Assessment Of Severity Research Articles

Biochemical markers in hand osteoarthritis: a path to precision medicine.

Hand osteoarthritis (HOA) is a heterogeneous joint disease with high radiographic and symptomatic prevalence. The diagnosis of HOA is based on clinical and radiographic features. The identification of potential biomarkers for diagnosis, prognosis, disease severity assessment, and therapeutic efficacy evaluation of НОА remains an active area of research. To summarize the eligible biomarker data, a comprehensive narrative review was performed using the PubMed and Scopus databases covering publications from inception to December 2024. Our search uncovered five distinct groups of biomarkers associated with HOA, categorized based on their origin and involvement in distinct biological processes: (1) cartilage synthesis and catabolism, (2) bone remodeling, (3) inflammation, (4) adipokines, and (5) others classified separately. Each biomarker was evaluated in accordance with the Burden of disease, Investigative, Prognostic, Efficacy of intervention, and Diagnostic (BIPED) criteria. In conclusion, no biomarker has yet demonstrated sufficient sensitivity, specificity, or reproducibility to meet the BIPED criteria for classification. The early diagnosis and treatment of HOA require the development of more sensitive assays, advanced platforms, and rigorous bio-clinical trials to stratify previously studied biomarkers and identify novel ones. Precision medicine in HOA demands reliable biomarkers, cost-effective assays, and standardized, reproducible methodologies for global applicability.

Blood lactate as a predictor of clinical outcomes and health-care resource needs in combat abdominal injuries

Background. Combat abdominal injuries (CAI) are cha­racterized by high mortality and occupy a leading position among the issues of battlefield surgery. It is very important to evaluate early and accurately the severity of CAI, which will allow starting correct treatment in time, preventing possible complications and improving clinical outcomes. The low sensitivity of commonly used cardiovascular parameters to detect the initial manifestations of tissue hypoperfusion induced by blood loss dictates the need to use more effective markers that reflect metabolic changes in tissues. The aim of this study is to determine the predictive efficacy of serum lactate regarding the risk of death and health-care resources needs in patients with CAI. Materials and methods. We examined 86 injured servicemen with CAI who were randomized into two groups — survivors and nonsurvivors. The predictive efficacy of capillary blood lactate and its clearance regarding the risk of death and health-care resource needs in CAI were studied. Six consecutive (within 48 h) measurements of lactate and lactate clearance corresponding to each measurement (except the first) were evaluated for each patient. Logistic regression models were constructed and analyzed to assess the influence of lactate level and lactate clearance on the risk of death and need for vasopressor support during medical evacuation to the Role 3 (after performing an emergency surgery). A correlation analysis was conducted on the association between lactate and the need for RBC transfusion, as well as assessment of the CAI severity using the Admission Trauma Score (AdTS). Results. In the group of nonsurvivors, lactate was higher (p = 0.001) at all stages of the study. We determined that an increase in the lactate level at the time of admission of a victim with CAI to the forward surgical team (LacpreOP) increased the risk of death by 1.5 times for every 1 mmol/l of lactate elevation (odds ratio (OR) 1.5, 95% confidence interval (CI) 1.22–1.85), and the chances of the need for vasopressor support during medical evacuation to the Role 3 — by 1.7 times for every 1 mmol/l of lactate elevation (OR 1.7, 95% CI 1.05–1.86). A strong positive correlation (ρ = 0.8) was found between LacpreOP and the need for RBC transfusion during the first 24 h after injury, as well as a moderate positive correlation (ρ = 0.5) between LacpreOP and CAI severity assessment on the AdTS. Conclusions. The results of the study indicate the high predictive efficacy of lactate regarding the risk of death (OR 1.5, 95% CI 1.22–1.85) and the need for vasopressor support during medical evacuation of victims with CAI to the Role 3 (OR 1.7, 95% CI 1.05–1.86). There was a positive correlation between lactate and the need for RBC transfusion du­ring first 24 h after injury (ρ = 0.8), as well as between lactate level and CAI severity according to the AdTS (ρ = 0.5).

Visual and somatosensory evoked potentials abnormalities among Behçet’s disease patients and their relation to disease activity, severity and antiphospholipid antibodies: a cross-sectional study

