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This study examined and illustrated real-world risks of unintended patient-level data egress from Trusted Research Environments (TREs) and Secure Data Environments (SDEs), using synthetic data to recreate cases encountered in PIONEER, the HDR UK Hub in Acute Care. Synthetic datasets with demographics and NEWS2 vital signs were created using SciPy and NumPy for two fictitious populations. These datasets were transformed for machine-learning and embedded into various formats to simulate potential egress scenarios. Three worked examples include binary serialisation of data, binary serialisation of complex objects, and plain text mark-up reports. Initial screening of exported files included checking reported sizes. While absolute size alone cannot confirm patient-level data, unusually large files can signal the need for closer inspection. In several cases, this prompted manual review that uncovered sensitive information. File size is therefore a useful signal within a layered egress checking process, not a diagnostic measure. Standard tools like Python or R do not warn of hidden data, reinforcing the need for explicit egress policies and independent verification. Converting binary formats only works for recognized code libraries and requires ongoing maintenance. Manual inspection alongside automation remains essential to identify and remove embedded data. These cases highlight the complexities in identifying and preventing identifiable data egress from TREs. Key insights include clear guidance for researchers, the limitations of binary serialisation for egress due to security vulnerabilities, and the importance of plain-text data exports for ease of verification.

We compared the risk of first and second concussions using Cox models in 11-17-year-old community ice hockey players with ≥2 concussions. Of 4418 participants, 20 participants with ≥2 concussions met our eligibility criteria. Participants without medical clearance had a 4-fold increased risk for second concussion, and those with medical clearance had no increased risk. Playing in a body-checking league did not affect the increase in risk. Although the sample size was small leading to large uncertainty, the results are qualitatively different from previous findings suggesting no increased risk in adults managed according to accepted concussion protocols.

Randomized controlled trials (RCTs) play a central role in assessing the benefits and harms of interventions. Incomplete reporting in RCT publications can compromise the verifiability and usefulness of RCTs. SPIRIT and CONSORT reporting guidelines aim to improve the completeness of RCT protocols and results publications, respectively. However, many RCTs are not reported completely. Checking manuscripts automatically could help authors improve the completeness of reports prior to publication. We previously annotated SPIRIT-CONSORT-TM, a corpus of 200 articles (comprising 100 protocol-results publication pairs) using 83 checklist items drawn from SPIRIT 2013 and CONSORT 2010. We also trained machine learning models to automatically assess reporting at the item level. Each checklist item can include multiple constituent elements (i.e., specific details required for that item), and an item might be considered fully reported when all of its elements are present. However, prior work does not explicitly capture or evaluate reporting at the element level. To address this gap, we extended SPIRIT-CONSORT-TM by incorporating element-level annotations and using them to assess reporting completeness (SPIRIT-CONSORT-ELM). We formulated element-level assessment as a machine reading comprehension task, operationalized through 119 questions, where each question targets a specific reporting element within a checklist item. Using the 200 articles included in SPIRIT-CONSORT-TM, two annotators independently answered 119 questions for 50 articles (25 protocol-results pairs) and resolved any discrepancies through discussion; the remaining 150 articles (75 protocol-results pairs) were assessed by a single annotator. We then developed an automated pipeline for element-level assessment using SPIRIT-CONSORT-ELM. The pipeline first applies a PubMedBERT-based model to identify sentences containing item-level reporting information, then it uses a generative large language model (LLM; GPT-5) with chain-of-thought reasoning to answer element-level questions based on the retrieved evidence. Agreement between the two annotators was high (Gwet's AC1: 0.782) and our pipeline achieved high accuracy in identifying element-level reporting evidence (F1: 0.822, Gwet's AC1: 0.796). Ablation studies indicate that chain-of-thought reasoning and the inclusion of illustrative in-context examples modestly improve LLM performance on the machine reading comprehension task. SPIRIT-CONSORT-ELM provides a benchmark for evaluating reporting guideline completeness at the element level, enabling assessment of RCT transparency beyond the simple presence or absence of checklist items and is publicly available at https://osf.io/kznx4/ . The automated pipeline establishes a robust baseline for assessing RCT reporting and demonstrates potential as a practical aid for authors, reviewers, and editors to identify and address gaps in completeness and transparency of RCT reports.

