Enhancing Coagulation Management after Cardiac Valve Replacement and Plastic: The Benefits of Home Monitoring

Enhancing Coagulation Management after Cardiac Valve Replacement and Plastic: The Benefits of Home Monitoring | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Enhancing Coagulation Management after Cardiac Valve Replacement and Plastic: The Benefits of Home Monitoring ChenXi Ying, LingShan Liu, BoHao Dai, YuFei Fu, Xin Chen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4113572/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective: The research aims to analyze the impact of home monitoring on INR control and complications in patients undergoing valve replacement and plastic surgery. It is also the first to assess and predict associated risk factors by using a nomogram graph. Study Design: A retrospective descriptive study Place and Duration of Study: Department of Cardiovascular Surgery, The First Affiliated Hospital Zhejiang University of Medicine, from January 2021 to January 2023 Methodology: Conducted at the First Affiliated Hospital of Zhejiang University, the retrospective study involved 505 patients initially, with 406 completing the follow-up. Data collection included patient characteristic, medical history, valve replacement details, and INR values. Results: The study found that self-management of INR testing significantly improved the time in therapeutic range (TTR), reduced INR variance, and decreased complications. Predictive factors for postoperative coagulation control included gender, history of atrial fibrillation, preoperative medication history, valve replacement type, and education level. Conclusion: With home monitoring of INR, patients can take more control of their coagulation management and decrease the frequency of hospital visits. Treatment compliance and outcomes are enhanced when this method is combined with patient education level. The use of a nomogram helps identify patients with stable coagulation function for clinical trials and allows for early intervention in high-risk patients. INR control time in therapeutic range (TTR) Home monitoring Coagulation management nomogram graph Figures Figure 1 Figure 2 Introduction Warfarin, a member of the coumarin family, is a vitamin K antagonist (VKA) that works by inhibiting the vitamin K-dependent (VKD) process. This inhibition hinders the synthesis of certain clotting factors necessary for normal coagulation in the liver, resulting in anticoagulant effects. It is commonly prescribed for stroke prevention in patients with atrial fibrillation and cardiac valve diseases, as well as for preventing venous thromboembolism(VTE) and other thromboembolic complications 1 , 2 . Patients with cardiac valve diseases receive oral anticoagulant therapy using vitamin K antagonists. In clinical practice, it is important to adjust the international normalized ratio (INR) range for patients based on their individual risk factors and the thrombogenic risk. This is necessary to ensure that patients receive the appropriate level of anticoagulation to prevent blood clots and potential complications. A study by Alec et al 3 .recommends regular testing of patients' INR after surgery to consistently achieve the target INR range and maximize time in therapeutic range (TTR) 4 , 5 . TTR is an essential measure for evaluating the effectiveness of anticoagulation with warfarin, and TTR is negatively correlated with major hemorrhage and thromboembolism 6 . Shen, A. Y. et al.'s study revealed that Asian patients on warfarin treatment have a significantly higher risk of intracranial hemorrhage 7 . Additionally, Lee et al.'s research indicated that a 10% increase in TTR is associated with a 10–12% decrease in the risk of thromboembolic events and a 29% decrease in the risk of death 8 . Generally, the TTR above 60% is considered indicative of effective anticoagulation in patients. Clinical trials have demonstrated the significance of achieving moderate anticoagulation with warfarin, with a recommended INR control range of 1.8–2.5 9 . However, some patients may find it difficult to keep their INR within this range, which could increase their risk of bleeding or thromboembolic events 10 . Insufficient control of coagulation function is a major concern for high-risk patients, as it can lead to complications that impact the proper functioning of cardiac valves, potentially requiring reoperation. Therefore, it is important to explore new monitoring approaches for anticoagulation in these patients, such as home monitor or more frequent clinic-based testing, to reduce the risk of abnormal coagulation function after surgery. The study conducted by Ørvim Sølvik et al 11 .found that self-management of INR testing for patients resulted in improved time in therapeutic range (TTR), reduced INR variance, fewer extreme INR values, and decreased complications after 2 years of warfarin therapy compared to conventional treatment. These results indicate that self-management can assist patients in controlling their postoperative coagulation function. As a result, this study aims to examine the differences in INR control and the occurrence of complications in patients undergoing cardiac valve replacement and Plastic surgery under home monitoring conditions, as well as to evaluate and predict the associated risk factors. Materials and methods Patients The First Affiliated Hospital of Zhejiang University of Medicine conducted a retrospective study from January 2021 to January 2023 to gather data on patients who had undergone cardiac valve replacement or plastic. The study included patients with rheumatic lesions, aortic valve stenosis or regurgitation due to degenerative lesions, mitral valve stenosis or regurgitation, and tricuspid valve stenosis or regurgitation. Patients with a history of mental illness, hearing impairment, communication barriers, other coagulation disorders, malignant tumors, pregnancy, or HIV infection were excluded from the study. A total of 505 patients were initially enrolled, and 406 patients completed the follow-up, resulting in a follow-up completion rate of 70.49%. The hospital's anticoagulation clinic set the target range for INR at 1.8 to 2.5, with INR 2.5 considered above the therapeutic range. Methods The follow-up approach conducted by Hangzhou Chenghui Medical Instrument will involve reviewing the electronic record system and conducting telephone interviews. We will collect clinical data on patients, including gender, age, education level, atrial fibrillation, smoking and alcohol history, warfarin dose, anticoagulation-related complications, information on disease conditions, cardiac valve replacement status, concomitant medication, anticoagulation status, and INR values. Coaguchek XS was used to monitor PT in patients with oral anticoagulation therapy. Anticoagulation stability is determined by the continuous use of a fixed warfarin dose for at least 14 days, with stable INR values within the target range of 80% − 120% for a minimum of 7 days. TTR is calculated as the ratio of the time it takes for a patient to achieve stable INR after 6 weeks of warfarin use to the total duration of medication. TTR was calculated using the Rosendaal linear interpolation method, which assumes a linear relationship between two INR values and assigns a specific INR value to each day for each patient 12 . Patients were then divided into the “poor” TTR (TTR < 60%) group and the “good” TTR (TTR ≥ 60%) group. This retrospective study has been approved by the Ethics Review Committee of the First Affiliated Hospital, Zhejiang University and adheres to the principles of the Helsinki Declaration. Statistical analysis Statistical analysis and risk prediction will be conducted using SPSS 26.0 and R 4.3.2. We will use the chi-square test for categorical variables and logistic regression models for multivariable analysis, with a significance level of P < 0.05 indicating statistical significance. To construct the risk model and select variables, we will use lasso regression in the R programming language. Lasso regression will help identify the optimal predictive features of risk factors among patients by applying a penalty to variables and selecting only those that contribute to out-of-sample performance through cross-validation. This approach is particularly useful for datasets with potential multi-collinearity and does not rely on P-values. The lasso regression model will then select features with non-zero coefficients, and a nomogram graph will be created for evaluation purposes. Results