BackgroundBehçet’s disease (BD) is a common disease with high morbidity and mortality. Ocular, neurological, and vascular affection in BD are a major cause of such morbidity and mortality. Evoked potential (EP) studies including visual evoked potentials (VEP) and somatosensory evoked potentials (SSEP) in addition to antiphospholipid antibodies (aPL) are valuable tools for detection of ocular, neurological and vascular affection and may be used for assessment of activity and severity in BD. We aimed to use EP studies and aPL as objective tools in BD assessment.ResultsAbnormal VEP was found in 76% of BD patients and has a significant association with ocular involvement (P = 0.003), Moreover, Abnormal VEP was significantly associated with ocular activity (P = 0.002). Abnormal SSEP in both median and tibial nerves was found in 62% of patients, prolonged central conduction time of median and tibial nerves was found in 46% and 22% of patients respectively and was significantly associated with neurological involvement in BD (P < 0.05). Abnormal VEP and SSEP studies were significantly associated with BD disease severity (P < 0.05) but not activity. Vascular involvement was significantly associated with elevated lupus anticoagulant and anti-cardiolipin IgM antibodies (P < 0.05), elevated lupus anticoagulant levels were associated with optic nerve involvement and abnormal VEP.ConclusionAbnormal VEP and SSEP studies can be considered as indicators for BD severity and hence poorer prognosis. VEP study is a valuable tool in BD and may indicate ocular involvement or ocular activity. Prolonged Central conduction time of upper limb and lower limb evaluated by N13- N20 IPL and N22-P39 IPL respectively may be used to detect nervous system involvement in BD patients. Optic nerve involvement may be suspected in BD patients with elevated lupus anticoagulant, elevated LA and aCL IgM can be used as indicators for vascular involvement in BD.

Effect of Seed Treatment and Sowing Time on Microdochium spp. Caused Root Rot in Winter Wheat Cultivars

Microdochium species are harmful pathogens of winter cereals, causing snow mould and stem base diseases such as root rot. With changing climatic conditions, including prolonged wet autumns and mild winters, addressing pathogens that thrive at low positive temperatures has become increasingly important. Integrated strategies, including optimized sowing times, resistant cultivars, and the use of seed treatment fungicides have been suggested as effective approaches to mitigate Microdochium-induced damage. Field trials were conducted between 2021 and 2024 using five winter wheat cultivars treated with different seed treatment fungicides and sown at either optimal or delayed sowing times. Laboratory analyses identified Microdochium spp. as the dominant pathogens on the stem base across all trial years. Disease severity assessments indicated that seed treatment fungicides were generally effective against root rot, with products containing fludioxonil and SDHI group fungicides delivering the best performance. While disease pressure varied between optimal and late sowing experiments, late-sown winter wheat exhibited slightly reduced damage in most years. Additionally, some of the tested winter wheat cultivars demonstrated better performance against Microdochium spp. damage compared to others, highlighting the importance of selecting resistant cultivars. This study provides valuable insights into the control of Microdochium spp. under changing climatic conditions, particularly during the early growth stages of winter wheat.

Challenges and Opportunities in Remote Sensing-Based Fuel Load Estimation for Wildfire Behavior and Management: A Comprehensive Review

Fuel load is a crucial input in wildfire behavior models and a key parameter for the assessment of fire severity, fire flame length, and fuel consumption. Therefore, wildfire managers will benefit from accurate predictions of the spatiotemporal distribution of fuel load to inform strategic approaches to mitigate or prevent large-scale wildfires and respond to such incidents. Field surveys for fuel load assessment are labor-intensive, time-consuming, and as such, cannot be repeated frequently across large territories. On the contrary, remote-sensing sensors quantify fuel load in near-real time and at not only local but also regional or global scales. We reviewed the literature of the applications of remote sensing in fuel load estimation over a 12-year period, highlighting the capabilities and limitations of different remote-sensing sensors and technologies. While inherent technological constraints currently hinder optimal fuel load mapping using remote sensing, recent and anticipated developments in remote-sensing technology promise to enhance these capabilities significantly. The integration of remote-sensing technologies, along with derived products and advanced machine-learning algorithms, shows potential for enhancing fuel load predictions. Also, upcoming research initiatives aim to advance current methodologies by combining photogrammetry and uncrewed aerial vehicles (UAVs) to accurately map fuel loads at sub-meter scales. However, challenges persist in securing data for algorithm calibration and validation and in achieving the desired accuracies for surface fuels.

ATM Expression and Activation in Ataxia Telangiectasia Patients with and without Class Switch Recombination Defects

BackgroundAtaxia telangiectasia mutated (ATM) kinase plays a critical role in DNA double-strand break (DSB) repair. Ataxia telangiectasia (A-T) patients exhibit abnormalities in immunoglobulin isotype expression and class switch recombination (CSR). This study investigates the role of residual ATM kinase expression and activity in the severity of A-T disease.MethodsA-T patients with defined genetic diagnoses were classified based on CSR and based on the severity of their medical complications. Isolated peripheral blood mononuclear cells from any patient were evaluated before and after exposure to 0.5 Gy ionizing radiation for one minute. Western blotting was performed to identify the expression of ATM and phosphorylated ATM (p-ATM) proteins compared to age-sex-matched healthy controls.ResultsIn severe A-T patients (n = 6), the majority (66.7%) had frameshift mutations, while 33.3% had nonsense mutations in the ATM gene. The mild group (n = 3) had two cases of splice errors and one missense mutation. All patients with CSR defect had elevated IgM serum levels, whereas all switched immunoglobulins were reduced in them. Expression of ATM and p-ATM proteins was significantly lower (p = 0.01) in all patients compared to healthy controls, both pre-and post- and post-radiation. Additionally, low ATM and p-ATM protein expression levels were linked with the clinical severity of patients but were not correlated with CSR defects.ConclusionExpression and activation of ATM protein were defective in A-T patients compared to healthy controls. Altered expression of ATM and p-ATM proteins may have potential clinical implications for prognostic evaluation and symptom severity assessment in individuals with A-T.