Maternal near-miss (MNM) events impose substantial emotional and professional strain on midwives and obstetricians, yet clinicians' experiences remain underexplored in Italy. This study explored how maternity clinicians experience and make sense of MNM events. We conducted a qualitative interview study underpinned by a contextualist epistemological position and analysed data using contextualist reflexive thematic analysis. Semi-structured interviews were undertaken with 13 clinicians (9 midwives, 4 obstetricians) in a level II maternity unit in Northern Italy between February and September 2024. Interviews were audio-recorded, transcribed verbatim, and analysed iteratively alongside data collection. Trustworthiness was supported through reflexive journaling/memos, iterative team discussions, and end-of-interview participant validation (summary checking). Four interrelated themes were developed: (1) Barriers to trauma processing, including judgmental audit cultures, limited formal support, and fragmented communication, with perceptions consistent with institutional betrayal; (2) Clinical confidence-building and largely informal emotional recovery, including teamwork, mentoring, and informal debriefing, highlighting peer solidarity as a key buffer; (3) Communication challenges, particularly delivering bad news to women and families and navigating interprofessional communication under pressure; and (4) Emotional complexity, characterised by guilt, responsibility, and enduring personal and professional impact. A central interpretive insight was emotional reciprocity, a bidirectional relationship between clinicians' "second victim" distress and perceived women's recovery trajectories. MNM events can have lasting psychological and occupational effects on maternity clinicians. Findings underscore the need for structured organisational responses alongside peer-based support to mitigate second-victim impacts and support workforce wellbeing.

The objective of this paper was to explore rheumatology healthcare professionals' (HCPs) perspectives on the potential role, value, and implementation challenges of digital biomarkers (dBMs) for monitoring inflammatory arthritis (IA), specifically psoriatic and rheumatoid arthritis. Following the Design Thinking methodology, 7 focus groups and 1 interview were conducted with a total of 34 rheumatology HCPs. The topic guide covered: (remote) monitoring psoriatic and rheumatoid arthritis; the clinical consultation; work satisfaction; and the role of digital technologies in rheumatology. Thematic analysis followed Braun and Clarke's methodology, supported by investigator triangulation and member checking to ensure credibility. Content analysis revealed 5 overarching themes. Participants described current IA care as high quality but increasingly unsustainable, prompting HCPs to seek more efficient, digitally supported models of care delivery (theme 1). Limitations in best-practice digital care, including reduced assessment accuracy and weakened HCP-patient communication, were identified, leading to more conservative treatment decisions (theme 2). dBMs were regarded as complementary tools to enhance care efficiency and support data-driven, high-resolution remote monitoring (theme 3), although concerns were voiced about their accuracy, impact on therapeutic relationships, and HCP workload (theme 4). Adoption is influenced by trust in technology, professional values, and patient-specific factors (eg, disease complexity and preferences). Successful integration will require patient-centred seamless workflows and careful consideration of patient readiness (theme 5). This study highlights that although HCPs see potential in dBMs, their adoption is contingent on trust, clinical relevance, alignment with professional values, and implementation. Development efforts should prioritise robust evidence, clinician and patient engagement, and thoughtful integration into routine practice.

