انفورماتیک پزشکی
مقالهها، منابع و پژوهشهای تازه حوزه انفورماتیک پزشکی
ورود به زیرشاخهنقشه موضوعی
جستوجوی دقیقانفورماتیک پزشکی و کتابداری سلامت
داده، اطلاعات، کتابداری و شواهد سلامت
زیرشاخهها
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بیوانفورماتیک
مقالهها، منابع و پژوهشهای تازه حوزه بیوانفورماتیک
ورود به زیرشاخهمدیریت اطلاعات سلامت
مقالهها، منابع و پژوهشهای تازه حوزه مدیریت اطلاعات سلامت
ورود به زیرشاخهپزشکی مبتنی بر شواهد
مقالهها، منابع و پژوهشهای تازه حوزه پزشکی مبتنی بر شواهد
ورود به زیرشاخهمرور نظاممند و متاآنالیز
مقالهها، منابع و پژوهشهای تازه حوزه مرور نظاممند و متاآنالیز
ورود به زیرشاخهکتابداری و اطلاعرسانی پزشکی
مقالهها، منابع و پژوهشهای تازه حوزه کتابداری و اطلاعرسانی پزشکی
ورود به زیرشاخهتازهترین رکوردها
شواهد انفورماتیک پزشکی و کتابداری سلامت
PubMed2026
[THE TRADITIONAL AND COMPLEMENTARY MEDICINE IN THE PUBLIC HEALTH SYSTEM OF THE RUSSIAN FEDERATION: ANALYSIS OF EVIDENCE BASE AND LEGAL ASPECTS OF INTEGRATION].
The article considers placement of methods of traditional and complementary medicine in the public health system of the Russian Federation, focusing on prevention and management of chronic non-communicable diseases. The analysis of the evidence base on key methods of traditional and complementary medicine (acupuncture, phytotherapy, homeopathy, manual therapy, osteopathy) was carried out, including differentiated estimate of level of evidence for forms of homeopathy based on the latest systematic review of meta-analyses. The legal framework of its application in Russia are explored. The corresponding collisions and barriers are identified. The following proposals concerning integrative health care model are formulated: differentiated register of methods, clinical guidelines, pilot integration into compulsory health insurance system and enhancement of research.
PubMed2026
Dynamic evolution, prediction and patient stratification of chemotherapy-induced neutropenia in a predominantly breast cancer cohort: A decision-support study for building a bundle care strategy.
BACKGROUND: Chemotherapy-induced neutropenia (CIN) is a common dose-limiting toxicity in patients with solid tumors, often leading to infections, treatment delays, or dose reductions. However, studies on the dynamic patterns of CIN across multiple chemotherapy cycles and their prediction remain limited. OBJECTIVES: To longitudinally observe CIN evolution across two consecutive cycles, develop a predictive model for severe CIN in cycle 2 (T2) based on cycle 1 (T1) characteristics, and classify patients by early recovery capacity to form a personalized bundle care strategy. METHODS: This single-center retrospective cohort study using electronic medical record (EMR) data enrolled 138 patients with solid tumors (89.1% breast cancer) who received ≥2 chemotherapy cycles between January 1, 2015, and January 31, 2025, at Zhuhai Maternal and Child Health Care Hospital, China. Neutrophil kinetic parameters were collected for T1 and T2. A multivariable logistic regression model predicted grade 3-4 CIN in T2 using T1 variables, with internal bootstrap validation. K-means clustering based on T1 recovery patterns identified patient subgroups. RESULTS: Severe CIN incidence decreased from 88.0% in T1 to 42.7% in T2 (p<0.001); neutrophil nadir rebounded from 0.40 × 109/L (IQR: 0.10-0.70) in cycle 1 to 1.05 × 109/L (IQR: 0.50-1.80) in cycle 2 (p<0.001). The prediction model (age, T1 nadir, T1 days to nadir, T1 recovery duration) achieved a test AUC of 0.677 and an accuracy of 78.6%. Out of the 138 total patients, 120 with complete recovery data were utilized for clustering analysis, identifying three groups: rapid (n=21), similar (n=79) and slow (n=20). The slow-recovery group exhibited significantly higher rates of febrile neutropenia (25.0% vs. 10.1% and 4.8%, p=0.043) and chemotherapy delays (35.0% vs. 15.2% and 9.5%, p=0.021). CONCLUSION: CIN severity generally improves from first to second cycle, but with substantial inter-individual heterogeneity. A T1-based prediction model combined with recovery stratification can identify high-risk patients for personalized CIN management. Further validation in diverse populations is warranted.
PubMed2026
Australian Research Related to Sporting and Musculoskeletal Injuries of the Foot and Ankle: A Bibliometric Analysis.
BACKGROUND: There is growing research evidence related to musculoskeletal and sports podiatry published by Australian researchers. This short report presents data from the musculoskeletal and sports podiatry stream of a national bibliometric review which aimed to map all Australian podiatry-related research from 1970 to 2024. METHODS: A systematic search of the literature was conducted via Scopus until December 2024. Studies were screened for eligibility using Covidence. Study meta-data was analysed using Biblioshiny to describe publications volume, authors, institutions, journals, and research collaborations. Via manual processes, each publication was categorised for: level of evidence using National Health and Medical Research Council criteria; research type using the United Kingdom Clinical Research Collaboration Health Research Classification System; and funding source, using Higher Education Research Data Collection specifications. RESULTS: The search strategy yielded 288 records published by 774 authors (19% international), with a total 12,593 citations, with 44.1 mean citations per article from 1991 to 2024 were included. A total of 65 articles (23%) were categorised as level I evidence. The British Journal of Sports Medicine and the Journal of Science and Medicine in Sport were equally the most frequent publication sources, publishing 23 (8%) articles respectively. Podiatry-related musculoskeletal and sports research is usually undertaken without dedicated funding (67%). The majority of published articles focussed on the evaluation of treatments and therapeutic interventions (36%) and on the aetiology of conditions (34%). CONCLUSION: The musculoskeletal and sports podiatry stream was the most widely researched, with the highest proportion of level I evidence among all streams of the national bibliometric review. Given the high burden of disease and adverse impacts on activities of daily living associated with musculoskeletal conditions, further attention in preventative care and the promotion of wellbeing in sports and musculoskeletal research would be beneficial.
PubMed2026
Validation of the International Weed Genomics Consortium genome annotation pipeline through reannotation of the model species Arabidopsis thaliana.
