUND

Malnutrition is associated with poor postoperative outcomes after knee, hip, and spine surgery. However, whether albumin labs should be part of the routine preoperative workup for shoulder arthroplasty remains understudied. This study investigated the role of preoperative albumin levels in predicting common postoperative adverse outcomes in patients undergoing shoulder arthroplasty.

METHODS

All shoulder arthroplasty cases performed at 2 tertiary referral centers between July 2013 and May 2019 (institution 1) and between June 2007 and Feb 2020 (institution 2) were reviewed. A total of 421 primary and 71 revision elective shoulder arthroplasty cases had preoperative albumin levels recorded. Common demographic variables and relevant Elixhauser comorbidities were pulled. Outcomes gathered included extended (>3 days) postoperative inpatient length of stay (eLOS), 90-day readmission, and discharge to rehab or skilled nursing facility (SNF).

RESULTS

The prevalence of malnutrition (albumin <3.5 g/dL) was higher in the revision group compared with the primary group (36.6% vs. 19.5%, P = .001). Reverse shoulder arthroplasty (P = .013) and increasing American Society of Anesthesiologists score (P = .016) were identified as independent risk factors for malnutrition in the primary group. In the revision group, liver disease was associated with malnutrition (P = .046). Malnourished primary shoulder arthroplasty patients had an increased incidence of eLOS (26.8% vs. 13.6%, P = .003) and discharge to rehab/SNF (18.3% vs. 10.3%, P = .045). On univariable analysis, low albumin had an odds ratio (OR) of 2.34 for eLOS (P = .004), which retained significance in a multivariable model including age, American Society of Anesthesiologists score, sex, and body mass index (OR 2.11, P = .03). On univariable analysis, low albumin had an OR of 1.94 for discharge to SNF/rehab (P = .048), but this did not reach significance in the multivariable model. Among revisions, malnourished patients had an increased incidence of eLOS (30.8% vs. 6.7%, P = .014) and discharge to rehab/SNF (26.9% vs. 4.4%, P = .010). In both the primary and revision groups, there was no difference in 90-day readmission rate between patients with low or normal albumin.

CONCLUSION

Malnutrition is more prevalent among revision shoulder arthroplasty patients compared with those undergoing a primary procedure. Primary shoulder arthroplasty patients with low preoperative albumin levels have an increased risk of eLOS and may have an increased need for postacute care. Low albumin was not associated with a risk of 90-day readmissions. Albumin level merits further investigation in large, prospective cohorts to clearly define its role in preoperative risk stratification.

Preoperative Nonsurgical Weight Loss Interventions Before Total Hip and Knee Arthroplasty: A Systematic Review

BACKGROUND

An upcoming total joint arthroplasty (TJA) may motivate patients with severe obesity (body mass index [BMI] > 40 kg/m²) to lose weight. Weight loss can optimize outcomes following TJA, and many surgeons use a 40 kg/m² cut-off for undergoing TJA to reduce the risk of complications. However, few patients who are denied TJA for severe obesity successfully lose weight. This is the first systematic review of nonsurgical weight loss interventions before TJA.

METHODS

Five electronic databases were searched for articles on January 11, 2021. Studies that utilized preoperative nonsurgical weight loss interventions for patients with obesity (BMI ≥ 30 kg/m²) scheduled for or awaiting TJA of the hip or knee were included. Two reviewers independently screened articles, assessed methodological quality, and extracted data.

RESULTS

We retrieved 1943 unique records, of which 7 met inclusion criteria including 2 randomized clinical trials and 5 single-arm case series. Overall, weight loss ranged from 5.0 to 32.5 kg. Four interventions reduced BMI by 3 kg/m² at 3-5 months, while 1 reduced BMI by 12.7 kg/m². Other weight outcomes and those related to pain, function, complications, and adverse events were inconsistently reported.

CONCLUSION

Although larger trials are needed, particularly randomized controlled trials that measure preoperative weight loss in a control group, nutritional status, and postoperative complications, the available evidence indicates that short-term, nonsurgical, preoperative weight loss interventions before TJA produce both statistically significant weight loss and reduced BMI before surgery. It remains unknown if the amount of weight loss from these interventions is clinically significant and sufficient to improve outcomes after TJA.