Contemporary clinical perspectives on chronic low back pain: The biology, mechanics, etc. underpinning clinical and radiological evaluation.

Pain of a chronic nature remains the foremost concern in tertiary spine clinics, yet its elusive nature and quantification challenges persist. Despite extensive research and education on low back pain (LBP), the realm of diagnostic practices lacks a unified approach. Clinically, LBP exhibits a multifaceted character, encompassing conventional assessments of severity and disability, alongside nuanced attributes like pain characterization, duration, and patient expectations. Common instigators of LBP encountered in spine surgical settings comprise degenerated intervertebral discs (IVD), herniated IVD, canal and foraminal stenosis, and spondylolisthesis. However, addressing the root cause necessitates its identification and substantiation through visualization. This perspective reviews the diagnostic complexities of LBP. Thorough history-taking and physical examinations offer preliminary insights into the underlying source of pain, whether it arises from discogenic origins, neural compression, or sagittal imbalance. The importance of classifying chronic LBP into the underlying pathophysiology is explored. Emphasis is placed on the necessity of aligning clinical observations with imaging findings to guide personalized treatment strategies. Currently, there exists a disparity globally between evidence-based recommendations and actual applications. Recent discoveries behind the pathophysiology of pain phenotypes signify the importance of classifying LBP into its neuropathic or nociceptive origins. The pivotal role of radiological investigations in validating clinical findings for an accurate diagnosis cannot be overstated. However, radiology should not operate in isolation; the disconnect between the clinical and radiological realms ultimately benefits neither the patient nor the surgeon. Additionally, more sensitive measures of IVD prolapse and the corresponding inflammatory pathway triggered are required to provide information on the underlying pathophysiological mechanism of pain generation. This perspective article underscores the imperative fusion of clinical acumen and radiological precision in the intricate landscape of LBP diagnosis. These findings advocate for a paradigm shift towards personalized medicine. By offering a compass for surgeons to navigate this complex terrain and deliver more effective, patient-centered care with targeted interventions this article aims to enhance management outcomes for chronic LBP.

Clinical significance of PCT, CRP, IL-6, NLR, and TyG Index in early diagnosis and severity assessment of acute pancreatitis: A retrospective analysis

To evaluate the clinical utility of PCT, CRP, IL-6, NLR, and TyG index in improving the early diagnosis and severity assessment of acute pancreatitis (AP). This retrospective study included 137 AP patients and 30 healthy controls from Hunan Provincial People’s Hospital (January 2021–September 2023). Univariate and multivariate logistic regression analyses assessed the associations between biomarkers and severe acute pancreatitis (SAP). Receiver operating characteristic (ROC) curves, DeLong test, and Bonferroni correction were used to evaluate predictive performance. Model robustness was validated via 5-fold cross-validation. PCT, CRP, IL-6, NLR, and TyG index levels were significantly elevated in AP patients compared to controls (P < 0.001) and correlated with disease severity (P < 0.05). CRP and NLR levels differed significantly among mild, moderate, and severe AP (P < 0.01). Alcohol consumption and hyperlipidemia were significantly linked to AP severity (P for trend < 0.0001). Multivariate analysis identified hyperlipidemia (OR = 3.030, P = 0.040), CRP (OR = 1.011, P < 0.001), and NLR (OR = 1.078, P = 0.020) as independent SAP predictors. The combined model of CRP + NLR + TyG achieved the highest AUC (0.882, sensitivity = 77.2%, specificity = 88.5%), though it was not significantly better than CRP + NLR or CRP + TyG models (P > 0.05). 5-fold cross-validation confirmed consistent performance (mean AUC = 0.817 ± 0.118). PCT, CRP, IL-6, NLR, and TyG index are valuable in diagnosing and assessing AP prognosis. Hyperlipidemia, CRP, and NLR are reliable independent predictors of SAP. Combining multiple biomarkers enhances diagnostic precision and provides guidance for personalized treatment strategies in AP.

Apathy in Alzheimer's disease: Eye movements characteristics and neurostructural basis.