The International Weed Genomics Consortium (IWGC) has sequenced and annotated the genomes of over 30 weed species, generating genomic resources to understand their biology, evolution, and adaptation. The objective of this study was to evaluate the semi-automated, isoform sequencing (Iso-seq)-based, IWGC genome annotation pipeline by reannotating the genome of the model species Arabidopsis thaliana with various amounts and types of extrinsic data and to measure the impact that varying inputs had on the annotation completeness and quality. Annotations were run comparing the effects of (1) the quantity and source of Iso-seq reads, (2) annotated proteins from botanically closely related or distantly related species, and (3) the number of proteins provided to the annotation program "MAKER-P." Reannotations were compared to each other and to the published annotation of the A. thaliana genome. The IWGC annotation pipeline annotated almost all the genes without manual curation when informed with an Iso-seq dataset and proteins of related species. In general, the pipeline produced more accurate, annotated genes with more input proteins, especially from closely related species, in the gene model prediction step. Furthermore, the combination of proteins from several closely related species increased the number of annotated genes. The number or source of Iso-seq reads did not have a significant effect if many proteins from closely related species were utilized. The annotation pipeline annotated nearly 90% of genes from additional crop species genomes. The IWGC genome annotation pipeline is robust in reannotating the A. thaliana genome and therefore is most likely performing well in the several non-model weed species it has been used on so far.
PubMed2026
An Evaluation of AI-Generated Clinical Notes in the OpenNotes Era: A Thematic Analysis of Clinician Discourse.
BACKGROUND: The integration of ambient artificial intelligence (AI) scribes into the OpenNotes environment presents a profound governance crisis in healthcare. While patient access to medical records was designed as a transparency reform, the introduction of machine-generated text introduces novel vulnerabilities regarding record integrity, liability, and patients' trust. OBJECTIVE: This study investigates how clinicians discursively negotiate the systemic risks and accountability challenges of patient-facing, AI-assisted documentation. METHODS: Employing a netnographically informed qualitative design, the research conducted a reflexive thematic analysis of 484 relevant comments across 120 threads from eight clinician-oriented subreddits spanning October 2020 to February 2026. RESULTS: The analysis revealed five distinct governance challenges. First, an accountability vacuum exists where the mandatory clinician signature functions merely as a legal shock absorber for institutional AI liability. Second, clinicians frame AI hallucinations as a mathematically inevitable epistemic risk rather than a correctable technical bug. Third, a "dual-audience" problem emerges, as algorithmic optimization compromises both the individual clinical voice needed for peer communication and the empathetic clarity required for patient readers. Fourth, existing privacy frameworks are structurally inadequate to manage commercial data extraction during patient encounters. Finally, institutional productivity demands and AI-driven over-documentation severely threaten the fiscal credibility of the medical record through inadvertent upcoding. CONCLUSIONS: The prevailing regulatory assumption-that a physician's digital signature combined with passive patient visibility guarantees documentation accountability-is a fragile fiction. To protect clinical truth, health systems must transition from models of passive disclosure toward contingent transparency. This requires establishing authoritative, enforceable mechanisms for provenance tracking, error contestation, and vendor accountability.
PubMed2026
Factors influencing discussion duration in breast cancer multidisciplinary team meetings: insights for streamlining care.
PURPOSE: Multidisciplinary team meetings (MDTMs) in breast cancer care improve outcomes but are time-consuming and costly. This study investigates using data from the Dutch national cancer registry (NCR) and hospital electronic medical records (EMR) to efficiently calculate MDTM discussion durations, while complying with privacy laws. METHODS: This retrospective study analyzed breast cancer MDTM discussion durations using NCR and EMR data from 2014 to 2018. Discussion times were estimated from EMR timestamps, excluding outliers, and analyzed statistically. Ethical approval was obtained, including only non-opt-out patients. RESULTS: The final dataset included 1,048 tumors, 996 patients, and 1,487 MDTM discussion times after exclusions for missing data, duplicates, and outliers. Discussion durations varied significantly, with pre-operative and no-surgery discussions being longer than post-operative ones (p = 0.000), and factors such as MRI availability, tumor differentiation, malignancy, menopausal status, and cancer stage influencing duration in pre-operative cases. In post-operative discussions, molecular subtype, cancer stage, and tumor size were significant, while age, tumor differentiation, and menopausal status had no impact. CONCLUSION: This study evaluates discussion durations in breast cancer MDTMs using retrospective data from the NCR and EMR, demonstrating a feasible approach to assess MDTM functioning. Differences in discussion duration based on patient and tumor characteristics may help optimize MDTM efficiency. CLINICAL TRIAL NUMBER: Not applicable.
PubMed2026
Multiomics integrative bioinformatics analysis of gene expression characteristics and molecular mechanisms in preeclampsia placental tissue.
Preeclampsia (PE) is a severe pregnancy-specific complication characterized by new-onset hypertension and proteinuria after 20 weeks of gestation, which can cause multi-organ damage and life-threatening outcomes for both mothers and foetuses. Its pathogenesis remains incompletely elucidated, with placental dysfunction widely recognized as a core pathogenic factor. This study integrated multiple placental transcriptome and single-cell sequencing datasets from the Gene Expression Omnibus (GEO) database, employing a multi-dimensional bioinformatics approach - including differential expression analysis, Weighted Gene Co-expression Network Analysis (WGCNA), machine learning, molecular subtype clustering, single-cell resolution analysis, and intercellular communication analysis - to systematically identify PE-related key genes, construct a diagnostic model, define molecular subtypes, and explore potential molecular mechanisms. Results showed 10 differentially expressed genes (DEGs) were identified in PE placental tissues; WGCNA pinpointed the turquoise module as the core PE-associated module. Further screening using 11 machine learning algorithms identified 9 feature genes with high diagnostic value (DDR1, DIO2, FSTL3, HK2, HTRA4, LEP, SERPINA3, TMEM45A, TREM1). A diagnostic model built with the 'Stepglm[forward]' algorithm exhibited excellent performance in both training and validation sets (average AUC = 0.865). Molecular subtype analysis classified PE samples into two subtypes (C1, C2) with significantly distinct immune infiltration profiles, where the C1 subtype showed higher immune cell infiltration. Single-cell analysis identified 11 cell types in PE placental tissue and highlighted TMEM45A as a key DEG. Intercellular communication analysis revealed the VEGF signalling pathway as the core driver of abnormal cellular crosstalk in PE, primarily mediating signal transduction between villous cytotrophoblast cells (VCT), extravillous trophoblast cells (EVT), and endothelial cells. Hypoxia scoring analysis demonstrated significantly higher hypoxia levels in the PE group compared to normal controls, with TMEM45A expression positively correlated with hypoxia scores. This study provides novel insights into the molecular pathogenesis of PE and offers potential biomarkers and a theoretical basis for its early diagnosis and targeted therapy.