Comparison of the Effect and Complications of Sequential Bilateral Arthroplasty at Different Time Intervals and Simultaneous Bilateral Total Knee Arthroplasty: A Single-Centre Retrospective Cohort Study

INTRODUCTION

To the authors' knowledge, there is no current consensus regarding the optimal interprocedural interval for patients who have undergone bilateral total knee arthroplasty (BTKA). The purpose of this study is to evaluate complication rates and functional outcome in patients who have undergone BTKA (simultaneous or sequential at different time intervals), and to determine an optimal time frame for the second knee.

METHODS

Data from 315 patients who were able to tolerate simultaneous BTKA according to the anaesthesiologist's preoperative assessment between 2016 and 2020 were analysed retrospectively. According to the operative time interval, they were divided into simultaneous, ≤ 1-month sequential, 1- to 3-month sequential, and ≥ 3-month sequential BTKA groups. The primary outcomes were revision and readmission rates during the follow-up period, and the secondary outcomes were hospital length of stay (LOS), transfusion and postoperative complications.

RESULTS

There was no difference in the implant survival or readmission rate between the groups (p > 0.05). Multivariable linear regression showed that interprocedural interval and body mass index (BMI) affected LOS; the LOS of simultaneous BTKA was the shortest (p < 0.05). BMI was associated with an increased LOS of 0.25 days (95% CI 0.02-0.48, p = 0.03). A modified Poisson regression model showed that the odds of blood transfusion were reduced in sequential BTKAs of any interval (p < 0.05), and preoperative haemoglobin (Hb) was also a risk factor (RR 0.96, 95% CI 0.95-0.98, p < 0.001). The interprocedural interval was not a risk factor for postoperative cardiovascular and cerebrovascular complications.

CONCLUSION

For appropriate patients, simultaneous BTKA is beneficial. However, higher preoperative haemoglobin was required to mitigate the high blood transfusion rate associated with simultaneous surgeries. If suitable patients refuse simultaneous BTKA for other non-medical reasons, sequential BTKA with an interval greater than 1 month is recommended.

Artificial neural network prediction of same-day discharge following primary total knee arthroplasty based on preoperative and intraoperative variables

AIMS

This study used an artificial neural network (ANN) model to determine the most important pre- and perioperative variables to predict same-day discharge in patients undergoing total knee arthroplasty (TKA).

METHODS

Data for this study were collected from the National Surgery Quality Improvement Program (NSQIP) database from the year 2018. Patients who received a primary, elective, unilateral TKA with a diagnosis of primary osteoarthritis were included. Demographic, preoperative, and intraoperative variables were analyzed. The ANN model was compared to a logistic regression model, which is a conventional machine-learning algorithm. Variables collected from 28,742 patients were analyzed based on their contribution to hospital length of stay.

RESULTS

The predictability of the ANN model, area under the curve (AUC) = 0.801, was similar to the logistic regression model (AUC = 0.796) and identified certain variables as important factors to predict same-day discharge. The ten most important factors favouring same-day discharge in the ANN model include preoperative sodium, preoperative international normalized ratio, BMI, age, anaesthesia type, operating time, dyspnoea status, functional status, race, anaemia status, and chronic obstructive pulmonary disease (COPD). Six of these variables were also found to be significant on logistic regression analysis.

CONCLUSION

Both ANN modelling and logistic regression analysis revealed clinically important factors in predicting patients who can undergo safely undergo same-day discharge from an outpatient TKA. The ANN model provides a beneficial approach to help determine which perioperative factors can predict same-day discharge as of 2018 perioperative recovery protocols. Cite this article: Bone Joint J 2021;103-B(8):1358-1366.

Body Mass Index, American Society of Anesthesiologists Score, and Elixhauser Comorbidity Index Predict Cost and Delay of Care During Total Knee Arthroplasty

BACKGROUND

Body mass index (BMI), American Society of Anesthesiologists (ASA) score, and Elixhauser Comorbidity Index are measures that are utilized to predict perioperative outcomes, though little is known about their comparative predictive effects. We analyzed the effects of these indices on costs, operating room (OR) time, and length of stay (LOS) with the hypothesis that they would have a differential influence on each outcome variable.