We sought to evaluate the characteristics of eye movements in Alzheimer's disease (AD) patients with apathy (AD-A) and their ability to identify AD-A and explore the shared neurostructure of eye movements and apathy. Total 32 normal controls, 36 AD-A and 72 AD with no apathy (AD-NA) patients were recruited. Parameters of smooth pursuit, fixation, prosaccade and antisaccade were compared among the three groups. Correlation analyses were conducted on apathy score, eye movement parameters and gray matter volume (GMV) in AD patients. Receiver operating characteristic curves were used to determine the power of eye movement parameters to identify AD-A patients. AD-A group exhibited a longer start-up duration of smooth pursuit, latency of gap and overlap prosaccades than AD-NA and normal control groups. In AD patients, apathy score was positively correlated with latency of overlap prosaccade. The GMVs of right pregenual anterior cingulate cortex (ACC) and left supracallosal ACC were negatively correlated with apathy score. Regions shared by apathy and latency of overlap prosaccade included right pregenual ACC and left supracallosal ACC. The area under curve discriminated AD-A from AD-NA patients by combining start-up duration, latency of gap and overlap prosaccade, and demographic information was 0.812. AD-A patients exhibit delayed initiation in eye movements, and the more prominent apathy indicates prolonged latency of overlap prosaccade in AD patients. Apathy and latency of overlap prosaccade share a neurostructural basis in AD patients. Our results contribute to providing a new method for early identification and severity assessment for AD-A.

The anti-dyskinetic effect of the clinic-ready mGluR2positive allosteric modulator AZD8529 in the 6-OHDA-lesioned rat.

L-3,4-dihydroxyphenylalanine (L-DOPA) remains the main treatment for motor symptoms of Parkinson's disease (PD). However, chronic use is associated with the development of complications such as L-DOPA-induced dyskinesia. We previously demonstrated that LY-487,379, a highly selective metabotropic glutamate receptor 2 (mGluR2) positive allosteric modulator (PAM), reduces the severity of L-DOPA-induced abnormal involuntary movements (AIMs) in the 6-hydroxydopamine (6-OHDA)-lesioned rat model of PD, without interfering with the anti-parkinsonian action of L-DOPA. Here, we seek to determine the effect of AZD8529, another highly selective mGluR2 PAM, on L-DOPA-induced AIMs in the 6-OHDA-lesioned rat. Unlike LY-487,379, AZD8529 has previously undergone clinical trials and could therefore be repurposed if proven efficacious in pre-clinical studies. We first determined the pharmacokinetic (PK) profile of AZD8529 to administer doses leading to clinically relevant plasma levels in the behavioural studies. Then, dyskinetic 6-OHDAlesioned rats were administered AZD8529 (0.1, 0.3, and 1 mg/kg) or vehicle in combination with L-DOPA followed by assessment of AIMs severity. The cylinder test was then used to evaluate the effect of AZD8529 on the anti-parkinsonian action of L-DOPA. We found that AZD8529 (0.1, 0.3 and 1 mg/kg) in combination with L-DOPA significantly reduced the severity of AIMs duration (P < 0.05), but not amplitude, when compared to L-DOPA/vehicle. AZD8529 administration did not interfere with L-DOPA anti-parkinsonian action. Our results provide evidence that mGluR2 positive allosteric modulation with AZD8529 may be a viable, yet relatively modest, treatment strategy to alleviate L-DOPA-induced.

P0089 Infra-red microspectroscopy provides quantitative assessment of fibro-inflammation in Crohn’s disease strictures and predicts post-operative recurrence

Abstract Background Quantitative assessment of fibro-inflammation in Crohn’s disease strictures remains a challenge despite its role in clinical decision making using immunomodulatory drugs or endoscopic/surgical interventions. While histology remains the gold standard, no validated histological scoring systems for Crohn’s disease strictures exist and assessment is subject to significant intra- and inter-observer variability. Fourier-transform infra-red (FTIR) microspectroscopy is a reproducible, label-free and non-destructive approach for analysing tissue biochemistry via molecular vibrations. We have previously shown accurate assessment of inflammation severity using this technique in colitis models (1). The aim of this study was to assess Crohn’s disease strictures using FTIR spectroscopy and to evaluate if tissue spectra can predict post-operative Crohn’s disease recurrence. Methods Full-thickness Crohn’s stricture resections (n=72) were obtained in paraffin and sectioned for hyperspectral imaging using the Agilent Cary 670 FPA-IR coupled with the Agilent Cary 620 microscope in transflection mode in the wavenumber region 1800–800 cm-1. Nearly 8 million spectra in total were acquired from regions of interest in each of the bowel wall layers per sample (Figure 1). Spectra was transformed to the second derivative, normalised and reduced to 25 spectra per sample prior to analysis using partial least squares discriminant analysis (PLSDA) with internal cross-validation. Adjacent tissue sections were stained with H&amp;E, Masson’s trichrome and α-smooth muscle actin. Histology was scored based on the averaged scores of three independent clinical histopathologists for inflammation, fibrosis and muscular changes. Results Tissue infra-red spectra demonstrated excellent performance defined by area under the receiver operating characteristic curve (AUC) of ≥0.9 using PLSDA to classify severe from mild inflammation and good (AUC ≥0.8) to excellent (AUC ≥0.9) performance to classify severe from mild fibrosis and muscular hyperplasia/hypertrophy. In those with complete macroscopic Crohn’s disease resection (n=51), spectra from index stricture resections demonstrated good performance (AUC ≥0.8) in discriminating between future significant endoscopic recurrence defined by Rutgeert’s score ≥ i2 (2) and excellent performance for surgical recurrence (AUC ≥0.9) defined as future surgical resection of Crohn’s recurrence. Conclusion FTIR microspectroscopy can detect biochemical differences underlying inflammation, fibrosis and muscular changes in Crohn’s strictures and provide simultaneous quantitative assessment. The biochemical tissue fingerprints demonstrate good to excellent discrimination for predicting endoscopic and surgical Crohn’s recurrence, respectively.

