Publications by authors named "Mohammadamin Rezazadehsaatlou"
Article Synopsis
- Primary hip and knee total joint arthroplasties (TJAs) are among the most common orthopedic surgeries in the U.S., with demand expected to reach two million annually by 2040; however, Medicare reimbursements for surgeons have been decreasing.
- A study analyzed Medicare claims data from 2017 to 2022, revealing a 2.9% rise in TJA procedures but a 4.2% drop in average reimbursement, which, when adjusted for inflation, shows a significant decrease of 19.6%.
- The findings emphasize the need for policy reforms to support fair and sustainable reimbursement for surgeons involved in primary TJA as trends differ by procedure type and region.
Background: Recent changes in Medicare reimbursement policies have facilitated the shift of primary total joint arthroplasty (TJA) volume to ambulatory surgical centers (ASC). The ASCs potentially provide a more cost-effective alternative to a hospital-setting TJA. This study investigated Medicare primary TJA utilization and reimbursement trends at ASCs compared to inpatient and outpatient settings between 2019 and 2022.
View Article and Find Full Text PDFBackground: The increasing incidence of primary total hip (THA) and knee (TKA) arthroplasty has been accompanied by a subsequent rise in revision surgeries. Revision total joint arthroplasty (TJA) is associated with major litigation risk, primarily due to procedural and postsurgical errors. However, the understanding of the causes and outcomes of revision TJA malpractice cases remains unstudied.
View Article and Find Full Text PDFArticle Synopsis
- Revision hip and knee surgeries cost more and are harder on doctors and hospitals than regular surgeries, but payments for these revision surgeries have been going down.
- The study looked at how much hospitals and surgeons were paid for these surgeries from 2017 to 2022 using Medicare data.
- Over that time, the number of revision surgeries went down by about 19%, while hospitals earned about the same but surgeons earned less, showing a need for better payments for surgeons.
Background: As the number of revision total knee arthroplasty (TKA) continues to rise, close attention has been paid to factors influencing postoperative length of stay (LOS). The aim of this study is to develop generalizable machine learning (ML) algorithms to predict extended LOS following revision TKA using data from a national database.
Methods: 23,656 patients undergoing revision TKA between 2013 and 2020 were identified using the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database.
Introduction: Prolonged length of stay (LOS) following revision total hip arthroplasty (THA) can lead to increased healthcare costs, higher rates of readmission, and lower patient satisfaction. In this study, we investigated the predictive power of machine learning (ML) models for prolonged LOS after revision THA using patient data from a national-scale patient repository.
Materials And Methods: We identified 11,737 revision THA cases from the American College of Surgeons National Surgical Quality Improvement Program database from 2013 to 2020.
Background: Total joint arthroplasty (TJA) is the most common procedure associated with malpractice claims within orthopaedic surgery. Although prior research has assessed prevalent causes and outcomes of TJA-related lawsuits before 2018, the dynamic healthcare environment demands regular re-evaluations. This study aimed to provide an updated analysis of the predominant causes and outcomes of TJA-related malpractice lawsuits and analyze the outcomes of subsequent appeals following initial jury verdicts.
View Article and Find Full Text PDFArticle Synopsis
- Revision hip and knee total joint arthroplasty (TJA) often leads to complications like surgical site infections and readmissions, impacting recovery and patient satisfaction.
- The study assessed 1,047 patients to explore the relationship between socioeconomic factors (measured by area deprivation index or ADI) and these complications within 90 days post-surgery.
- Results showed that while depression and high ASA scores were linked to higher complication rates, ADI did not significantly predict postoperative issues, suggesting that more comprehensive indicators of health determinants are needed.
Generalizability of machine learning models predicting 30-day unplanned readmission after primary total knee arthroplasty using a nationally representative database.
Med Biol Eng Comput
August 2024
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.
View Article and Find Full Text PDFBackground: Chronic renal failure is a progressive and irreversible loss of kidney function, and the hemodialysis (HD) is one of the most common modalities in this regard. Oxidative stresses [like interleukin-8 (IL-8) and tumor necrosis factor-alpha (TNF-α)] and inflammation are the main risk factors associated with cardiovascular diseases and other complications in many organs in hemodialysis patients; meanwhile, antioxidants like alpha lipoic acid (ALA) may reduce the oxidative stress markers and the levels of inflammatory cytokines, so can improve of the patient's quality of life.
Methods: In this randomized clinical trial study, 60 HD patients were randomly categorized in two case and control groups.