METHODS

A retrospective review of the institutional database was completed on primary TKA patients from 2015 to 2018. Univariable and multivariable models were constructed to evaluate the strength of BMI, ASA, and Elixhauser comorbidities for predicting changes to total hospital and surgical costs, OR time, and LOS.

RESULTS

In total, 1313 patients were included. ASA score was independently predictive of all outcome variables (OR time, LOS, total hospital and surgical costs). BMI, however, was associated with intraoperative resource utilization through time and cost, but only remained predictive of OR time in an adjusted model. Total Elixhauser comorbidities were independently predictive of LOS and total hospital cost incurred outside of the operative theater, though they were not predictive of intraoperative resource consumption.

CONCLUSION

Although ASA, BMI, and Elixhauser comorbidities have the potential to impact outcomes and cost, there are important differences in their predictive nature. Although BMI is independently predictive of intraoperative resource utilization, other measures like Elixhauser and ASA score were more indicative of cost outside of the OR and LOS. These data highlight the differing impact of BMI, ASA, and patient comorbidities in impacting cost and time consumption throughout perioperative care.

Which Patient Factors Best Predict Discharge Destination After Primary Total Knee Arthroplasty? The ARISE Trial

BACKGROUND

The role of inpatient rehabilitation after total knee arthroplasty (TKA) remains uncertain, with evidence suggesting no better functional outcomes for those who discharge to rehabilitation to those who discharge home. The aim of this study is to develop and implement a pre-operative predictive tool, ARISE (Arthroplasty Rehabilitation Initial Screening Evaluation), that incorporated psychological, functional, and socio-demographic factors to determine discharge destination.

METHODS

One week prior to TKA, the ARISE tool was administered to 100 patients, in addition to an EQ-5D-5L survey and other demographic data being recorded. The primary outcome was discharge destination. An enhanced recovery pathway, which included an anesthetic protocol designed to optimize early mobilization, was utilized. Univariable and multivariable logistic regression analysis was performed to determine the likelihood of discharge destination.

RESULTS

Patients in the rehabilitation group were, on average, 4.5 years older than the home group (P = .036). After multivariable regression, ARISE questions were predictive of discharge destination related to beliefs around the superiority of inpatient rehabilitation (odds ratio = 9.9 [2.6-37.9]) and post-discharge level of support (odds ratio = 6.3 [1.5-26.8]). No question around self-reported physical function was predictive.

CONCLUSION

Pre-operative patient beliefs regarding rehabilitation and future home support are highly predictive of discharge destination after primary TKA. Pre-operative patient-reported functional status and demographic variables, with the exception of increasing age, were not shown to be predictive. Predicting those that are most likely to discharge to rehabilitation allows for early, targeted interventions to optimize resources and increase likelihood of home discharge.

Association between interhospital transfer and morbid obesity in emergency general surgery procedures

BACKGROUND

Obese patients may have unique surgical needs. The goal of this study is to determine if there is an association between obesity and transfer in patients undergoing EGS.

METHODS

EGS patients were identified in the NSQIP 2011-2016 database. Outcome variables included interhospital transfer, days to surgery, SSI, postoperative LOS, discharge destination, and 30-day readmission. Descriptive statistics and multivariable regression were utilized.

RESULTS

419,373 EGS patients were identified, and transfer status varied by obesity class. After controlling for other factors, obese patients had increased odds of interhospital transfer (OR = 1.07-1.53), SSI (OR = 1.22-1.69), and decreased odds of discharge to home (OR = 0.42-0.71, all p < 0.01) but not of 30-day readmission or delay from admission to surgical intervention.

CONCLUSIONS

Obese patients undergoing EGS procedures have an increased likelihood of transfer from an acute care hospital. As obese EGS patients are increasingly prevalent, determining best triage practices for this unique patient population warrants additional investigation.

Differences in patient characteristics and external validity of randomized clinical trials on pain management following total hip and knee arthroplasty: a systematic review

Background

The external validity of randomized controlled trials (RCTs) is critical for the relevance of trial results in a clinical setting. We aimed to assess the external validity of RCTs investigating postoperative pain treatment after total hip and knee arthroplasty (THA and TKA) by comparing patient characteristics in these trials with a clinical cohort. Further, we assessed the use of exclusion criteria of the included RCTs.

