Predictors for readmission following primary total hip and total knee arthroplasty

Impact of time from discharge to readmission on outcomes: an observational study from the US National Readmission Database

BACKGROUND

The Hospital Readmission Reduction Programme (HRRP) was created to decrease the number of hospital readmissions for acute myocardial infarction (AMI), chronic obstructive pulmonary disease (COPD), heart failure (HF), pneumonia (PNA), coronary artery bypass graft (CABG), elective total hip arthroplasty (THA) and total knee arthroplasty.

OBJECTIVES

To analyse the impact of the HRRP on readmission rates from 2010 to 2019 and how time to readmission impacted outcomes.

DESIGN

Population-based retrospective study.

SETTING

All patients included in the US National Readmission database from 2010 to 2019.

PATIENTS

We recorded demographic and clinical variables.

MEASUREMENTS

Using linear regression models, we analysed the association between readmission status and timing with death and length of stay (LOS) outcomes. We transformed LOS and charges into log-LOS and log-charges to normalise the data.

RESULTS

There were 31 553 363 records included in the study. Of those, 4 593 228 (14.55%) were readmitted within 30 days. From 2010 to 2019, readmission rates for COPD (20.8%-19.8%), HF (24.9%-21.9%), PNA (16.4%-15.1%), AMI (15.6%-12.9%) and TKR (4.1%-3.4%) decreased whereas CABG (10.2%-10.6%) and THA (4.2%-5.8%) increased. Readmitted patients were at higher risk of mortality (6% vs 2.8%) and had higher LOS (3 (2-5) vs 4 (3-7)). Patients readmitted within 10 days had a mortality 6.4% higher than those readmitted in 11-20 days (5.4%) and 21-30 days (4.6%). Increased time from discharge to readmission was associated with a lower likelihood of mortality, like LOS.

CONCLUSION

Over the last 10 years, readmission rates decreased for most conditions included in the HRRP except CABG and THA. Patients readmitted shortly after discharge were at higher risk of death.

Generalizability of machine learning models predicting 30-day unplanned readmission after primary total knee arthroplasty using a nationally representative database

Unplanned readmission after primary total knee arthroplasty (TKA) costs an average of US $39,000 per episode and negatively impacts patient outcomes. Although predictive machine learning (ML) models show promise for risk stratification in specific populations, existing studies do not address model generalizability. This study aimed to establish the generalizability of previous institutionally developed ML models to predict 30-day readmission following primary TKA using a national database. Data from 424,354 patients from the ACS-NSQIP database was used to develop and validate four ML models to predict 30-day readmission risk after primary TKA. Individual model performance was assessed and compared based on discrimination, accuracy, calibration, and clinical utility. Length of stay (> 2.5 days), body mass index (BMI) (> 33.21 kg/m2), and operation time (> 93 min) were important determinants of 30-day readmission. All ML models demonstrated equally good accuracy, calibration, and discriminatory ability (Brier score, ANN = RF = HGB = NEPLR = 0.03; ANN, slope = 0.90, intercept =  - 0.11; RF, slope = 0.93, intercept =  - 0.12; HGB, slope = 0.90, intercept =  - 0.12; NEPLR, slope = 0.77, intercept = 0.01; AUCANN = AUCRF = AUCHGB = AUCNEPLR = 0.78). This study validates the generalizability of four previously developed ML algorithms in predicting readmission risk in patients undergoing TKA and offers surgeons an opportunity to reduce readmissions by optimizing discharge planning, BMI, and surgical efficiency.

Predicting 30-day unplanned hospital readmission after revision total knee arthroplasty: machine learning model analysis of a national patient cohort

