What Is the 30-Day Mortality Burden After Elective Total Hip Arthroplasty? An Analysis of 194,062 Patients

Outpatient Total Hip Arthroplasty Volume up Nearly 8-Fold After Regulatory Changes With Expanding Demographics and Unchanging Outcomes: A 10-Year Analysis

BACKGROUND

With the removal of total hip arthroplasty (THA) from the inpatient-only (IPO) lists, the orthopedic landscape across the United States has changed rapidly. Thus, this study aimed to: 1) characterize the change in THA volume for outpatient and inpatient surgeries; 2) elucidate demographical differences before and after removal from the IPO list; and 3) analyze 30-day complications, readmissions, and reoperations.

METHODS

The National Surgical Quality Improvement Program database was queried for primary THAs between January 2010 and December 2021. The primary outcome was the annual volume of outpatient and inpatient THAs. Secondary outcomes involved 30-day complications, readmissions, and reoperations. The variables between cohorts were analyzed using goodness-of-fit Chi-square tests with summary statistics.

RESULTS

Of the 332,423 THAs between 2010 and 2021, 88% were inpatient THAs (n = 292,974) and 12% were outpatient THAs (n = 39,449). From 2019 to 2021, the volume of inpatient THA decreased by 55% (42,779 to 19,075), while outpatient THA increased by 751% (2,518 to 21,424). Patients who had a THA after 2019 were older (P < .001), more commonly women (P < .001), white (P < .001), and more likely American Society of Anesthesiologists Class III (P < .001). The outpatient cohort had fewer 30-day complications, readmissions, and reoperations. The length of stay for both cohorts decreased until 2019, before increasing in 2020 and 2021 for inpatient THAs, while home discharge and operative time increased for both.

CONCLUSIONS

The volume of outpatient THA increased almost eightfold after its removal from the IPO lists in 2020. Despite expanding eligibility with older patients and more comorbidities, 30-day complications, readmissions, and reoperations remain low. These findings support the safe transition to outpatient THA with appropriate patient selection and optimization.

Prediction of 30-Day Mortality Following Revision Total Hip and Knee Arthroplasty: Machine Learning Algorithms Outperform CARDE-B, 5-Item, and 6-Item Modified Frailty Index Risk Scores

BACKGROUND

Although risk calculators are used to prognosticate postoperative outcomes following revision total hip and knee arthroplasty (total joint arthroplasty [TJA]), machine learning (ML) based predictive tools have emerged as a promising alternative for improved risk stratification. This study aimed to compare the predictive ability of ML models for 30-day mortality following revision TJA to that of traditional risk-assessment indices such as the CARDE-B score (congestive heart failure, albumin (< 3.5 mg/dL), renal failure on dialysis, dependence for daily living, elderly (> 65 years of age), and body mass index (BMI) of < 25 kg/m2), 5-item modified frailty index (5MFI), and 6MFI.

METHODS

Adult patients undergoing revision TJA between 2013 and 2020 were selected from the American College of Surgeons National Surgical Quality Improvement Program database and randomly split 80:20 to compose the training and validation cohorts. There were 3 ML models - extreme gradient boosting, random forest, and elastic-net penalized logistic regression (NEPLR) - that were developed and evaluated using discrimination, calibration metrics, and accuracy. The discrimination of CARDE-B, 5MFI, and 6MFI scores was assessed individually and compared to that of ML models.

RESULTS

All models were equally accurate (Brier score = 0.005) and demonstrated outstanding discrimination with similar areas under the receiver operating characteristic curve (AUCs, extreme gradient boosting = 0.94, random forest = NEPLR = 0.93). The NEPLR was the best-calibrated model overall (slope = 0.54, intercept = -0.004). The CARDE-B had the highest discrimination among the scores (AUC = 0.89), followed by 6MFI (AUC = 0.80), and 5MFI (AUC = 0.68). Albumin < 3.5 mg/dL and BMI (< 30.15) were the most important predictors of 30-day mortality following revision TJA.