PubMed2026
Pseudo-publication bias in robotic surgery: structural mapping of narrative inertia.
The rapid worldwide adoption of robotic surgery often outpaces high-level comparative evidence. While evidence-based medicine relies on a hierarchical pyramid where causal inference resides at the apex, most of the scientific output is concentrated at the non-comparative base. It remains unknown whether the directional conclusions of these literature layers are symmetrically aligned. This study aimed to map the structural distribution of conclusions across the evidence hierarchy in visceral robotic surgery to evaluate potential narrative discordance. A stratified random sampling of intracavitary robotic surgery publications (thoracic, abdominal, and pelvic) was conducted from PubMed (1997-2026). Our sample size was calculated to achieve maximum representativeness (n = 800). Publications were equally partitioned into two pragmatic functional layers based on the presence of a control group: the Upper Hierarchy Zone (comparative layer, n = 400) and the Lower Hierarchy Zone (non-comparative layer, (n = 400). Directional orientations of author conclusions were operationally categorized as Favorable, Neutral, or Unfavorable. To ensure non-biased processing and scalability, semantic classification was executed via a Large Language Model (GPT-5.4), previously validated against a three-evaluator human pilot trial (absolute agreement 92%, Cohen's kappa > 0.81). Statistical analysis utilized Chi-square tests and Odds Ratio (OR) calculation with 95% Confidence Intervals (CI), with a secondary bipartite analysis (favorable vs. non-favorable). The global overview of the entire dataset (n = 800) demonstrated an illusion of literary equilibrium: 51.75% (n = 414) favorable, 45.50% (n = 364) neutral, and 2.75% (n = 22) unfavorable conclusions. However, stratification revealed a massive structural asymmetry (chi^2 = 312.9, p < 0.001). Within the upper hierarchy, conclusions were overwhelmingly non-favorable (79.50% vs. 20.50% favorable), dominated by neutral comparative outcomes (77.75%). Conversely, the lower hierarchy was heavily skewed toward favorable outcomes (83.00% favorable vs. 17.00% non-favorable). The lower zone also served as a sharper sensor of surgical failure, reporting a higher raw unfavorable rate (3.75%) than the apex (1.75%). Pragmatic bipartite analysis demonstrated that a publication at the base of the evidence pyramid has nearly 19 times higher odds of reporting a favorable conclusion compared to those at the comparative apex (OR 18.93, 95% CI: 13.84-26.87). A profound structural asymmetry exists within the robotic surgery literature. The disproportionate volume of highly favorable, lower-tier evidence numerically overwhelms comparative data, creating a phenomenon of "pseudo-publication bias." This structural distortion generates a powerful narrative inertia that drives global clinical adoption and shapes professional perception through cumulative enthusiasm rather than demonstrated methodological superiority.
PubMed2026
Radiological mass effect and neurological status are associated with mortality after burr-hole drainage for chronic subdural hematoma: a 10-year cohort study.
Chronic subdural hematoma (CSDH) is increasingly common in older adults and in patients receiving antithrombotic therapy. Although burr-hole drainage is generally safe and effective, perioperative mortality remains a concern, and reliable preoperative predictors are incompletely defined. We aimed to identify independent preoperative predictors of in-hospital mortality after burr-hole drainage for CSDH, with explicit characterization of causes of death, comorbidity burden, and the discriminative performance of candidate predictors. This single-center retrospective cohort study included 121 consecutive adult patients surgically treated for CSDH between January 2015 and December 2024. Preoperative variables included demographics, Glasgow Coma Scale (GCS) score, hematoma thickness, midline shift (MLS), cerebral edema on CT, antithrombotic use, and a comprehensive set of comorbidities (chronic kidney disease, chronic obstructive pulmonary disease, congestive heart failure, coronary artery disease, atrial fibrillation, diabetes mellitus, dementia, malignancy). Intensive care unit admission and postoperative complications were also recorded. The primary outcome was in-hospital mortality. Causes of death were systematically categorized. Associations were evaluated using Firth penalized logistic regression. Discriminative performance was assessed using receiver operating characteristic (ROC) analysis with bootstrap confidence intervals. A prespecified exploratory interaction analysis between cerebral edema and significant midline shift was performed. In-hospital mortality was 12.4% (15/121). The principal cause of death was cerebral herniation (9/15, 60.0%); extracranial complications (respiratory, septic, cardiac) accounted for 6/15 (40.0%). In the original multivariable Firth model, GCS ≤ 13 (adjusted OR 11.71, 95% CI 2.82-48.61, p < 0.001) and cerebral edema (adjusted OR 8.90, 95% CI 1.93-40.98, p = 0.005) were independently associated with mortality. In an extended model incorporating comorbidities, chronic kidney disease (OR 23.78, p = 0.025) and congestive heart failure (OR 42.39, p = 0.043) emerged as additional independent predictors, while cerebral edema (OR 61.89, p = 0.008) and GCS ≤ 13 (OR 5.80, p = 0.032) retained their associations. Combined model discrimination was excellent (Model 1: AUC 0.920; Model 2 with comorbidities: AUC 0.958). Subgroup analysis demonstrated a marked mortality gradient: 0% in patients with neither cerebral edema nor significant midline shift (n = 59), versus 72.2% in patients with both findings (n = 18). The exploratory interaction term (cerebral edema × midline shift ≥ 5 mm) was directionally consistent with synergy but did not reach statistical significance (OR 39.19, 95% CI 0.26-∞, p = 0.152), reflecting limited statistical power. Preoperative neurological impairment and cerebral edema are independently associated with in-hospital mortality after burr-hole drainage for CSDH. The coexistence of cerebral edema and significant midline shift identifies a clinically recognizable high-risk phenotype that may warrant heightened perioperative attention. Renal and cardiac comorbidities further contribute to mortality risk. These findings are hypothesis-generating and require validation in larger, prospective cohorts before incorporation into clinical risk stratification.Clinical trial number: not applicable.
PubMed2026
Research trends and hotspots of CAR-T cell therapy for acute lymphoblastic leukemia: A bibliometric analysis.