Revision total knee arthroplasty (TKA) is associated with a higher risk of readmission than primary TKA. Identifying individual patients predisposed to readmission can facilitate proactive optimization and increase care efficiency. This study developed machine learning (ML) models to predict unplanned readmission following revision TKA using a national-scale patient dataset. A total of 17,443 revision TKA cases (2013-2020) were acquired from the ACS NSQIP database. Four ML models (artificial neural networks, random forest, histogram-based gradient boosting, and k-nearest neighbor) were developed on relevant patient variables to predict readmission following revision TKA. The length of stay, operation time, body mass index (BMI), and laboratory test results were the strongest predictors of readmission. Histogram-based gradient boosting was the best performer in distinguishing readmission (AUC: 0.95) and estimating the readmission probability for individual patients (calibration slope: 1.13; calibration intercept: -0.00; Brier score: 0.064). All models produced higher net benefit than the default strategies of treating all or no patients, supporting the clinical utility of the models. ML demonstrated excellent performance for the prediction of readmission following revision TKA. Optimization of important predictors highlighted by our model may decrease preventable hospital readmission following surgery, thereby leading to reduced financial burden and improved patient satisfaction.

Factors Correlated with the Quality of Life after Total Knee Arthroplasties: A Literature Review

Introduction

Total Knee Arthroplasty (TKA) has been widely reported to improve outcomes and quality of life (QoL) in patients with knee osteoarthritis (KOA), but there are still 15 - 20% of patients still experience pain, physical limitations, and other complications after TKA. Therefore, it is necessary to identify various factors that correlate with QoL from current evidence. The objective is to review the literature on factors that correlate with QoL in patients who underwent TKA.

Materials and methods

A literature search was conducted on five databases, i.e. ProQuest, CINAHL, Medline, Embase, and Scopus, using the following keywords: total knee arthroplasty (TKA), post-operative, quality of life (QoL), and outcome. There were no restrictions on the research design.

Results

This review found 14 articles (7 prospective studies and 7 retrospective studies) involving 15,972 patients who underwent TKA, with an age range of 32 - 94 years. All articles reported improvement in QoL after TKA. The review revealed 30 factors, of which 15 factors were significantly correlated with QoL after TKA. The factors were grouped into four types: demographic, socioeconomic, clinical, and psychosocial factors.

Conclusion

Information regarding factors that correlate with QoL after TKA can be used for directing treatment and discharge planning according to the patient's factors.

Modified Frailty Index as a Predictor of Adverse Outcomes in Elective Primary Hip and Knee Replacement Surgery Patients at a Tertiary Care Hospital in Pakistan: A Cross-Sectional Study

Objective The objective was to evaluate the modified frailty index as a predictor of early (within 30 days) postoperative complications in total joint arthroplasty patients, in a low middle-income country. Material and methods A cross-sectional study was carried out which included patients with ages ranging from 23 to 86 years, who underwent elective primary Total Hip or Knee Arthroplasties (TKA or THA) between December 2021 and February 2023. Modified frailty index (mFI-5) was calculated and 30-day morbidity and mortality were recorded. Post-operative complications were categorized as either surgical or medical and recorded. Results A total of 175 patients were included, amongst whom the majority were females (68.6%, n=120) and the mean age was 60.5 ± 13.2 years. 85 patients (48.6%) had a mFI-5 score of one while 48 patients (27.4%) had a score of two. Superficial surgical site infection was the most common complication overall in 6 patients (3.4%); however, no case of prosthetic joint infection was noted. Deep vein thrombosis (DVT) was the most common medical complication (1.7%, n=3). 5 patients (2.9%) required re-admission and two mortalities were recorded within the 30-day interval. A significant association was noted between post-operative surgical complications and mFI-5 score (p-value = < 0.001), with the risk of complications increasing with a higher mFI-5 score. Smoking was noted to be a risk factor for post-operative medical complications as well as 30-day mortality. Conclusion The current study shows that the mFI-5 index can effectively be used as a predictor of postoperative complications in the South Asian region such as Pakistan. This should be calculated routinely and can be used as a tool for pre-operative assessment and counseling.

Morbidly Obese Patients Undergoing Unicompartmental Knee Arthroplasty Compared to Total Knee Arthroplasty: A Retrospective Case-Controlled Analysis

BACKGROUND

In this study, we assess the effects that morbid obesity (body mass index (BMI) ≥ 40) has on: (1) Ninety-day medical complications and readmission rates; (2) costs of care and lengths of stay (LOS); and (3) 2-year implant complications in patients undergoing unicompartmental knee arthroplasty (UKA) versus total knee arthroplasty (TKA).