From January 2021 to January 2023, we conducted a follow-up study on 406 patients who had undergone cardiac valve replacement or plastic, focusing on their long-term home monitoring of INR values. A total of 6331 INR values were collected, with each patient having a mean of 2.1±0.56 INR values. The study found that the mean TTR was 59.2%±19.4%, and the mean monitoring interval for the patient was 62.6±30.1 days. Based on their TTR, patients were divided into the "poor" group (TTR < 60%) and the "good" group (TTR≥60%). The study included 220 male and 186 female patients, with an average age of 58.49±14.63 years (ranging from 14 to 90 years). We analyzed all patient data, including their surgical, personal, and medical history, using logistic regression in both groups (refer to Table 1 for details). Univariate analyses of preoperative variables associated with TTR<60% are shown in Table 1. The results revealed a statistically significant disparity in gender between the two groups (p=0.008) with female patients exhibiting inferior postoperative coagulation control compared to male patients. The mean age in the TTR ≥60% group was 51.9±13.8, and the mean age in the TTR < 60% group was 58.56±14.63; There was no statistical significance (p = 0.994). However, factors such as history of atrial fibrillation (p=1.567), preoperative medication history (p=0.754), and involvement of multiple valves (p=0.992) did not display significant differences between the two groups. Table 1 Differences between demographic and clinical characteristics of “good” and “poor” groups Factors TTR≥60%,n=211 TTR＜60%,n=195 P-value Gender（Female） 85 94 0.008 Age 58.43±14.67 58.56±14.63 0.994 Atrial fibrillation history 63 50 1.567 Smoking 24 27 0.479 Drinking 26 20 1.495 Preoperative medication history 0.754 None 175 155 Aspirin 21 16 New anticoagulants 15 24 Education level 0.863 Primary (0–9 years) 103 83 Secondary (9–12 years) 49 54 Higher (＞12 years) 59 58 Replaced valve type 0.940 Mechanical valve 64 55 biological valve 97 86 Forming ring 50 54 The replaced valve 0.992 A 61 65 M 47 39 T 10 19 A+M 18 9 A+T 3 3 M+T 48 33 A+M+T 24 27 Postoperative Complications 6 7 0.920 Cerebral infarction history 13 10 1.178 Abbreviations : A: Aortic valve, M: Mitral valve, T: Tricuspid valve After conducting lasso regression analysis on the cohort of 406 patients, it was found that 11 features were reduced to 5 potential predictive factors with non-zero coefficients in the lasso regression model (see Figure 1). These factors included gender, history of atrial fibrillation, preoperative medication history, valve replacement, and education level (refer to Table 2). Table 2 Predictors of control of coagulation factors in patients after valve surgery Factors Prediction model β Odds ratio (95% CI) P-value Intercept -0.02611 0.974(0.570-1.666) 0.924 Gender（Female） 0.65255 1.920(1.244-2.985) 0.003 Preoperative medication history Aspirin 0.10898 1.115(0.528-2.384) 0.775 New anticoagulants -0.75815 0.469(0.220-0.966) 0.043 Atrial fibrillation history 0.36518 1.441(0.876-2.392) 0.153 Replaced valve type biological valve -0.02956 0.971(0.596-1.579) 0.905 Forming ring -0.1497 0.861(0.501-1.478) 0.587 Education level Secondary (9–12 years) -0.39375 0.675(0.407-1.113) 0.124 Higher (＞12 years) -0.24451 0.783(0.475-1.289) 0.337 Note : β is the regression coefficient. Abbreviations : CI, confidence interval The results of the logistic regression analysis for gender, preoperative medication history, history of atrial fibrillation, cardiac valve replacement, and education level are presented in Table 2. A model incorporating these independent predictive factors was constructed and depicted using a forest plot. It is important to note that the use of novel anticoagulant medications prior to cardiac valve replacement is associated with improved postoperative coagulation control, with significant differences observed. With the predictive model, a nomogram graph can be created to evaluate postoperative coagulation control in valve surgery patients (see Figure 2). The nomogram graph is a visual tool that helps predict the patiens’ anticoagulant quality after cardiac valve replacement and plastic surgery. This study examined the impact of five factors - history of atrial fibrillation, gender, type of valve replacement, preoperative medication history, and education level - on postoperative coagulation function. Figure 3 illustrates the scoring system based on patients' preoperative data, enabling the prediction of the probability of achieving the target TTR of warfarin after valve replacement surgery. For example, female patients with a history of atrial fibrillation, undergoing mechanical valve replacement, long-term preoperative use of aspirin, and a lower education level may exhibit poorer coagulation control following surgery. Conversely, patients who have received newer anticoagulants such as rivaroxaban before surgery might experience improved postoperative coagulation control. Discussion According to this study, female patients exhibit poorer postoperative control of coagulation function compare to male patients. This difference may be a result of physiological and anatomical distinctions between the two genders, which affect the metabolism and anticoagulant effects of warfarin. For instance, females may have a higher clearance rate of warfarin than males, resulting in decreased sensitivity to the medication and inferior anticoagulant effects. Additionally, estrogen levels in females may impact the anticoagulant effects of warfarin 14-16 . In a study conducted by Zhu, Chen 17,18 ,it was found that female, atrial fibrillation, and compliance were linked to TTR of less than 60% among cardiac valve replacement patients receiving outpatient follow-up. However, our study findings revealed a significant improvement in patients' compliance and postoperative coagulation function control, particularly in individuals with atrial fibrillation, through the implementation of long-term home monitoring. This improvement can be attributed to the fact that home monitoring enables patients to monitor their INR values at home, eliminating the need for frequent hospital visits and reducing time and transportation costs. With home monitoring, patients can monitor their INR values at any time and provide timely feedback to doctors or caregivers, which in turn allows for adjustments to anticoagulant treatments and better control of blood coagulation 19,20 . Moreover, patients were more involved in their treatment through education on self-monitoring at home, allowing them to take an active role in their anticoagulant therapy and increasing their accountability for their health. Additionally, increased monitoring and adjustments to warfarin dosage through home monitoring may decrease the risk of bleeding and blood clotting complications, leading to better patient outcomes. It is important to note that, based on lasso regression analysis, patients who were on novel anticoagulant medications before surgery had better control of their coagulation function after the surgery. Novel anticoagulant medications, such as rivaroxaban, have been found to have better anticoagulant effects compared to traditional medications like aspirin 21 . This is likely due to patients who were already taking novel anticoagulant medications before surgery also had higher awareness of anticoagulation management compared to those who started anticoagulant medications after surgery. Patients who take aspirin before surgery may have various underlying conditions, such as hypertension or diabetes, which could impact their coagulation function. This could potentially limit the anticoagulant effects of aspirin and result in differences in the anticoagulant effects of warfarin after surgery. Thus, the preoperative cultivation of patients' anticoagulation awareness is essential in cardiothoracic surgery. Educating and empowering patients will enhance their understanding and compliance, leading to safer surgeries and improved postoperative outcomes. According to our study findings, despite warfarin dose adjustment for each hom monitoring patients based on their INR value, the average time in TTR was found to be only 59.2%. This could be attributed to some patients occasionally failing to report their target INR values. To ensure data integrity and reliability, we are currently designing a mobile application for long-term monitoring of patients' INR values. With this app, patients can easily measure and upload their INR values, and the healthcare providers