DOP078 Machine learning assessment of endoscopic severity in Ulcerative Colitis trials: Model evaluation against the 2 + 1 reference standard

Abstract Background Regulatory guidance recommends the endoscopy subscore, a component of the modified Mayo Score, as a primary endpoint in ulcerative colitis (UC) therapeutic trials. The endoscopy subscore is typically assessed via the 2 + 1 central reading paradigm, a workflow involving independent video review by multiple readers and, most commonly, statistical methods in cases of disagreement1. Disagreement in centrally read endoscopic assessments can impact the reliability and reproducibility of trial results2. Machine learning (ML) provides an opportunity for standardization. The objective of this study is to evaluate a novel ML model to assess the endoscopy subscore in UC trials compared to a 2 + 1 reference standard. Methods Endoscopic videos from the mirikizumab Phase 2 (NCT02589665) and Phase 3 induction (NCT03518086) trials in UC were added to a database of endoscopic recordings from routine practice to create a cohort of 18,169 videos. 639 videos (~25%) from the Phase 3 induction trial (week 0 and 12 procedures) with a 2 + 1 centrally read endoscopy subscore, per protocol, were randomly selected with a distribution of endoscopic severity similar to the overall study population (82.2% moderate-to-severe) and held out to evaluate performance of the final, locked model. Remaining videos were used to develop a state-of-the-art multi-stage deep learning algorithm to assess the endoscopy subscore on full-length UC endoscopic videos. Quadratic weighted kappa (QWK) was used to evaluate the inter-rater agreement between the model-assessed endoscopy subscore and the 2 + 1 reference standard. Results In the holdout test cohort (n=639) there was 62.4% agreement rate between the first two human readers (local vs central reader 1) in determining the centrally read endoscopy subscore with 2.5% cases of disagreement by 2 classes, in line with published data3,4. QWK between the model-assessed endoscopy subscore and the 2 + 1 reference standard was 0.77 (95% confidence interval (CI) 0.74-0.80). Disagreement by 2 classes occurred in 1.9% of videos. Binary accuracy for inactive-to-mild vs moderate-to-severe disease and inactive vs mild-to-moderate-to-severe disease, definitions of endoscopic improvement and remission in trials, was 89.8% (95% CI 87.5-92.2%) and 94.2% (95% CI 92.4-96.0%), respectively. Conclusion This ML algorithm effectively assesses the endoscopy subscore on full-length endoscopic videos in UC. Given the performance, ML models such as this could potentially standardize the assessment of inflammation, addressing a notable challenge currently posed in UC therapeutic development programs due to inconsistencies among human readers. Future research will investigate ML-based reading paradigms for the assessment of endoscopic endpoints in trials. References Food and Drug Administration. Ulcerative Colitis: Developing Drugs for Treatment [Internet]. 2022 [cited 2024 Oct 17]. Available from: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/ulcerative-colitis-developing-drugs-treatment Wils, P., Jairath, V., Sands, B. E., Magro, F., Reinisch, W., Rubin, D., . . . &amp; Peyrin-Biroulet, L. (2023). Comparison of treatment effect between phase 2 and phase 3 trials in patients with inflammatory bowel disease. United European Gastroenterology Journal, 11(8), 797-806. Hashash, J. G., Yu Ci Ng, F., Farraye, F. A., Wang, Y., Colucci, D. R., Baxi, S., . . . &amp; Melmed, G. Y. (2024). Inter-and intraobserver variability on endoscopic scoring systems in crohn’s disease and ulcerative colitis: A systematic review and meta-analysis. Inflammatory Bowel Diseases, izae051. Feagan, B. G., Khanna, R., Sandborn, W. J., Vermeire, S., Reinisch, W., Su, C., . . . &amp; Sands, B. E. (2021). Agreement between local and central reading of endoscopic disease activity in ulcerative colitis: Results from the tofacitinib OCTAVE trials. Alimentary Pharmacology &amp; Therapeutics, 54(11-12), 1442-1453.