This study aims to analyze the global research patterns and emerging trends in CAR-T cell therapy for ALL through a bibliometric analysis. Publications were retrieved from the Web of Science Core Collection database. The bibliometric analysis utilized VOSviewer, CiteSpace, and the R package "bibliometrix" to visualize collaborations, keyword co-occurrences, and emerging research trends. A total of 844 articles from 253 journals by 6,459 authors across 44 countries were analyzed, showing an annual growth rate of 40.08%. The USA (372 articles, 38,065 citations) and China (275 articles, 5,636 citations) dominated research output. The University of Pennsylvania (353 articles), Memorial Sloan Kettering Cancer Center (170), and Children's Hospital of Philadelphia (131) were the most productive institutions, while Blood (41 articles) published the most articles. Stephan A. Grupp (38 articles, H-index = 30), Carl H. June (26 articles, H-index = 24), and Shannon L. Maude (25 articles, H-index = 20) were the most influential authors. Keyword analysis revealed five research clusters, including basic mechanisms, CAR design, population treatment integration, clinical outcomes, and toxicity management. Burst keyword analysis showed the evolution from basic science (2010-2013) to clinical translation (2014-2016), toxicity management (2017-2019), and recently to long-term outcomes and risk assessment (2020-2024), with "term follow-up" and "risk" as the only keywords with active bursts in 2024. This bibliometric analysis reveals that research on CAR-T therapy for ALL has progressed from foundational concepts to clinical implementation and now focuses on optimizing long-term outcomes and patient selection. Future research should prioritize biomarker development, next-generation CAR designs, and combination strategies to overcome persistence, toxicity, and resistance limitations in ALL treatment.
PubMed2026
A systematic review of neuroimaging studies of adults aged 35 and older with clinical, symptomatic and genetic risk for attention-deficit/hyperactivity disorder.
Attention-deficit/hyperactivity disorder (ADHD) affects 2.5% of adults and is associated with cognitive decline and dementia. The neurobiological mechanisms contributing to adverse outcomes in ADHD are poorly understood. ADHD-related brain alterations may persist into later life and interact with ageing-related processes, potentially increasing susceptibility to neuropathology. This preregistered systematic review synthesised neuroimaging findings in adults aged 35 years and older with clinical, symptomatic, or genetic risk for ADHD, and summarised cognitive and clinical correlates. A search of five databases produced 13 included studies. Risk of bias was assessed using the Newcastle-Ottawa Scale. Most studies (11/13) had low risk of bias. Compared to controls, ADHD groups exhibited alterations in fronto-striatal, fronto-parietal, and limbic systems implicated in executive control and attention. Middle-aged adults with clinical ADHD showed more widespread cortical structural differences, whereas older adults demonstrated abnormalities primarily in frontal regions, possibly reflecting attenuation of differences through ageing. Two functional studies in those with clinical ADHD reported frontal hypoactivation alongside parietal hyperactivation, consistent with compensatory recruitment. Among undiagnosed samples, there were interactions between genetic risk for ADHD and Alzheimer's disease-related pathology affecting brain and cognitive outcomes. Overall, ADHD-associated neurobiological alterations appear to persist into older age. Longitudinal investigations are needed to clarify these relationships.
PubMed2026
Predictive modeling of fluid status in hemodialysis: model development and internal validation using the MONitoring dialysis outcomes (MONDO) global database.
BACKGROUND: Optimized fluid management is crucial in dialysis care because extracellular volume overload drives adverse cardiovascular outcomes. At the same time, comorbidities such as inflammation and protein energy wasting lead to decreased muscle mass and intracellular water. Accurate assessment of total body water (TBW) and its extracellular water (ECW) and intracellular water (ICW) compartments is therefore essential to guide ultrafiltration, evaluate dialysis adequacy, and monitor patient risk. METHOD: Using adult patients from the MONitoring Dialysis Outcomes (MONDO) 2012 cohort, we developed predictive models to estimate fluid volume compartments based on demographic data, laboratory values, treatment parameters, and multi-frequency whole-body bioimpedance spectroscopy (BIS) measurements. Clinical features were aggregated over an up-to-90-day look-back window, yielding 18,600 patients and 162,479 dialysis treatments. eXtreme Gradient Boosting (XGBoost) models were trained and tested using patient-level splits, with parallel models built either incorporating or excluding prior BIS measurements. RESULTS: Models including BIS data showed excellent accuracy (R2 > 0.85), models excluding BIS features achieved inferior performance (R2 = 0.73-0.81). In models using BIS inputs, recent bioimpedance changes dominated feature importance. Models without BIS data relied primarily on urea distribution volume, age, and height. CONCLUSION: These findings indicate that fluid volume compartments can be reliably estimated from routinely collected clinical data and history BIS measurements, offering valuable support for interim assessment of fluid status between scheduled BIS measurements.
PubMed2026
Dysregulated proteins in plasma distinguishing Loeys-Dietz syndrome from other heritable thoracic aortic disease - an explorative study.
Objectives. Thoracic aortic aneurysms (TAAs) are often found in younger individuals and approximately 20% may be associated with heritable thoracic aortic disease (HTAD). There are some data on genomic biomarkers reflecting inflammation and extracellular matrix remodelling in HTAD. However, data that accurately reflect the corresponding protein changes are scarce. Our aim was to quantify proteins by using targeted proteomics in HTAD patients versus healthy controls, to better understand the underlying pathophysiology. Methods. Patients with Loeys-Dietz syndrome (LDS, n = 8), Marfan syndrome (MFS, n = 11), and familial TAA 6, i.e. actin alpha 2 (ACTA2, n = 7) pathogenic variants were recruited at our outpatient clinic. For comparison, blood samples were drawn from 16 healthy controls. Plasma samples were analysed by targeted proteome analysis of 276 proteins using immunoaffinity proteomics. Results. Whereas oncostatin M and pentraxin 3 levels appeared generally higher in HTAD patients, after adjusting for several confounders, significantly higher levels for these markers as well as TNF receptor superfamily member 9 (TNFRSF9), granulysin (GNLY), CD5, vasorin and glycoprotein 1b-α (GP1BA) were only observed in LDS patients compared to healthy controls. Levels of TNFRSF9, GNLY, GP1BA and CD5 correlated positively with Th17 and platelet counts. Conclusions. This discovery study suggests that LDS could represent a particular inflammatory subgroup of HTAD patients potentially reflecting the involvement of Th17 and platelet related mechanisms in the progression of TAA. Larger studies are needed to evaluate if the identified proteins could be used as biomarkers in these patients.
PubMed2026
Neurocritical factors associated with mortality and functional recovery in pediatric trauma patients admitted to a tertiary PICU.