will provide guidance on adjusting their warfarin dose. We will incorporate built-in checks to ascertain the accuracy of entered INR values, promptly flagging any outliers or irregular readings for further validation. This new method aims to be more efficient and convenient for both patients and healthcare providers. In addition, nomogram charts are widely used in oncology and contribute to enhancing precision and offering intuitive prognosis assessment, which is beneficial for clinical decision-making 22,23 . Our research is the initial one to utilize the nomogram chart in evaluating the management of coagulation function in patients undergoing cardiac valve replacement. We have created a valuable tool for predicting the risk of poor control of coagulation function in patients. This tool can assist doctors in early identification of high-risk patients with inadequate postoperative coagulation function control. For these patients, it is recommended to provide thorough education during their hospital stay and encourage long-term self-monitoring at home, with feedback to healthcare providers to adjust medication as needed to control their coagulation function. Home monitoring not only offers convenience, real-time monitoring, increased patient engagement, and reduced complication risks for postoperative coagulation function control, but also helps doctors gain a comprehensive understanding of patients' coagulation status and adjust treatment plans based on real-time data, enabling more personalized management of anticoagulant therapy for each patient. The developed nomogram chart will help researchers select suitable patients with stable coagulation function control for clinical trials. In retrospective studies, we can exclude patients exhibiting impaired coagulation function to mitigate the potential influence of complications, such as bleeding and thrombosis, on the trial outcomes. There are some limitations in this study. Firstly, it is a retrospective research. Secondly, the TTR result in this study is sampled from a limited number of patients. These limitations might influence the generalizability of the findings and may not accurately reflect the entire population. Consequently, future studies with larger, prospective designs and a more diverse patient population are necessary to provide more comprehensive and reliable evidence in this area. Conclusion Home monitoring for patients who have undergone cardiac valve replacement surgery can greatly enhance coagulation management. It empowers patients to keep track of their INR values from the comfort of their own home, eliminating the need for frequent hospital visits. This not only saves time and money on transportation but also allows patients to communicate their results to healthcare providers for prompt adjustments to their anticoagulation therapy. By combining home monitoring with patient education, patients can become more engaged and accountable in their anticoagulation treatment, potentially leading to better treatment compliance. In addition, regular monitoring of INR values at home can help lower the risk of complications like bleeding and blood clots, leading to better outcomes for patients. Using a nomogram chart can also make it easier to identify patients with consistent coagulation function for clinical trials. Providing early interventions such as medication reminders, drug monitoring, and home support can be beneficial for patients with coagulation issues. For patients at high risk, promoting home mornitoring or increasing the frequency of INR monitoring during outpatient visits can be a cost-effective way to improve treatment adherence. Declarations Ethics approval and consent to participate The study received approval from the ethical committees of The First Affiliated Hospital Zhejiang University of Medicine (IIT20210517A) and individual consent for this retrospective analysis was waived. Consent for publication Not applicable. Acknowledgement This work was supported by the Hangzhou Chenghui Medical Instrument. Funding This research received no external funding. Conflict of Interest The authors declare no conflict of interest. References Burn J, Pirmohamed M. Direct oral anticoagulants versus warfarin: is new always better than the old? Open Heart. 2018;5:e000712. 10.1136/openhrt-2017-000712 . Weitz JI et al. Trends in Prescribing Oral Anticoagulants in Canada, 2008–2014. Clin Ther 37, 2506–2514 e2504, 10.1016/j.clinthera.2015.09.008 (2015). Vahanian A, et al. 2021 ESC/EACTS Guidelines for the management of valvular heart disease. Eur Heart J. 2022;43:561–632. 10.1093/eurheartj/ehab395 . Ansell J. Point-of-care patient self-monitoring of oral vitamin K antagonist therapy. J Thromb Thrombolysis. 2013;35:339–41. 10.1007/s11239-013-0878-z . Ansell J et al. Pharmacology and management of the vitamin K antagonists: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines (8th Edition). Chest 133, 160S-198S, 10.1378/chest.08-0670 (2008). Zhang H, Dong Y, Ao X, Zhu D, Dong L. Optimal oral anticoagulant therapy in Chinese patients with mechanical heart valves. Eur J Pharm Sci. 2020;144:105202. 10.1016/j.ejps.2019.105202 . Shen AY, Yao JF, Brar SS, Jorgensen MB, Chen W. Racial/ethnic differences in the risk of intracranial hemorrhage among patients with atrial fibrillation. J Am Coll Cardiol. 2007;50:309–15. 10.1016/j.jacc.2007.01.098 . Lee SL, et al. Patients' time in therapeutic range on warfarin among atrial fibrillation patients in Warfarin Medication Therapy Adherence Clinic. World J Cardiol. 2021;13:483–92. 10.4330/wjc.v13.i9.483 . Thrombosis prevention trial. : randomised trial of low-intensity oral anticoagulation with warfarin and low-dose aspirin in the primary prevention of ischaemic heart disease in men at increased risk. The Medical Research Council's General Practice Research Framework. Lancet. 1998;351:233–41. Boulanger L, et al. Warfarin exposure and the risk of thromboembolic and major bleeding events among medicaid patients with atrial fibrillation. Ann Pharmacother. 2006;40:1024–9. 10.1345/aph.1G408 . Solvik UO, et al. Quality of Warfarin Therapy and Quality of Life are Improved by Self-Management for Two Years. Thromb Haemost. 2019;119:1632–41. 10.1055/s-0039-1693703 . Rodriguez F, et al. Limited English proficient patients and time spent in therapeutic range in a warfarin anticoagulation clinic. J Am Heart Assoc. 2013;2:e000170. 10.1161/JAHA.113.000170 . Kidd AC, et al. Survival prediction in mesothelioma using a scalable Lasso regression model: instructions for use and initial performance using clinical predictors. BMJ Open Respir Res. 2018;5:e000240. 10.1136/bmjresp-2017-000240 . Fournier JP, et al. Concurrent use of statins and hormone therapy and risk of venous thromboembolism in postmenopausal women: a population-based case-control study. Menopause. 2014;21:1023–6. 10.1097/GME.0000000000000279 . Zingone MM, Guirguis AB, Airee A, Cobb D. Probable drug interaction between warfarin and hormonal contraceptives. Ann Pharmacother. 2009;43:2096–102. 10.1345/aph.1M382 . Avarello I, Bianchi S, Toschi V, Zighetti ML, Faioni EM. Time in therapeutic range is lower in women than in men and is not explained by differences in age or comorbidity. Thromb Res. 2021;203:18–21. 10.1016/j.thromres.2021.04.011 . Zhu X, et al. Rosendaal linear interpolation method appraising of time in therapeutic range in patients with 12-week follow-up interval after mechanical heart valve replacement. Front Cardiovasc Med. 2022;9:925571. 10.3389/fcvm.2022.925571 . Chen QL, et al. Security and cost comparison of INR self-testing and conventional hospital INR testing in patients with mechanical heart valve replacement. J Cardiothorac Surg. 2015;10(4). 10.1186/s13019-015-0205-1 . Gadisseur AP, Kaptein AA, Breukink-Engbers WG, van der Meer FJ, Rosendaal FR. Patient self-management of oral anticoagulant care vs. management by specialized anticoagulation clinics: positive effects on quality of life. J Thromb Haemost. 2004;2:584–91. 10.1111/j.1538-7836.2004.00659.x . Connock M et al. Clinical effectiveness and cost-effectiveness of different models of managing long-term oral anticoagulation therapy: a systematic review and economic modelling. Health Technol Assess 11, iii-iv, ix-66, 10.3310/hta11380 (2007). Patel MR, et al. Rivaroxaban versus warfarin in nonvalvular atrial fibrillation. N Engl J Med. 2011;365:883–91. 10.1056/NEJMoa1009638 . Iasonos A, Schrag D, Raj GV, Panageas KS. How to build and interpret a nomogram for cancer prognosis. J Clin Oncol. 2008;26:1364–70. 