Real Patient Research Articles

Metodologias de ensino para atenção primária na graduação de medicina e fisioterapia: uma revisão sistemática

Primary Health Care enables an inclusive and efficient approach with universal health coverage to meet people's health needs. Thus, the aim of this review was to find out the teaching methods and educational tools, which do not involve contact with real patients, are used in the training of undergraduate medical and physical therapy students for primary care. The databases used were Education Resources Information Center and Pubmed with the studies published until November 21, 2019, in English, Spanish and Portuguese. Methods and tools used, they were divided into non-experiential, experiential and mixed. It was possible to present several teaching methods and educational tools used and their effectiveness; the profile of professionals for this practice scenario; the change in the training of professionals with a person-centered, not disease-centered, look; as well as, gaps on the topic in the literature and elaborate recommendations for future studies. This review presents teaching methods and educational tools, which do not involve contact with real patients and can contribute methodological strategies to enable students to practice.

Laryngeal surface reconstructions from monocular endoscopic videos: a structure from motion pipeline for periodic deformations.

Surface reconstructions from laryngoscopic videos have the potential to assist clinicians in diagnosing, quantifying, and monitoring airway diseases using minimally invasive techniques. However, tissue movements and deformations make these reconstructions challenging using conventional pipelines. To facilitate such reconstructions, we developed video frame pre-filtering and featureless dense matching steps to enhance the Alicevision Meshroom SfM pipeline. Time and the anterior glottic angle were used to approximate the rigid state of the airway and to collect frames with different camera poses. Featureless dense matches were tracked with a correspondence transformer across subsets of images to extract matched points that could be used to estimate the point cloud and reconstructed surface. The proposed pipeline was tested on a simulated dataset under various conditions like illumination and resolution as well as real laryngoscopic videos. Our pipeline was able to reconstruct the laryngeal region based on 4, 8, and 16 images obtained from simulated and real patient exams. The pipeline was robust to sparse inputs, blur, and extreme lighting conditions, unlike the Meshroom pipeline which failed to produce a point cloud for 6 of 15 simulated datasets. The pre-filtering and featureless dense matching modules specialize the conventional SfM pipeline to handle the challenging laryngoscopic examinations, directly from patient videos. These 3D visualizations have the potential to improve spatial understanding of airway conditions.

Nursing Strategies for Diabetic Patient Management: Predicting Parameter Values Post-Exenatide Treatment with Machine Learning Algorithm

The global escalation of DM parallels the rise in obesity rates, with Turkey experiencing a prevalence of 13.7% for diabetes and 32% for obesity among adults. Managing diabetic patients necessitates a comprehensive approach due to the intertwined nature of diabetes and obesity, along with the heightened risk of additional chronic illnesses. Diabet nurses play a pivotal role in diabetic care, encompassing regular assessments, blood glucose monitoring, medication management, patient education. Incretin-mimetic glucagon-like peptide-1 receptor-agonists (GLP-1A) have demonstrated superiority in diabetes, weight control, positioning them as second-line treatments. Weight management remains fundamental in diabetes care, with Diabet nurses providing vital support through dietary guidance, physical activity promotion, and weight loss assistance for diabetic patients. Predicting patient responses to GLP-1A therapy is crucial for optimizing treatment outcomes, streamlining decisions, averting potential complications. Artificial intelligence (AI) and machine learning (ML) offer promising avenues for enhancing healthcare delivery. Our study aimed to forecast fasting blood sugar levels, HbA1C values, and weight loss outcomes in diabetic patients using exenatide, utilizing the random forest algorithm. Analyzing real patient data from the Western-Mediterranean, this study achieved substantial success rates of %99.9, %99.9 and %97.3 in predicting weight loss, fasting blood sugar levels, and HbA1C values, respectively. Our findings underscore the potential of AI-driven approaches in nursing, particularly in prognostic modeling for diabetic patient management. By leveraging ML, nurses can anticipate treatment responses, streamline decision-making, and elevate patient care quality. As AI applications evolve, integrating these technologies into nursing roles promises to advance patient-centered care and optimize health outcomes.

