OBJECTIVE: Accurate diagnosis and quantification of polyps and symptoms are pivotal for planning the therapeutic strategy of Chronic rhinosinusitis with nasal polyposis (CRSwNP). This pilot study aimed to develop an artificial intelligence (AI)-based image analysis system capable of segmenting nasal polyps from nasal endoscopy videos.
METHODS: Recorded nasal videoendoscopies from 52 patients diagnosed with CRSwNP between 2019 and 2022 were retrospectively analyzed. Images extracted were manually segmented on the web application Roboflow. A dataset of 342 images was generated and divided into training (80%), validation (10%), and testing (10%) sets. The Ultralytics YOLOv8.0.28 model was employed for automated segmentation.
RESULTS: The YOLOv8s-seg model consisted of 195 layers and required 42.4 GFLOPs for operation. When tested against the validation set, the algorithm achieved a precision of 0.91, recall of 0.839, and mean average precision at 50% IoU (mAP50) of 0.949. For the segmentation task, similar metrics were observed, including a mAP ranging from 0.675 to 0.679 for IoUs between 50% and 95%.
CONCLUSIONS: The study shows that a carefully trained AI algorithm can effectively identify and delineate nasal polyps in patients with CRSwNP. Despite certain limitations like the focus on CRSwNP-specific samples, the algorithm presents a promising complementary tool to existing diagnostic methods.

OBJECTIVE: This study aimed to compare and evaluate the efficiency and accuracy of computerized adaptive testing (CAT) under two stopping rules (SEM 0.3 and 0.25) using both real and simulated data in medical examinations in Korea.
METHODS: This study employed post-hoc simulation and real data analysis to explore the optimal stopping rule for CAT in medical examinations. The real data were obtained from the responses of 3rd-year medical students during examinations in 2020 at Hallym University College of Medicine. Simulated data were generated using estimated parameters from a real item bank in R. Outcome variables included the number of examinees\' passing or failing with SEM values of 0.25 and 0.30, the number of items administered, and the correlation. The consistency of real CAT result was evaluated by examining consistency of pass or fail based on a cut score of 0.0. The efficiency of all CAT designs was assessed by comparing the average number of items administered under both stopping rules.
RESULTS: Both SEM 0.25 and SEM 0.30 provided a good balance between accuracy and efficiency in CAT. The real data showed minimal differences in pass/fail outcomes between the 2 SEM conditions, with a high correlation (r = 0.99) between ability estimates. The simulation results confirmed these findings, indicating similar average item numbers between real and simulated data.
CONCLUSIONS: The findings suggest that both SEM 0.25 and 0.30 are effective termination criteria in the context of the Rasch model, balancing accuracy and efficiency in CAT.

UNASSIGNED: Severe outcomes of COVID-19 are associated with advancing age and comorbidities. The specific aim of our study was to determine the impact of COVID-19 on the clinical course and outcome of patients with cirrhosis.
UNASSIGNED: We retrieved data from VA national repository and identified patients tested for SARS-CoV-2 RNA who had cirrhosis. Each virus positive patient was propensity-matched with virus negative subjects by demographics and comorbidities. Primary endpoint was death within 30 days of COVID-19 diagnosis and secondary endpoint was hospitalization within 14 days.
UNASSIGNED: Among 1,115,037 individuals tested for SARS-CoV-2 RNA, 31,680 had cirrhosis. Of those patients, 4456 virus positive patients were propensity-matched with 8752 virus negative subjects. In this cohort of 13,208, median age was 67 years and 95% were male. Most had multiple comorbidities. Alcohol use, hepatitis C and MASH were the dominant etiologies of cirrhosis. At baseline, median MELD was 6% and 21% had hepatic decompensation. Advanced age was the most significant determinant of hospitalization and mortality. Comorbidities, alcohol use and MELD increased the likelihood of hospitalization whereas SARS-CoV-2 positivity had lower Day-14 hospitalization hazard. MELD was associated with higher mortality hazard whereas vaccination reduced the hazard of hospitalization and death. SARS-CoV-2 positivity increased the hazard of death at Day-30 by 72% and at Day-90 by 26%.
UNASSIGNED: Although patients with cirrhosis who developed COVID-19 were less likely to be hospitalized, they were more likely to die within 30 days compared to their virus negative counterparts. Vaccination was effective in reducing both hospitalization and death.