Methods

We searched PubMed, Embase, and Cochrane Central Register of Controlled Trials for relevant RCTs up to June 2019. Data on patient characteristics from this research population were compared with an unselected clinical cohort from the Danish Hip and Knee Arthroplasty Registries in the period 2005–2019. Trends in patient characteristics and the use of exclusion criteria were assessed with control charts.

Results

In total, 550 RCTs with 48 962 participants were included in the research cohort. The clinical cohort included 101 439 THA patients and 90 505 TKA patients. Patient characteristics (age, body mass index (BMI), American Society of Anesthesiologists (ASA) score and sex distribution) in the research cohort resembled those of the clinical cohort. Age, BMI and ASA scores did not change over time in the research cohort. In the clinical cohort, age increased among both THA and TKA patients, and BMI and ASA scores increased among TKA patients. Most commonly used exclusion criteria in the RCTs were high ASA score (62%), older age (45%), obesity (32%) and chronic opioid use (41%). Exclusion of chronic opioid users and individuals with obesity increased over time.

Conclusion

Patient characteristics in research trials investigating postoperative pain management after THA and TKA currently resemble those of a clinical cohort. However, individuals in the clinical cohort are getting older, and TKA patients more obese with increasing ASA scores. Concomitantly, RCTs increase the tendency to exclude patients with older age, obesity, chronic pain and/or opioid use. This trending discrepancy can hinder the generalizability of future research results, and therefore increased focus on pragmatic trials resembling real-world conditions are needed.

PROSPERO registration number

CRD42019125691

Intrinsic patient factors predictive of inpatient rehabilitation facility discharge following primary total knee arthroplasty: a systematic review and meta-analysis

Background

Total Knee Arthroplasty (TKA) reduces pain and improves function in those suffering from severe osteoarthritis. A significant cost of TKA is post-acute care, however, current evidence suggests that discharge to an Inpatient Rehabilitation Facility (IRF) has inferior outcomes to home discharge, with no greater benefit in physical function. Only individual studies have investigated TKA patient characteristics predictive of discharge destination, therefore, the aim is to systematically review the literature and meta-analyse intrinsic patient factors predictive of IRF discharge. If predictive factors are known, then early discharge planning and intervention strategies could be implemented.

Methods

Databases PubMed, CINAHL, Embase, Cochrane, and Pedro were searched up to October 2019 for all studies investigating pre-operative intrinsic patient factors predictive of IRF discharge. For assessing the methodological quality of included studies, the Quality In Prognosis Studies (QUIPS) tool was used. Statistical analysis and graphical reporting were conducted in R statistical software. To assess the effect of predictors of discharge destination, odds ratios with the corresponding 95%CI were extracted from the results of univariate and multivariable analyses.

Results

A total of 9 articles published between 2011 to 2018 with 218,151 TKA patients were included. Of the 13 intrinsic patient factors reported, 6 met the criteria for synthesised review: age, obesity, comorbidity, gender, SF-12/VR-12 survey, and smoking. Due to the heterogeneity of statistical analysis and reporting 2 variables could undergo meta-analysis, gender and smoking. Female gender increased the likelihood of IRF discharge by 78% (OR = 1.78; 95%CI = 1.43–2.20; I2 = 33.3%), however, the relationship between smoking status and discharge destination was less certain (OR = 0.80; 95%CI = 0.42–1.50; I2 = 68.5%).

Conclusion

In this systematic literature review and meta-analysis female gender was shown to be predictive of IRF discharge after total knee arthroplasty. There was also a trend for those of older age and increased comorbidity, as measured by the Charlson Comorbidity Index, or the severely obese to have an increased likelihood of IRF discharge. The marked heterogeneity of statistical methods and reporting in existing literature made pooled analysis challenging for intrinsic patient factors predictive of IRF discharge after TKA. Further, high quality studies of prospective design on predictive factors are warranted, to enable early discharge planning and optimise resource allocation on post-acute care following TKA.

Trial registration

This review was registered with PROSPERO (CRD42019134422).

Predicting implant size in total knee arthroplasty using demographic variables

AIMS

The purpose of this investigation was to determine the relationship between height, weight, and sex with implant size in total knee arthroplasty (TKA) using a multivariate linear regression model and a Bayesian model.