The present study aimed to investigate the facilitators and barriers encountered by primary nurses and designated checkers in their participation with the designated independent double-checking (IDC) process for the administration of high-alert medications in the emergency department, employing the systems engineering initiative for patient safety (SEIPS) framework. Designated IDC acts as a safety measure to prevent medication errors, provided by an experienced checker. However, the facilitators and barriers that influence this process remain unclear. An exploratory qualitative study was conducted using a purposive sample of 26 primary nurses and designated checkers. Data were collected through individual semistructured interviews and analysed using Braun and Clarke's six phases of thematic analysis. Our analysis revealed 15 facilitators and 16 barriers, which were classified according to the SEIPS domains: environment, organisation, people, task, tools and technology, process and outcome. The findings concerning the facilitators and barriers to implementing a designated IDC are a vital initial step in developing evidence-based interventions to enhance medication safety. The findings may suggest the maintenance of clear documentation, the promotion of effective communication, the conduct of regular audits, and the incorporation of IDC training into both orientation programmes and in-service training, which is especially crucial for junior staff. These factors guide policymakers in restructuring the environmental layout, standardising IDC guidelines, ensuring sufficient staffing, fostering a nonhierarchical atmosphere, and promoting the adoption of technology.

The volatility of the illicit drug market increased during the COVID-19 pandemic, contributing significantly to increased rates of overdose mortality in the United States. Given this unprecedented period and its associated impacts, we examined how various macro and micro-environmental factors, namely disruptions of the drug market, impacted the overdose risk of women who use drugs (WWUDs) during the pandemic. Grounded in the COVID Action Research Engagement (CARE) study among WWUD (N = 227 in Baltimore, Maryland) (August 2021 to December 2022), this analysis investigated the influence of drug market factors on nonfatal overdose risk during the first two years of the COVID-19 pandemic among study participants. We used a multivariable GEE Poisson regression clustered by enrollment location to examine environmental risk factors associated with nonfatal overdose among WWUD during the pandemic. In the clustered adjusted regression, WWUD who overdosed during the pandemic compared to those that did not were significantly more likely to report drug market changes in accessing drugs (aRR = 1.22; 95% CI = 1.04, 1.43) and in drug prices (aRR = 1.30; 95% CI = 1.26, 1.35), as well as increased drug purchasing frequency (aRR = 1.42; 95% CI = 1.03, 1.98). During the pandemic in Baltimore, WWUD's overdose risk was significantly elevated by disruptions to local drug markets. Drug checking and safer supply interventions are necessary to mitigate drug market-related risks. Future research warrants further investigation of the impact of drug market changes post-pandemic to better understand how to reach a diversity of women and assess overdose interventions among WWUD.

The dual-factor model of mental health suggests that positive and negative aspects are distinct, allowing adolescents to be categorized into four groups: flourishing, languishing, symptomatic but content, and troubled, based on different combinations of strengths and difficulties. However, prior research has often focused solely on emotional indicators, neglecting behavioral dimensions in both positive and negative domains. In addition, most studies have been cross-sectional, leaving it unclear whether these patterns remain stable over time or how various factors predict adolescents' subgroup trajectories. To this end, this study used composite indicators of depressive symptoms, well-being, conduct problems and prosocial behavior to examine the heterogeneous developmental trajectories of mental health during middle adolescence, while also assessing the predictive roles of stress and emotion regulation. Using five waves of longitudinal data from 1,391 Chinese adolescents and parallel-process latent class growth model, we identified four distinct trajectories: "flourishing and improving"; "emotionally adaptive but behaviorally troubled"; "emotionally troubled but behaviorally adaptive"; and "Troubled". Moreover, stress (including daily and early-life stress) and emotion regulation (including cognitive reappraisal and expressive suppression) showed distinct associations with adolescents' trajectory membership. These findings support a developmental test of the dual-factor model by showing that both emotional and behavioral domains are crucial for distinguishing the heterogeneous mental health trajectories, as positive and negative indicators demonstrate greater independence across domains than within them. In addition, they highlight subgroup-specific predictors, providing guidance for targeted interventions.