The development of platforms for distributed analytics has been driven by a growing need to comply with various governance-related or legal constraints. Among these platforms, the so-called Personal Health Train (PHT) is one representative that has emerged over the recent years. However, in projects that require data from sites featuring different PHT infrastructures, institutions are facing challenges emerging from the combination of multiple PHT ecosystems, including data governance, regulatory compliance, or the modification of existing workflows. In these scenarios, the interoperability of the platforms is preferable. In this work, we introduce a conceptual framework for the technical interoperability of the PHT covering five essential requirements: Data integration, unified station identifiers, mutual metadata, aligned security protocols, and business logic. We evaluated our concept in a feasibility study that involves two distinct PHT infrastructures: PHT-meDIC and PADME. We analyzed data on leukodystrophy from patients in the University Hospitals of Tübingen and Leipzig, and patients with differential diagnoses at the University Hospital Aachen. The results of our study demonstrate the technical interoperability between these two PHT infrastructures, allowing researchers to perform analyses across the participating institutions. Our method is more space-efficient compared to the multi-homing strategy, and it shows only a minimal time overhead.

Access to individual-level health data is essential for gaining new insights and advancing science. In particular, modern methods based on artificial intelligence rely on the availability of and access to large datasets. In the health sector, access to individual-level data is often challenging due to privacy concerns. A promising alternative is the generation of fully synthetic data, i.e., data generated through a randomised process that have similar statistical properties as the original data, but do not have a one-to-one correspondence with the original individual-level records. In this study, we use a state-of-the-art synthetic data generation method and perform in-depth quality analyses of the generated data for a specific use case in the field of nutrition. We demonstrate the need for careful analyses of synthetic data that go beyond descriptive statistics and provide valuable insights into how to realise the full potential of synthetic datasets. By extending the methods, but also by thoroughly analysing the effects of sampling from a trained model, we are able to largely reproduce significant real-world analysis results in the chosen use case.

BACKGROUND: The incentive spirometer is a basic and common medical device from which electronic health care data cannot be directly collected. As a result, despite numerous studies investigating clinical use, there remains little consensus on optimal device use and sparse evidence supporting its intended benefits such as prevention of postoperative respiratory complications.
OBJECTIVE: The aim of the study is to develop and test an add-on hardware device for data capture of the incentive spirometer.
METHODS: An add-on device was designed, built, and tested using reflective optical sensors to identify the real-time location of the volume piston and flow bobbin of a common incentive spirometer. Investigators manually tested sensor level accuracies and triggering range calibrations using a digital flowmeter. A valid breath classification algorithm was created and tested to determine valid from invalid breath attempts. To assess real-time use, a video game was developed using the incentive spirometer and add-on device as a controller using the Apple iPad.
RESULTS: In user testing, sensor locations were captured at an accuracy of 99% (SD 1.4%) for volume and 100% accuracy for flow. Median and average volumes were within 7.5% (SD 6%) of target volume sensor levels, and maximum sensor triggering values seldom exceeded intended sensor levels, showing a good correlation to placement on 2 similar but distinct incentive spirometer designs. The breath classification algorithm displayed a 100% sensitivity and a 99% specificity on user testing, and the device operated as a video game controller in real time without noticeable interference or delay.
CONCLUSIONS: An effective and reusable add-on device for the incentive spirometer was created to allow the collection of previously inaccessible incentive spirometer data and demonstrate Internet-of-Things use on a common hospital device. This design showed high sensor accuracies and the ability to use data in real-time applications, showing promise in the ability to capture currently inaccessible clinical data. Further use of this device could facilitate improved research into the incentive spirometer to improve adoption, incentivize adherence, and investigate the clinical effectiveness to help guide clinical care.

UNASSIGNED: The VIVID (Videos for Addressing Racial Disparities in Implantable Cardioverter Defibrillator Therapy via Innovative Designs) study was a multicenter, randomized controlled trial aimed at evaluating the effectiveness of a video-based decision support tool in enhancing informed consent for implantable cardioverter defibrillator (ICD) implantation among Black patients who met guideline criteria for primary prevention ICDs. Within the broader VIVID randomized trial, a qualitative investigation was conducted to elucidate the decisional factors among Black individuals considering ICD implantation for the primary prevention of sudden cardiac arrest.
UNASSIGNED: Between October 2016 and July 2019, in-depth interviews were conducted at 2 time points from randomization, ≈7 days (time interval for the decision) and at 90 days; the time interval for determining ICD implantation. Interview findings were categorized by randomized groups, those assigned to 1 of the 2 encounter-based video decision support tools or standard care (without video). Interview participants were purposefully selected to ensure diversity across gender, age, educational background, research site, and randomization group; participants were sampled from 14 academic and community-based electrophysiology clinics in the United States. Data analysis employed applied thematic analysis techniques.
UNASSIGNED: A diverse sample of Black individuals were interviewed at 1 week (n=59; female, 37.3%) and 90 days (n=48; female, 39.6%). The primary factors influencing the decisions of Black individuals considering a primary prevention ICD implantation were (1) their clinicians\' recommendations for ICD implantation; (2) their perception of their cardiac health status; and (3) a desire to prolong their lives for the sake of their families.
UNASSIGNED: These findings offer valuable insights that may guide clinicians in their communication with Black patients during shared decision-making encounters related to ICD implantation.