10.1200/JCO.2007.12.9791 . Balachandran VP, Gonen M, Smith JJ, DeMatteo RP. Nomograms in oncology: more than meets the eye. Lancet Oncol. 2015;16:e173–180. 10.1016/S1470-2045(14)71116-7 . Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4113572","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":299479827,"identity":"dd4a0037-8e19-4a10-93e1-a199a23d0528","order_by":0,"name":"ChenXi Ying","email":"","orcid":"","institution":"The First Affiliated Hospital Zhejiang University of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"ChenXi","middleName":"","lastName":"Ying","suffix":""},{"id":299479833,"identity":"4026eeab-d5f1-4abc-9245-b99f1a735918","order_by":1,"name":"LingShan Liu","email":"","orcid":"","institution":"The First Affiliated Hospital Zhejiang University of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"LingShan","middleName":"","lastName":"Liu","suffix":""},{"id":299479838,"identity":"40080012-fe2b-4013-990f-421607172f92","order_by":2,"name":"BoHao Dai","email":"","orcid":"","institution":"The First Affiliated Hospital Zhejiang University of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"BoHao","middleName":"","lastName":"Dai","suffix":""},{"id":299479842,"identity":"4a810d3f-703e-4317-99b0-ac8f2102cccf","order_by":3,"name":"YuFei Fu","email":"","orcid":"","institution":"Zhejiang Chinese Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"YuFei","middleName":"","lastName":"Fu","suffix":""},{"id":299479846,"identity":"56cfdcec-3d8e-49a3-a264-5a2558087905","order_by":4,"name":"Xin Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8UlEQVRIiWNgGAWjYDACCRBhwMDDxt/Y+ICBB8RLIE6LHJ/E4WYDErQwMBjLMaS3QdkEtPDPbj72mKfgTmIbw8G2yh8yhxn42XMMGH7uwGPJnWPphjMMniW2MTe23ZDgOcwg2fPGgLH3DG4tBhI5ZhIfDA6DbblhANRicCPHgJmxDZ+W/G8SCWAtiW0FCUAt9oS15LCBbDFmA2phOACyRYKAFokbaWaSMwwOy7FJHGyWbOBJ55E486zgYC8eLfwzkp9J8/w5zCPf3/7w488eazn+9uSND37i0YIKGHsgkXmAWA1A8IMEtaNgFIyCUTBiAAAN0U5xQ3LTOAAAAABJRU5ErkJggg==","orcid":"","institution":"The First Affiliated Hospital Zhejiang University of Medicine","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2024-03-16 14:17:46","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4113572/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4113572/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":56196969,"identity":"cb7f2d80-011d-45a4-b44c-2df9ddb3713d","added_by":"auto","created_at":"2024-05-09 18:17:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":136341,"visible":true,"origin":"","legend":"\u003cp\u003eDemographic and clinical feature selection using the LASSO binary logistic regression model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNotes:\u003c/strong\u003e (\u003cstrong\u003eA\u003c/strong\u003e) The LASSO model's optimal parameter (lambda) was chosen through fivefold cross-validation using the minimum criteria\u003csup\u003e13\u003c/sup\u003e. A plot of the partial likelihood deviance (binomial deviance) versus log(lambda) was created, with dotted vertical lines indicating the optimal values based on the minimum criteria and the 1 SE of the minimum criteria (the 1-SE criteria).\u003c/p\u003e\n\u003cp\u003e(\u003cstrong\u003eB\u003c/strong\u003e) The coefficient profiles of the 9 features were plotted using LASSO against a sequence of log(lambda) values. A vertical line was drawn at the value determined through fivefold cross-validation, which resulted in an optimal lambda and five features with nonzero coefficients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e LASSO, least absolute shrinkage and selection operator; SE, standard error.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4113572/v1/454bc750d85fd8fe153c2b18.png"},{"id":56196240,"identity":"aa673cc3-3f4b-4dc0-9db3-6ded83f1862d","added_by":"auto","created_at":"2024-05-09 18:08:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":72818,"visible":true,"origin":"","legend":"\u003cp\u003eThe TTR reaching the target nomogram\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u003c/strong\u003e The TTR reaching the target nomogram was developed in the cohort, with Valve surgery, Antithrombotic medication history, Gender, Atrial fibrillation history and education level.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations: \u003c/strong\u003eValve (Valve surgery: 1 mechanical valve, 2 biological valve, 3 annuloplasty ring), Medical (Antithrombotic medication history: 1 none, 2 preoperative aspirin use, 3 preoperative novel anticoagulant use), Gender (male, female), AF (Atrial fibrillation history: No, Yes), Edu (Education level: Primary (0–9 years), Secondary (9–12 years), Higher (＞12 years)).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4113572/v1/8b617807c36b968448ea3f50.png"},{"id":58411838,"identity":"7f2c7e3c-00c2-47cb-bd20-e83125136269","added_by":"auto","created_at":"2024-06-15 10:01:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":695342,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4113572/v1/c97bd0cf-9a19-4dd7-b894-3e981dc9a336.pdf"},{"id":56196303,"identity":"1fc9ac9f-89c5-46a8-a741-787a23cbfcb9","added_by":"auto","created_at":"2024-05-09 18:09:18","extension":"rdata","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":26793,"visible":true,"origin":"","legend":"","description":"","filename":"file.rdata","url":"https://assets-eu.researchsquare.com/files/rs-4113572/v1/b7995c0dced33ea8ce65bc7d.rdata"},{"id":56196216,"identity":"10365c8a-ff00-4dbb-a14a-552b38844da9","added_by":"auto","created_at":"2024-05-09 18:08:44","extension":"txt","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":12147,"visible":true,"origin":"","legend":"","description":"","filename":"input.txt","url":"https://assets-eu.researchsquare.com/files/rs-4113572/v1/fe0d30000d122b70faa329f2.txt"}],"financialInterests":"No competing interests reported.","formattedTitle":"Enhancing Coagulation Management after Cardiac Valve Replacement and Plastic: The Benefits of Home Monitoring","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWarfarin, a member of the coumarin family, is a vitamin K antagonist (VKA) that works by inhibiting the vitamin K-dependent (VKD) process. This inhibition hinders the synthesis of certain clotting factors necessary for normal coagulation in the liver, resulting in anticoagulant effects. It is commonly prescribed for stroke prevention in patients with atrial fibrillation and cardiac valve diseases, as well as for preventing venous thromboembolism(VTE) and other thromboembolic complications\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePatients with cardiac valve diseases receive oral anticoagulant therapy using vitamin K antagonists. In clinical practice, it is important to adjust the international normalized ratio (INR) range for patients based on their individual risk factors and the thrombogenic risk. This is necessary to ensure that patients receive the appropriate level of anticoagulation to prevent blood clots and potential complications. A study by Alec et al\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.recommends regular testing of patients' INR after surgery to consistently achieve the target INR range and maximize time in therapeutic range (TTR)\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. TTR is an essential measure for evaluating the effectiveness of anticoagulation with warfarin, and TTR is negatively correlated with major hemorrhage and thromboembolism\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Shen, A. Y. et al.'s study revealed that Asian patients on warfarin treatment have a significantly higher risk of intracranial hemorrhage\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Additionally, Lee et al.'s research indicated that a 10% increase in TTR is associated with a 10\u0026ndash;12% decrease in the risk of thromboembolic events and a 29% decrease in the risk of death\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Generally, the TTR above 60% is considered indicative of effective anticoagulation in patients. Clinical trials have demonstrated the significance of achieving moderate anticoagulation with warfarin, with a recommended INR control range of 1.8\u0026ndash;2.5\u003csup\u003e9\u003c/sup\u003e. However, some patients may find it difficult to keep their INR within this range, which could increase their risk of bleeding or thromboembolic events\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Insufficient control of coagulation function is a major concern for high-risk patients, as it can lead to complications that impact the proper functioning of cardiac valves, potentially requiring reoperation. Therefore, it is important to explore new monitoring approaches for anticoagulation in these patients, such as home monitor or more frequent clinic-based testing, to reduce the risk of abnormal coagulation function after surgery.