METHODS

A retrospective query of TKA and UKA patients were identified using a national database. Morbidly obese UKA patients were matched 1:5 to morbidly obese TKA patients by demographic and comorbidity profiles. Subgroup analyses were conducted using the same process between morbidly obese UKA patients and BMI <40 TKA patients, as well as to BMI <40 UKA patients.

RESULTS

Morbidly obese patients who underwent UKA had significantly fewer medical complications, readmissions, and periprosthetic joint infections than TKA patients; however, UKA patients had greater odds of mechanical loosening (ML). The TKA patients had significantly longer LOS (3.0 versus 2.4 days, P < .001), as well as significantly greater costs of care than UKA patients ($12,869 versus $7,105). Morbidly obese UKA patients had similar rates of medical complications, and significantly lower readmissions, decreased LOS, and decreased costs when compared to TKA patients who had a BMI <40.

CONCLUSION

In patients who have morbid obesity, complications were decreased in UKA compared to TKA. Moreover, morbidly obese UKA patients had lower medical utilizations and similar complication rates when compared to TKA patients with the recommended cutoff of BMI <40. However, UKA patients had greater rates of ML than TKA patients. A UKA may be an acceptable treatment option for unicompartmental osteoarthritis in morbidly obese patients.

Exploring Overnutrition, Overweight, and Obesity in the Hospital Setting-A Point Prevalence Study

Malnutrition is an international healthcare concern associated with poor patient outcomes, increased length of stay, and healthcare costs. Although malnutrition includes both under and overnutrition, there is a large body of evidence that describes the impacts of undernutrition with limited data on overnutrition in hospitalized patients. Obesity itself is a modifiable risk factor associated with hospital-associated complications. However, there is limited reporting of the prevalence of obesity in hospitals. This one-day cross-sectional study (n = 513) captures the prevalence of both under and overnutrition in a hospitalized population and explores dietetic care provided compared to the Nutrition Care Process Model for hospitalized patients who have obesity. The main findings were: (1) the largest proportion of patients were in the overweight and obese classifications (57.3%, n = 294/513); 5.3% of these patients had severe obesity (class III); (2) patients who were overweight and obese had lower malnutrition risk profiles as well as the prevalence of malnutrition; (3) 24.1% of patients who had obesity (n = 34/141) were receiving dietetic intervention; (4) 70.6% (n = 24/34) did not have a nutrition diagnosis that followed the Nutrition Care Process Model. Study results provide valuable clinical insight into the prevalence of overnutrition and opportunities to improve nutrition care for this vulnerable patient group.

Learning Curve for Short-Stem Total HIP Arthroplasty through an Anterolateral Approach

Background and Objectives: Short-stem total hip arthroplasty has become increasingly popular in recent years. While many studies have shown excellent clinical and radiological results, very little is known about the learning curve for short-stem total hip arthroplasty through an anterolateral approach. Therefore, the aim of this study was to determine the learning curve for short-stem total hip arthroplasty among five residents in training. Materials and Methods: We performed retrospective data analysis of the first 30 cases of five randomly selected residents (n = 150 cases) with no experience before the index surgery. All patients were comparable, and several surgical parameters and radiological outcomes were analyzed. Results: The only surgical parameter with a significant improvement was the surgical time (p = 0.025). The changes in other surgical parameters and radiological outcomes showed no significant changes; only trends can be derived. As a result, the correlation between surgical time, blood loss, length of stay, and incision/suture time can also be seen. Only two of the five residents showed significant improvements in all examined surgical parameters. Conclusions: There are individual differences among the first 30 cases of the five residents. Some improved their surgical skills faster than others. It could be assumed that they assimilated their surgical skills after more surgeries. A further study with more than 30 cases of the five surgeons could provide more information on that assumption.

Emergency Department Visits Within 90 Days of Total Ankle Replacement

Background

Total ankle replacement (TAR) utilization in the United States has steeply increased in recent decades. Emergency department (ED) visits following TAR impacts patient satisfaction and health care costs and warrant exploration.