Effective treatment monitoring and treatment decisions in relapsing-remitting multiple sclerosis (RRMS) require accurate and individualized prediction of future disease courses. Guidelines from the Magnetic Resonance Imaging in Multiple Sclerosis (MAGNIMS) group and the Canadian Multiple Sclerosis Working Group (CMSWG) frequently cite MRI outcomes as predictive, but the methodological quality of this evidence is uncertain. This study aims to critically assess the methodological standards underlying predictive claims about MRI outcomes in four major relevant MS guidelines. We conducted a content review of citations in the MAGNIMS 2015 and 2021 and the CMSWG 2013 and 2020 guideline publications. Each source was evaluated for whether it reported quantitative predictive evidence: either predictive values with confidence intervals, Kaplan-Meier-based risk estimates, or externally validated models that provide accurate risk estimates (good calibration) and correctly separate high- from low-risk patients (good discrimination); We also checked if measures such as correlations, odds ratios, hazard ratios, Prentice criteria, or likelihood ratio tests were used. Across all four guidelines, most predictive statements relied on secondary citations and association-based measures. Odds ratios, hazard ratios, correlations, or Prentice criteria were commonly reported. Some studies reported predictive values, but confidence intervals were frequently not provided. Only isolated examples of properly validated prediction models were cited, and only one had undergone full external validation. Advanced methods, such as the likelihood reduction factor, were absent. Current guideline statements on MRI prediction in RRMS often rely on associations rather than validated individualized predictions. They do not quantify individual risk or provide evidence for accuracy, calibration, discrimination, or robustness (reliability of predictions across different patients and settings). To ensure trustworthy and actionable evidence, future guidelines should require prospective risk estimates with confidence intervals, externally validated models with calibration and discrimination, predefined thresholds for predictive usefulness, and evaluation of clinical utility (e.g., decision curve analysis). Why was the study done? To effectively treat relapsing-remitting multiple sclerosis (RRMS), reliable individualized prediction of disease worsening based on MRI findings is needed. Four widely used guidelines cite sources that provide such predictive information. However, it is unclear if the presented evidence supports good individual predictions. Thus, this study aims to assess the quality of predictive information in the literature cited by the guidelines on the prediction quality of MRI in RRMS. What did the researchers do? The sources claiming predictive ability of MRI in two guidelines from the Magnetic Resonance Imaging in Multiple Sclerosis (MAGNIMS) group and two guidelines from the Canadian Multiple Sclerosis Working Group (CMSWG) were extracted. The objectives, methodology, and content of the sources were analyzed. The methodologies were then grouped into ten statistical categories, and each category was assessed for its quality in individual prediction. What did the researchers find? In total, 75 sources were identified, which were directly or indirectly cited in the guidelines to show the predictive quality of MRI information. About 80% of sources used association measures to show individual prediction. The cited evidence was mostly insufficient to enable clinically relevant individual predictions. Neither groups report the quality of evidence they used in their guidelines. They also do not report measures for uncertainty of estimates (e.g., confidence intervals). However, one study included an independently tested model, while one other study used a statistically sound prediction model. What do these findings mean? Current guideline statements on MRI prediction in RRMS often rely on associations and rarely employ well-validated methods. There is a need for the Multiple Sclerosis scientific community to set minimum standards for the evidence accepted to support individualized prediction and to rank and assess the contribution of each evidence.

