People with serious mental illness (SMI) can experience significant physical health challenges. The Health Champions intervention was developed to support their physical health through using trained volunteers. However, volunteer and patient perspectives on the impact and implementation of this intervention have yet to be understood.

To compare the views of patients and volunteers on the Health Champions intervention.

A qualitative thematic analysis was conducted on interviews with 29 study participants. Interviews were carried out either face-to-face, via Microsoft Teams, or by telephone and included 12 patients (6 men and 6 women) and 17 volunteers (the Health Champions) (5 men and 12 women).

Four overarching themes were identified, highlighting both similarities and differences between stakeholders’ perspectives: (1) supporting goal setting; (2) impact on positive lifestyle; (3) experiences and perception of the programme and (4) navigating challenges during the programme. Both groups found the programme to be largely successful, by motivating patients to work towards their physical health goals and facilitating successful matching of patients with volunteers. Volunteers and patients valued good communication with the research team. Though both groups shared some views on the challenges with scheduling and a lack of face-to-face contact during the COVID-19 pandemic, their perceptions on how patients incorporated their health changes during and after the programme, as well as other administrative concerns such as views on the efficacy of journaling and breakdown of roles, differed.

The Health Champions intervention was perceived as useful to improve the physical health of patients with SMI. Differences in the views between the two stakeholders may result from their distinct experiences and expectations. Future volunteering programmes should further support the diverse physical health needs of patients with SMI.

Self-care plays a pivotal role in the management of heart failure (HF). Health literacy and empowerment are considered the prerequisites of effective self-care. This project aims to improve self-management in people with HF by describing, analysing and enhancing the communication practices of clinicians and patients to support people with HF to increase their health literacy skills and participate in shared decision-making.

A multimethod research design incorporating an interview component, a concurrent mixed-methods component and a pilot intervention study is used. The study is currently being conducted at two Australian hospitals in metropolitan areas (one public and one private). The interview component involves semistructured interviews with healthcare providers and hospital executives and managers at the participating sites to explore perceived barriers and facilitators to HF self-management and understand the institutional context of HF care. The concurrent mixed-methods components include: (a) tracking and audio recording the clinical interactions of patients with HF (n=30) during their hospitalisation and up to 6 months after discharge and semistructured interviews with the patient (and the carer) and the participating clinician after each clinical interaction and (b) collecting longitudinal survey data (n=180, patients) to track patients’ health literacy, empowerment and self-management over 6 months. The pilot feasibility study includes developing a complex intervention for clinicians and patients and evaluating its acceptability and potential in improving health literacy and reducing readmissions, length of stay and costs.

This study was approved by the Australian Capital Territory Health (2023.ETH.00007) and Edith Cowan University (023–04314-SAUNDERS) Human Research Ethics Committees. Informed consent was obtained and will continue to be sought from all participants. Study results will be disseminated in peer-reviewed journals.

Assessment of Different NEoplasias in the adneXa (ADNEX) and Risk of Malignancy Index (RMI) are models that estimate the risk of malignancy in ovarian masses based on clinical and ultrasound information. The aim is to perform a meta-analysis of studies that compared the performance of the two models in the same patients (‘head-to-head comparison’).

Systematic review and meta-analysis.

Systematic literature search from publication of ADNEX model (15/10/2014) up to 31/07/2024 in Embase, Web of Science, Scopus, Medline (via PubMed) and EuropePMC.

We included all studies that externally validated the performance of ADNEX (with or without CA125) and RMI on the same data.

Two independent reviewers extracted data using a standardised extraction sheet. We assessed risk of bias using PROBAST. We performed random effects meta-analysis of the area under the receiver operating characteristic curve (AUC), sensitivity, specificity and clinical utility (net benefit, relative utility and probability of being useful in a hypothetical new centre) at thresholds commonly used clinically (10% risk of malignancy for ADNEX, 200 for RMI).

We included 11 studies comprising 8271 tumours. Most studies were at high risk of bias. The summary AUC to distinguish benign from malignant tumours in operated patients for ADNEX with CA125 was 0.92 (95% CI 0.90 to 0.94) and for RMI it was 0.85 (0.81 to 0.89). Sensitivity and specificity for ADNEX with CA125 were 0.93 (0.90 to 0.96) and 0.77 (0.71 to 0.81) and for RMI, they were 0.61 (0.56 to 0.67) and 0.92 (0.89 to 0.94). The probability of the test being useful in a hypothetical new centre in operated patients was 96% for ADNEX with CA125 and 15% for RMI at the selected thresholds.

