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  • 1.
    Blom, Mathias Carl
    et al.
    Department of Clinical Sciences, Lund University, Lund, Sweden.
    Ashfaq, Awais
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. Halland Hospital, Region Halland, Halmstad, Sweden.
    Pinheiro Sant'Anna, Anita
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Anderson, Philip D.
    Department of Emergency Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, USA & Harvard Medical School, Boston, Massachusetts, USA.
    Lingman, Markus
    Halland Hospital, Region Halland, Sweden & Department of Molecular and Clinical Medicine/Cardiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
    Training machine learning models to predict 30-day mortality in patients discharged from the emergency department: a retrospective, population based registry study2019In: BMJ Open, ISSN 2044-6055, E-ISSN 2044-6055, Vol. 9, no 8, article id e028015Article in journal (Refereed)
    Abstract [en]

    Background: Aggressive treatment at end-of-life (EOL) can be traumatic to patients and may not add clinical benefit. Absent an accurate prognosis of death, individual level biases may prevent timely discussions about the scope of EOL care and patients are at risk of being subject to care against their desire. The aim of this work is to develop predictive algorithms for identifying patients at EOL, with clinically meaningful discriminatory power.

    Methods: Retrospective, population-based study of patients utilizing emergency departments (EDs) in Sweden, Europe. Electronic health records (EHRs) were used to train supervised learning algorithms to predict all-cause mortality within 30 days following ED discharge. Algorithm performance was validated out of sample on EHRs from a separate hospital, to which the algorithms were previously unexposed.

    Results: Of 65,776 visits in the development set, 136 (0.21%) experienced the outcome. The algorithm with highest discrimination attained ROC-AUC 0.945 (95% CI 0.933 - 0.956), with sensitivity 0.869 (95% CI 0.802, 0.931) and specificity 0.858 (0.855, 0.860) on the validation set.

    Conclusions: Multiple algorithms displayed excellent discrimination and outperformed available indexes for short-term mortality prediction. The practical utility of the algorithms increases as the required data were captured electronically and did not require de novo data collection.

    Trial registration number: Not applicable.

  • 2.
    Landgren, Ellen
    et al.
    Department of Clinical Sciences, Section of Rheumatology, Lund University, Lund, Sweden & Skåne University Hospital, Lund, Sweden & RandD Spenshult, Halmstad, Sweden.
    Bremander, Ann
    Department of Clinical Sciences, Section of Rheumatology, Lund University, Lund, Sweden & Skåne University Hospital, Lund, Sweden & RandD Spenshult, Halmstad, Sweden & Department of Regional Health Research, University of Southern Denmark, Odense, Denmark & Danish Hospital for Rheumatic Diseases, University Hospital of Southern Denmark, Sonderborg, Denmark.
    Lindqvist, Elisabeth
    Department of Clinical Sciences, Section of Rheumatology, Lund University, Lund, Sweden & Skåne University Hospital, Lund, Sweden.
    Van der Elst, Kristien
    Department of Rheumatology, University Hospitals Leuven, Leuven, Belgium & Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven–University of Leuven, Leuven, Belgium.
    Larsson, Ingrid
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI). RandD Spenshult, Halmstad, Sweden.
    “To regain one’s health” – patients’ preferencesof treatment outcomes in early rheumatoid arthritis – a qualitative study2019In: Annals of the Rheumatic Diseases, ISSN 0003-4967, E-ISSN 1468-2060, Vol. 78, no Suppl 2, p. 648-648Article in journal (Refereed)
    Abstract [en]

    Background: Rheumatology care strives to identify and meet the needs of the patients, and to understand disease and treatment impact from the patients’ perspective. A better understanding of patients’ expectations from the treatment is needed to enable a patient centered approach in clinical practice and a shared-decision making as recommended in the EULAR treatment recommendations for rheumatoid arthritis (RA). Understanding of patients’ expectations in the early stage of the RA disease may facilitate adherence to treatment, patient independence and prevent unmet needs in the future.

    Objectives: To explore patients’ preferred treatment outcomes in early rheumatoid arthritis (eRA).

    Methods: A qualitative, explorative study. Individual interviews were conducted with 31 patients with eRA, defined as disease duration of ≤ 1 year and disease-modifying antirheumatic drugs (DMARDs) treatment for 3-6 months 1 . Interviews were analyzed using a constant comparison method according to the Qualitative Analysis Guide of Leuven (QUAGOL) and lasted in a core category and four related concepts.

    Results: The patient-preferred treatment outcomes in eRA were described in the core category “to regain one’s health” and the four related concepts: to experience external control of the disease, to experience independence, to regain identity and to experience joy in everyday life. The patients expected to experience external control of the disease by the given treatment to regain one’s health. It was perceived as controlling the symptoms and as absence of disease. Independence was perceived as regaining former activity levels, experiencing autonomy and using active coping strategies. Patients wanted to regain identity through participation, empowerment and their self-image. Joy in everyday life was perceived as vitality and believing in the future.

    Conclusion: Patients’ preferred treatment outcomes in eRA were to regain one’s health including both external and internal control. External control as disease control and independence as well as internal control as identity and joy in everyday life. The results from this study can assist healthcare professionals to better understand patients’ preferred treatment outcomes early in the disease process and to tailor the interventions accordingly to improve long term treatment outcome. © Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.

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