{
    "abstract": "The decision to convert from catheter to arteriovenous access is difficult yet very important. The ability to accurately predict fistula survival prior to surgery would significantly improve the decision making process. Many previously investigated demographic and clinical features have been associated with fistula failure. However, it is not conclusively understood how reliable predictions based on these parameters are at an individual level. The aim of this study was to investigate the probability of arteriovenous fistula maturation and survival after conversion using machine learning workflows.\nA retrospective cohort study on multicentre data from a large North American dialysis organisation was conducted. The study population comprised 73\u2009031 chronic in centre haemodialysis patients. The dataset included 49 variables including demographic and clinical features. Two distinct feature selection and prediction pipelines were used: LASSO regression and Boruta followed by a random forest classifier. Predictions were facilitated for re-conversion to catheter within one year. Additionally, all cause mortality predictions were conducted to serve as a comparator.\nIn total, 38\u2009151 patients (52.2%) had complete data and made up the main cohort. Sensitivity analyses were conducted in 67\u2009421 patients (92.3%) after eliminating variables with a high proportion of missing data points. Selected features diverged between datasets and workflows. A previously failed arteriovenous access appeared to be the most stable predictor for subsequent failure. Prediction of re-conversion based on the demographic and clinical information resulted in an area under the receiver operating characteristic curve (ROCAUC) between 0.541 and 0.571, whereas models predicting all cause mortality performed considerably better (ROCAUC 0.662 - 0.683).\nWhile group level depiction of major adverse outcomes after catheter to arteriovenous fistula or graft conversion is possible using the included variables, patient level predictions are associated with limited performance. Factors during and after fistula creation as well as biomolecular and genetic biomarkers might be more relevant predictors of fistula survival than baseline clinical conditions.",
    "authors": [
        {
            "affiliation": "Department of Vascular and Endovascular Surgery, Klinik Ottakring, Vienna, Austria. Electronic address: ah.reply@outlook.com.",
            "firstname": "Amun G",
            "initials": "AG",
            "lastname": "Hofmann"
        },
        {
            "affiliation": "Fresenius Medical Care, Global Medical Office, Waltham, MA, USA.",
            "firstname": "Suman",
            "initials": "S",
            "lastname": "Lama"
        },
        {
            "affiliation": "Renal Research Institute, New York, NY, USA.",
            "firstname": "Hanjie",
            "initials": "H",
            "lastname": "Zhang"
        },
        {
            "affiliation": "Department of Vascular and Endovascular Surgery, Klinik Ottakring, Vienna, Austria.",
            "firstname": "Afshin",
            "initials": "A",
            "lastname": "Assadian"
        },
        {
            "affiliation": "Azura Vascular Care, Malvern, PA, USA.",
            "firstname": "Murat",
            "initials": "M",
            "lastname": "Sor"
        },
        {
            "affiliation": "Fresenius Medical Care, Global Medical Office, Waltham, MA, USA.",
            "firstname": "Jeffrey",
            "initials": "J",
            "lastname": "Hymes"
        },
        {
            "affiliation": "Renal Research Institute, New York, NY, USA; Icahn School of Medicine at Mount Sinai, New York, NY, USA.",
            "firstname": "Peter",
            "initials": "P",
            "lastname": "Kotanko"
        },
        {
            "affiliation": "Renal Research Institute, New York, NY, USA; Katz School of Science and Health at Yeshiva University, New York, NY, USA.",
            "firstname": "Jochen",
            "initials": "J",
            "lastname": "Raimann"
        }
    ],
    "conclusions": "While group level depiction of major adverse outcomes after catheter to arteriovenous fistula or graft conversion is possible using the included variables, patient level predictions are associated with limited performance. Factors during and after fistula creation as well as biomolecular and genetic biomarkers might be more relevant predictors of fistula survival than baseline clinical conditions.",
    "copyrights": "Copyright \u00a9 2024 European Society for Vascular Surgery. Published by Elsevier B.V. All rights reserved.",
    "doi": "10.1016/j.ejvs.2024.06.002",
    "journal": "European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery",
    "keywords": [
        "Arteriovenous fistula",
        "Central venous catheter",
        "Haemodialysis",
        "Machine learning",
        "Vascular access"
    ],
    "methods": null,
    "publication_date": "2024-06-11",
    "pubmed_id": "38857878",
    "results": "In total, 38\u2009151 patients (52.2%) had complete data and made up the main cohort. Sensitivity analyses were conducted in 67\u2009421 patients (92.3%) after eliminating variables with a high proportion of missing data points. Selected features diverged between datasets and workflows. A previously failed arteriovenous access appeared to be the most stable predictor for subsequent failure. Prediction of re-conversion based on the demographic and clinical information resulted in an area under the receiver operating characteristic curve (ROCAUC) between 0.541 and 0.571, whereas models predicting all cause mortality performed considerably better (ROCAUC 0.662 - 0.683).",
    "title": "Editor's Choice - Challenges of Predicting Arteriovenous Access Survival Prior to Conversion from Catheter.",
    "xml": "<Element 'PubmedArticle' at 0x788503cc6520>"
}