ADNEX has better discrimination and clinical utility than RMI.

CMC are children who have complex chronic conditions, often with a spectrum of severity that requires ongoing healthcare.1 The changing landscape and increasing population of CMC across the world is due to improved health services and advancements in technologies.2 CMC are dependent on their parents and/or caregivers for the coordination of their care, including the...

Perioperative adverse events increase morbidity and mortality. The rate and severity of complications and the risk for subsequent mortality are increased after high-risk procedures and in elevated-risk patients. Over the past decades, a multitude of prognostic studies identified perioperative risk factors at the population level. However, to allow for the advancement of precision surgery strategies, improved risk prediction on the individual patient level is warranted. Comprehensive, consecutive, multisource, structured, high-quality patient-related and procedure-related data sets, together with thorough follow-up and combined with state-of-the-art machine-learning analyses, are needed to facilitate precise prediction of perioperative complications. Therefore, we designed and currently conduct the Heidelberg Perioperative Deep Data study (HeiPoDD). Here, we report the rationale and design of the HeiPoDD study.

HeiPoDD is a prospective, single-centre, exploratory cohort study aiming to build up a large-scale deep-data base and corresponding biomaterial collection. 1040 adult patients planned for elective high-risk, non-cardiac surgery for any indication at Heidelberg University Hospital, Germany will be included. The obtained study-specific data set includes clinical data, lab values, genome- and proteome analysis as well as plasma, serum and peripheral blood mononuclear cells (PBMC) collected before and at days 1, 3 and 7 postsurgery. Urine samples are collected before and at day 1 postsurgery. Structured follow-up for perioperative complications such as redo-surgery, length of intensive care stay or length of hospital stay is conducted at days 30, 90 and 1 year postsurgery and for disease progression and survival after 3 and 5 years postsurgery. All study data will be transferred to the HeiPoDD registry to allow merging with all available routine clinical data from the hospital information system including imaging studies as well as haemodynamic and respiratory biosignals. Biomaterials will be stored in the HeiPoDD biomaterial bank to allow further analyses.

The trial protocol and amendments were approved by the ethics committee of the University of Heidelberg (S-758/2021). The protocol is registered with the German Clinical Trial Register (DRKS00024625). Participating patients’ data will be recorded only in pseudonymised form. After completion of the study, data collected during the study will be kept on file for up to 30 years. Biomedical samples collected during the study and entered into the biobank will be held for the same amount of time. The findings will be disseminated in peer-reviewed academic journals.

Outcome after surgery depends on both patient-related as well as procedure-related risks. Complications after surgery are a significant burden to patients and to the health system. A vast amount of often unstructured data from different sources are generated during surgery, which contain valuable information associated with outcome. Advances in computer hardware and machine learning now increasingly facilitate the development of prediction models in standardised, parametric, information-rich areas such as the perioperative setting. For the development and validation of risk scores and prediction models, high-fidelity data sources are required to arrive at meaningful and reliable predictions. However, data quality standards in retrospective studies are rarely met. Therefore, the prospective Heidelberg Perioperative Deep Data Registry and Biomaterial Bank (HeiPoDD - Registry and Bio Bank) was started to implement a clinical data base and a corresponding biobank merging the entirety of available clinical records.

The HeiPoDD - Registry and Bio Bank is a study-driven, prospective, single-centre observational registry data base and biomaterial bank. It contains data and material from eligible patients who give informed consent and undergo elective non-cardiac high-risk surgery at the surgical centre of the Heidelberg University Hospital. The screening for eligibility started in January 2022, with no maximum sample size specified in advance. Routine data are recorded and stored during hospital stay and potential readmissions within 90 days after index surgery. The data are merged with the potentially available genome, proteome, flow cytometry, and bio signal data. Endpoints are obtained from routine observations, stored data in the hospital information system and follow-up visits. Further, data and biological specimens from separate perioperative studies with the patients’ consent can be transferred into the HeiPoDD - Registry and Bio Bank as well. This large-scale data collection will allow the calculation of endpoint-specific prediction models using logistic regression models as well as machine learning models. The first 1040 patients included in the HeiPoDD - Registry and Bio Bank are also included in the HeiPoDD study.

The trial protocol and subsequent amendments were approved by the ethics committee of the University of Heidelberg (S-745/2021). Participating patients’ data will be entered only in pseudonymised form. Data and biomaterials will be kept for up to 30 years. The findings will be disseminated in peer-reviewed academic journals.

DRKS00025924, registered on 2021-11-12.