Methods

This retrospective cohort study utilized the 2010 to 2019 M91Ortho PearlDiver data set to identify TAR patients with at least 90 days of follow-up. PearlDiver contains billing claims data across all sites of care throughout the United States for all indications for care. Patient factors extracted included age, sex, Elixhauser Comorbidity Index (ECI), region of the country in which surgery was performed, insurance plan, and postoperative hospital length of stay. Ninety-day postoperative ED visit incidence, timing, frequency, and primary diagnoses were identified and compared to 1-year postoperative ED visit baseline data. Univariate and multivariate logistic regression analyses were used to determine risk factors for ED visits.

Results

Of 5930 TAR patients identified, ED visits within 90 days were noted for 497 (8.4%) patients. Of all ED visits, 32.0% occurred within 2 weeks following surgery. Multivariate analysis revealed several predictors of ED utilization: younger age (odds ratio [OR] 1.35 per decade decrease), female sex (OR 1.20), higher ECI (OR 1.32 per 2-point increase), TAR performed in the western US (OR 1.34), and Medicaid coverage (OR 2.70; 1.71-4.22 relative to Medicare) (P < .05 each). Surgical site issues comprised 78.0% of ED visits, with surgical site pain (57.0%) as the most common problem.

Conclusion

Of 5930 TAR patients, 8.4% returned to the ED within 90 days of surgery, with predisposing demographic factors identified. The highest incidence of ED visits was in the first 2 postoperative weeks, and surgical site pain was the most common reason. Pain management pathways following TAR should be able to be adjusted to minimize the occurrence of postoperative ED visits, thereby improving patient experiences and decreasing health care utilization/costs.

Level of Evidence

Level III, retrospective cohort study.

Which Factors Predict 30-Day Readmission After Total Hip and Knee Replacement Surgery?

Background

The Centers for Medicare and Medicaid Services enacted the Hospital Readmissions Reduction Program to impose penalties for diagnoses with high readmission rates. Despite several elective orthopedic procedures being included in this program, readmission rates have not declined, and associated costs have reached critical levels for total knee and total hip arthroplasty. Readmissions drastically impact patient outcomes. There are many known contributors to patient readmission rates, including infection, pain, and hematomas. However, evidence is inconclusive regarding other aspects, such as demographics, insurance, and discharge disposition. The purpose of this manuscript is to 1) measure hospital readmission rates for total knee and total hip arthroplasty, 2) evaluate the causes of readmissions, and 3) provide a predictive profile of risk factors associated with hospital readmissions.

Methods

Patients who underwent total knee or total hip arthroplasty were identified through a retrospective database review. An electronic chart review extracted data concerning patient demographics, comorbidities, surgical information, 30-day outcomes, and reasons for 30-day readmissions. Continuous and categorical variables were assessed with the Wilcoxon rank-sum test and the Chi-square test, respectively.

Results

A total of 6,065 patients were included, with 269 (4.4%) having at least one surgery-related 30-day readmission. No differences in readmission were noted with age, sex, or ethnicity; however, differences were found in weight and body mass index. Statistically significant comorbidities were heart failure, chronic obstructive pulmonary disease, dialysis, and alcohol use or abuse.

Conclusion

Our research indicated that surgery type, length of stay, and heart failure most significantly impacted 30-day readmission rates. By assessing readmission rates, we can take steps to optimize care for non-elective surgeries that will improve patient outcomes and cost-effectiveness.

Rates of readmission and reoperation following pelvic osteotomy in adolescent patients: a database study evaluating the pediatric health information system