Virtual patients versus standardized patients for improving clinical reasoning skills in ophthalmology residents. A randomized controlled trial

BackgroundHistory taking and clinical reasoning are important skills that require knowledge, cognition and meta-cognition. It is important that a trainee must experience multiple encounters with different patients to practice these skills. However, patient safety is also important, and trainees are not allowed to handle critically ill patients. To address this issue, a randomized controlled trial was conducted to determine the effectiveness of using Virtual Patients (VP) versus Standardized Patients (SP) in acquiring clinical reasoning skills in ophthalmology postgraduate residents.MethodsPostgraduate residents from two hospitals in Lahore, Pakistan, were randomized to either the VP group or the SP group and were exposed to clinical reasoning exercise via the VP or SP for 30 min after the pretest. This was followed by a posttest. One month after this activity, a follow-up posttest was conducted. The data were collected and analysed using IBM-SPSS version 25. Repeated measures ANOVA was used to track the effect of learning skills over time.ResultsThe mean age of the residents was 28.5 ± 3 years. The male to female ratio was 1:1.1. For the SP group, the mean scores were 12.6 ± 3.08, 16.39 ± 3.01 and 15.39 ± 2.95, and for the VP group, the mean scores were 12.7 ± 3.84, 16.30 ± 3.19 and 15.65 ± 3.18 for the pretest, posttest and follow-up posttest, respectively (p value < 0.00). However, the difference between the VP and SP groups was not statistically significant (p = 0.896). Moreover, there was no statistically significant difference between the VP and SP groups regarding the retention of clinical reasoning ability. In terms of learning gain, compared with the VP group, the SP group had a score of 51.46% immediately after clinical reasoning exercise as compared to VP group, in which it was 49.1%. After one month, it was 38.01 in SP and 40.12% in VP group.ConclusionVPs can be used for learning clinical reasoning skills in postgraduate ophthalmology residents in a safe environment. These devices can be used repeatedly without any risk to the real patient. Although similarly useful, SP is limited by its nonavailability for repeated exercises.

Brain Arteriovenous Malformation In Vitro Model for Transvenous Embolization Using 3D Printing and Real Patient Data.

Transvenous embolization has emerged as a novel technique for treating selected brain AVMs with high reported occlusion rates. However, it requires anatomic and technical skills to be successful and to ensure patient safety. Therefore, training and testing are essential for preparing clinicians to perform these procedures. Our aim was to develop and test a novel, patient-specific brain AVM in vitro model for transvenous embolization by using 3D printing technology. We developed a brain AVM in vitro model based on real patient data by using stereolithography resin 3D printing. We created a closed pulsed circuit with flow passing from the arterial side to the venous side, and we tested the effect of mean arterial pressure on retrograde nidal filling with contrast injections. Transvenous embolization simulations were conducted for each of the 12 identical models divided into 2 groups (2×6). This involved the use of an ethylene-vinyl alcohol liquid embolic agent injected through microcatheters either without or with a coil in the vein (groups 1 and 2, respectively). Retrograde contrast advance to nidus was directly related to lower mean arterial pressure. Transvenous embolization tests with a liquid embolic agent adequately reproduced the usual embolization plug and push technique. We found no differences between the 2 group conditions, and additional venous coil neither increased nidus penetration nor reduced injection time in the model (57.6 versus 61.2% nidus occlusion rate, respectively). We were able to develop and test a functional in vitro brain AVM model for transvenous embolization by using 3D printing to emulate its conditions and characteristics. Better contrast penetration was achieved with less mean arterial pressure, and no embolization advantage was found by adding coil to the vein in this model.

Artificial intelligence applied for the diagnosis of absence epilepsy with simultaneously tested patient’s consciousness level in ictal event

Background. Given the difficulties in identifying absences and assessing the level of consciousness in epilepsy patients, it is extremely relevant to develop digital programs for automatic registration and testing of this type of epileptic seizures and related electroencephalographic (EEG) patterns, including those based on artificial intelligence.Objective: development of an algorithm for automatic detection of absence seizures to test real time patient's consciousness level during long-term video-EEG monitoring.Material and methods. The work on creating an algorithm was carried out during joint doctor/engineer cooperation. Doctors prepared a set of labeled EEG recordings of patients with verified absence epilepsy. Two independent experts in the generated examinations database mapped typical episodes of absence seizures that allowed to develop training and testing samples for a neural network algorithm to detect EEG absence epiactivity. Next, trained neural network was incorporated into Neuron- Spectrum.NET software to compare its accuracy with similar approaches published elsewhere.Results. A neural network algorithm was developed and trained using a mapped database to detect EEG absence epiactivity. A comparative analysis of the effectiveness for the proposed method vs. other approaches showed that the former is comparable in quality, whereas in some aspects – even superior to the latter. Accuracy was assessed using a publicly available database with mapped epiactivity episodes.Conclusion. A hardware and software system for automated assessment of patient’s consciousness level during absence seizure in continuous video-EEG monitoring was proposed. Potentially, neural networks may be applied not only to assess patient’s consciousness level, but also to stop stimulation-mediated seizure onset in the future.