\u003c/p\u003e \u003cp\u003eThe study conducted by \u0026Oslash;rvim S\u0026oslash;lvik et al\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.found that self-management of INR testing for patients resulted in improved time in therapeutic range (TTR), reduced INR variance, fewer extreme INR values, and decreased complications after 2 years of warfarin therapy compared to conventional treatment. These results indicate that self-management can assist patients in controlling their postoperative coagulation function. As a result, this study aims to examine the differences in INR control and the occurrence of complications in patients undergoing cardiac valve replacement and Plastic surgery under home monitoring conditions, as well as to evaluate and predict the associated risk factors.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eThe First Affiliated Hospital of Zhejiang University of Medicine conducted a retrospective study from January 2021 to January 2023 to gather data on patients who had undergone cardiac valve replacement or plastic. The study included patients with rheumatic lesions, aortic valve stenosis or regurgitation due to degenerative lesions, mitral valve stenosis or regurgitation, and tricuspid valve stenosis or regurgitation. Patients with a history of mental illness, hearing impairment, communication barriers, other coagulation disorders, malignant tumors, pregnancy, or HIV infection were excluded from the study. A total of 505 patients were initially enrolled, and 406 patients completed the follow-up, resulting in a follow-up completion rate of 70.49%. The hospital's anticoagulation clinic set the target range for INR at 1.8 to 2.5, with INR\u0026thinsp;\u0026lt;\u0026thinsp;1.8 considered below the therapeutic range and INR\u0026thinsp;\u0026gt;\u0026thinsp;2.5 considered above the therapeutic range.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe follow-up approach conducted by Hangzhou Chenghui Medical Instrument will involve reviewing the electronic record system and conducting telephone interviews. We will collect clinical data on patients, including gender, age, education level, atrial fibrillation, smoking and alcohol history, warfarin dose, anticoagulation-related complications, information on disease conditions, cardiac valve replacement status, concomitant medication, anticoagulation status, and INR values. Coaguchek XS was used to monitor PT in patients with oral anticoagulation therapy. Anticoagulation stability is determined by the continuous use of a fixed warfarin dose for at least 14 days, with stable INR values within the target range of 80% \u0026minus;\u0026thinsp;120% for a minimum of 7 days. TTR is calculated as the ratio of the time it takes for a patient to achieve stable INR after 6 weeks of warfarin use to the total duration of medication. TTR was calculated using the Rosendaal linear interpolation method, which assumes a linear relationship between two INR values and assigns a specific INR value to each day for each patient\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Patients were then divided into the \u0026ldquo;poor\u0026rdquo; TTR (TTR\u0026thinsp;\u0026lt;\u0026thinsp;60%) group and the \u0026ldquo;good\u0026rdquo; TTR (TTR\u0026thinsp;\u0026ge;\u0026thinsp;60%) group. This retrospective study has been approved by the Ethics Review Committee of the First Affiliated Hospital, Zhejiang University and adheres to the principles of the Helsinki Declaration.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis and risk prediction will be conducted using SPSS 26.0 and R 4.3.2. We will use the chi-square test for categorical variables and logistic regression models for multivariable analysis, with a significance level of P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicating statistical significance. To construct the risk model and select variables, we will use lasso regression in the R programming language. Lasso regression will help identify the optimal predictive features of risk factors among patients by applying a penalty to variables and selecting only those that contribute to out-of-sample performance through cross-validation. This approach is particularly useful for datasets with potential multi-collinearity and does not rely on P-values. The lasso regression model will then select features with non-zero coefficients, and a nomogram graph will be created for evaluation purposes.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eFrom January 2021 to January 2023, we conducted a follow-up study on 406 patients who had undergone cardiac valve replacement or plastic, focusing on their long-term home monitoring of INR values. A total of 6331 INR values were collected, with each patient having a mean of 2.1\u0026plusmn;0.56 INR values. The study found that the mean TTR was 59.2%\u0026plusmn;19.4%, and the mean monitoring interval for the patient was 62.6\u0026plusmn;30.1 days. Based on their TTR, patients were divided into the \u0026quot;poor\u0026quot; group (TTR \u0026lt; 60%) and the \u0026quot;good\u0026quot; group (TTR\u0026ge;60%). The study included 220 male and 186 female patients, with an average age of 58.49\u0026plusmn;14.63 years (ranging from 14 to 90 years). We analyzed all patient data, including their surgical, personal, and medical history, using logistic regression in both groups (refer to Table 1 for details).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUnivariate analyses of preoperative variables associated with TTR\u0026lt;60% are shown in Table 1. The results revealed a statistically significant disparity in gender between the two groups (p=0.008) with female patients exhibiting inferior postoperative coagulation control compared to male patients. The mean age in the TTR \u0026ge;60% group was 51.9\u0026plusmn;13.8, and the mean age in the TTR \u0026lt; 60% group was 58.56\u0026plusmn;14.63; There was no statistical significance (p = 0.994). However, factors such as history of atrial fibrillation (p=1.567), preoperative medication history (p=0.754), and involvement of multiple valves (p=0.992) did not display significant differences between the two groups.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"568\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Differences between demographic and clinical characteristics of \u0026ldquo;good\u0026rdquo; and \u0026ldquo;poor\u0026rdquo; groups\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003eFactors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003eTTR\u0026ge;60%,n=211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003eTTR＜60%,n=195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003eP-value\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender（Female）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e58.43\u0026plusmn;14.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e58.56\u0026plusmn;14.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e0.994\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAtrial fibrillation history\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e1.567\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e0.479\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDrinking\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e1.495\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreoperative medication history\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e0.754\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e175\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003eAspirin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003eNew anticoagulants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e0.863\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003ePrimary (0\u0026ndash;9 years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003eSecondary (9\u0026ndash;12 years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003eHigher (＞12 years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReplaced valve type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e0.940\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Mechanical valve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; biological valve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Forming ring\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u003cstrong\u003eThe