PURPOSE: To identify early neuroprognostic factors associated with functional neurological outcome in pediatric trauma patients requiring PICU admission. The primary outcome was Glasgow Outcome Scale (GOS) at discharge and 6 months; secondary outcomes were in-hospital mortality and brain death. METHODS: We conducted a retrospective cohort study of 425 consecutive pediatric trauma admissions to a tertiary PICU from June 2014 to December 2021. Demographics, mechanisms of injury, admission severity scores (GCS, PRISM III, PTS), cranial CT findings, early laboratory markers, and key interventions were analyzed. Factors independently associated with mortality were assessed using multivariable logistic regression, and discrimination was evaluated with receiver operating characteristic analyses. RESULTS: Median age was 78 months and 64.2% were male. Falls and traffic accidents were the most common mechanisms. Overall mortality was 7.3% and was predominantly attributable to severe traumatic brain injury (29 of 31 deaths). Brain death occurred in 4.5%. At discharge, 349 of 425 patients (82.1%) had a good neurological outcome (GOS 4-5), whereas 76 (17.9%) had a poor outcome (GOS 1-3), including 31 in-hospital deaths (GOS 1). Among 394 hospital survivors, 6-month follow-up was available for 377 (95.7%); of these, 364 (96.6%) achieved good recovery and 13 (3.4%) had persistent poor outcomes. Among survivors with a poor outcome at discharge and available follow-up, 25 of 38 (65.8%) improved to a good outcome by six months. Seventeen survivors were lost to follow-up. Poor outcome (GOS 1 to 3) was associated with low admission GCS, cerebral edema or midline shift, and early physiologic stress including hyperglycemia and elevated lactate. Factors independently associated with mortality were inotropic support (OR 6.98), blood product administration (OR 6.52), albumin administration (OR 3.69), cerebral edema (OR 3.59), and admission GCS 8 or less (OR 6.82). PRISM III and PTS showed strong discrimination. CONCLUSION: In critically injured children, early neurological compromise and systemic instability that are identifiable during initial stabilization were the strongest factors associated with mortality and functional recovery, supporting neurofocused risk stratification and timely escalation of care.
PubMed2026
Benchmarking Fast Healthcare Interoperability Resources-Based Analytics: Quantitative Study of RESTful Server Queries and Big Data Engines.
BACKGROUND: Electronic health records offer vast clinical data for health care research, but interoperability challenges often hinder comprehensive analysis. The Health Level Seven Fast Healthcare Interoperability Resources (FHIR) standard addresses these challenges, although its nested and interconnected resource format can be complex for analytics. Several tools have emerged to facilitate analytical access, either by querying FHIR servers via representational state transfer (REST) APIs or encoding resources in relational formats. However, the performance implications of these methods remain largely unexplored. OBJECTIVE: This study aimed to benchmark the performance characteristics of different FHIR-based analytical approaches comparing REST API queries against SQL- and Spark-based big data frameworks operating on FHIR-encoded data. METHODS: We benchmarked the FHIR-PYrate library, which interfaces with a FHIR server's REST API, against Pathling, a library built for analytics based on Apache Spark, and Trino, a general-purpose SQL query engine. We defined and implemented multiple queries in each engine using 3 common analytics scenarios-data aggregation, counting, and extraction. Execution times were measured across Synthea-generated datasets of increasing size. RESULTS: On the largest dataset, containing 71,285,064 FHIR resources, Trino completed the aggregate query more than 12,000 times faster, and Pathling did so approximately 500 times faster than FHIR-PYrate. On average across all queries, Trino outperformed FHIR-PYrate, executing extraction queries 33 times faster and count queries 1.8 times faster. Pathling achieved a 2.6-time speedup for extraction queries, but FHIR-PYrate was approximately 13 times faster for count queries. CONCLUSIONS: While the REST-based FHIR search API is useful for standard queries and retrieving specific patient records and can outperform alternatives for some count queries, it generally lacks the performance and expressiveness needed for complex analytics. In contrast, alternative engines such as Trino and Pathling demonstrated substantial performance advantages for these scenarios.
PubMed2026
Clinicians' experiences in diagnosing and treating complex post-traumatic stress disorder in adults: a reflexive thematic analysis.
Background: Complex post-traumatic stress disorder (C-PTSD) has been included in the International Classification of Diseases, 11th revision (ICD-11) to recognize the impact of significant trauma(s) on an affected individual. C-PTSD has the core symptoms of post-traumatic stress disorder (PTSD) with additional symptoms of disturbances of self-organization. While the ICD-11 has been in use globally since 2022, research is limited on how clinicians working in routine adult mental health (AMH) services adapt to diagnosing and treating C-PTSD.Objective: To investigate the experiences of clinicians in applying and treating C-PTSD with adults in a public AMH setting.Method: A reflexive thematic analysis approach was used to code and analyse results from semi-structured interviews conducted with 20 psychologists and psychiatrists.Results: Three key themes were identified from clinicians' experiences: (1) 'C-PTSD is beyond a simple diagnosis', reflecting challenges regarding understanding trauma history and differential diagnosis; (2) 'Balancing treatment on a tightrope', highlighting trust as a foundation required in the therapeutic relationship before attempting trauma processing through various treatment modalities; and (3) 'Resourcing for C-PTSD treatment success', emphasizing how adequate resources, regular supervision, training, and attuned trauma services are needed to overcome barriers to treatment of C-PTSD in public AMH settings.Conclusions: Clinicians reported key challenges in working with C-PTSD diagnosis in AMH settings. While clinicians are aware of the diagnostic criteria, building a therapeutic relationship with C-PTSD clients remains a challenge before engaging in effective interventions. The need for adequate access to resources, such as evidence-based treatment pathways, further training on C-PTSD across multidisciplinary teams, regular supervision, and trauma-informed services that are attuned to individuals' needs, is a key issue for clinicians that requires addressing in public AMH services.
PubMed2026
Implementing an Interdisciplinary Order Set for Amputation: A Cross-Sectional Quality Improvement Study.