METHODS

A retrospective review of an institutional registry was performed of primary TKAs performed between January 2005 and December 2016. Patient demographics including patient age, sex, height, weight, and body mass index (BMI) were obtained from registry and medical record review. In total, 8,100 primary TKAs were included. The mean age was 67.3 years (SD 9.5) with a mean BMI of 30.4 kg/m² (SD 6.3). The TKAs were randomly split into a training cohort (n = 4,022) and a testing cohort (n = 4,078). A multivariate linear regression model was created on the training cohort and then applied to the testing cohort . A Bayesian model was created based on the frequencies of implant sizes in the training cohort. The model was then applied to the testing cohort to determine the accuracy of the model at 1%, 5%, and 10% tolerance of inaccuracy.

RESULTS

Height had a relatively strong correlation with implant size (femoral component anteroposterior (AP) Pearson correlation coefficient (ρ) = 0.73, p < 0.001; tibial component mediolateral (ML) ρ = 0.77, p < 0.001). Weight had a moderately strong correlation with implant size, (femoral component AP ρ = 0.46, p < 0.001; tibial ML ρ = 0.48, p < 0.001). There was a significant linear correlation with height, weight, and sex with implant size (femoral component R² = 0.607, p < 0.001; tibial R² = 0.695, p < 0.001). The Bayesian model showed high accuracy in predicting the range of required implant sizes (94.4% for the femur and 96.6% for the tibia) accepting a 5% risk of inaccuracy.

CONCLUSION

Implant size was correlated with basic demographic variables including height, weight, and sex. The linear regression and Bayesian models accurately predicted required implant sizes across multiple manufacturers based on height, weight, and sex alone. These types of predictive models may help improve operating room and implant supply chain efficiency. Level of Evidence: Level IV Cite this article: Bone Joint J 2020;102-B(6 Supple A):85-90.

In pursuit of enhanced recovery after total joint replacement: a narrative review of drivers of length of stay

A continual increase in the prevalence of osteoarthritis drives growing demand for total joint arthroplasty. So far, a decrease in length of stay has been the target for health professionals globally. However, a consensus pathway of achieving this has not yet been reached. This article reviews recent advances in pre-operative and perioperative factors impacting length of stay.

Use of Computerized Adaptive Testing to Develop More Concise Patient-Reported Outcome Measures

Background

Patient-reported outcome measures (PROMs) are essential tools that are used to assess health status and treatment outcomes in orthopaedic care. Use of PROMs can burden patients with lengthy and cumbersome questionnaires. Predictive models using machine learning known as computerized adaptive testing (CAT) offer a potential solution. The purpose of this study was to evaluate the ability of CAT to improve efficiency of the Veterans RAND 12 Item Health Survey (VR-12) by decreasing the question burden while maintaining the accuracy of the outcome score.

Methods

A previously developed CAT model was applied to the responses of 19,523 patients who had completed a full VR-12 survey while presenting to 1 of 5 subspecialty orthopaedic clinics. This resulted in the calculation of both a full-survey and CAT-model physical component summary score (PCS) and mental component summary score (MCS). Several analyses compared the accuracy of the CAT model scores with that of the full scores by comparing the means and standard deviations, calculating a Pearson correlation coefficient and intraclass correlation coefficient, plotting the frequency distributions of the 2 score sets and the score differences, and performing a Bland-Altman assessment of scoring patterns.

Results

The CAT model required 4 fewer questions to be answered by each subject (33% decrease in question burden). The mean PCS was 1.3 points lower in the CAT model than with the full VR-12 (41.5 ± 11.0 versus 42.8 ± 10.4), and the mean MCS was 0.3 point higher (57.3 ± 9.4 versus 57.0 ± 9.6). The Pearson correlation coefficients were 0.97 for PCS and 0.98 for MCS, and the intraclass correlation coefficients were 0.96 and 0.97, respectively. The frequency distribution of the CAT and full scores showed significant overlap for both the PCS and the MCS. The difference between the CAT and full scores was less than the minimum clinically important difference (MCID) in >95% of cases for the PCS and MCS.

Conclusions

The application of CAT to the VR-12 survey demonstrated an ability to lessen the response burden for patients with a negligible effect on score integrity.