replaced valve\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e0.992\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; A+M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; A+T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; M+T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; A+M+T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePostoperative Complications\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e0.920\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6278659611993%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCerebral infarction history\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.158730158730158%\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.27689594356261%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.936507936507937%\"\u003e\n \u003cp\u003e1.178\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eA: Aortic valve, M: Mitral valve, T: Tricuspid valve \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAfter conducting lasso regression analysis on the cohort of 406 patients, it was found that 11 features were reduced to 5 potential predictive factors with non-zero coefficients in the lasso regression model (see Figure 1). These factors included gender, history of atrial fibrillation, preoperative medication history, valve replacement, and education level (refer to Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e Predictors of control of coagulation factors in patients after valve surgery\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"594\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" rowspan=\"2\"\u003e\n \u003cp\u003eFactors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"57.57575757575758%\" colspan=\"2\"\u003e\n \u003cp\u003ePrediction model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.090909090909092%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOdds ratio (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eIntercept\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.02611\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.974(0.570-1.666)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.924\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eGender（Female）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.65255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.920(1.244-2.985)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePreoperative medication history\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAspirin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.10898\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.115(0.528-2.384)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.775\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNew anticoagulants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.75815\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.469(0.220-0.966)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAtrial fibrillation history\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.36518\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.441(0.876-2.392)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.153\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eReplaced valve type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ebiological valve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.02956\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.971(0.596-1.579)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.905\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eForming ring\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.1497\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.861(0.501-1.478)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.587\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSecondary (9\u0026ndash;12 years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.39375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.675(0.407-1.113)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.124\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHigher (＞12 years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;-0.24451\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.783(0.475-1.289)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.337\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003e\u0026beta; is the regression coefficient.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eCI, confidence interval\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe results of the logistic regression analysis for gender, preoperative medication history, history of atrial fibrillation, cardiac valve replacement, and education level are presented in Table 2. A model incorporating these independent predictive factors was constructed and depicted using a forest plot. It is important to note that the use of novel anticoagulant medications prior to cardiac valve replacement is associated with improved postoperative coagulation control, with significant differences observed. With the predictive model, a nomogram graph can be created to evaluate postoperative coagulation control in valve surgery patients (see Figure 2).\u003c/p\u003e\n\u003cp\u003eThe nomogram graph is a visual tool that helps predict the patiens\u0026rsquo; anticoagulant quality after cardiac valve replacement and plastic surgery. This study examined the impact of five factors - history of atrial fibrillation, gender, type of valve replacement, preoperative medication history, and education level - on postoperative coagulation function. Figure 3 illustrates the scoring system based on patients\u0026apos; preoperative data, enabling the prediction of the probability of achieving the target TTR of warfarin after valve replacement surgery. For example, female patients with a history of atrial fibrillation, undergoing mechanical valve replacement, long-term preoperative use of aspirin, and a lower education level may exhibit poorer coagulation control following surgery. Conversely, patients who have received newer anticoagulants such as rivaroxaban before surgery might experience improved postoperative coagulation control.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAccording to this study, female patients exhibit poorer postoperative control of coagulation function compare to male patients. This difference may be a result of physiological and anatomical distinctions between the two genders, which affect the metabolism and anticoagulant effects of warfarin. For instance, females may have a higher clearance rate of warfarin than males, resulting in decreased sensitivity to the medication and inferior anticoagulant effects. Additionally, estrogen levels in females may impact the anticoagulant effects of warfarin\u003csup\u003e14-16\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn a study conducted by Zhu, Chen\u003csup\u003e17,18\u003c/sup\u003e,it was found that female, atrial fibrillation, and compliance were linked to TTR of less than 60% among cardiac valve replacement patients receiving outpatient follow-up. However, our study findings revealed a significant improvement in patients\u0026apos; compliance and postoperative coagulation function control, particularly in individuals with atrial fibrillation, through the implementation of long-term home monitoring. This improvement can be attributed to the fact that home monitoring enables patients to monitor their INR values at home, eliminating the need for frequent hospital visits and reducing time and transportation costs. With home monitoring, patients can monitor their INR values at any time and provide timely feedback to doctors or caregivers, which in turn allows for adjustments to anticoagulant treatments and better control of blood coagulation\u003csup\u003e19,20\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMoreover, patients were more involved in their treatment through education on self-monitoring at home, allowing them to take an active role in their anticoagulant therapy and increasing their accountability for their health. Additionally, increased monitoring and adjustments to warfarin dosage through home monitoring may decrease the risk of bleeding and blood clotting complications, leading to better patient outcomes. It is important to note that, based on lasso regression analysis, patients who were on novel anticoagulant medications before surgery had better control of their coagulation function after the surgery. Novel anticoagulant medications, such as rivaroxaban, have been found to have better anticoagulant effects