Blood clot formation, a crucial process in hemostasis and thrombosis, has garnered substantial attention for its implications in various medical conditions. Microscopic examination of blood clots provides vital insights into their composition and structure, aiding in the understanding of clot pathophysiology and the development of targeted therapeutic strategies. This study explores the use of topological data analysis (TDA) to assess plasma clot characteristics microscopically, focusing on the identification of the elements components, holes and Wasserstein distances. This approach should enable researchers to objectively classify fibrin networks based on their topologic architecture. We tested this mathematical characterization approach on plasma clots formed in static conditions from porcine and human citrated plasma samples, where the effect of dilution and direct thrombin inhibition was explored. Confocal microscopy images showing fluorescence labeled fibrin networks were analyzed. Both treatments resulted in visual differences in plasma clot architecture, which could be quantified using TDA. Significant differences between baseline and diluted samples, as well as blood anticoagulated with argatroban, were detected mathematically. Therefore, TDA could be indicative of clots with compromised stability, providing a valuable tool for thrombosis risk assessment. In conclusion, microscopic examination of plasma clots, coupled with Topological Data Analysis, offers a promising avenue for comprehensive characterization of clot microstructure. This method could contribute to a deeper understanding of clot pathophysiology and thereby refine our ability to assess clot characteristics.

BACKGROUND: An embedded single case-study design was used to explore the experiences of men in rural New Zealand accessing mental health services. It is essential for researchers to acknowledge positionality in case study research and the lead author used reflexive practice to acknowledge his values and beliefs.
OBJECTIVE: To explore and demonstrate the reflexive process of the lead author\'s position as an inside researcher.
CONCLUSIONS: Three groups were involved in the research: men with mental health challenges, their partners, and mental health clinicians. The article presents the initial research through memos and diarying in the context of current literature.
CONCLUSIONS: Reflexivity is essential for ensuring the research process is complete and biases are identified. Positionality exists on a continuum and it is critical for researchers to be honest with themselves, the topic and the group being investigated, to show respect for the participants and the people they represent, as well as to be committed to revealing the truth.
CONCLUSIONS: Insider research has the potential to bridge the gap between academia and practice. It facilitates the transfer of research knowledge directly to practitioners, leading to more evidence-informed decision-making and practice.

BACKGROUND: Healthcare regulators in many countries undertake inspections of healthcare providers and publish inspection outcomes with the intention of improving quality of care. Comprehensive inspections of general practices in England by the Care Quality Commission began for the first time in 2014. It is assumed that inspection and rating will raise standards and improve care, but the presence and extent of any improvements is unknown. We aim to determine if practice inspection ratings are associated with past performance on prescribing indicators and if prescribing behaviour changes following inspection.
METHODS: Longitudinal study using a dataset of 6771 general practices in England. Practice inspection date and score was linked with monthly practice-level data on prescribing indicators relating to antibiotics, hypnotics and non-steroidal anti-inflammatory drugs. The sample covers practices receiving their first inspection between September 2014 and December 2018. Regression analysis and the differential timing of inspections is used to identify the impact on prescribing.
RESULTS: Better-rated practices had better prescribing in the period before inspections began. In the six months following inspections, no overall change in prescribing was observed. However, the differences between the best and worse rated practices were reduced but not fully. The same is also true when taking a longer-term view. There is little evidence that practices responded in anticipation of inspection or reacted differently once the ratings were made public.
CONCLUSIONS: While some of the observed historic variation in prescribing behaviour has been lessened by the process of inspection and ratings, we find this change is small and appears to come from both improvements among lower-rated practices and deteriorations among higher-rated practices. While inspection and rating no doubt had other impacts, these prescribing indicators were largely unchanged.