DOP077 EndoUC: an AI-assisted endoscopic Ulcerative Colitis activity grading application for deployment in clinical trials

Abstract Background Manual scoring of ulcerative colitis (UC) disease activity from endoscopy videos using the Modified Mayo Score (mMS) by experts is known to have high inter-rater and intra-rater variability.1 In clinical trials, central reviewers review endoscopy videos and provide a single score for the entire video leading to a loss of transparency with no evidence of scoring rationale or segmental involvement. We developed an AI-assisted severity scoring application for clinical trials to address this challenge by intelligently highlighting video segments showing pathological information and providing a continuous scoring approach to severity grading. Methods Unlike previous approaches that rely heavily on large-scale, expensive, and restrictive frame-level expert labels, we developed our models on video-level grading available in typical clinical trial settings. We used data from the brazikumab clinical trial [NCT03616821], comprising 423 videos from 249 patients scored on the mMS scale. Our preprocessing module removes uninformative, low-quality frames and applies detection, tracking and alignment algorithms to identify regions of interest across frames. Our EndoUC model has 3 components: a pathology-enriched frame identification module (PEFIM), an aggregator, and a classifier.The PEFIM module identifies regions that characterise signs of UC, such as ulcers or erosions. The aggregator and classifier modules learn to combine the information at the video level. We focus on the clinical utility of the EndoUC model in two ways: (i) having task-specific classifiers focusing on clinical decision boundaries of UC and (ii) enhancing scoring granularity of UC severity prediction using ordinal regression. Results We developed an application to enable experts to review lengthy endoscopy footage in clinical trials efficiently. The app allows seamless navigation to key regions identified by the EndoUC and transparently reveals the basis of the AI model’s assessments. We conducted 5-fold cross-validation on the clinical trial data and evaluated the model on a held-out test set with 87 videos. The remission (mMS 0, 1 vs 2, 3) model performs with an AUC-ROC of 0.85, F1 of 0.87, normal/inactive and severe models with AUC-ROC of 0.81and 0.83 respectively. The continuous grading model has an MSE of 0.42 and MAE of 0.40. Conclusion We developed an AI-assisted reading tool for UC endoscopic severity assessment to help accelerate clinical trails through rapid evaluation of patient eligibility, detection of treatment response grounded by key region evidence, and potential for continuous grading of endoscopic changes.

P0298 Revolutionizing Diagnostics: Evaluating ChatGPT-4’s Performance in Ulcerative Colitis Endoscopic Assessment

Abstract Background The Mayo Endoscopic Subscore (MES) is a widely utilized measure for assessing endoscopic disease activity in ulcerative colitis (UC). This assessment has a key role in clinical practice as endoscopic remission is a long-term therapeutic objective. Artificial intelligence has emerged as a promising tool for enhancing diagnostic precision and addressing inter-observer variability among endoscopists. This study aims to evaluate the diagnostic accuracy of ChatGPT-4, a multimodal large language model (LLM), in identifying and grading endoscopic images of UC patients using the MES as a reference standard, without prior configuration or fine-tuning. Methods Real-world endoscopic images of UC patients were obtained for severity assessment and reviewed by an expert consensus board. Each image was classified by severity grade (0-3) based on the MES. Only images that were uniformly graded by the consensus board were subsequently provided to three IBD specialists and ChatGPT-4 in three separate sessions. Severity gradings of the IBD specialists and ChatGPT-4 were compared with assessments made by the expert consensus board. Results Fifty endoscopic images were initially evaluated by the expert consensus board. Of those, 30 images (60%) were graded with complete agreement of MES among the experts. Compared to the consensus board, ChatGPT4’s MES gradings were accurate in 26/30 (86.7%), 21/30 (70%) and 24/30 (80%) with a mean accuracy rate of 78.9%. The IBD specialists gradings were accurate in 24/30 (80%), 24/30 (80%) and 25/30 (83.3%) with a mean accuracy rate of 81.1% (figure 1). There was no statistically significant difference in mean accuracy rates between the two groups (p = 0.71). Conclusion ChatGPT-4 has the potential of assessing mucosal inflammation severity from endoscopic images of UC patients, without prior configuration or fine-tuning. Performance rates were comparable to IBD specialists. Further research and validation are warranted to explore the broader applications of LLMs and their integration into diagnostic workflows.

Limitations of the Boston Carpal Tunnel Questionnaire in Assessing Severity in a Homogeneous Occupational Cohort.