Preoperative Patient Factors Affecting Length of Stay following Total Knee Arthroplasty: A Systematic Review and Meta-Analysis

BACKGROUND

Total knee arthroplasty (TKA) yields substantial improvements in quality of life for patients with severe osteoarthritis. Previous research has shown that TKA outcomes are inferior in patients with certain demographic and clinical factors. Length of stay (LOS) following TKA is a major component of costs incurred by healthcare providers. It is hypothesized that patient-related factors may influence LOS following TKA. The purpose of this systematic review and meta-analysis is to investigate these factors.

METHODS

Three databases (PubMed, Embase, and OVID Medline) were searched using variants of the terms "total knee arthroplasty" and "length of stay". Studies were screened and data abstracted in duplicate. The primary outcome was the effect of prognostic variables on LOS following TKA. Meta-analysis was performed using the Review Manager (RevMan) software (version 5.3. Copenhagen: The Nordic Cochrane Center, The Cochrane Collaboration, 2014).

RESULTS

A total of 68 studies met all inclusion criteria for this review. These studies comprised 21,494,459 patients undergoing TKA with mean age 66.82 years (range, 15-95 years) and 63.8% (12,165,160 of 19,060,572 reported) females. The mean MINORS score was 7, suggesting that studies had a low quality of evidence. Mean LOS following TKA has steadily decreased over the past 4 decades, partially because of the implementation of fast-track programs. Demographic factors associated with increased LOS were age >70 years (mean difference [MD] = 0.81; 95% confidence interval [CI] = 0.38-1.24), female gender (MD = 0.32; 95% CI = 0.29-0.48), body mass index >30 (MD = 0.09; 95% CI = 0.01-0.16), and non-White race (MD = 0.20; 95% CI = 0.10-0.29). Clinical factors associated with increased LOS were American Society of Anesthesiologists score 3-4 vs 1-2 (MD = 1.12; 95% CI = 0.58 to 1.66), Charlson Comorbidity Index > 0 vs 0 (MD = 0.77; 95% CI = 0.32 to 1.22), and preoperative hemoglobin < 130 g/L (MD = 0.66; 95% CI = 0.34 to 0.98).

CONCLUSION

This systematic review and meta-analysis showed that increased age, female gender, body mass index ≥ 30, non-White race, American Society of Anesthesiologists > 2, Charlson Comorbidity Index > 0, and preoperative hemoglobin < 130 g/L were predictors of increased LOS. Mean LOS has steadily decreased over the past decades with the implementation of perioperative "fast-track" programs. Future research should investigate the benefits of preoperative risk factor modification on LOS, in addition to novel surgical approaches, anesthetic adjuvants, and physiotherapy modifications.

LEVEL OF EVIDENCE

IV, systematic review, and meta-analysis of level III and IV evidence.

Preoperative Weight Loss for Morbidly Obese Patients Undergoing Total Knee Arthroplasty: Determining the Necessary Amount

BACKGROUND

Many surgeons require or request weight loss among morbidly obese patients (those with a body mass index [BMI] of ≥40 kg/m) before undergoing total knee arthroplasty. We sought to determine how much weight reduction was necessary to improve operative time, length of stay, discharge to a facility, and physical function improvement.

METHODS

Using a retrospective review of cohort data that were prospectively collected from 2011 to 2016 at 1 tertiary institution, we identified 203 patients who were morbidly obese at least 90 days before the surgical procedure and had their BMI measured again at the immediate preoperative visit. All heights and weights were clinically measured. We used logistic and linear regression models that adjusted for preoperative age, sex, year of the surgical procedure, bilateral status, physical function (Patient-Reported Outcomes Measurement Information System [PROMIS]-10 physical component score [PCS]), mental function (PROMIS-10 mental component score [MCS]), and the Charlson Comorbidity Index.

RESULTS

Of the 203 patients in the study, 41% lost at least 5 pounds (2.27 kg) before the surgical procedure, 29% lost at least 10 pounds (4.54 kg), and 14% lost at least 20 pounds (9.07 kg). Among morbidly obese patients, losing 20 pounds before a total knee arthroplasty was associated with lower adjusted odds of discharge to a facility (odds ratio [OR], 0.28 [95% confidence interval (CI), 0.09 to 0.94]; p = 0.039), lower odds of extended length of stay of at least 4 days (OR, 0.24 [95% CI, 0.07 to 0.88]; p = 0.031), and an absolute shorter length of stay (mean difference, -0.87 day [95% CI, -1.39 to -0.36 days]; p = 0.001). There were no differences in operative time or PCS improvement. Losing 5 or 10 pounds was not associated with differences in any outcome.

