{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T01:57:22Z","timestamp":1777946242781,"version":"3.51.4"},"reference-count":61,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2024,8,29]],"date-time":"2024-08-29T00:00:00Z","timestamp":1724889600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Blair Foundation"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proteomes"],"abstract":"<jats:p>Soluble interleukin 1 receptor-like 1 (ST2) is a circulating protein demonstrated to be associated with cardiovascular diseases; however, it has not been studied as a biomarker for peripheral artery disease (PAD). Using a prospectively recruited cohort of 476 patients (312 with PAD and 164 without PAD), we conducted a prognostic study of PAD using clinical\/biomarker data. Plasma concentrations of three circulating proteins [ST2, cytokine-responsive gene-2 (CRG-2), vascular endothelial growth factor (VEGF)] were measured at baseline and the cohort was followed for 2 years. The outcome of interest was a 2-year major adverse limb event (MALE; composite of major amputation, vascular intervention, or acute limb ischemia). Using 10-fold cross-validation, a random forest model was trained using clinical characteristics and plasma ST2 levels. The primary model evaluation metric was the F1 score. Out of the three circulating proteins analyzed, ST2 was the only one that was statistically significantly higher in individuals with PAD compared to patients without PAD (mean concentration in plasma of 9.57 [SD 5.86] vs. 11.39 [SD 6.43] pg\/mL, p &lt; 0.001). Over a 2-year period, 28 (9%) patients with PAD experienced MALE. Our predictive model, incorporating clinical features and plasma ST2 levels, achieved an F1 score of 0.713 for forecasting 2-year MALE outcomes. Patients identified as high-risk by this model showed a significantly increased likelihood of developing MALE (HR 1.06, 95% CI 1.02\u20131.13, p = 0.003). By combining clinical characteristics and plasma ST2 levels, our proposed predictive model offers accurate risk assessment for 2-year MALE in PAD patients. This algorithm supports risk stratification in PAD, guiding clinical decisions regarding further vascular evaluation, specialist referrals, and appropriate medical or surgical interventions, thereby potentially enhancing patient outcomes.<\/jats:p>","DOI":"10.3390\/proteomes12030024","type":"journal-article","created":{"date-parts":[[2024,8,29]],"date-time":"2024-08-29T11:09:53Z","timestamp":1724929793000},"page":"24","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Investigating the Prognostic Potential of Plasma ST2 in Patients with Peripheral Artery Disease: Identification and Evaluation"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7191-1034","authenticated-orcid":false,"given":"Ben","family":"Li","sequence":"first","affiliation":[{"name":"Department of Surgery, University of Toronto, Toronto, ON M5S 1A1, Canada"},{"name":"Division of Vascular Surgery, St. Michael\u2019s Hospital, Unity Health Toronto, University of Toronto, Toronto, ON M5B 1W8, Canada"},{"name":"Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A1, Canada"},{"name":"Temerty Centre for Artificial Intelligence Research and Education in Medicine (T-CAIREM), University of Toronto, Toronto, ON M5S 1A1, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Farah","family":"Shaikh","sequence":"additional","affiliation":[{"name":"Division of Vascular Surgery, St. Michael\u2019s Hospital, Unity Health Toronto, University of Toronto, Toronto, ON M5B 1W8, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abdelrahman","family":"Zamzam","sequence":"additional","affiliation":[{"name":"Division of Vascular Surgery, St. Michael\u2019s Hospital, Unity Health Toronto, University of Toronto, Toronto, ON M5B 1W8, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rawand","family":"Abdin","sequence":"additional","affiliation":[{"name":"Department of Medicine, McMaster University, Hamilton, ON L8S 4L8, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammad","family":"Qadura","sequence":"additional","affiliation":[{"name":"Department of Surgery, University of Toronto, Toronto, ON M5S 1A1, Canada"},{"name":"Division of Vascular Surgery, St. Michael\u2019s Hospital, Unity Health Toronto, University of Toronto, Toronto, ON M5B 1W8, Canada"},{"name":"Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A1, Canada"},{"name":"Li Ka Shing Knowledge Institute, St. Michael\u2019s Hospital, Unity Health Toronto, University of Toronto, Toronto, ON M5B 1W8, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,29]]},"reference":[{"key":"ref_1","unstructured":"Zemaitis, M.R., Boll, J.M., and Dreyer, M.A. (2021). Peripheral Arterial Disease. StatPearls, StatPearls Publishing."