Rates and reasons for readmission and reoperation following adolescent pelvic osteotomy are not well-defined. This study aimed to (1) determine 30-day and 90-day readmission rates and the 2-year reoperation rate after pelvic osteotomy in adolescents and (2) identify reasons for readmission and reoperation. The Pediatric Health Information System database was queried between 10 January 2015 and 1 January 2020 for patients meeting selected International Classification of Diseases (ICD-10) procedure and diagnosis codes relating to pelvic osteotomies. Readmission rates were calculated within 30 and 90 days from index osteotomy. The ipsilateral reoperation rate was calculated within 2 years from index osteotomy. Reasons for these outcomes were identified. Univariate and multivariate analyses were utilized to identify readmission risks. Of 1475 patients, 5.4% and 9.2% were readmitted within 30 and 90 days, respectively. Reasons for readmission were consistent across both time points and included infection, hip-related orthopedic conditions and neurologic conditions. Younger age (OR 0.83, 95% CI: 0.76, 0.89; P < 0.0001) and male sex (OR 1.77, 95% CI: 1.23–2.54; P = 0.002) were predictive of readmission within 90 days. The 2-year reoperation rate was 32.1%, of which 79.8% underwent reoperation for hardware removal, 17.7% for revision and 1.3% for hip replacement. 30-day readmission, 90-day readmission and 2-year reoperation rates after adolescent pelvic osteotomy were 5.4%, 9.2% and 32.1%, respectively. Younger age and male sex were predictive of 90-day readmission. Most ipsilateral reoperations were for hardware removal. Understanding readmission and reoperation risks following pelvic osteotomy can benefit patient counseling and improve expectations of post-surgical outcomes.

Level of Evidence:

IV, case series.

Modifiable Individual Risks of Perioperative Blood Transfusions and Acute Postoperative Complications in Total Hip and Knee Arthroplasty

BACKGROUND

The primary aim of this study was to identify modifiable patient-related predictors of blood transfusions and perioperative complications in total hip and knee arthroplasty. Individual predictor-adjusted risks can be used to define preoperative treatment thresholds.

METHODS

We performed this retrospective monocentric study in orthopaedic patients who underwent primary total knee or hip arthroplasty. Multivariate logistic regression models were used to assess the predictive value of patient-related characteristics. Predictor-adjusted individual risks of blood transfusions and the occurrence of any perioperative adverse event were calculated for potentially modifiable risk factors.

RESULTS

3754 patients were included in this study. The overall blood transfusion and complication rates were 4.8% and 6.4%, respectively. Haemoglobin concentration (Hb, p < 0.001), low body mass index (BMI, p < 0.001) and estimated glomerular filtration rate (eGFR, p = 0.004) were the strongest potentially modifiable predictors of a blood transfusion. EGFR (p = 0.001) was the strongest potentially modifiable predictor of a complication. Predictor-adjusted risks of blood transfusions and acute postoperative complications were calculated for Hb and eGFR. Hb = 12.5 g/dL, BMI = 17.6 kg/m², and eGFR = 54 min/mL were associated, respectively, with a 10% risk of a blood transfusion, eGFR = 59 mL/min was associated with a 10% risk of a complication.

CONCLUSION

The individual risks for blood transfusions and acute postoperative complications are strongly increased in patients with a low preoperative Hb, low BMI or low eGFR. We recommend aiming at a preoperative Hb ≥ 13g/dL, an eGFR ≥ 60 mL/min and to avoid a low BMI. Future studies must show if a preoperative increase of eGFR and BMI is feasible and truly beneficial.

The Effects of Dexamethasone in Diabetic Patients Undergoing Primary Total Joint Arthroplasty

Dexamethasone reduces postoperative pain and nausea, with no evidence of increased rate of infection in total joint arthroplasty. However, the effects of dexamethasone on diabetic patients undergoing total joint arthroplasty remain relatively unexplored. The purpose of this study was to examine the effects of dexamethasone on postoperative blood glucose levels, prosthetic joint infections (PJIs), and 90-day hospital returns in diabetic patients following total joint arthroplasty. Retrospective analysis was performed on 228 adult patients with a diagnosis of diabetes who underwent primary total joint arthroplasty. Patients were stratified by intraoperative dexamethasone administration. In total, 173 (75.9%) patients received intraoperative dexamethasone, with no differences in demographic variables compared with patients who did not receive dexamethasone. There was no significant difference in PJIs or 90-day hospital returns. Patients who received dexamethasone had significantly increased blood glucose concentration on Postoperative Day 1 and were significantly more likely to have blood glucose levels exceeding 180 g/dl. Although postoperative blood glucose levels were significantly increased, it is unclear what effects, if any, transient hyperglycemia may have on outcomes. The outcomes of this study support perioperative administration of dexamethasone in diabetic patients.