Addressing High-value Care with Generative Pretrained Transformer 4

Abstract Background: High-value care emphasizes services offering significant health benefits, aligning with patient preferences while minimizing costs and interventions of little benefit. This approach is increasingly vital in a healthcare environment constrained by finite resources and rising costs. Large Language Models (LLMs) like Generative Pretrained transformer-4 (GPT-4), with their vast data processing capabilities, offer a promising avenue for supporting healthcare providers in making evidence-based, high-value care decisions. Aims: This study aims to evaluate the performance of OpenAI’s GPT-4 in providing responses to high-value care clinical scenarios within internal medicine, assessing its accuracy, relevance, and reasoning against established medical guidelines and literature. Materials and Methods: An observational study was conducted using MKSAP-19’s high-value care questions, comparing GPT-4’s responses to the correct answers based on established studies, trials, and guidelines. The study did not involve real patient data, circumventing the need for Institutional Review Board (IRB) approval. Performance metrics focused on the accuracy, relevance, and consistency of GPT-4’s answers. Results: GPT-4 demonstrated a 74.4% accuracy rate (32 out of 43 questions) across a range of high-value care clinical scenarios, including image-based questions. Errors made by GPT-4 were similar to those by medical residents using MKSAP-19, suggesting areas for model improvement and potential educational applications. The study detailed GPT-4’s decision-making pattern, emphasizing its clinical reasoning capabilities. Conclusion: The findings suggest that GPT-4 can significantly support high-value care in internal medicine by providing accurate, evidence-based responses to complex clinical scenarios. Despite its limitations, including a 25.6% error rate and the scope of its training data, GPT-4’s performance indicates its potential as both a clinical and educational tool in healthcare.

SPINNED: Simulation-based physics-informed neural network for deconvolution of dynamic susceptibility contrast MRI perfusion data.

To propose the simulation-based physics-informed neural network for deconvolution of dynamic susceptibility contrast (DSC) MRI (SPINNED) as an alternative for more robust and accurate deconvolution compared to existing methods. The SPINNED method was developed by generating synthetic tissue residue functions and arterial input functions through mathematical simulations and by using them to create synthetic DSC MRI time series. The SPINNED model was trained using these simulated data to learn the underlying physical relation (deconvolution) between the DSC-MRI time series and the arterial input functions. The accuracy and robustness of the proposed SPINNED method were assessed by comparing it with two common deconvolution methods in DSC MRI data analysis, circulant singular value decomposition, and Volterra singular value decomposition, using both simulation data and real patient data. The proposed SPINNED method was more accurate than the conventional methods across all SNR levels and showed better robustness against noise in both simulation and real patient data. The SPINNED method also showed much faster processing speed than the conventional methods. These results support that the proposed SPINNED method can be a good alternative to the existing methods for resolving the deconvolution problem in DSC MRI. The proposed method does not require any separate ground-truth measurement for training and offers additional benefits of quick processing time and coverage of diverse clinical scenarios. Consequently, it will contribute to more reliable, accurate, and rapid diagnoses in clinical applications compared with the previous methods including those based on supervised learning.