CONCLUSIONS

Losing at least 20 pounds before total knee arthroplasty was associated with shorter length of stay and lower odds of facility discharge for morbidly obese patients, even while most patients remained morbidly or severely obese. Although there were no differences in operative time or physical function improvement, this has considerable implications for patient burden and cost reduction. Patients and providers may want to focus on larger preoperative weight loss targets.

LEVEL OF EVIDENCE

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

The Main Predictors of Length of Stay After Total Knee Arthroplasty: Patient-Related or Procedure-Related Risk Factors

BACKGROUND

Often, differences in length of stay after total knee arthroplasty are solely attributed to patient factors. Therefore, our aim was to determine the influence of patient-related and procedure or structural-related risk factors as predictors of length of stay after total knee arthroplasty.

METHODS

A prospective cohort of 4,509 patients (54.6% of whom had Medicare for insurance) underwent primary total knee arthroplasty across 4 facilities in a single health-care system (from January 1, 2016, to September 30, 2017). Risk factors were categorized as patient-related risk factors (demographic characteristics, smoking status, Veterans RAND 12 Item Health Survey Mental Component Summary score [VR-12 MCS], Charlson Comorbidity Index, surgical indication, Knee injury and Osteoarthritis Outcome Score [KOOS], deformity, range of motion, and discharge location probability assessed by a nomogram predicting location after arthroplasty) or as procedure or structural-related risk factors (hospital site, surgeon, day of the week when the surgical procedure was performed, implant type, and surgical procedure start time). Multivariable cumulative link (proportional odds logistic regression) models were built to identify significant predictors from candidate risk factors for 1-day, 2-day, and ≥3-day length of stay. Performance was compared between a model containing patient-related risk factors only and a model with both patient-related and procedure or structural-related risk factors, utilizing the Akaike information criterion (AIC) and internally validated concordance probabilities (C-index) for discriminating a 1-day length of stay compared with >1-day length of stay.

RESULTS

Patient-related risk factors were significant predictors of length of stay (p < 0.05). A longer length of stay was predicted by older age, higher body mass index (BMI), higher Charlson Comorbidity Index, lower VR-12 MCS, and female sex. However, when the procedure or structural factors were added to the patients' risk factors, the AIC decreased by approximately 1,670 units. This indicates that procedure or structural-related risk factors provide clinically relevant improvement in explaining length of stay in addition to patient-related risk factors.

CONCLUSIONS

Despite patient-related factors such as age, sex, and comorbidities providing substantial predictive value for length of stay after total knee arthroplasty, the main driving predictors of single-day length of stay after total knee arthroplasty were procedure or structural-related factors, including hospital site and surgeon. Understanding the risk factors that affect outcomes after total knee arthroplasty provides the opportunity to influence and potentially modify them favorably to optimize care.

Comparison of Surgeon Performance of Rotator Cuff Repair: Risk Adjustment Toward a More Accurate Performance Measure

BACKGROUND

Movement toward a value-based health-care system necessitates the development of performance measures to compare physicians, hospitals, and health-care systems. Patient-reported outcomes (PROs) are a potential metric. However, valid use of PROs hinges on the ability to risk-adjust for baseline patient differences across a surgeon's panel of patients. The purpose of this study was to propose an approach for baseline risk adjustment and evaluate the importance of risk adjustment when comparing surgeons' performance of rotator cuff repair.

METHODS

Patients (n = 995) treated with arthroscopic rotator cuff repair by 34 surgeons from 2010 to 2017 were identified from a large sports medicine clinical data registry. A linear regression model was used to adjust for baseline PROs, patient demographics, and clinical characteristics to predict American Shoulder and Elbow Surgeons (ASES) change scores for each surgeon. A risk-adjusted performance measure was calculated as the difference between the average unadjusted ASES change scores and the risk-adjusted predicted ASES change scores across all patients treated by a surgeon.