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"678","DOI":"10.4065\/mcp.2010.0133","article-title":"Peripheral Artery Disease: Current Insight into the Disease and Its Diagnosis and Management","volume":"85","author":"Olin","year":"2010","journal-title":"Mayo Clin. Proc."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1016\/j.tcm.2020.06.005","article-title":"Premature Atherosclerotic Peripheral Artery Disease: An Underrecognized and Undertreated Disorder with a Rising Global Prevalence","volume":"31","author":"Mehta","year":"2021","journal-title":"Trends Cardiovasc. Med."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"101766","DOI":"10.1016\/j.eclinm.2022.101766","article-title":"Validating Fatty Acid Binding Protein 3 as a Diagnostic and Prognostic Biomarker for Peripheral Arterial Disease: A Three-Year Prospective Follow-up Study","volume":"55","author":"Zamzam","year":"2023","journal-title":"eClinicalMedicine"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Stojkovic, S., Demyanets, S., Kopp, C.W., Hengstenberg, C., Wojta, J., Eichelberger, B., Panzer, S., and Gremmel, T. (2020). Association of Soluble Suppression of Tumorigenesis 2 (sST2) with Platelet Activation, Monocyte Tissue Factor and Ischemic Outcomes Following Angioplasty and Stenting. Front. Cardiovasc. Med., 7.","DOI":"10.3389\/fcvm.2020.605669"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3418","DOI":"10.1182\/blood.V93.10.3418.410k23_3418_3431","article-title":"Vascular Endothelial Genes That Are Responsive to Tumor Necrosis Factor-Alpha in Vitro Are Expressed in Atherosclerotic Lesions, Including Inhibitor of Apoptosis Protein-1, Stannin, and Two Novel Genes","volume":"93","author":"Horrevoets","year":"1999","journal-title":"Blood"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1080\/14728222.2021.1940139","article-title":"Peripheral Vascular Disease: Preclinical Models and Emerging Therapeutic Targeting of the Vascular Endothelial Growth Factor Ligand-Receptor System","volume":"25","author":"Ganta","year":"2021","journal-title":"Expert Opin. Ther. Targets"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1595","DOI":"10.1016\/j.jvs.2018.07.027","article-title":"Medical and Lifestyle Management of Peripheral Arterial Disease","volume":"68","author":"Parvar","year":"2018","journal-title":"J. Vasc. Surg."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Cornejo Del R\u00edo, V., Mostaza, J., Lahoz, C., S\u00e1nchez-Arroyo, V., Sab\u00edn, C., L\u00f3pez, S., Patr\u00f3n, P., Fern\u00e1ndez-Garc\u00eda, P., Fern\u00e1ndez-Puntero, B., and Vicent, D. (2017). Prevalence of Peripheral Artery Disease (PAD) and Factors Associated: An Epidemiological Analysis from the Population-Based Screening PRE-Diabetes and Type 2 DIAbetes (SPREDIA-2) Study. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0186220"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"342","DOI":"10.1177\/1358863X12445102","article-title":"An Evidence-Based Score to Detect Prevalent Peripheral Artery Disease (PAD)","volume":"17","author":"Duval","year":"2012","journal-title":"Vasc. Med."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.atherosclerosis.2021.07.003","article-title":"Clinical Factors Associated with Peripheral Artery Disease in Patients with Documented Coronary Artery Disease: A Post Hoc Analysis of the COMPASS Trial","volume":"331","author":"Gouda","year":"2021","journal-title":"Atherosclerosis"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"World Medical Association (2013). World Medical Association Declaration of Helsinki: Ethical Principles for Medical Research Involving Human Subjects. JAMA, 310, 2191\u20132194.","DOI":"10.1001\/jama.2013.281053"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"e078378","DOI":"10.1136\/bmj-2023-078378","article-title":"TRIPOD + AI Statement: Updated Guidance for Reporting Clinical Prediction Models That Use Regression or Machine Learning Methods","volume":"385","author":"Collins","year":"2024","journal-title":"BMJ"},{"key":"ref_14","unstructured":"Gul, F., and Janzer, S.F. (2021). Peripheral Vascular Disease. StatPearls, StatPearls Publishing."