Background: Carpal tunnel syndrome (CTS) is a common peripheral neuropathy, often assessed using the Boston Carpal Tunnel Questionnaire (BCTQ). The BCTQ evaluates symptom severity (SSS) and functional status (FSS) but has limitations in stratifying CTS severity, particularly in severe cases. Objective: This study aimed to evaluate the utility of the BCTQ in a homogeneous cohort of female workers engaged in repetitive manual tasks, exploring its correlation with objective clinical measures and its performance in detecting CTS severity. Methods: A cross-sectional study was conducted on 24 right-hand-dominant female workers with repetitive occupational tasks. CTS diagnosis was confirmed via clinical and electrodiagnostic criteria. Subjects completed the BCTQ, and correlations between BCTQ scores and objective measures such as median nerve cross-sectional area and nerve conduction studies were analyzed. Statistical analyses included comparisons across CTS severity groups and subgroup evaluations based on age and tenure. Results: The BCTQ demonstrated moderate correlations with objective measures, with a strong correlation between SSS and FSS scores (r = 0.86, p < 0.001). However, the sensitivity of the SSS and FSS was limited, particularly for severe CTS cases. Paradoxically lower scores in severe cases may reflect questionnaire limitations or adaptive responses. Targeted questions addressing pain and sensory symptoms showed better sensitivity (>80%) and may guide clinicians in identifying slight CTS cases. Conclusions: While the BCTQ remains a valuable tool for assessing CTS, its limitations necessitate complementary use of objective diagnostic tools, particularly for severe cases. Future refinements, such as tailored scoring systems and integration with clinical measures, could enhance its diagnostic utility and ensure comprehensive assessment of CTS severity.

International Expert-Based Consensus Definition, Classification Criteria, and Minimum Data Elements for Osteoradionecrosis of the Jaw: An Inter-Disciplinary Modified Delphi Study.

Osteoradionecrosis of the jaw (ORNJ) is a severe iatrogenic disease characterized by bone death after radiation therapy (RT) to the head and neck. With over 9 published definitions and at least 16 classification systems, the true incidence and severity of ORNJ are obscured by lack of a standard for disease definition and severity assessment, leading to inaccurate estimation of incidence, reporting ambiguity, and likely under-diagnosis worldwide. This study aimed to achieve consensus on an explicit definition and phenotype of ORNJ and related precursor states through data standardization to facilitate effective diagnosis, monitoring, and multidisciplinary management of ORNJ. The ORAL Consortium comprised 69 international experts, including representatives from medical, surgical, radiation oncology, and oral/dental disciplines. Using a web-based modified Delphi technique, panelists classified descriptive cases using existing classification systems, reviewed systems for feature extraction and specification, and iteratively classified cases based on clinical/imaging feature combinations. The Consortium ORNJ definition was developed in alignment with SNOMED-CT terminology and recent ISOO-MASCC-ASCO guideline recommendations. Case review using existing ORNJ classification systems showed high rates of inability to classify (up to 76%). Ten consensus statements and nine minimum data elements (MDEs) were outlined for prospective collection and classification of precursor/ORNJ disease states. This study provides an international, consensus-based definition and MDE foundation for standardized ORNJ reporting in cancer survivors treated with RT. Head and neck surgeons, radiation, surgical, medical oncologists, and dental specialists should adopt MDEs to enable scalable health information exchange and analytics. Work is underway to develop both a human- and machine-readable knowledge representation for ORNJ (i.e., ontology) and multidisciplinary resources for dissemination to improve ORNJ reporting in academic and community practice settings.

Inflammation severity, rather than respiratory failure, is strongly associated with mortality of ARDS patients in high-altitude ICUs

IntroductionIn high-altitude cities located above 2,500 m, hospitals face a concerning mortality rate of over 50% among intensive care unit (ICU) patients with acute respiratory distress syndrome (ARDS). This elevated mortality rate is largely due to the absence of altitude-specific medical protocols that consider the unique physiological adaptations of high-altitude residents to hypoxic conditions. This study addresses this critical gap by analyzing demographic, clinical, sex-specific, and preclinical data from ICUs in Bogotá, Colombia (2,650 m) and El Alto, Bolivia (4,150 m).MethodsA cohort of seventy ARDS patients, aged 18 and older, was evaluated within 24 h of ICU admission. Data collected included demographic information (age, sex), clinical characteristics (primary pathology, weight, height), vital signs, respiratory variables, cardiorespiratory parameters, blood count results, inflammatory markers, severity assessment scores, and comorbidities. Advanced statistical analyses, such as multivariate logistic regression and principal component analysis, were utilized to identify key clinical predictors of ARDS-related mortality.ResultsOur findings indicate that in high-altitude ICUs, monitoring inflammatory markers may be more beneficial for improving ARDS survival rates than emphasizing respiratory failure markers. Unexpectedly, we found no significant differences in clinical outcomes between altitudes of 2,650 and 4,150 m or between male and female patients.ConclusionThe study concludes that, in high-altitude settings, ARDS patient survival in ICUs is more closely associated with managing inflammatory responses than with focusing solely on respiratory parameters. Further large-scale studies are recommended to validate the impact of inflammatory marker monitoring on survival outcomes in high-altitude ICUs.

