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We aimed to describe clinical and diagnostic characteristics of primary care patients with heart failure and physicians’ adherence to guideline-directed medical therapy (GDMT) for treating chronic heart failure.
Cross-sectional study based on baseline data from the prospective primary care-based study Heart failure in Southern Sweden (HISS).
Patients with heart failure were included from 20 primary healthcare centres in the southernmost region of Sweden (Skåne).
Between 2020 and 2023, patients were included in HISS, resulting in a total of 587 participants. Of these, 558 patients (95% of the HISS participants) had available data on left ventricular ejection fraction and were included in this study. Adult patients aged 18 years or older diagnosed with heart failure (International Classification of Diseases, 10th Revision codes I50, I11.0, I42, I43) were considered eligible for inclusion in HISS. Community-dwelling patients with assisted care were excluded.
The primary outcome measures were distribution of heart failure subtypes and prescribed medications. The secondary outcomes were temporal trends in GDMT and the association between physicians’ adherence to GDMT and clinical characteristics of patients, using logistic regression models.
Heart failure with preserved ejection fraction (HFpEF) was the most prevalent subtype (42%), followed by mildly reduced (30%) and reduced ejection fraction (HFrEF, 28%). Among patients with HFrEF, 20% were prescribed the recommended GDMT according to the European Society of Cardiology (ESC) 2021 guidelines, which consisted of a renin-angiotensin system inhibitor, a beta-blocker, a mineralocorticoid receptor antagonist and a sodium-glucose 2 inhibitor. We observed no significant change in the prescribing trends for the quadruple therapy in patients with HFrEF when comparing the 2 years before and after the publication of the ESC 2021 guidelines. Similarly, we observed no association between patient characteristics and the prescription of GDMT according to ESC 2021 for patients with HFrEF.
HFpEF was the most prevalent subtype, with conclusive and recent echocardiography data among two-thirds of the cohort. Temporal trends in prescription patterns showed no appreciable increase in the use of GDMT for HFrEF during the two years following guideline publication compared with the two preceding years. These findings indicate a need for inclusion of primary care patients as a basis for intensified medical recommendations and implementation strategies.
Cardiac anxiety is common following acute coronary syndrome (ACS) and is characterised by fear of recurrence, heightened attention to cardiac sensations and avoidance of cardiac-related activities in daily life. It is associated with depression, reduced quality of life (QoL) and an adverse cardiac prognosis. We have developed a digital cognitive–behavioural therapy protocol for cardiac anxiety (CA-CBT) post ACS, previously evaluated in clinical trials including one randomised controlled trial (RCT), in which the intervention was compared to usual care. This protocol article describes a follow-up RCT, designed to further evaluate the efficacy of CA-CBT compared with an active control receiving a digital cardiac lifestyle intervention (CLI).
Participants with ACS (ST-elevation myocardial infarction (STEMI)/non-STEMI/unstable angina ≥6 months prior) and elevated cardiac anxiety (Cardiac Anxiety Questionnaire; CAQ ≥18 and as per clinical interviews) (n=176) are randomised 1:1 to 8 weeks of CA-CBT or CLI. Primary outcome is change in cardiac anxiety, measured by the CAQ, from pre-intervention to post-intervention. Analyses will be conducted according to the ‘intention-to-treat’ principle, using hierarchical linear mixed-effects model, with random intercepts and including 10 weekly assessments collected during the treatment period. Secondary outcomes include disease-specific Quality of Life (Heart QoL), depression (Patient Health Questionnaire-9), insomnia (Insomnia Severity Index), in addition to both self-rated and accelerometer-measured physical activity. Secondary outcomes will be analysed using similar statistical methods.
The study was approved by the Swedish Ethical Review Authority (Dnr 2023-07605-01), and the first patient enrolled on 7 March 2024. Recruitment is ongoing, and the completion date is expected to fall in the latter half of 2026. All participants receive information about the study and provide informed consent in accordance with ethical guidelines before inclusion. The results will be analysed at group level, and trial outcomes will be published in a peer-reviewed scientific journal, regardless of results.
Exposure is a central component in the treatment of a range of mental disorders. However, despite high efficacy and efficiency, dissemination of exposure-based treatments is limited. Important factors that contribute to this limited dissemination are negative beliefs about exposure on the part of the public, the therapists, and the patients. While patients perceive exposure therapy as burdensome, therapists are concerned about putting too much strain on their patients during exposure, leading to suboptimal delivery of exposure. In a previous study, in which healthy participants underwent a differential fear conditioning paradigm, we found initial evidence that the integration of a therapy dog into exposure reduces participants’ anxiety and increases participants’ positive affect without causing poor treatment outcome. Thus, the integration of a therapy dog into exposure might be a promising approach to address patients’ and therapists’ concerns and, thus, to (1) foster dissemination of exposure that is (2) delivered in an optimal manner. To scrutinise our findings in a clinical sample, we designed the present study. We test the following hypotheses: (H1) participants in the dog group report significantly less anxiety during the course of the treatment than participants in the control group. (H2) Participants in the dog group report significantly more positive affect during the course of the treatment than participants in the control group. (H3) Participants in the dog group report significantly higher therapy motivation than participants in the control group. (H4) Participants in the dog group report significantly lower anticipatory anxiety than participants in the control group. (H5) The treatment in the dog group is not inferior to the treatment in the control group.