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"e285","DOI":"10.1016\/j.jacc.2018.11.003","article-title":"2018 AHA\/ACC\/AACVPR\/AAPA\/ABC\/ACPM\/ADA\/AGS\/APhA\/ASPC\/NLA\/PCNA Guideline on the Management of Blood Cholesterol","volume":"73","author":"Grundy","year":"2019","journal-title":"J. Am. Coll. Cardiol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"e127","DOI":"10.1016\/j.jacc.2017.11.006","article-title":"2017 ACC\/AHA\/AAPA\/ABC\/ACPM\/AGS\/APhA\/ASH\/ASPC\/NMA\/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults","volume":"71","author":"Whelton","year":"2018","journal-title":"J. Am. Coll. Cardiol."},{"key":"ref_17","unstructured":"(2023, May 06). Luminex Assays, Multiplex Immunoassays. Available online: https:\/\/www.bio-techne.com\/."},{"key":"ref_18","unstructured":"(2021, December 18). MAGPIX\u00ae System|xMAP Instrument|Luminex Corporation. Available online: https:\/\/www.luminexcorp.com\/magpix-system\/."},{"key":"ref_19","unstructured":"(2021, December 18). Luminex Assays\u2014CA. Available online: https:\/\/www.thermofisher.com\/ca\/en\/home\/life-science\/antibodies\/immunoassays\/procartaplex-assays-luminex.html."},{"key":"ref_20","unstructured":"(2024). xPONENT\u00ae Software for xMAP\u00ae Instruments, Luminex Corporation."},{"key":"ref_21","unstructured":"(2024, July 15). Understanding LLD, LLOQ, and ULOQ in Luminex Multiplex Cytokine Assays\u2014Creative Proteomics. Available online: https:\/\/cytokine.creative-proteomics.com\/llq-lloq-uloq-luminex-cytokine-assays.htm."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"31","DOI":"10.17849\/insm-47-01-31-39.1","article-title":"Random Forest","volume":"47","author":"Rigatti","year":"2017","journal-title":"J. Insur. Med."},{"key":"ref_23","first-page":"130","article-title":"Decision Tree Methods: Applications for Classification and Prediction","volume":"27","author":"Song","year":"2015","journal-title":"Shanghai Arch. Psychiatry"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1016\/j.jss.2021.02.045","article-title":"Machine Learning and Surgical Outcomes Prediction: A Systematic Review","volume":"264","author":"Elfanagely","year":"2021","journal-title":"J. Surg. Res."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"3100","DOI":"10.1007\/s00268-022-06728-1","article-title":"Machine Learning Algorithms for Predicting Surgical Outcomes after Colorectal Surgery: A Systematic Review","volume":"46","author":"Tuynman","year":"2022","journal-title":"World J. Surg."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"476","DOI":"10.1016\/j.wneu.2017.09.149","article-title":"Machine Learning and Neurosurgical Outcome Prediction: A Systematic Review","volume":"109","author":"Senders","year":"2018","journal-title":"World Neurosurg."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"569","DOI":"10.6339\/21-JDS1023","article-title":"Variable Importance Scores","volume":"19","author":"Loh","year":"2021","journal-title":"J. Data Sci."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Hicks, S.A., Str\u00fcmke, I., Thambawita, V., Hammou, M., Riegler, M.A., Halvorsen, P., and Parasa, S. (2022). On Evaluation Metrics for Medical Applications of Artificial Intelligence. Sci. Rep., 12.","DOI":"10.1038\/s41598-022-09954-8"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"419","DOI":"10.1002\/bimj.200710415","article-title":"Youden Index and Optimal Cut-Point Estimated from Observations Affected by a Lower Limit of Detection","volume":"50","author":"Ruopp","year":"2008","journal-title":"Biom. J."},{"key":"ref_30","unstructured":"(2021, December 18). SPSS Software. Available online: https:\/\/www.ibm.com\/analytics\/spss-statistics-software."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Li, B., Shaikh, F., Zamzam, A., Syed, M.H., Abdin, R., and Qadura, M. (2024). The Identification and Evaluation of Interleukin-7 as a Myokine Biomarker for Peripheral Artery Disease Prognosis. J. Clin. Med., 13.","DOI":"10.3390\/jcm13123583"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"e004741","DOI":"10.1161\/CIRCOUTCOMES.118.004741","article-title":"Predicting Future Cardiovascular Events in Patients with Peripheral Artery Disease Using Electronic Health Record Data","volume":"12","author":"Ross","year":"2019","journal-title":"Circ. Cardiovasc. Qual. Outcomes"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"827","DOI":"10.1038\/nrd2660","article-title":"The IL-33\/ST2 Pathway: Therapeutic Target and Novel Biomarker","volume":"7","author":"Kakkar","year":"2008","journal-title":"Nat. Rev. Drug Discov."