Simulating vision impairment in virtual reality: a comparison of visual task performance with real and simulated tunnel vision

In this work, we explore the potential and limitations of simulating gaze-contingent tunnel vision conditions using Virtual Reality (VR) with built-in eye tracking technology. This approach promises an easy and accessible way of expanding study populations and test groups for visual training, visual aids, or accessibility evaluations. However, it is crucial to assess the validity and reliability of simulating these types of visual impairments and evaluate the extend to which participants with simulated tunnel vision can represent real patients. Two age-matched participant groups were acquired: The first group (n = 8, aged 20–60, average 49.1 ± 13.2) consisted of patients diagnosed with Retinitis pigmentosa (RP). The second group (n = 8, aged 27–59, average 46.5 ± 10.8) consisted of visually healthy participants with simulated tunnel vision. Both groups carried out different visual tasks in a virtual environment for 30 min per day over the course of four weeks. Task performances as well as gaze characteristics were evaluated in both groups over the course of the study. Using the ’two one-sided tests for equivalence’ method, the two groups were found to perform similar in all three visual tasks. Significant differences between groups were found in different aspects of their gaze behavior, though most of these aspects seem to converge over time. Our study evaluates the potential and limitations of using Virtual Reality technology to simulate the effects of tunnel vision within controlled virtual environments. We find that the simulation accurately represents performance of RP patients in the context of group averages, but fails to fully replicate effects on gaze behavior.

Abstract P19: Comprehensive Benchmark of Somatic Mutation Callers on Cell-Free DNA Next-Generation Sequencing Data in Cancer Liquid Biopsy

Abstract Circulating tumour DNA (ctDNA) has emerged as a rich source of biomarkers in precision oncology. However, ctDNA sequence data is often noisier than that derived from standard tissue biopsies, posing significant challenges for accurate cancer mutation detection. Besides, there is a lack of standardised and unbiased benchmark datasets to evaluate and compare performance of variant callers on ctDNA. To address this issue, we present a novel benchmarking approach and comprehensive benchmark of cancer somatic mutation callers on cell-free DNA (cfDNA) Next Generation Sequencing (NGS) data. To create a large-scale benchmark dataset, we developed a new methodology using real colorectal cancer patients plasma samples exhibiting either ultra-high and an ultra-low levels of ctDNA. This enabled the generation of dilution series of deep Whole Genome Sequencing (WGS, 150x) and the creation of high-quality consensus ground truth calls. We evaluated the performance of 9 SNV callers and 7 short INDEL callers frequently used in academic research, including 2 callers that were specifically designed for cfDNA. We further validated our findings at higher depth of coverage using deep Whole Exome Sequencing (WES, &amp;gt;2,000x) data. We further investigated each caller's features to develop practical guidelines for users depending on their application setting: unguided analysis focusing on overall accuracy vs. guided analysis focusing on sensitivity. Citation Format: Hanaé Carrié, Ngak Leng Sim, Pui Mun Wong, Anna Gan, Yi Ting Lau, Polly Poon, Saranya Thangaraju, Iain Tan, Yoon Sim Yap, Limsoon Wong, Anders Skanderup. Comprehensive Benchmark of Somatic Mutation Callers on Cell-Free DNA Next-Generation Sequencing Data in Cancer Liquid Biopsy [abstract]. In: Proceedings of Frontiers in Cancer Science; 2023 Nov 6-8; Singapore. Philadelphia (PA): AACR; Cancer Res 2024;84(8_Suppl):Abstract nr P19.

Thyroid and contralateral breast surface dose variation in mammography: a phantom study on the role of breast tissue composition

The organs of the thyroid and contralateral breast can be exposed to radiation because of scattered x-rays during mammography. It is important to determine the dose values of these quantities in terms of the risk of triggering a second cancer induction for both organs. In the present study, thyroid and contralateral breast surface doses were investigated with LiF:Mg,Ti (TLD-100) dosimeters for three types of BR-12 phantoms with glandularity/fat tissue ratios (70%/30%, 50%/50% and 30%/70%) over four views as in the real patient situation in Mo/Mo and Mo/Rh anode/filter combinations in each phantom thickness as opposed to a single glandular/fat tissue commonly used in the literature. Both thyroid and contralateral surface doses increased with increasing both phantom thickness and glandularity/fat ratio. The thyroid surface doses changed within 0.06–0.18 mGy and 0.05–0.14 mGy according to phantom thickness of 2 to 6 cm for the glandularity/adipose of 50%/50% in the Mo/Mo and Mo/Rh, respectively. On the other hand, the contralateral breast surface doses were within 0.35–1.39 mGy and 0.40–0.99 mGy for 50%/50% in the Mo/Mo and Mo/Rh, respectively. Based on a 70%/30% breast composition with a phantom thickness of 6 cm, the thyroid and contralateral breast surface doses increased by approximately 40% compared with 50%/50% for both Mo/Mo and Mo/Rh. These results showed that both thyroid and contralateral breast surface doses significantly depend on the glandularity/fat composition of the breast. Therefore, the outputs of this study may contribute to future studies aimed at reducing the doses received by organs during examination.