compared to traditional medications like aspirin\u003csup\u003e21\u003c/sup\u003e. This is likely due to patients who were already taking novel anticoagulant medications before surgery also had higher awareness of anticoagulation management compared to those who started anticoagulant medications after surgery. Patients who take aspirin before surgery may have various underlying conditions, such as hypertension or diabetes, which could impact their coagulation function. This could potentially limit the anticoagulant effects of aspirin and result in differences in the anticoagulant effects of warfarin after surgery. Thus, the preoperative cultivation of patients\u0026apos; anticoagulation awareness is essential in cardiothoracic surgery. Educating and empowering patients will enhance their understanding and compliance, leading to safer surgeries and improved postoperative outcomes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAccording to our study findings, despite warfarin dose adjustment for each hom monitoring patients based on their INR value, the average time in TTR was found to be only 59.2%. This could be attributed to some patients occasionally failing to report their target INR values. To ensure data integrity and reliability, we are currently designing a mobile application for long-term monitoring of patients\u0026apos; INR values. With this app, patients can easily measure and upload their INR values, and the healthcare providers will provide guidance on adjusting their warfarin dose. We will incorporate built-in checks to ascertain the accuracy of entered INR values, promptly flagging any outliers or irregular readings for further validation. This new method aims to be more efficient and convenient for both patients and healthcare providers. \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition, nomogram charts are widely used in oncology and contribute to enhancing precision and offering intuitive prognosis assessment, which is beneficial for clinical decision-making\u003csup\u003e22,23\u003c/sup\u003e. Our research is the initial one to utilize the nomogram chart in evaluating the management of coagulation function in patients undergoing cardiac valve replacement.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe have created a valuable tool for predicting the risk of poor control of coagulation function in patients. This tool can assist doctors in early identification of high-risk patients with inadequate postoperative coagulation function control. For these patients, it is recommended to provide thorough education during their hospital stay and encourage long-term self-monitoring at home, with feedback to healthcare providers to adjust medication as needed to control their coagulation function. Home monitoring not only offers convenience, real-time monitoring, increased patient engagement, and reduced complication risks for postoperative coagulation function control, but also helps doctors gain a comprehensive understanding of patients\u0026apos; coagulation status and adjust treatment plans based on real-time data, enabling more personalized management of anticoagulant therapy for each patient. The developed nomogram chart will help researchers select suitable patients with stable coagulation function control for clinical trials. In retrospective studies, we can exclude patients exhibiting impaired coagulation function to mitigate the potential influence of complications, such as bleeding and thrombosis, on the trial outcomes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;There are some limitations in this study. Firstly, it is a retrospective research. Secondly, the TTR result in this study is sampled from a limited number of patients. These limitations might influence the generalizability of the findings and may not accurately reflect the entire population. Consequently, future studies with larger, prospective designs and a more diverse patient population are necessary to provide more comprehensive and reliable evidence in this area.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eHome monitoring for patients who have undergone cardiac valve replacement surgery can greatly enhance coagulation management. It empowers patients to keep track of their INR values from the comfort of their own home, eliminating the need for frequent hospital visits. This not only saves time and money on transportation but also allows patients to communicate their results to healthcare providers for prompt adjustments to their anticoagulation therapy. By combining home monitoring with patient education, patients can become more engaged and accountable in their anticoagulation treatment, potentially leading to better treatment compliance. In addition, regular monitoring of INR values at home can help lower the risk of complications like bleeding and blood clots, leading to better outcomes for patients. Using a nomogram chart can also make it easier to identify patients with consistent coagulation function for clinical trials. Providing early interventions such as medication reminders, drug monitoring, and home support can be beneficial for patients with coagulation issues. For patients at high risk, promoting home mornitoring or increasing the frequency of INR monitoring during outpatient visits can be a cost-effective way to improve treatment adherence.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003c/strong\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study received approval from the ethical committees of The First Affiliated Hospital Zhejiang University of Medicine (IIT20210517A) and\u0026nbsp;individual consent for this retrospective analysis was waived.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Hangzhou Chenghui Medical Instrument.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBurn J, Pirmohamed M. Direct oral anticoagulants versus warfarin: is new always better than the old? Open Heart. 2018;5:e000712. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/openhrt-2017-000712\u003c/span\u003e\u003cspan address=\"10.1136/openhrt-2017-000712\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeitz JI et al. Trends in Prescribing Oral Anticoagulants in Canada, 2008\u0026ndash;2014. \u003cem\u003eClin Ther\u003c/em\u003e 37, 2506\u0026ndash;2514 e2504, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.clinthera.2015.09.008\u003c/span\u003e\u003cspan address=\"10.1016/j.clinthera.2015.09.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVahanian A, et al. 2021 ESC/EACTS Guidelines for the management of valvular heart disease. Eur Heart J. 2022;43:561\u0026ndash;632. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/eurheartj/ehab395\u003c/span\u003e\u003cspan address=\"10.1093/eurheartj/ehab395\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnsell J. Point-of-care patient self-monitoring of oral vitamin K antagonist therapy. J Thromb Thrombolysis. 2013;35:339\u0026ndash;41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11239-013-0878-z\u003c/span\u003e\u003cspan address=\"10.1007/s11239-013-0878-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnsell J et al. Pharmacology and management of the vitamin K antagonists: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines (8th Edition). \u003cem\u003eChest\u003c/em\u003e 133, 160S-198S, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1378/chest.08-0670\u003c/span\u003e\u003cspan address=\"10.1378/chest.08-0670\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2008).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang H, Dong Y, Ao X, Zhu D, Dong L. Optimal oral anticoagulant therapy in Chinese patients with mechanical heart valves. Eur J Pharm Sci. 2020;144:105202. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ejps.2019.105202\u003c/span\u003e\u003cspan address=\"10.1016/j.ejps.2019.105202\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShen AY, Yao JF, Brar SS, Jorgensen MB, Chen W. Racial/ethnic differences in the risk of intracranial hemorrhage among patients with atrial fibrillation. J Am Coll Cardiol. 2007;50:309\u0026ndash;15. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jacc.2007.01.098\u003c/span\u003e\u003cspan address=\"10.1016/j.jacc.2007.01.098\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee SL, et al. Patients' time in therapeutic range on warfarin among atrial fibrillation patients in Warfarin Medication Therapy Adherence Clinic. World J Cardiol. 2021;13:483\u0026ndash;92. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4330/wjc.v13.i9.483\u003c/span\u003e\u003cspan address=\"10.4330/wjc.v13.i9.483\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThrombosis prevention trial. : randomised trial of low-intensity oral anticoagulation with warfarin and low-dose aspirin in the primary prevention of ischaemic heart disease in men at increased risk. The Medical Research Council's General Practice Research Framework. Lancet. 1998;351:233\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoulanger L, et al. Warfarin exposure and the risk of thromboembolic and major bleeding events among medicaid patients with atrial fibrillation. Ann Pharmacother. 2006;40:1024\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1345/aph.1G408\u003c/span\u003e\u003cspan address=\"10.1345/aph.1G408\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSolvik UO, et al. Quality of Warfarin Therapy and Quality of Life are Improved by Self-Management for Two Years. Thromb Haemost. 2019;119:1632\u0026ndash;41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1055/s-0039-1693703\u003c/span\u003e\u003cspan address=\"10.1055/s-0039-1693703\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRodriguez F, et al. Limited English proficient patients and time spent in therapeutic range in a warfarin anticoagulation clinic. J Am Heart Assoc. 2013;2:e000170. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1161/JAHA.113.000170\u003c/span\u003e\u003cspan address=\"10.1161/JAHA.113.000170\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKidd AC, et al. Survival prediction in mesothelioma using a scalable Lasso regression model: instructions for use and initial performance using clinical predictors. BMJ Open Respir Res. 2018;5:e000240. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmjresp-2017-000240\u003c/span\u003e\u003cspan address=\"10.1136/bmjresp-2017-000240\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFournier JP, et al. Concurrent use of statins and hormone therapy and risk of venous thromboembolism in postmenopausal women: a population-based case-control study. Menopause. 2014;21:1023\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/GME.0000000000000279\u003c/span\u003e\u003cspan address=\"10.1097/GME.0000000000000279\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZingone MM, Guirguis AB, Airee A, Cobb D. Probable drug interaction between warfarin and hormonal contraceptives. Ann Pharmacother. 2009;43:2096\u0026ndash;102. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1345/aph.1M382\u003c/span\u003e\u003cspan address=\"10.1345/aph.1M382\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAvarello I, Bianchi S, Toschi V, Zighetti ML, Faioni EM. Time in therapeutic range is lower in women than in men and is not explained by differences in age or comorbidity. Thromb Res. 2021;203:18\u0026ndash;21. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.thromres.2021.04.011\u003c/span\u003e\u003cspan address=\"10.1016/j.thromres.2021.04.011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu X, et al. Rosendaal linear interpolation method appraising of time in therapeutic range in patients with 12-week follow-up interval after mechanical heart valve replacement. Front Cardiovasc Med. 2022;9:925571. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fcvm.2022.925571\u003c/span\u003e\u003cspan address=\"10.3389/fcvm.2022.925571\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen QL, et al. Security and cost comparison of INR self-testing and conventional hospital INR testing in patients with mechanical heart valve replacement. J Cardiothorac Surg. 2015;10(4). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13019-015-0205-1\u003c/span\u003e\u003cspan address=\"10.1186/s13019-015-0205-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGadisseur AP, Kaptein AA, Breukink-Engbers WG, van der Meer FJ, Rosendaal FR. Patient self-management of oral anticoagulant care vs. management by specialized anticoagulation clinics: positive effects on quality of life. J Thromb Haemost. 2004;2:584\u0026ndash;91. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1538-7836.2004.00659.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1538-7836.2004.00659.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eConnock M et al. Clinical effectiveness and cost-effectiveness of different models of managing long-term oral anticoagulation therapy: a systematic review and economic modelling. \u003cem\u003eHealth Technol Assess\u003c/em\u003e 11, iii-iv, ix-66, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3310/hta11380\u003c/span\u003e\u003cspan address=\"10.3310/hta11380\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2007).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePatel MR, et al. Rivaroxaban versus warfarin in nonvalvular atrial fibrillation. N Engl J Med. 2011;365:883\u0026ndash;91. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1056/NEJMoa1009638\u003c/span\u003e\u003cspan address=\"10.1056/NEJMoa1009638\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIasonos A, Schrag D, Raj GV, Panageas KS. How to build and interpret a nomogram for cancer prognosis. J Clin Oncol. 2008;26:1364\u0026ndash;70. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1200/JCO.2007.12.9791\u003c/span\u003e\u003cspan address=\"10.1200/JCO.2007.12.9791\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBalachandran VP, Gonen M, Smith JJ, DeMatteo RP. Nomograms in oncology: more than meets the eye. Lancet Oncol. 2015;16:e173\u0026ndash;180. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S1470-2045(14)71116-7\u003c/span\u003e\u003cspan address=\"10.1016/S1470-2045(14)71116-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"INR control, time in therapeutic range (TTR), Home monitoring, Coagulation management, nomogram graph","lastPublishedDoi":"10.21203/rs.3.rs-4113572/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4113572/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003eThe research aims to analyze the impact of home monitoring on INR control and complications in patients undergoing valve replacement and plastic surgery. It is also the first to assess and predict associated risk factors by using a nomogram graph.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy Design: \u003c/strong\u003eA retrospective descriptive study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePlace and Duration of Study:\u003c/strong\u003e Department of Cardiovascular Surgery, The First Affiliated Hospital Zhejiang University of Medicine, from January 2021 to January 2023\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethodology:\u003c/strong\u003eConducted at the First Affiliated Hospital of Zhejiang University, the retrospective study\u003c/p\u003e\n\u003cp\u003einvolved 505 patients initially, with 406 completing the follow-up. Data collection included patient\u003c/p\u003e\n\u003cp\u003echaracteristic, medical history, valve replacement details, and INR values.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe study found that self-management of INR testing significantly improved the time in\u003c/p\u003e\n\u003cp\u003etherapeutic range (TTR), reduced INR variance, and decreased complications. Predictive factors for\u003c/p\u003e\n\u003cp\u003epostoperative coagulation control included gender, history of atrial fibrillation, preoperative\u003c/p\u003e\n\u003cp\u003emedication history, valve replacement type, and education level.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003eWith home monitoring of INR, patients can take more control of their coagulation management and decrease the frequency of hospital visits. Treatment compliance and outcomes are enhanced when this method is combined with patient education level. The use of a nomogram helps identify patients with stable coagulation function for clinical trials and allows for early intervention in high-risk patients.\u003c/p\u003e","manuscriptTitle":"Enhancing Coagulation Management after Cardiac Valve Replacement and Plastic: The Benefits of Home Monitoring","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-09 18:06:28","doi":"10.21203/rs.3.rs-4113572/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1462e9a8-6332-433c-a6ce-3b027b48d9b8","owner":[],"postedDate":"May 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-15T09:53:41+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-09 18:06:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4113572","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4113572","identity":"rs-4113572","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}