Position-based assessment of head impact frequency, severity, type, and location in high school American football.

Research on head impact characteristics, especially position-specific investigations in football, has predominantly focused on collegiate and professional levels, leaving a gap in understanding the risks faced by high school players. Therefore, this study aimed to investigate the effect of three factors-player position, impact location, and impact type-on the frequency, severity, and characteristics of impacts in high school American football. Additionally, we examined whether and how player position influences the distribution of impact locations and types. Sixteen high school football players aged 14 to 17 participated in this study. Validated mouthguard sensors measured head impact kinematics, including linear acceleration, angular acceleration, and angular velocity across ten games, and were used to identify impact locations on the head. Video recordings verified true impacts, player position, and impact type at the moment of each recorded impact. Head impact kinematics were input into a head finite element model to determine the 95th percentile of the maximum principal strain and strain rate. Several novel and systematic approaches, such as normalization, binning, and clustering, were introduced and utilized to investigate the frequency and severity of head impacts across the three aforementioned factors while addressing some of the limitations of previous methodologies in the field. To that end, the number of recorded impacts for each player position during each game was divided by the number of players in that position, and then averaged across ten games. Instead of averaging, impacts were categorized into four severity bins: low, mid-low, mid-high and high. Clusters for the three factors were also identified according to the characteristics of impacts. Results revealed that offensive linemen and running backs experienced a higher normalized frequency and more severe impacts across all head kinematics and brain tissue deformation parameters. Frontal impacts, resulting from "head-to-head" impacts, were the most frequent and severe impact locations. The distributions of impact location and type for each specific position were distinct. Offensive linemen had the highest proportion of frontal impacts, while quarterbacks and centerbacks had more impacts at the rear location. These findings can inform interventions in game regulations, training practices, and helmet design to mitigate injury risks in high school football.

Associations of Atopic Dermatitis in Late Adolescence with Occupation, Mental Health, Income from Work and Marital Status: A National Longitudinal Study.

The main aim of this study was to evaluate longitudinal associations between atopic dermatitis (AD) in late adolescence and occupational socioeconomic group, labour market participation, income from work, and marital status later in adult life. Using Swedish population-based registry data a total of 205,394 men were included, born between 1952 and 1956 in Sweden and who underwent military conscription examination including assessment of atopic dermatitis (AD) and AD severity. The associations between AD and AD severity in late adolescence and labour market participation, income from work, marital status, and medication for anxiety and depression later in adult life were examined. In this study, men with AD in adolescence, especially those with severe AD, more often had a prescription for antidepressants or anxiolytics at the age of 50-57 years (unadjusted HR 1.55, 95% CI 1.32-1.81). Interestingly, despite increased risk of poorer mental health, AD was not found to be associated with a disadvantage in terms of occupational socioeconomic group, income from work, and unemployment benefits. Individuals with mild AD showed a lower risk of holding routine and lower technical jobs compared with men without AD. Persons with AD in late adolescence seem not to differ regarding registered partnerships and marital status compared with those without AD.

Osteopontin as a Biomarker for Coronary Artery Disease.

Osteopontin (OPN) is a sialylated phosphoprotein highly expressed in atherosclerosis and upregulated in settings of both acute and chronic inflammation. It is hypothesised that plasma levels of OPN may correlate with the presence of coronary artery disease, "CAD". This offers potential as a point-of-care testing biomarker for early diagnosis, disease monitoring, and prognosis. This review evaluates the current literature on the association between plasma OPN levels and coronary artery disease and what is currently known to support its potential as a biomarker for future practice. Electronic searches of MEDLINE and EMBASE databases were undertaken from inception until July 2024. Thirty-three studies met the inclusion criteria. All studies were observational, with gross heterogeneity in methods used to analyse the association of plasma OPN with clinical characteristics. They included case series, case-control, cross-sectional, and cohort study designs. OPN has been linked to higher cardiovascular risk and unfavourable cardiovascular outcomes. However, the evidence regarding the direct assessment of CAD severity using tools like the SYNTAX or TIMI scores, which focus on anatomical complexity and risk factors, is less definitive. This suggests that OPN may be a more precise reflection of the inflammatory processes and atherosclerotic activity contributing to unfavourable outcomes rather than a direct indicator of the anatomical severity of CAD itself. Consequently, OPN is increasingly perceived as a marker of a poor prognosis rather than a tool for assessing the severity of coronary artery lesions.