RESULTS

The differences between unadjusted and risk-adjusted performance scores varied widely across surgeons (range, -13.8 to 10.3 ASES points). Use of the risk-adjusted performance scores resulted in a dramatic change in the relative ranking of surgeons, compared with the ranking based on the observed ASES change scores, with 31 of the 34 surgeons' rank changing following risk adjustment. On average, the observed ASES scores improved from 49.5 ± 17.5 at baseline to 78.0 ± 22.5 at 6 months across all surgeons. In the risk-adjustment model (R = 0.44), male sex, Workers' Compensation status, higher scores on the Veterans RAND 12-item Health Survey (VR-12), lower baseline ASES scores, fair and poor tendon quality, and night pain all had a significant effect on the predicted ASES change scores (p < 0.05).

CONCLUSIONS

Our results show wide variation of nearly 25 points in the risk-adjusted 6-month ASES performance difference from the highest to the lowest-performing surgeons. Additionally, 91% of surgeons' rank changed following risk adjustment. This suggests that performance measurement that does not account for baseline patient characteristics would likely result in incorrect conclusions about a surgeon's relative performance based on PROs.

LEVEL OF EVIDENCE

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

Patient Outcomes After Total Knee Arthroplasty in Patients Older Than 80 Years

BACKGROUND

Patients aged 80 and above who suffer from end-stage osteoarthritis may benefit from total knee arthroplasty (TKA), but at high potential risk. Additionally, there is controversy about whether functional improvement in patients above age 80 is similar to younger patients. We compared functional improvement, length of stay (LOS), and facility discharge rates after TKA between this cohort and patients less than 80 years of age.

METHODS

We completed a retrospective cohort study comparing TKA patients aged 80 and above with all patients younger than 80. We utilized data from a prospectively collected institutional repository of 2308 TKAs performed from April 2011 through July 2016 at an academic medical center in the United States. We performed multivariable logistic regression to determine the association between age group and clinically significant improvement in the Patient-Reported Outcome Measurement Information System (PROMIS)-10 physical component summary (PCS) score. Secondary outcomes included the magnitude of PCS change, LOS, and facility discharge.

RESULTS

There were 175 (7.6%) TKAs in patients older than 80 years compared with 2133 TKAs in patients younger than 80. Patients over 80 had similar adjusted odds of achieving clinically significant PCS improvement following TKA (P = .366), and there was no statistical difference in adjusted postoperative PCS improvement between the 2 age groups. Age 80 and above was associated with a longer adjusted LOS and demonstrated increased odds of facility discharge (odds ratio 4.11, P < .001) after TKA.

CONCLUSION

Following TKA, patients older than 80 years demonstrate similar adjusted functional improvement in comparison to younger patients. However, older patients did require substantially more resources as they remained in the hospital longer and were discharged to rehabilitation more often.

Do Age and Co-morbidy, Among other Factors, affect Length of Hospital Stay following Total Knee Arthroplasty

Introduction: The only treatment for grade IV knee osteoarthritis is total knee arthroplasty (TKA) irrespective of the age of the patient. Most of the grade IV OA patient are elderly and most likely to have some comorbidities. Age and comorbidities are the major reasons for patient's reluctance to undergo TKA. A clinical pathway with standard length of stay (LOS) could justify the patient's hesitation for TKA. The aim of this study was to determine the factors, including age and comorbidity, that affect the LOS of patients treated with TKA. Materials and Methods: This is a retrospective study of TKA patients in Surabaya Orthopedics and Traumatology Hospital from January 2011 to July 2017. Preoperative comorbidities were scored using Charlson Comorbidity Index (CCI) and physical status by ASA (American Society of Anesthesiologist), classification for age, sex, BMI, blood loss, operation time, method of anaesthesia and postoperative day of rehabilitation were recorded as factors potentially affecting LOS. The discharge criteria for the patients were ability to ambulate to the bathroom and clean operative wound with no complications. The data obtained were analysed statistically. Results: The average LOS was 5.58 days, ranging from three to eight days. There were no demographic factors that affected the patients' LOS. BMI, ASA, CCI, and blood loss did not significantly affect LOS. Operation time was between 90-140 minutes, and spinal anaesthesia showed significant longer LOS, but within the average. Conclusion: Age and comorbidity did not affect length of stay in TKA patients.