Background: Despite the extensive literature on racial disparities in care and outcomes after total knee arthroplasty (TKA), data on manipulation under anesthesia (MUA) is lacking. We aimed to determine (1) the relationship between race and rate of (and time to) MUA after TKA, and (2) annual trends in racial differences in MUA from 2013 to 2018.
Methods: This retrospective cohort study (using 2013-2018 Medicare Limited Data Set claims data) included 836,054 primary TKA patients. The primary outcome was MUA <1 year after TKA; time from TKA to MUA in days was also recorded. A mixed-effects multivariable model measured the association between race (White, Black, Other) and odds of MUA. Odds ratios (OR) and 95% confidence intervals (CI) were reported. A Cochran Armitage Trend test was conducted to assess MUA trends over time, stratified by race.
Results: MUA after TKA occurred in 1.7%, 3.2% and 2.1% of White, Black, and Other race categories, respectively (SMD = 0.07). After adjustment for covariates, (Black vs White) patients had increased odds of requiring an MUA after TKA: odds ratio (OR) 1.97, 95% confidence intervals (CI) 1.86-2.10, P < .0001. Moreover, White (compared to Black) patients had significantly shorter time to MUA after TKA: 60 days (interquartile range [IQR] 46-88) versus 64 days (interquartile range [IQR] 47-96); P < .0001. These disparities persisted from 2013 through 2018.
Conclusion: Continued racial differences exist for rates and timing of MUA following TKA signifying the continued need for efforts aimed toward understanding and eliminating inequalities that exist in total joint arthroplasty (TJA) care.
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http://dx.doi.org/10.1016/j.arth.2022.03.088 | DOI Listing |
Lupus Sci Med
January 2025
Division of Rheumatology, Emory University, Atlanta, Georgia, USA.
Objective: Black people in the USA have a higher incidence and severity of SLE and worse outcomes, yet they are significantly under-represented in SLE clinical trials. We assessed racial differences in clinical trial perceptions among a large cohort of predominantly Black people with SLE.
Methods: Georgians Organised Against Lupus (GOAL) is a population-based, prospective cohort of people with a validated diagnosis of SLE living in Atlanta.
HPB (Oxford)
December 2024
Department of Surgery, Division of Surgical Oncology, The Ohio State University, Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA.
Background: Genomic variations related to racial and sex differences among patients with hepatocellular carcinoma (HCC) have not been investigated. We sought to characterize the mutational landscape of patients with HCC relative to race and sex.
Methods: The American Association for Cancer Research GENIE project (v16.
Int J Urol
January 2025
Department of Urology, Dokkyo Medical University Saitama Medical Center, Saitama, Japan.
Background: C-reactive protein (CRP) is a prognostic biomarker for clear cell renal cell carcinoma (ccRCC). However, there may be potential racial heterogeneity in distribution and prognostic impact of CRP level. We investigated potential racial differences in distribution and prognostic impact of preoperative CRP among Asian (AS), African American (AA), and Caucasian (CAUC) patients with non-metastatic ccRCC (nmccRCC).
View Article and Find Full Text PDFImplement Sci Commun
January 2025
Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, IL, Chicago, USA.
Background: Studies have demonstrated that standardizing labor induction (IOL), often with the use of protocols, may reduce racial inequities in obstetrics. IOL protocols are complex, multi-component interventions. To target identified implementation barriers, audit and feedback (A&F) was selected as an implementation strategy.
View Article and Find Full Text PDFJMIR Ment Health
December 2024
Department of Psychiatry, Northwell Health, Zucker Hillside Hospital, Glen Oaks, NY, United States.
Background: Digital health technologies are increasingly being integrated into mental health care. However, the adoption of these technologies can be influenced by patients' digital literacy and attitudes, which may vary based on sociodemographic factors. This variability necessitates a better understanding of patient digital literacy and attitudes to prevent a digital divide, which can worsen existing health care disparities.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!