Bipolar patellofemoral chondral defects in young, active patients present a challenging clinical problem due to persistent pain, functional limitation, and complex biomechanical contributors. While cartilage restoration procedures such as matrix-induced autologous chondrocyte implantation (MACI), osteochondral allograft (OCA) transplantation, and tibial tubercle osteotomy (TTO) have demonstrated favorable outcomes individually, combined restoration strategies addressing both focal cartilage loss and patellofemoral mechanics are less well described. We performed a single-stage, triple-modality comprehensive patellofemoral cartilage restoration, including a trochlear OCA, a patellar MACI, and TTO to offload and realign the patellofemoral joint. The described combined procedure was indicated in a healthy, active 37-year-old female with bilateral symptomatic full-thickness bipolar patellofemoral chondral defects refractory to extensive nonoperative treatment. Imaging demonstrated bipolar patellofemoral cartilage lesions consisting of a full-thickness trochlear osteochondral defect and a full-thickness patellar chondral defect with associated lateral patellar subluxation but without instability, abnormal patellar height, or elevated tibial tubercle-trochlear groove distance. The patellar defect was prepared with stable vertical walls for MACI implantation while preserving the subchondral bone. The trochlear lesion was sized, reamed, and reconstructed using a size-matched fresh OCA prepared to achieve flush articular congruity. A TTO with approximately 1 cm medialization and anteriorization was performed to reduce patellofemoral contact pressures and protect the cartilage restoration constructs. The MACI graft was then trimmed to match the patellar defect and secured with fibrin glue. Standard layered closure and structured rehabilitation with protected weightbearing and early motion were utilized postoperatively. At 5-month follow-up, the patient demonstrated improved pain, full patellar mobility, and range of motion from 0° to 135°, with return to baseline activities. Radiographs demonstrated healed tibial tubercle osteotomies and well-incorporated OCAs bilaterally. These findings are consistent with the existing literature, which demonstrates significant improvements in patient-reported outcomes after combined cartilage restoration and patellofemoral unloading procedures, including high satisfaction and return-to-sport rates after MACI, OCA, and TTO procedures. This case demonstrates a comprehensive approach to bipolar patellofemoral cartilage disease that simultaneously addresses focal cartilage pathology and the underlying biomechanical environment. The literature supports the use of MACI for isolated chondral defects, OCA for osteochondral lesions with subchondral involvement, and TTO to improve graft protection and patellofemoral mechanics. Hybrid restoration strategies combining these techniques may provide favorable functional outcomes and joint preservation in appropriately selected patients. Further prospective studies are needed to clarify long-term survivorship, optimal graft selection, and return-to-sport outcomes after combined OCA/MACI reconstruction procedures. The author(s) attests that consent has been obtained from any patient(s) appearing in this publication. If the individual may be identifiable, the author(s) has included a statement of release or other written form of approval from the patient(s) with this submission for publication.

Long-term deep ocean temperature monitoring is crucial for understanding the ocean's role in climate variability and storage of heat in the deep ocean. Observation of the ocean surface is relatively accessible via both in-situ and remote sensing; however, continuous, high-temporal resolution, decade-long temperature records from abyssal depths face the technical challenges of sustained deep ocean deployments. The addition of calibrated, internally-recording temperature sensors to deep-ocean moorings not far from the sea floor provides a means of making high temporal resolution temperature observations. Quality controlling and merging records from successive mooring deployments results in a decade-long time series. Our work has been to optimize approaches for ensuring data quality and continuity in multi-year deep ocean temperature datasets. Here we show a comprehensive processing framework that yields 13 years (2012 to 2025) of continuous temperature measurements at approximately 4200 to 4500 meters depth from the Stratus Ocean Reference Station near 22 °S, 85 °W, 1500 km off the coast of Chile in the Southeast Pacific. Our framework incorporates timing checks, automated spike detection, systematic multi-sensor validation, statistical validation, human-in-the-loop quality control, and merging protocols. This framework establishes reproducible standards for processing long term oceanographic observations from multiple deployments. For the Stratus data set, the result is a unique, decade-long abyssal temperature record with quantified uncertainties that constitutes a benchmark time series for evaluating the realism of deep ocean temperature in models.

Background Type 1 diabetes mellitus (T1DM) is a common childhood condition requiring proper management, with teachers playing a vital role in recognizing symptoms and providing support. This study assesses their knowledge, attitudes, and practices to identify gaps and recommend improvements. Aim The study aims to assess school teachers' knowledge, attitudes, and practices regarding the management of T1DM in children in the UAE. Methods A descriptive cross-sectional study was conducted among 402 primary school teachers using convenience sampling. A structured, adapted 47-item questionnaire was developed and piloted. Data were analyzed using SPSS Version 25 (IBM SPSS Statistics for Windows, IBM Corp., Armonk, NY) with descriptive statistics and chi-square tests (p &#x2264; 0.05), and multivariable logistic regression was performed. Results were presented using bar and pie charts. Results Participants were predominantly female (293, 72.9%). A total of 277 (69.1%) participants were aged 31-50 years. Good knowledge was highest for questions such as blood glucose level determining dose of treatment (81.6%) and first-aid response when students felt unwell (80.8%), but lower for exercise precautions (52.7%) and hypoglycemia management (56.0%). Positive attitudes were widespread, with 91.6% strongly supporting school-based diabetes initiatives. Practices varied; while most teachers regularly observed blood glucose checks and insulin administration, only 38 of the experienced teachers (21.3%) had received formal training, and 116 (65.2%) followed standardized protocols. Knowledge was significantly associated with age, gender, family history of chronic illnesses and T1DM, scientific major, and prior experience with diabetic students (p < 0.05), while attitudes were mainly associated with knowledge and good practices (p < 0.001). Conclusion The study shows that the teachers' willingness to support T1DM students exceeds their preparedness to manage care and emergencies. Establishing a unified, tiered-training and algorithm-based action plan, adapted from successful models by the ADA, across all UAE schools may potentially provide structured, step-wise instructions for routine and emergency care. Such a system may possibly enhance safety, reduce variability in practice, and ensure consistent, evidence-based support for students with T1DM.