An algorithm for the National Institute of Health Stroke Scale assessment: A multicenter, two-arm and cluster randomized study

BackgroundThe NIH Stroke Scale (NIHSS) is a validated tool for assessing stroke severity, increasingly used by general practitioners in telemedicine services. Mobile apps may enhance its reliability. We aim to validate a digital platform (SPOKES) for NIHSS assessment in telemedicine and healthcare settings. MethodsHospitals using a telemedicine service were randomly allocated to control or SPOKES-user groups. The discrepancy between the NIHSS scores reported and those confirmed by experts was evaluated. Healthcare providers from comprehensive stroke centers were invited for interrater validation. Participants were randomized to assess the NIHSS using videos of real patients. Weighted Kappa (wk) statistics analyzed the agreement, and logistic regression determined the correlation with the congruency. ResultsA total of 299 telemedicine consultations from 12 hospitals were included. The difference between the NIHSS scores reported and double-checked was lower in the SPOKES group (p = 0.03), with a significantly higher level of complete agreement (72.5 % vs. 50.4 %, p = 0.005). Adoption of SPOKES was associated with complete congruency (OR 4.01, 95 %CI 1.42–11.35, p = 0.009). For interrater validation, 20 participants were considered. In the SPOKES group, almost-perfect and strong agreement occurred in 13.3 %(n = 6/45) and 84.4 %(n = 38/45) of ratings, respectively; in the control group, 6.7 %(n = 3/45) were almost-perfect, 28.9 %(n = 13/45) strong and 51 %(n = 23/45) were minimal. ConclusionA free and reliable mobile application for NIHSS assessment can significantly improve interrater agreement between healthcare professionals, and between NIHSS-certified neurologists and general practitioners. Our results underscore the importance of ongoing training and education in enhancing the consistency and reliability of NIHSS scores.

Livestreaming clinical experience to remotely located learners: A critical narrative review.

Medical education relies on real patient learning (RPL) to provide medical students with essential clinical experience. However, growing demand for clinical placements continues to be a challenge in providing sufficient RPL opportunities. The COVID-19 pandemic forced academic institutions to rethink the delivery of traditional clinical training and innovations in online clinical learning experiences, specifically livestreamed clinical experiences, have emerged which show promise in addressing the capacity limitations of traditional placements. Although previous reviews have explored the use of livestreamed clinical experiences during the pandemic, there is a lack of rigorous theoretical framing to support these innovations. The aim of this review is two-fold: to examine the effectiveness of livestreamed clinical experiences through an experience-based learning (ExBL) theory perspective and to provide practical recommendations to optimise and implement these innovations. A review of literature was conducted to identify journal articles published between September 2019 and January 2023 reporting on innovations relating to livestreamed clinical experiences. The search focused on undergraduate and postgraduate medical education but relevant evidence from other healthcare professions were also included due to a limited evidence base. Strengths and weaknesses were derived from the literature and analysed in relation to ExBL components. Principal strengths of livestreamed clinical experiences included expanded access to RPL opportunities and medical specialties, enhanced standardisation of learning experiences and positive perceptions from students regarding convenience. Clinical educators found these innovations enabled teaching at scale. Patients did not perceive such innovations to negatively impact their standard of care. Limitations included the inability to practice physical examination skills, challenges in ensuring learner engagement and connectivity issues. Livestreamed clinical experiences have the potential to effectively expand placement capacity and provide high-quality educational experiences for medical students. Although certain limitations exist, technological and pedagogical adaptations can help overcome these challenges. The application of theoretical frameworks to future online innovations will be fundamental to ensure effective clinical learning.

Data on Ocrelizumab Treatment Collected by MS Patients in Germany Using Brisa App.