CONCLUSIONS

The ML models outperform traditional risk-assessment indices in predicting postoperative 30-day mortality after revision TJA. Our findings highlight the utility of ML for risk stratification in a clinical setting. The identification of hypoalbuminemia and BMI as prognostic markers may allow patient-specific perioperative optimization strategies to improve outcomes following revision TJA.

30-day to 10-year mortality rates following total hip arthroplasty: a meta-analysis of the last decade (2011-2021)

BACKGROUND

Mortality after total hip arthroplasty (THA) is a rare but devastating complication. This meta-analysis aimed to: (1) determine the mortality rates at 30 days, 90 days, 1 year, 5 years and 10 years after THA; (2) identify risk factors and causes of mortality after THA.

METHODS

Pubmed, MEDLINE, Cochrane, EBSCO Host, and Google Scholar databases were queried for studies reporting mortality rates after primary elective, unilateral THA. Inverse-proportion models were constructed to quantify the incidence of all-cause mortality at 30 days, 90 days, 1 year, 5 years and 10 years after THA. Random-effects multiple regression was performed to investigate the potential effect modifiers of age (at time of THA), body mass index, and gender.

RESULTS

A total of 53 studies (3,297,363 patients) were included. The overall mortality rate was 3.9%. The 30-day mortality was 0.49% (95% CI; 0.23-0.84). Mortality at 90 days was 0.47% (95% CI, 0.38-0.57). Mortality increased exponentially between 90 days and 5 years, with a 1-year mortality rate of 1.90% (95% CI, 1.22-2.73) and a 5-year mortality rate of 9.85% (95% CI, 5.53-15.22). At 10-year follow-up, the mortality rate was 16.43% (95% CI, 1.17-22.48). Increasing comorbidity indices, socioeconomic disadvantage, age, anaemia, and smoking were found to be risk factors for mortality. The most commonly reported causes of death were ischaemic heart disease, malignancy, and pulmonary disease.

CONCLUSIONS

All-cause mortality remains low after contemporary THA. However, 1 out of 10 patients and 1 out of 6 patients were deceased after 5 years and 10 years of THA, respectively. As expected, age, but not BMI or gender, was significantly associated with mortality.

The association between perioperative blood transfusions and venous thromboembolism risk following surgical management of hip fractures

Introduction

Despite high rates of transfusion reported among hip fracture patients in the perioperative period, the relationship between perioperative transfusions and VTE has not been thoroughly explored. Therefore, we used a national database to evaluate how perioperative transfusions among patients undergoing surgical management of hip fractures impacted 1) deep vein thrombosis (DVT) and 2) pulmonary embolism (PE) risk.

Methods

The Targeted Hip Fracture Database of the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) was queried for patients undergoing surgical management of hip fractures from 2016 to 2019. A multivariate logistic regression was conducted using various patient-specific variables to identify risk factors for DVT and PE. A nearest-neighbor propensity score matched (PSM) comparison between patients receiving and not receiving perioperative blood transfusions (1:1) was additionally conducted.

Results

Prior to our PSM, preoperative transfusions were not associated with DVT incidence (OR: 1.48, 95% CI: 0.80-2.50; p = 0.2). However, intra-operative/post-operative transfusions (OR: 1.26, 95% CI: 1.02-1.56; p = 0.00.30) as well as the receipt of both transfusion types (OR: 1.81, 95% CI: 1.10-2.81; p = 0.012) were associated with an increased risk of DVT. The latter of these findings remained significant following PSM (OR: 1.73, 95% CI: 1.04-2.73; p = 0.025). No relationship was demonstrated between PE risk and perioperative transfusion receipt.

Conclusion

Our findings emphasize the importance of perioperative blood management strategies among patients undergoing surgical repair of hip fracture. Specifically, orthopaedic surgeons should aim to optimize hip fracture patients prior to surgical intervention as well as intra-operatively to reduce transfusion incidence.