PURPOSE: This quality improvement study evaluated a novel, electronic medical record (EMR)-based order set designed to standardize interdisciplinary care coordination for patients undergoing lower extremity amputation at a large academic medical center. When activated, the order set automatically placed consultations for an interdisciplinary team consisting of physical therapy, occupational therapy, physical medicine and rehabilitation (PM&R), chaplaincy, and orthotics/prosthetics. METHODS: Patients (n=637) who underwent lower extremity amputation were divided into 2 cohorts: those with and without use of the amputation order set. Interdisciplinary consultation patterns, length of stay (LOS), and discharge disposition were analyzed. RESULTS: The order set significantly increased consultations with PM&R, chaplaincy, and orthotics/prosthetics services. While overall hospital LOS was longer in the order set group, patients who received preoperative order set placement had significantly shorter time from surgery to discharge. In addition, patients in the order set group were more likely to be discharged to inpatient rehabilitation facilities, as opposed to skilled nursing facilities or directly home. CONCLUSIONS: Findings suggest that structured interdisciplinary coordination, particularly when initiated preoperatively, can enhance discharge planning and facilitate higher-quality rehabilitation pathways. The implementation of a standardized amputation consultation panel within the EMR supports provider adoption and may reduce disparities in care access.
PubMed2026
Use of Digital Clinical Decision Support System Increases Adherence to Provision of Evidence-Based Interventions for Elevated Intracranial Pressure During Simulated Care of Patients with Traumatic Brain Injury.
INTRODUCTION: Clinical decision support (CDS) tools have been demonstrated to improve patient care and outcomes yet remain under-utilized in many clinical domains, including en route care. STUDY OBJECTIVE: This study evaluated whether a decision-tree CDS tool integrated within the government-created Battlefield Assisted Trauma Distributed Observation Kit (BATDOK; AFRL) clinical care software improves adherence to Joint Trauma System (JTS) guidelines for severe traumatic brain injury (TBI). METHODS: In a randomized crossover simulation of military clinicians (N = 24), paired participants managed a patient with elevated intracranial pressure (ICP) using either usual care (UC) or BATDOK with TBI CDS in a simulated fixed-wing air transport mission. Outcomes included completion of critical actions by simulation conclusion, time to completion of critical actions, adherence to tiered interventions as outlined in JTS Clinical Practice Guideline (CPG), and user evaluations of the CDS tool using the validated instrument, System Usability Scale (SUS). RESULTS: There were no significant differences in the primary outcome, percentage of critical items completed. Teams completed a median 83.3% of the critical items in the UC scenario, compared to 91.7% in the CDS scenario (P = 0.58; median difference 4.2%, 95% CI of the difference -8.1% to 16.4%). The mean SUS score for the CDS platform was 77.6 (SD = 16.0), which is associated with a "good" usability rating. Most participants rated the CDS platform favorably on every item of the SUS. CONCLUSION: The BATDOK with TBI CDS did not statistically increase completion of critical tasks in this initial evaluation of usability. However, these data suggest that BATDOK enhanced with CDS improved tiered guideline-concordant sequencing of ICP interventions outlined by the JTS CPG and was favorably rated by users, suggesting feasibility for operational integration.
PubMed2026
Users' opinions on the use of electronic health records at the Upper East Regional Hospital, Ghana: a qualitative study.
BACKGROUND: The use of technology in healthcare to manage patient records, guide diagnosis, and make referrals is termed electronic healthcare. An electronic health record system called Lightwave Health Information Management System (LHIMS) was implemented in 2021 at Bolgatanga Regional Hospital (BRH). This study evaluated the opinion of users on the use of LHIMS among healthcare workers, focusing on the extent to which its use has enhanced the main dimensions of clinical work. METHOD: A qualitative research design was employed to explore healthcare providers' experiences with the LHIMS. Purposive sampling was employed to recruit eleven (11) participants comprising nurses and doctors who had at least two years of experience using the LHIMS. An interview guide was used to facilitate in-depth, face-to-face interviews with all participants. RESULTS: Healthcare providers expressed overall satisfaction with LHIMS, citing its time-saving features, efficiency, data security, cost-effectiveness, and ease of use. Users reported receiving support from IT personnel, experienced colleagues, and stable network systems; however, challenges included inadequate staff training, documentation difficulties among nurse midwives, limited computer availability, insufficient user manuals, and frequent power interruptions. CONCLUSION: The study found that most LHIMS users were satisfied with the system, particularly its user-friendly interface and efficiency in managing and synchronizing patient data. To enhance system performance and sustain user satisfaction, the hospital should ensure uninterrupted power supply, provide mandatory training for new staff, integrate a comprehensive user manual into the LHIMS platform, and supply adequate computer resources to support effective use.
PubMed2026
Cost-effectiveness of ferumoxtran-enhanced macrophage-specific-MRI and PSMA-PET/CT versus ePLND for nodal staging in primary prostate cancer: a decision analysis based on updated phase-3 trial data.
BACKGROUND AND OBJECTIVE: Accurate nodal staging in intermediate- to high-risk prostate cancer (PCa) is crucial for treatment decisions. While extended pelvic lymph node dissection (ePLND) is the standard, it is invasive and has a low diagnostic yield. A 2019 analysis suggested that non-invasive imaging such as PSMA-PET/CT and ferumoxtran-enhanced macrophage-MRI (m-MRI) is cost-effective, but at the possible expense of a small QALY loss compared to ePLND, based on limited evidence. Recent Phase 3 trials have provided new data, prompting a reevaluation. Therefore, the aim of this article is to update a model with recent trial data to assess the cost-effectiveness of m-MRI and PSMA-PET/CT versus ePLND in Germany. MATERIAL AND METHODS: We adapted a Markov model to simulate lifetime outcomes for men with intermediate- to high-risk PCa from a German insurer's perspective, with costs updated to 2025 level. Diagnostic accuracy data were derived from recent multicenter trials. Costs and QALYs were calculated using a 3% discount rate. Sensitivity analyses tested uncertainties. A practical interactive online-tool is provided for clinical decision-making and research purposes, which can incorporate various input data (https://macrophage-mri.app). RESULTS: Both imaging options were dominant over ePLND (€37,855; 18.11 QALYs). PSMA-PET/CT was €7,869 cheaper and gained 0.800 QALYs; m-MRI was €9,985 cheaper and gained 0.990 QALYs. m-MRI was superior, saving €2,116 and gaining 0.19 QALYs over PSMA-PET/CT. The probabilistic analysis showed that m-MRI was optimal over 95% of the time at an €80,000/QALY threshold; the probability of PSMA-PET/CT being optimal was less than 5%. CONCLUSIONS: An imaging-first approach outperforms routine ePLND, with m-MRI as a cost-effective option. PSMA-PET/CT's low sensitivity limits its usefulness, though it is still cheaper than ePLND. These results support including m-MRI in guidelines for initial staging.
PubMed2026
Effects on mortality of different blood purification techniques in sepsis patients: an umbrella review of systematic reviews and meta-analyses.