Oral cancer survival remains poor in Scotland, which is partly due to the delay of early detection. Patients' poor awareness contributes to such delays. Dentists often avoid raising the topic of oral cancer during routine check-ups, fearing patient anxiety. Question Prompt Lists (QPLs) may help by shifting the initiative to patients. This study explored dentists' perceived acceptability of using a QPL to facilitate oral cancer discussions in primary dental care. A pre-study patient focus group informed the design. Semi-structured interviews were conducted with 21 primary care dentists working in NHS Scotland. Purposive sampling was used to ensure variation in experience. Interview data were analysed using framework analysis informed by the Theoretical Framework of Acceptability (TFA). Dentists welcomed the QPL as a valuable, patient-centred tool that could fulfil their ethical duty to inform patients about oral cancer screening. However, significant concerns emerged around time constraints and staffing shortages within high-pressured NHS environments, making any additional intervention feel burdensome. For successful implementation, dentists suggested two prerequisites: (1) design optimisation using short, categorised design with simple language, and (2) systemic integration which was proposed to embed QPLs into booking systems with clear clinical guidelines and systematic training. While dentists supported QPLs as an acceptable and ethical aid for opening difficult conversations about oral cancer, its successful implementation is contingent upon a user-friendly design of the tool and a systemic integration by addressing the fundamental structural inhibitors of NHS dentistry. Future interventions should focus on integrating QPLs into routine workflows rather than treating them as an add-on task.

The exponential growth of publicly available genomic data has created unprecedented opportunities for sequence-based discovery. Locating specific k-mers is fundamental to diverse applications, including metagenomic classification, pathogen and cancer detection, and variant calling yet efficient identification of multiple k-mer patterns across large sequencing data and massive databases remains a significant computational challenge. We implement two quantum algorithms for DNA multi-pattern string matching for k-mer detection, leveraging Grover's amplitude amplification under the idealized quantum random access memory (QRAM) framework. The first algorithm uses an enumerate-m oracle that sequentially checks a loaded text substring against all m patterns achieving O (&#x221a;S) query complexity for S text positions but requiring O (m &#xb7; L) work per oracle call. The second algorithm employs nested Grover search with an outer loop over text positions and an inner loop over pattern space, reducing oracle complexity to O(L) while performing O (&#x221a;S &#xb7; &#x221a;m) in total. These asymptotic gains highlight the potential advantages that could be unlocked by future large-scale, low-noise QRAM architectures, positioning our results as a promising proof-of-concept foundation. This work introduces two quantum implementations of multi-pattern string matching tailored for k-mer detection. Leveraging quantum parallelism and Grover-inspired search primitives, our methods accelerate dictionary-based pattern matching, particularly in contexts involving large sequences, such as genomic data, and extensive pattern sets. While implementation challenges such as QRAM overhead remain, this study demonstrates both the promise and current limitations of quantum-enhanced string matching, establishing a foundational step toward quantum readiness in bioinformatics. To maximize accessibility and practical use, we provide our methodology at: https://github.com/Georgakopoulos-Soares-lab/quantum-multi-motif-finder.