With a rising number of multiple sclerosis (MS) cases and increasing pressure on health systems, digital companion apps like Brisa, designed specifically for people with MS, can play an important role in the patient journey. These apps enable the collection of real-time longitudinal data that are critical to our understanding of the pathophysiology and progression of MS. This retrospective, descriptive analysis consists of data from Brisa users who registered between 6 August 2021 and 8 September 2022. Of the unique users, 37.7% (n = 1593) fulfilled the inclusion criteria including information about medication and demographics and tracked one or more symptoms and/or patient-reported outcomes. Users were classified as moderate-efficacy treatment users, high-efficacy treatment users and ocrelizumab users, and the reporting frequency and scores of symptoms and patient-reported outcomes were analyzed. The largest cohort of Brisa users (405) reported treatment with ocrelizumab and were mostly diagnosed 2-5 years before the survey. The most reported MS symptoms were similar between OUs (ocrelizumab users), HETUs (high-efficacy treatment users) and METUs (moderate-efficacy treatment users). OUs on average reported symptoms and answered questionnaires more frequently. Baseline scores between HETUs and OUs were similar, whereas baseline scores of METUs were slightly lower in comparison. In a further analysis of OUs, disability scores increased with age; users aged 26-45 years had higher pain scores than 18-25-year-olds. No significant differences were found in quality of life, bowel control and vision between age groups. These findings show that the characteristics of the Brisa cohort are similar to the results of other studies and registries and can provide a representative overview of everyday disease management. Thereby, these results can bridge the gap between clinical research and real patient experience, but they also raise new questions, such as how often the hard-and-early therapy approach is already used and whether baseline characteristics and reasons for choosing a particular treatment contribute to the different outcomes over time. Answering these questions requires further research and analysis.

Safety and effectiveness of glycoprotein IIb/IIIa inhibitors in acute coronary syndromes: insights from the SPUM-ACS study.

Data on glycoprotein IIb/IIIa inhibitor (GPI) use in real-world acute coronary syndrome (ACS) patients following the introduction of potent P2Y12 inhibitors and newer-generation stents are scant. Here, we aimed to assess the utilization, effectiveness, and safety of GPI in a large prospective multicentre cohort of contemporary ACS patients. SPUM-ACS prospectively recruited patients presenting with ACS between 2009 and 2017. The primary endpoint of the present study was major adverse cardiovascular events (MACE), a composite of all-cause death, non-fatal myocardial infarction, and non-fatal stroke at 1 year. Secondary endpoints were defined as any bleeding events, Bleeding Academic Research Consortium (BARC) 3-5 bleeding, and net adverse cardiovascular events (NACE). A total of 4395 ACS patients were included in the analysis. GPI-treated patients had more total coronary artery occlusion (56%vs. 35%, P<0.001) and thrombus (60%vs. 35%, P<0.001) at angiography. Among the propensity score-matched (PSM) population (1992 patients equally split into two groups), GPI-treated patients showed lower risk of MACE [PSM adjusted hazard ratio (HR) 0.70, 95% CI 0.49-0.99], but a higher risk of any (PSM adjusted HR 1.46, 95% CI 1.06-1.99) and major bleedings (PSM adjusted HR 1.73, 95% CI 1.09-2.76), resulting in a neutral effect on NACE (PSM adjusted HR 0.87, 95% CI 0.65-1.17). These results remained consistent across all subgroups. In patients with ACS undergoing percutaneous coronary intervention and receiving potent P2Y12 inhibitors, we observed a reduced risk of MACE and an increased risk of major bleedings at 1 year in patients treated with GPI. Although the routine use of GPI is currently not recommended, they might be considered in selected patients following a personalized balancing between ischaemic and bleeding risks.

Cellular senescence and metabolic reprogramming model based on bulk/single-cell RNA sequencing reveals PTGER4 as a therapeutic target for ccRCC