Sepsis remains a leading cause of mortality worldwide, and extracorporeal blood purification has been widely implemented despite ongoing uncertainty regarding its survival benefit. We conducted an umbrella review of 42 systematic reviews and meta-analyses evaluating mortality across major extracorporeal blood purification modalities. Mortality estimates generally favored extracorporeal blood purification over conventional care, but effect sizes and consistency varied substantially by modality, and the overall certainty of evidence for mortality was low. At the review level, polymyxin B hemoperfusion showed a relatively consistent direction toward lower mortality, whereas renal replacement therapy-based strategies were typically closer to the null. However, most included reviews were of low or critically low methodological quality, with downgrading driven by risk of bias, inconsistency, and potential publication bias. Therefore, these findings should be interpreted cautiously and should not be considered definitive evidence of survival benefit. They highlight persistent evidentiary fragility and underscore the need for rigorously designed, phenotype-informed trials to clarify modality-specific effects in sepsis.
PubMed2026
Recent Advances in AI for Automated ICD Coding: A Systematic Literature Review.
International Classification of Diseases (ICD) codes enable correct billing, insurance reimbursement, and healthcare analytics. However, manual coding is time-consuming, expensive, and error-prone, creating bottlenecks in clinical workflow and limiting scalability. Artificial intelligence (AI) has emerged as a promising solution for automated ICD code assignment from unstructured clinical text. This systematic review explores the current state of automated ICD coding research, examining models applied to diverse clinical documents including discharge summaries, electronic health records, nursing notes, and pathology reports. Following PRISMA guidelines, we searched six databases for studies published between 2019 and 2024, selecting 54 relevant studies from 4,280 initial citations. Our analysis reveals the use of diverse datasets, preprocessing techniques, and feature extraction methods, alongside a clear evolution from traditional machine learning to deep learning approaches, with substantial architectural diversity across convolutional, recurrent, transformer, and hybrid models. Performance varies considerably across dataset configurations, with models achieving higher accuracy on frequent code subsets compared to full label spaces. However, critical gaps persist: overreliance on single-language, single-institution datasets limits generalizability; difficulties in predicting rare codes remain unresolved; lack of model interpretability undermines clinical trust; and inconsistent evaluation protocols hinder meaningful comparison. To address these challenges, we propose a 5P evidence-grounded research agenda: Population Diversity, Performance Robustness, Prediction of Rare Codes, Provenance Transparency, and Practical Integration. These findings underscore AI's potential to transform ICD coding while highlighting the need for standardized benchmarks, rigorous external validation, multilingual datasets, and explainable architectures to enable equitable and effective deployment in real-world healthcare systems.
PubMed2026
Systematic review of prognostic scores and individual predictor variables for short-term mortality after acute pulmonary embolism.
BACKGROUND: For patients with acute pulmonary embolism (PE), assessment of prognosis helps with risk stratification, triage for level of care, management strategy, and communication among healthcare workers and patients. We sought to identify prognostic models and individual factors associated with short-term outcomes after acute symptomatic PE. METHODS: We performed a systematic review of prognostic factors for PE, searching MEDLINE, Embase, and Web of Science for records up to 1 June 2024. Studies of any design evaluating potential prognostic models or individual variables (not contained in the models) associated with short-term mortality after acute PE were included. RESULTS: We identified 314 studies that included 2,495,115 patients. Of these, 225 studies included 2,267,952 patients and evaluated 24 prognostic models for patients with acute PE. The most frequently used validated models were the simplified Pulmonary Embolism Severity Index (sPESI) (127 studies), the original PESI (79 studies), and the European Society of Cardiology risk schema (34 studies). Each model-development study had a c-index ≥ 0.7. Individual factors associated with prognosis included older age, presence of coexisting conditions, abnormal clinical signs and symptoms, clot burden, markers of right‑ventricle dilatation/dysfunction and myocardial injury, altered laboratory results indicating impaired haemodynamics, and tests that assess for systemic inflammation. Pooled odds ratios for variables not contained in any eligible prognostic model ranged from 1.43 (for D-dimer) to 2.65 (for right heart thrombi). CONCLUSIONS: This systematic review identified 24 prognostic models and 18 individual variables distinct from the prognostic models associated with short-term mortality after acute PE.
PubMed2026
A Framework for Transparent Reporting of Data Quality Analysis Across the Clinical Electronic Health Record Data Lifecycle.
Data quality (DQ) and transparency of secondary data are critical factors that delay the adoption of clinical AI models and affect clinician trust in them. Many DQ studies fail to clarify where, along the lifecycle, quality checks occur, leading to uncertainty about provenance and fitness for reuse. This study develops a framework for transparent reporting of DQ assessments across the clinical electronic health record (EHR) data lifecycle. The reporting framework was developed through iterative analysis to identify actors and phases of the clinical data lifecycle. The framework distinguishes between data-generating organisations and data-receiving organisations to allow users to map DQ parameters to stages across the data lifecycle. The framework defines five key lifecycle phases and multiple actors. When applied to the real-world dataset, the framework demonstrated applicability in revealing where DQ issues may originate. The framework provides a structured approach for reporting DQ assessments, which can enhance transparency regarding data fitness for reuse, supporting reliable clinical research, AI model development, and internal organisational governance. This work provides practical guidance for researchers to understand data provenance and for organisations to target DQ improvement efforts across the data lifecycle.
PubMed2026
Causal association and shared mechanisms between Graves' disease and prostate cancer: insights from Mendelian randomization, machine learning, and comprehensive bioinformatics.
BACKGROUND: Observational studies link hyperthyroidism to increased prostate cancer (PCa) risk, but causality and mechanisms remain unclear. Graves' disease (GD), the primary cause of hyperthyroidism, involves chronic immune dysregulation that may influence PCa through shared immune pathways. METHODS: We performed bidirectional two-sample Mendelian randomization (MR) using IEU Open GWAS data, then integrated differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning on Gene Expression Omnibus (GEO) datasets to identify shared gene, validated by ROC curves, and analyzed immune profilesusing ssGSEA. RESULTS: MR analysis indicated that genetic predisposition to GD significantly reduced PCa risk (OR = 0.997, 95% CI = 0.996-0.999, p = 0.004), with consistentsensitivity and no reverse causality. Four key genes (BTG2, JUN, JUNB, FOS) were identified as robust shared genes with high predictive accuracy in external validation. Immune profiles analysis revealed disease-specific associations of these genes: BTG2 and JUNB correlated with memory CD8 T cells in GD, whereas all four genes correlated with dendritic cells, mast cells and NK cells in PCa. CONCLUSION: This study provided novel insights into the protective effect of GD against PCa and identified shared genes and immune mechanisms, offering a deeper understanding of the common mechanisms between GD and PCa.