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1007\/s12265-013-9459-y","article-title":"ST2 as a Cardiovascular Risk Biomarker: From the Bench to the Bedside","volume":"6","author":"Januzzi","year":"2013","journal-title":"J. Cardiovasc. Transl. Res."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Stojkovic, S., Kaun, C., Basilio, J., Rauscher, S., Hell, L., Krychtiuk, K.A., Bonstingl, C., de Martin, R., Gr\u00f6ger, M., and Ay, C. (2016). Tissue Factor Is Induced by Interleukin-33 in Human Endothelial Cells: A New Link between Coagulation and Inflammation. Sci. Rep., 6.","DOI":"10.1038\/srep25171"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2080","DOI":"10.1161\/ATVBAHA.111.231431","article-title":"Interleukin-33 Induces Expression of Adhesion Molecules and Inflammatory Activation in Human Endothelial Cells and in Human Atherosclerotic Plaques","volume":"31","author":"Demyanets","year":"2011","journal-title":"Arterioscler. Thromb. Vasc. Biol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1379","DOI":"10.1160\/TH16-10-0784","article-title":"IL-33 Stimulates the Release of Procoagulant Microvesicles from Human Monocytes and Differentially Increases Tissue Factor in Human Monocyte Subsets","volume":"117","author":"Stojkovic","year":"2017","journal-title":"Thromb. Haemost."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/j.cyto.2014.02.014","article-title":"An Increase of Interleukin-33 Serum Levels after Coronary Stent Implantation Is Associated with Coronary in-Stent Restenosis","volume":"67","author":"Demyanets","year":"2014","journal-title":"Cytokine"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Demyanets, S., Speidl, W.S., Tentzeris, I., Jarai, R., Katsaros, K.M., Farhan, S., Krychtiuk, K.A., Wonnerth, A., Weiss, T.W., and Huber, K. (2014). Soluble ST2 and Interleukin-33 Levels in Coronary Artery Disease: Relation to Disease Activity and Adverse Outcome. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0095055"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1016\/j.cyto.2019.05.010","article-title":"IL-33\/IL-33R in Various Types of Carotid Artery Atherosclerotic Lesions","volume":"120","author":"Stankovic","year":"2019","journal-title":"Cytokine"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1163","DOI":"10.1016\/j.ahj.2011.03.025","article-title":"Interleukin 33 and ST2 in Non-ST-Elevation Myocardial Infarction: Comparison with Global Registry of Acute Coronary Events Risk Scoring and NT-proBNP","volume":"161","author":"Dhillon","year":"2011","journal-title":"Am. Heart J."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"2193","DOI":"10.1016\/j.jacc.2019.08.1039","article-title":"Clinical and Prognostic Significance of sST2 in Heart Failure: JACC Review Topic of the Week","volume":"74","author":"Aimo","year":"2019","journal-title":"J. Am. Coll. Cardiol."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"e325","DOI":"10.1016\/j.jvs.2022.03.761","article-title":"Urinary Fatty Acid Binding Protein 3 (uFABP3) Has Diagnostic and Prognostic Value in Peripheral Artery Disease","volume":"75","author":"Li","year":"2022","journal-title":"J. Vasc. Surg."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Li, B., Djahanpour, N., Zamzam, A., Syed, M.H., Jain, S., Arfan, S., Abdin, R., and Qadura, M. (2022). The Prognostic Capability of Inflammatory Proteins in Predicting Peripheral Artery Disease Related Adverse Events. Front. Cardiovasc. Med., 9.","DOI":"10.3389\/fcvm.2022.1073751"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"109081","DOI":"10.1016\/j.isci.2024.109081","article-title":"A Machine Learning Algorithm for Peripheral Artery Disease Prognosis Using Biomarker Data","volume":"27","author":"Li","year":"2024","journal-title":"iScience"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1016\/j.jvs.2024.03.450","article-title":"Development and Evaluation of a Prediction Model for Peripheral Artery Disease-Related Major Adverse Limb Events Using Novel Biomarker Data","volume":"80","author":"Li","year":"2024","journal-title":"J. Vasc. Surg."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Li, B., Zamzam, A., Syed, M.H., Jahanpour, N., Jain, S., Abdin, R., and Qadura, M. (2022). Urinary Cystatin C Has Prognostic Value in Peripheral Artery Disease. Biomolecules, 12.","DOI":"10.3390\/biom12070860"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1099","DOI":"10.1111\/j.1553-2712.2011.01185.x","article-title":"Logistic Regression: A Brief Primer","volume":"18","author":"Stoltzfus","year":"2011","journal-title":"Acad. Emerg. Med."