The one-minute sit-to-stand-test performance is associated with health-related quality of life in patients with pulmonary hypertension.

INTRODUCTION: Patients with pulmonary hypertension (PH) have an impaired functional capacity and poor health-related quality of life (HRQoL). The one-minute sit-to-stand test (1-min STST) can be used for the assessment of functional capacity. AIMS: Our aim was to evaluate the 1-min STST performance and its association with patient-reported HRQoL in patients with PH. METHODS: We prospectively assessed functional capacity in 98 PH patients (mean age 66 ± 15 years, 55% female) using the 1-min STST. Patients had to stand up and sit down from a chair as many times as possible within one minute. Patients' HRQoL was evaluated with the Cambridge Pulmonary Hypertension Outcome Review (CAMPHOR) questionnaire, which consists of the three subcategories symptoms, activities and quality of life (QoL). RESULTS: We observed a significant correlation of the 1-min STST performance with all HRQoL subcategories assessed with the CAMPHOR questionnaire: A lower number of 1-min STST repetitions correlated with more symptoms (rs = -.398, p < .001), worse functioning (rs = -.551, p < .001) and a decreased QoL (rs = -.407, p < .001). Furthermore, in the multivariable linear regression analysis, adjusted for age, sex, body mass index (BMI) and mean pulmonary artery pressure (mPAP), lower 1-min STST performance was an independent predictor for worse symptoms (est. ß = -0.112, p = .003), activities (est. ß = -0.198, p < .001) and QoL (est. ß = -0.130, p < .001) assessed with the CAMPHOR questionnaire. CONCLUSION: Our results indicate that regardless of age, sex, BMI and mPAP the 1-min STST performance is associated with all CAMPHOR HRQoL subcategories in patients with PH. Therefore, the 1-min STST performance might be a new option to assess functional capacity correlated to HRQoL in patients with PH.

AI assisted reader evaluation in acute CT head interpretation (AI-REACT): protocol for a multireader multicase study.

INTRODUCTION: A non-contrast CT head scan (NCCTH) is the most common cross-sectional imaging investigation requested in the emergency department. Advances in computer vision have led to development of several artificial intelligence (AI) tools to detect abnormalities on NCCTH. These tools are intended to provide clinical decision support for clinicians, rather than stand-alone diagnostic devices. However, validation studies mostly compare AI performance against radiologists, and there is relative paucity of evidence on the impact of AI assistance on other healthcare staff who review NCCTH in their daily clinical practice. METHODS AND ANALYSIS: A retrospective data set of 150 NCCTH will be compiled, to include 60 control cases and 90 cases with intracranial haemorrhage, hypodensities suggestive of infarct, midline shift, mass effect or skull fracture. The intracranial haemorrhage cases will be subclassified into extradural, subdural, subarachnoid, intraparenchymal and intraventricular. 30 readers will be recruited across four National Health Service (NHS) trusts including 10 general radiologists, 15 emergency medicine clinicians and 5 CT radiographers of varying experience. Readers will interpret each scan first without, then with, the assistance of the qER EU 2.0 AI tool, with an intervening 2-week washout period. Using a panel of neuroradiologists as ground truth, the stand-alone performance of qER will be assessed, and its impact on the readers' performance will be analysed as change in accuracy (area under the curve), median review time per scan and self-reported diagnostic confidence. Subgroup analyses will be performed by reader professional group, reader seniority, pathological finding, and neuroradiologist-rated difficulty. ETHICS AND DISSEMINATION: The study has been approved by the UK Healthcare Research Authority (IRAS 310995, approved 13 December 2022). The use of anonymised retrospective NCCTH has been authorised by Oxford University Hospitals. The results will be presented at relevant conferences and published in a peer-reviewed journal. TRIAL REGISTRATION NUMBER: NCT06018545.