PubMed2026
Effectiveness and usability of artificial intelligence-powered assistive technologies in Supporting daily activities of children with cerebral palsy: a systematic review.
BACKGROUND: Cerebral Palsy (CP) is the main cause of motor disabilities in childhood, necessitating innovative approaches to rehabilitation and assistive technology (AT). Simultaneously, artificial intelligence (AI) is increasingly being integrated into devices to create more adaptive, personalized, and effective AT. This systematic review aimed to evaluate the effectiveness and usability of AI-powered assistive technologies designed to support daily activities and rehabilitation in children with CP. MATERIALS AND METHODS: Five databases, including Scopus, Web of Science, PubMed, Embase, and IEEE Xplore, were systematically searched, and 23 articles were included in the final analysis. Articles were identified, selected, and categorized into emerging thematic areas based on the primary function and application of the technology. RESULTS: Five key thematic topics were identified: 1) AI-driven motor rehabilitation and gait training for functional mobility; 2) intelligent assessment and monitoring systems for clinical decision support; 3) AI-supported communication, social interaction, and intention recognition tools; 4) gamified and virtual reality-based interventions to enhance engagement and usability; and 5) smart assistive systems supporting daily living and independent mobility. The findings demonstrate a strong trend toward the application of AI technologies in personalized, engaging, and data-driven interventions for children with CP. However, the field is predominantly in the proof-of-concept stage, with limitations including small sample sizes, lack of long-term clinical validation, challenges in user-centered design, and usability for children with CP. CONCLUSION: AI-powered assistive technologies hold significant potential for transforming the care of children with CP by enabling highly personalized and engaging interventions. To actualize this potential, future work must realize that practical application remains challenging owing to limited clinical validation, technological integration, and usability barriers for children with CP. Future research must prioritize user-centered design and multidisciplinary collaboration to ensure that AI and robotic advancements improve the usability and quality of life for children with CP.
PubMed2026
Exploratory multi-omics links CCL2/TIMP1 axis to immunosuppressive TME in glioblastoma.
Glioblastoma (GBM) is defined by extreme lethality and transcriptomic plasticity, but the signatures driving the most aggressive tumors remain incompletely defined. In this exploratory in silico study, TCGA-GBM patients were stratified using a strict 1-year overall survival threshold. We integrated differential expression analysis, WGCNA, single-cell RNA-seq, spatial transcriptomics, and virtual knockout simulations. A high-risk signature centered on CCL2 and TIMP1 was identified. Single-cell and spatial mapping linked these genes to an inflammatory, macrophage-enriched microenvironment. The signature inversely correlated with neuronal synapse mimicry scores, suggesting that extreme aggressiveness involves a macroscopic shift from differentiated neuronal states toward an undifferentiated inflammatory phenotype. Virtual perturbation modeling confirmed CCL2 and TIMP1 as highly interconnected network hubs. Despite limitations inherent to computational and retrospective cohorts, our rigorous multi-omics validation identifies the CCL2/TIMP1 axis as a driver of potential prognostic indicator. These findings generate the hypothesis that these mediators reflect a critical inflammatory, mesenchymal-like tumor microenvironment shift, warranting independent cohort validation and experimental investigation.
PubMed2026
Multi-omic modelling of body mass index response to a dietary weight loss intervention.
Obesity is a multifactorial condition, and there is wide heterogeneity in responses to weight loss interventions. Although it remains challenging, modeling responses to weight loss interventions can help tailor treatments, increase weight loss success, or improve our understanding of underlying pathophysiology. We leveraged multi-omic (genetics; gut microbiota: taxonomy, inferred gene pathways and metabolite dynamics; blood metabolomics) and clinical data (e.g., lipids, blood glucose) from a 12-month behavioral weight loss trial of adults (n = 150) with overweight/obesity, to forecast longitudinal body mass index (BMI) and BMI change (ΔBMI) using Mixed Effects Random Forests (MERF) and GLMM-Lasso. Across modeling approaches and outcomes, routinely available clinical variables and blood metabolomics consistently improved prediction over basic demographics, and metabolomics added value beyond clinical information. Across models, the combined omic risk score most improved models of longitudinal BMI trajectories, explaining 20.5-26.0% marginal variance (R2m), whereas metabolomic risk scores most improved BMI change prediction (R2m = 52.9-59.3%). Gut microbial taxonomy and inferred gene pathways offered modest but significant gains for some models and outcomes, while metabolite dynamics consistently failed to enhance performance. The most important features in the models included insulin, glycoprotein acetyls, lipoprotein sizes, and certain amino acids, aligning with known inflammatory and metabolic mechanisms. These findings support that select blood-based biomarkers correlate with individual responses to weight loss efforts.
PubMed2026
Starting the Conversation: Implementation of Updated Initial Patient Assessment Documentation in the Electronic Medical Record.
The Initial Patient Assessment (IPA) documentation within the selected healthcare organisation's electronic medical record (EMR) is a key component of nursing documentation and planning for patients' hospitalisations. Since its implementation in 2019, the EMR IPA documentation has not been re-assessed for usefulness or completeness. A project was developed to assess, re-design and implement an updated IPA using the Exploration, Preparation, Implementation, Sustainment (EPIS) framework. New IPA forms were co-designed with consumers and nurses to be more conversational and implemented across the organisation for neonatal admissions, paediatric admissions, adult admissions, and adult and paediatric day ward admissions. Improvement in completeness and usefulness was sustained, and this project filled a gap in the literature by providing a co-designed approach to nursing documentation within the EMR with end-users and consumers.
PubMed2026
Towards FHIR Pattern Languages: Reusable Guidance for HIE.
HL7® FHIR® is increasingly used for health information exchange, yet delivery outcomes vary and teams frequently re-solve similar problems. This paper presents a "towards" contribution that captures proven practice as two complementary pattern languages: one for authoring FHIR artefacts (profiles, terminology, implementation guides) and one for implementing distributed systems that exchange FHIR at scale. The pattern languages make forces and trade-offs explicit, enabling reuse across teams and contexts. A publication pipeline produces multiple output formats-static website, EPUB, and DocBook-from a single machine-readable source, including a machine-consumable llms.txt index to support AI-assisted navigation. The approach is described, the generated outputs presented, and the plans for operational validation and AI-assisted quick-start pathways are outlined.