In this parallel randomised controlled trial of two groups, n=88 participants (spider phobics without: a current diagnosis of a mental disorder other than a specific phobia, insect bite allergy, dog hair allergy, fear of dogs, current psychopharmacological treatment, and current psychotherapeutic treatment; the sample size calculation is based on the results from our previous study) are randomly allocated (with a 1:1 allocation as per a computer-generated randomisation schedule) to either an ambulant one-session in vivo exposure treatment of spider phobia with a therapy dog (dog group) or without a dog (control group). Due to the nature of the intervention, neither participants nor therapists can be blinded once participants are allocated to one of the two groups. However, the person conducting screening and diagnostics is blind to the allocation, participants are blind to the hypotheses and the respective other group, and the researchers are blind to the allocation while analysing the data. We will test (H1) and (H2), concerned with our primary outcomes, by means of 2x4 mixed analyses of variance with the between-subjects factor group (dog group vs. control group), the within-subjects factor time (with four levels, one for each time point anxiety and affect are measured during treatment), and anxiety or positive affect as the dependent variable, respectively. We will test (H3) and (H4) by means of an analyses of covariance with therapy motivation/anticipatory anxiety at baseline as the covariate, the between-subjects factor group (dog group vs. control group) and therapy motivation/anticipatory anxiety at pre-treatment as the dependent variable, respectively. We will test (H5) by means of 95% CIs and non-inferiority zones.
This trial was approved by our university’s ethics committee (reference number 24–11). Any deviations from this study protocol or the preregistrations as well as any adverse events potentially arising in the course of the trial, will be made explicit in the publication of the trial results. All participants provided written informed consent prior to the inclusion into the trial. The findings from this trial will be disseminated by means of common academic pathways, including peer-reviewed publications and conference presentations. Following common open science practices, data and analysis code will also be made publicly available in anonymised form on the Open Science Framework (osf.io).
On 18 June 2024, this study was registered at the German Clinical Trials Register (ID: DRKS00034494; https://drks.de/search/de/trial/DRKS00034494) and preregistered at AsPredicted (
Histopathological evaluation of prostate biopsies using the Gleason scoring system is critical for prostate cancer diagnosis and treatment selection. However, grading variability among pathologists can lead to inconsistent assessments, risking inappropriate treatment. Similar challenges complicate the assessment of other prognostic features like cribriform cancer morphology and perineural invasion. Many pathology departments are also facing an increasingly unsustainable workload due to rising prostate cancer incidence and a decreasing pathologist workforce coinciding with increasing requirements for more complex assessments and reporting. Digital pathology and artificial intelligence (AI) algorithms for analysing whole slide images show promise in improving the accuracy and efficiency of histopathological assessments. Studies have demonstrated AI’s capability to diagnose and grade prostate cancer comparably to expert pathologists. However, external validations on diverse data sets have been limited and often show reduced performance. Historically, there have been no well-established guidelines for AI study designs and validation methods. Diagnostic assessments of AI systems often lack preregistered protocols and rigorous external cohort sampling, essential for reliable evidence of their safety and accuracy.
This study protocol covers the retrospective validation of an AI system for prostate biopsy assessment. The primary objective of the study is to develop a high-performing and robust AI model for diagnosis and Gleason scoring of prostate cancer in core needle biopsies, and at scale evaluate whether it can generalise to fully external data from independent patients, pathology laboratories and digitalisation platforms. The secondary objectives cover AI performance in estimating cancer extent and detecting cribriform prostate cancer and perineural invasion. This protocol outlines the steps for data collection, predefined partitioning of data cohorts for AI model training and validation, model development and predetermined statistical analyses, ensuring systematic development and comprehensive validation of the system. The protocol adheres to Transparent Reporting of a multivariable prediction model of Individual Prognosis Or Diagnosis+AI (TRIPOD+AI), Protocol Items for External Cohort Evaluation of a Deep Learning System in Cancer Diagnostics (PIECES), Checklist for AI in Medical Imaging (CLAIM) and other relevant best practices.
Data collection and usage were approved by the respective ethical review boards of each participating clinical laboratory, and centralised anonymised data handling was approved by the Swedish Ethical Review Authority. The study will be conducted in agreement with the Helsinki Declaration. The findings will be disseminated in peer-reviewed publications (open access).
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