DARE-ISC model for prediction of 1-year ischaemic stroke risk in the general population and atrial fibrillation patients: a Danish nationwide cohort study.

OBJECTIVES: To develop a risk assessment model (DAnish REgister Ischaemic Stroke Classifier, DARE-ISC) for predicting 1-year primary ischaemic stroke/systemic embolism (SE) in the general population. Secondly, to validate the accuracy DARE-ISC in atrial fibrillation (AF) patients where well-established models and risk scores exist. DESIGN: Retrospective cohort study. DARE-ISC was developed using gradient boosting decision trees with information from 375 covariates including baseline information on relevant diagnoses, demographic characteristics, registered health-services, lifestyle-related covariates, hereditary stroke components, drug prescriptions and stress proxies. SETTING: Danish nationwide registries. PARTICIPANTS: All Danish individuals aged ≥18 from 2010 to 2017 (n=35 519 348 person-years). The model was trained on the 2010-2016 cohorts with validation in the 2017 cohort. PRIMARY AND SECONDARY OUTCOME MEASURES: Model optimisation and validation were performed through comparison of the area under the receiver operating characteristic curve (AUC) and average precision scores. Additionally, the relative importance of the model covariates was derived using SHAP values. RESULTS: DARE-ISC had an AUC (95% CI) of 0.874 (0.871 to 0.876) in the general population. In AF patients, DARE-ISC was superior to the GARFIELD-AF risk model and CHA2DS2-VASc score with AUC of 0.779 (95% CI 0.75 to 0.806), 0.704 (95% CI 0.674 to 0.732) and 0.681 (95% CI 0.652 to 0.709), respectively. Furthermore, in AF patients, DARE-ISC had an average threefold and fourfold higher ratio of correctly identified strokes compared with the GARFIELD-AF risk model and CHA2DS2-VASc score, as indicated by average precision scores of 0.119, 0.041 and 0.034, respectively. CONCLUSIONS: DARE-ISC had a very high stroke prediction accuracy in the general population and was superior to the GARFIELD-AF risk model and CHA2DS2-VASc score for predicting ischaemic stroke/SE in AF patients.

Daily Self-Monitoring of Symptoms and Skills Learning in Patients With Borderline Personality Disorder Through a Mobile Phone App: Protocol for a Pragmatic Randomized Controlled Trial.

BACKGROUND: Patient self-monitoring via mobile phones during psychotherapy can enhance and provide an overview of psychotherapeutic progress by graphically displaying current and previous symptom scores, providing feedback to the patient, delivering psychoeducative material, and providing timely data to the therapist or treatment team. OBJECTIVE: This study will aim to assess the effects of using a mobile phone to self-monitor symptoms and acquire coping skills instead of using pen and paper during psychotherapy in patients with borderline personality disorder (BPD). Dialectical behavior therapy will be performed to treat BPD. The primary outcome is the mean time needed to learn coping skills directed at emotion regulation; the secondary outcome is changes in the BPD symptom score as measured by the Zanarini Rating Scale for Borderline Personality Disorder. METHODS: This study is a pragmatic, multicenter randomized controlled trial. Participants were recruited through five public general psychiatric outpatient treatment facilities in Denmark. Patients are randomly assigned, on a 1:1 basis, to either the mobile phone condition (using the Monsenso mDiary mobile app) or pen-and-paper condition. Patients will complete several self-report questionnaires on symptom severity; assessments by trained raters on BPD severity will be performed as well. Survival analysis with a shared frailty model will be used to assess the primary outcome. RESULTS: Recruitment began in June 2017 and was completed in February 2019 after 80 participants were recruited. The study ended in February 2020. It is expected that the benefits of mobile phone-based self-report compared to the pen-and-paper method will be demonstrated for skill learning speed and registration compliance. To our knowledge, this is the first trial exploring the impact of cloud-based mobile registration in BPD treatment. CONCLUSIONS: This trial will report on the effectiveness of mobile phone-based self-monitoring during psychiatric treatment. It has the potential to contribute to evidence-based clinical practice since apps are already in use clinically. TRIAL REGISTRATION: ClinicalTrials.gov NCT03191565; https://clinicaltrials.gov/ct2/show/NCT03191565. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/17737.

The costs of acute readmissions to a different hospital - Does the effect vary across provider types?

Treatment costs are found to vary substantially and systematically within DRGs. Several factors have been shown to contribute to the variation in costs within DRGs. We argue that readmissions might also explain part of the observed variation in costs. A substantial number of all readmissions occur to a different hospital. The change in hospital indicates that a progression of the illness has occurred since the initial hospitalisation. As a result, different-hospital readmissions might be more costly compared to same-hospital admissions. The aim of this paper is twofold. Firstly, to analyse differences in costs between different-hospital readmissions and same-hospital readmissions within the same DRG. Secondly, to investigate whether the effect of different-hospital readmission on costs vary depending of provider type (general versus teaching hospital). We use a rich Danish patient-level administrative data set covering inpatient stays in the period 2008-2010. We exploit the fact that some patients are readmitted within the same DRG and that some of these readmissions occur at different hospitals in a propensity score difference-in-difference design. The estimates are based on a restricted sample of n = 328 patients. Our results show that the costs of different-hospital readmissions are significantly higher relative to the costs of same-hospital readmission (approx. €777). Furthermore, the cost difference is found to be almost twice the size for patients readmitted to a teaching hospital (approx. €1016) (P < 0.10) compared to patients readmitted to a different general hospital (approx. €511) (P < 0.10). The results suggest that hospitals in general face a potential risk by treating different-hospital readmissions, and that the financial consequences are highest among teaching hospitals. If teaching hospitals are not compensated for the additional costs of treating different-hospital readmission patients, they might be unfairly funded under a DRG-based payment scheme.