Clinical laboratory results guide the vast majority of medical management pathways and Occurrence Management ensures diagnostic safety across the total testing process (TTP). However, execution in resource-limited settings (RLS) is severely hindered by infrastructural constraints like grid instability, workforce shortages, unreliable paper-based data systems, and punitive institutional cultures that suppress incident reporting and error capture. This review evaluates unique system-level and organizational barriers to error management in low-resource laboratories and synthesizes a scalable, phased operational framework to optimize continuous quality improvement and patient safety. A comprehensive literature search was conducted across PubMed/MEDLINE, Scopus, Web of Science, Google Scholar, and AJOL for publications from January 2010 to April 2026. Guided by the TTP framework integrated with the Plan-Do-Check-Act (PDCA) cycle, a PRISMA-informed screening isolated 67 eligible records for thematic synthesis and framework development. Laboratory errors are highly asymmetric, with up to 68.2% concentrated in the pre-analytical phase. Primary failure points stem from human-system interface lapses, manual transcription workflows, and cold-chain failures during power outages. To bridge the gap with international quality standards (ISO 15189:2022), this paper establishes a phased, six-stage occurrence management roadmap scaled for varying tiers of healthcare delivery. Practical, low-cost interventions include implementing non-punitive "just culture" reporting policies, using cost-effective in-house pooled patient sera for quality control, deploying offline-capable open-source laboratory information systems, and forming interdisciplinary clinical-laboratory committees. To facilitate bench deployment, the framework is supported by open-access templates designed to guide standardized reporting, structured root cause analysis (Five Whys/Ishikawa checklists), corrective actions, ledger tracking, and automated Process Sigma performance indicator dashboard monitoring. Strengthening error tracking in RLS is fully viable through targeted operational changes without extensive capital investment. Shifting from an individual blame orientation to system-centric learning, paired with stepwise accreditation mentorship models (SLMTA/SLIPTA), significantly reduces diagnostic defects and ensures health system sustainability.

Cancer screening is central to early detection and healthy ageing, yet evidence on how major life transitions shape screening uptake remains limited. Using four waves of the Household, Income and Labour Dynamics in Australia (HILDA) Survey covering 2009, 2013, 2017, and 2021, with 18,875 person-wave observations from 8343 individuals aged 50-75, we estimate the causal effect of retirement on cancer screening using an instrumental-variable design that exploits discontinuities in Age Pension eligibility. Retirement significantly increases participation in organised cancer screening, with the clearest effects appearing in low-friction, invitation-based programmes. The strongest and most robust increases are observed for bowel cancer screening, and among women we also find positive effects for breast screening. By contrast, we find little evidence of comparable changes in broader health care use or in tests that rely more heavily on patient or provider initiative. This pattern points to the importance of programme architecture: retirement matters most where screening is actively prompted, easy to access, and simple to complete. These findings identify retirement as an important phase for engagement with organised screening and underscore the role of institutional design in translating additional time into preventive action in ageing societies.

Background: Ticks are ectoparasites of major veterinary and medical importance due to their capacity to vector numerous pathogens. Bacterial, viral, and protozoan diseases that affect livestock and companion animals can cause economic losses and reduce productivity. To protect animal health, ensure food safety, and reduce the incidence of tick-borne disease in humans, effective surveillance and integrated control of ticks are essential. The objective of this article was to employ morphological identification and molecular techniques to detect and confirm Ixodes holocyclus ticks infesting imported domestic cats. A study of a total of 100 imported domestic cats from importers, which were brought to the veterinary clinic for regular check-ups. Under a stereomicroscope, ticks were identified by their morphology and using standard taxonomic keys. DNA obtained from every individual tick sampled was examined by targeting tick-specific gene markers through conventional PCR. Real-time PCR detects and confirms the types of tick species and their associated pathogens in their natural habitats. The results of morphological identification revealed the presence of the tick in 18 out of 100 cats (18%), exhibiting the morphological characteristics of the I. holocyclus. The positive samples were then identified as isolates using conventional PCR based on the cox1 mitochondrion. The cox1 gene had Ct values of 18.00 to 18.30; for EF1-&#x3b1;, it was around 21.49 to 21.55, and thus consistent. The melt curve data of both genes produced a single peak, indicating the high specificity of the assay. A phylogenetic analysis of the 18 sequenced isolates based on partial mitochondrial COX1 gene sequences showed four clusters. The largest cluster was comprised of 11 isolates that were closely related to OQ675411.1 (Ixodes holocyclus isolate H1). Overall, the isolates were confirmed as Ixodes holocyclus, with minor differences. The real-time PCR method was able to detect Ixodes holocyclus ticks with speed, accuracy, and 100% specificity. Ticks can infest cats, allowing them to carry these parasites into both the house and the environment. This also raises the risk of transmission, including zoonotic transmission. Furthermore, this can also pose a public health hazard.