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Kia, B., Mendes, A., Parnami, A., George, R., Mobley, K., and Ditto, W.L. (2020). Nonlinear Dynamics Based Machine Learning: Utilizing Dynamics-Based Flexibility of Nonlinear Circuits to Implement Different Functions. PLoS ONE, 15.","DOI":"10.1371\/journal.pone.0228534"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1179","DOI":"10.1007\/s12551-021-00849-y","article-title":"Human Disease Biomarker Panels through Systems Biology","volume":"13","author":"Smith","year":"2021","journal-title":"Biophys. Rev."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Couronn\u00e9, R., Probst, P., and Boulesteix, A.-L. (2018). Random Forest versus Logistic Regression: A Large-Scale Benchmark Experiment. BMC Bioinform., 19.","DOI":"10.1186\/s12859-018-2264-5"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1833","DOI":"10.1161\/CIRCRESAHA.121.318224","article-title":"Leveraging Machine Learning and Artificial Intelligence to Improve Peripheral Artery Disease Detection, Treatment, and Outcomes","volume":"128","author":"Flores","year":"2021","journal-title":"Circ. Res."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1136\/jms.9.3.133","article-title":"Baseline Tests or Screening: What Tests Do Family Physicians Order Routinely on Their Healthy Patients?","volume":"9","author":"Nakar","year":"2002","journal-title":"J. Med. Screen."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1016\/S0895-7967(02)70029-X","article-title":"Accreditation and Credentialing in the Vascular Laboratory","volume":"15","author":"Akbari","year":"2002","journal-title":"Semin. Vasc. Surg."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"584","DOI":"10.1136\/bmj.326.7389.584","article-title":"Management of Peripheral Arterial Disease in Primary Care","volume":"326","author":"Burns","year":"2003","journal-title":"BMJ"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"352","DOI":"10.1111\/j.1445-2197.2007.04058.x","article-title":"Vascular Surgery Consults: A Significant Workload","volume":"77","author":"Koh","year":"2007","journal-title":"ANZ J. Surg."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"e313","DOI":"10.1161\/ATVBAHA.120.313609","article-title":"Recent Advances in Vascular Imaging","volume":"40","author":"Nishimiya","year":"2020","journal-title":"Arterioscler. Thromb. Vasc. Biol."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"1319","DOI":"10.1056\/NEJMoa1709118","article-title":"Rivaroxaban with or without Aspirin in Stable Cardiovascular Disease","volume":"377","author":"Eikelboom","year":"2017","journal-title":"N. Engl. J. Med."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"2305","DOI":"10.1056\/NEJMoa2207899","article-title":"Surgery or Endovascular Therapy for Chronic Limb-Threatening Ischemia","volume":"387","author":"Farber","year":"2022","journal-title":"N. Engl. J. Med."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1449","DOI":"10.1007\/s00270-020-02604-4","article-title":"Successful Revascularization Has a Significant Impact on Limb Salvage Rate and Wound Healing for Patients with Diabetic Foot Ulcers: Single-Centre Retrospective Analysis with a Multidisciplinary Approach","volume":"43","author":"Caetano","year":"2020","journal-title":"Cardiovasc. Interv. Radiol."},{"key":"ref_61","first-page":"727","article-title":"Health Care Resources and Costs for Treating Peripheral Artery Disease in a Managed Care Population: Results from Analysis of Administrative Claims Data","volume":"11","author":"Margolis","year":"2005","journal-title":"J. Manag. Care Pharm."}],"container-title":["Proteomes"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2227-7382\/12\/3\/24\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:44:47Z","timestamp":1760111087000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2227-7382\/12\/3\/24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,29]]},"references-count":61,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2024,9]]}},"alternative-id":["proteomes12030024"],"URL":"https:\/\/doi.org\/10.3390\/proteomes12030024","relation":{},"ISSN":["2227-7382"],"issn-type":[{"value":"2227-7382","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8,29]]}}}