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      Timing of total joint arthroplasty post-COVID-19: an evaluation of the optimal window to minimize perioperative risks

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          Abstract

          Background

          Total hip arthroplasty (THA) and total knee arthroplasty (TKA) are commonly performed orthopedic procedures. This study aimed to evaluate the impact of COVID-19 status on postoperative complications and mortality in patients undergoing THA and TKA.

          Methods

          A total of 110,186 underwent either THA or TKA. Patients were grouped based on their COVID-19 status, gathered from the National COVID-19 Cohort Collaborative (N3C) in the 12 weeks preceding surgery and compared for various variables, including age, sex, BMI, and Charlson Comorbidity Index (CCI) scores. COVID-19 status was defined as a positive test result that was closest to the date of surgery regardless of testing positive previously. Postoperative complications such as venous thromboembolism (VTE), sepsis, surgical site infection, bleeding, acute kidney injury (AKI), 30-day, and 1-year all-cause mortality were examined. To compare the variables, an odds ratio with a 95% confidence interval was calculated with a significant level set at P < 0.05. Logistic regression using R programming was utilized for these calculations.

          Results

          Univariate analysis was performed and rates of VTE (1.02% vs. 3.35%), 30-day mortality (0.25% vs. less than 5%), and 1-year mortality (1.42% vs. 5.43%) were higher in the COVID-19-positive group for THA patients ( P < 0.001). For TKA patients, only 30-day mortality was significantly higher in the COVID-19-positive group ( P = 0.034). Multivariate logistic regression revealed that a positive COVID-19 diagnosis within two weeks of surgery and a CCI score > 3 were significant predictors of postoperative complications and mortality for both TKA and THA.

          Conclusions

          Patients with a positive COVID-19 diagnosis within 12 weeks of THA or TKA carried a significantly higher risk for postoperative complications and mortality. In addition, a CCI score > 3 is also a significant risk factor. These findings emphasize the importance of vigilant preoperative screening and risk stratification in the era of COVID-19.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s42836-024-00275-x.

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          Most cited references23

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          The hypercoagulable state in COVID-19: Incidence, pathophysiology, and management

          The 2019 coronavirus disease (COVID-19) presents with a large variety of clinical manifestations ranging from asymptomatic carrier state to severe respiratory distress, multiple organ dysfunction and death. While it was initially considered primarily a respiratory illness, rapidly accumulating data suggests that COVID-19 results in a unique, profoundly prothrombotic milieu leading to both arterial and venous thrombosis. Consistently, elevated D-dimer level has emerged as an independent risk factor for poor outcomes, including death. Several other laboratory markers and blood counts have also been associated with poor prognosis, possibly due to their connection to thrombosis. At present, the pathophysiology underlying the hypercoagulable state is poorly understood. However, a growing body of data suggests that the initial events occur in the lung. A severe inflammatory response, originating in the alveoli, triggers a dysfunctional cascade of inflammatory thrombosis in the pulmonary vasculature, leading to a state of local coagulopathy. This is followed, in patients with more severe disease, by a generalized hypercoagulable state that results in macro- and microvascular thrombosis. Of concern, is the observation that anticoagulation may be inadequate in many circumstances, highlighting the need for alternative or additional therapies. Numerous ongoing studies investigating the pathophysiology of the COVID-19 associated coagulopathy may provide mechanistic insights that can direct appropriate interventional strategies.
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            Long COVID: post-acute sequelae of COVID-19 with a cardiovascular focus

            Abstract Emerging as a new epidemic, long COVID or post-acute sequelae of coronavirus disease 2019 (COVID-19), a condition characterized by the persistence of COVID-19 symptoms beyond 3 months, is anticipated to substantially alter the lives of millions of people globally. Cardiopulmonary symptoms including chest pain, shortness of breath, fatigue, and autonomic manifestations such as postural orthostatic tachycardia are common and associated with significant disability, heightened anxiety, and public awareness. A range of cardiovascular (CV) abnormalities has been reported among patients beyond the acute phase and include myocardial inflammation, myocardial infarction, right ventricular dysfunction, and arrhythmias. Pathophysiological mechanisms for delayed complications are still poorly understood, with a dissociation seen between ongoing symptoms and objective measures of cardiopulmonary health. COVID-19 is anticipated to alter the long-term trajectory of many chronic cardiac diseases which are abundant in those at risk of severe disease. In this review, we discuss the definition of long COVID and its epidemiology, with an emphasis on cardiopulmonary symptoms. We further review the pathophysiological mechanisms underlying acute and chronic CV injury, the range of post-acute CV sequelae, and impact of COVID-19 on multiorgan health. We propose a possible model for referral of post-COVID-19 patients to cardiac services and discuss future directions including research priorities and clinical trials that are currently underway to evaluate the efficacy of treatment strategies for long COVID and associated CV sequelae.
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              The National COVID Cohort Collaborative (N3C): Rationale, Design, Infrastructure, and Deployment

              Abstract Objective COVID-19 poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level data from many centers. Methods The Clinical and Translational Science Award (CTSA) Program and scientific community created N3C to overcome technical, regulatory, policy, and governance barriers to sharing and harmonizing individual-level clinical data. We developed solutions to extract, aggregate, and harmonize data across organizations and data models, and created a secure data enclave to enable efficient, transparent, and reproducible collaborative analytics. Organized in inclusive workstreams, in two months we created: legal agreements and governance for organizations and researchers; data extraction scripts to identify and ingest positive, negative, and possible COVID-19 cases; a data quality assurance and harmonization pipeline to create a single harmonized dataset; population of the secure data enclave with data, machine learning, and statistical analytics tools; dissemination mechanisms; and a synthetic data pilot to democratize data access. Discussion The N3C has demonstrated that a multi-site collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multi-organizational clinical data for COVID-19 analytics. We expect this effort to save lives by enabling rapid collaboration among clinicians, researchers, and data scientists to identify treatments and specialized care and thereby reduce the immediate and long-term impacts of COVID-19. LAY SUMMARY COVID-19 poses societal challenges that require expeditious data and knowledge sharing. Though medical records are abundant, they are largely inaccessible to outside researchers. Statistical, machine learning, and causal research are most successful with large datasets beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level data from many clinical centers to reveal patterns in COVID-19 patients. To create N3C, the community had to overcome technical, regulatory, policy, and governance barriers to sharing patient-level clinical data. In less than 2 months, we developed solutions to acquire and harmonize data across organizations and created a secure data environment to enable transparent and reproducible collaborative research. We expect the N3C to help save lives by enabling collaboration among clinicians, researchers, and data scientists to identify treatments and specialized care needs and thereby reduce the immediate and long-term impacts of COVID-19.
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                Author and article information

                Contributors
                jprchan@hs.uci.edu
                Journal
                Arthroplasty
                Arthroplasty
                Arthroplasty
                BioMed Central (London )
                2524-7948
                4 October 2024
                4 October 2024
                2024
                : 6
                : 53
                Affiliations
                Department of Orthopaedic Surgery, University of California Irvine, ( https://ror.org/04gyf1771) Orange, CA 92868 USA
                Author information
                http://orcid.org/0000-0002-2164-4724
                Article
                275
                10.1186/s42836-024-00275-x
                11452997
                39367443
                2c4d5cad-97c7-4b85-a417-568c0f1a7cfd
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 16 May 2024
                : 31 July 2024
                Categories
                Research
                Custom metadata
                © Arthroplasty Society in Asia 2024

                total hip arthroplasty,total knee arthroplasty,covid-19,charlson comorbidity index,postoperative complications,venous thromboembolism

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