Establishing the Korean Pediatric and Congenital Heart Surgery Database (KPCHSD) and linking it to the World Database for Pediatric and Congenital Heart Surgery (WDPCHS) is an important step toward creating a global network for quality care. Worldwide outcomes data are needed to support quality assurance and advocacy for necessary resources for pediatric and congenital cardiac care. The Korean Society for Thoracic and Cardiovascular Surgery collaborated with the World Society for Pediatric and Congenital Heart Surgery (WSPCHS) to develop and implement the KPCHSD. Variables selected for collection met the specific needs of Korean congenital heart surgery practice and were harmonized with the WDPCHS. Software was developed to link the databases in a secure environment, transfer data from KPCHSD to the WDPCHS, and produce outcomes reports. The initial data upload from the KPCHSD to the WDPCHS was successfully completed in 2023. Over 2,500 operations from a 2-year period were transferred from the KPCHSD into the WDPCHS. Comparisons of individual center data will be made with both national and international aggregates. These comparisons will be available to individual centers via a password-protected cloud-based dashboard. Working in collaboration with our Korean colleagues, the WSPCHS has taken the next step toward developing a global network to share knowledge and expertise and to promote quality improvement in the treatment of congenital heart disease. Using this platform, countries perform data validation and completeness checks while maintaining control over their data. This aggregated data can support quality assessment and help secure the necessary resources for all countries, regardless of economic status.

Pediatric Advanced Life Support guidelines recommend pulse assessment within 10-s, yet manual palpation during pediatric cardiac arrest is often inaccurate. Point-of-care ultrasound (POCUS) can improve detection of arterial pulsatility, identify cardiac activity or standstill, and diagnose reversible causes of arrest. However, pediatric-specific protocols for integrating POCUS into cardiac arrest management are limited, and concerns persist that POCUS may prolong interruptions in CPR. This study aimed to develop, implement, and evaluate a structured protocol integrating POCUS into pediatric cardiac arrest management. We designed a simulation-based curriculum using rapid cycle deliberate practice. A flipped-classroom model combined an online module with in-person simulation. The primary outcome of the study was pulse detection accuracy (correct identification of pulse presence/absence). Secondary outcomes for the online module included completion of responses within 10-s and interpretation time. For in-person simulation sessions, secondary outcomes included decision time, CPR pause duration, self-reported confidence and perceived skill improvement. 37 physicians (21 PEM faculty, 16 fellows) completed the online module (total of 740 pulse checks). Pulse detection accuracy was 88.0% for pulse presence and 89.3% for absence; 86.5% met the 10-s target, with a median interpretation time of 5&#xa0;s. During simulation, accuracy was 100% (5/5) for pulse presence and 94% (17/18) for pulselessness. Median decision time was 4.6 s (IQR 3.8-8.1). Confidence increased from 2.5/5 to 3.9/5 (Cohen's d&#xa0;=&#xa0;1.47, large effect size), with high satisfaction reported. A structured POCUS pulse-check curriculum was associated with improved accuracy, efficiency, and clinician confidence without prolonging CPR pauses, suggesting that a multimodal training approach may support integration of POCUS into pediatric resuscitation.