Clear cell renal cell carcinoma (ccRCC) is the prevailing histological subtype of renal cell carcinoma and has unique metabolic reprogramming during its occurrence and development. Cell senescence is one of the newly identified tumor characteristics. However, there is a dearth of methodical and all-encompassing investigations regarding the correlation between the broad-ranging alterations in metabolic processes associated with aging and ccRCC. We utilized a range of analytical methodologies, such as protein‒protein interaction network analysis and least absolute shrinkage and selection operator (LASSO) regression analysis, to form and validate a risk score model known as the senescence-metabolism-related risk model (SeMRM). Our study demonstrated that SeMRM could more precisely predict the OS of ccRCC patients than the clinical prognostic markers in use. By utilizing two distinct datasets of ccRCC, ICGC-KIRC (the International Cancer Genome Consortium) and GSE29609, as well as a single-cell dataset (GSE156632) and real patient clinical information, and further confirmed the relationship between the senescence-metabolism-related risk score (SeMRS) and ccRCC patient progression. It is worth noting that patients who were classified into different subgroups based on the SeMRS exhibited notable variations in metabolic activity, immune microenvironment, immune cell type transformation, mutant landscape, and drug responsiveness. We also demonstrated that PTGER4, a key gene in SeMRM, regulated ccRCC cell proliferation, lipid levels and the cell cycle in vivo and in vitro. Together, the utilization of SeMRM has the potential to function as a dependable clinical characteristic to increase the accuracy of prognostic assessment for patients diagnosed with ccRCC, thereby facilitating the selection of suitable treatment strategies.

Identification of patients with orfan pathology as a result of routine creatine phosphokinase level analysis. The experience of the Krasnoyarsk Territory

Background. Duchenne muscular dystrophy (DMD) is a severe genetic disease that usually affects boys and it is characterized by a gradual loss of muscle strength up to respiratory arrest from the childhood. Currently, there are several types of successful pathogenic therapies for the disease, but it is most effective before the age of 5 years. Thereby, the problem of verifying the diagnosis before the treatment fails to work (when treatment can still make the patient’s life easier) becomes urgent. In the Russian Federation only about 1,500 boys are diagnosed with DMD, when the calculated value is 3,500.Aim. To identify all cases of DMD among patients in the neurological departments of hospitals in the Krasnoyarsk region by measuring the level of creatine phosphokinase.Materials and methods. This study was estimated by neurologists in the Krasnoyarsk Interdistrict Children’s Clinical Hospital No. 1 and the Krasnoyarsk Regional Clinical Center for Maternal and Child Health. When elevated levels of creatine phosphokinase were detected in children, genetic analysis was performed to verify DMD.Results and conclusion. Innovate experience of Krasnoyarsk region made it possible to identify all patients with DMD in the neurological departments of the Krasnoyarsk Interdistrict Children’s Clinical Hospital No. 1 and the Krasnoyarsk Regional Clinical Center for Maternal and Child Health using cheap creatine phosphokinase level analysis. The number of patients diagnosed with DMD is now ~4 cases per year. As a result, there is a correspondence between the number of real patients and the epidemiological estimate quantity for the Krasnoyarsk region.

Understand the FDA-cleared fentanyl testing: A clinical evaluation of the SEFRIA fentanyl immunoassay

BackgroundScreening for fentanyl has been adopted by many clinical laboratories to detect illicit drug use and monitor medication adherence. However, compared to other urine drug testing, fentanyl screening assays are relatively new and therefore their clinical performances are largely unknown. This study extensively evaluated the clinical performance, positive cutoff, and interference profile of SEFRIA fentanyl immunoassay in real patient settings. MethodsThe FDA-cleared cutoff of 1.0 was verified with 21 urine samples with low or undetectable levels of fentanyl. After assay implementation, all screened-positive samples were confirmed by liquid chromatography-tandem mass spectrometry. A new cutoff was derived from the numeric values of the false positive (FP) screening results. The FP rates before and after implementing the new cutoff were compared. Interferences were identified by an untargeted drug analysis and confirmed by spiking experiments. ResultsA total of 3951 screening results were reviewed in the first two months of the assay utilization, 410 were screened-positive, and 157 (38 %) were FP. After a new cutoff of 1.3 was implemented, the FP rate was reduced to 17 % based on 11119 screening results. Trazodone, labetalol, and haloperidol were identified as major interferents, accounting for 56 % of the FP results using the cutoff of 1.3. ConclusionBy applying the new cutoff and including an interference comment to positive screening results, the FP rate was reduced from initial 38 % to 7.5 % (17 % times 56 %).

Efficacy of a Virtual 3D Simulation-Based Digital Training Module for Building Dental Technology Students' Long-Term Competency in Removable Partial Denture Design: Prospective Cohort Study.

Removable partial denture (RPD) design is crucial to long-term success in dental treatment, but shortcomings in RPD design training and competency acquisition among dental students have persisted for decades. Digital production is increasing in prevalence in stomatology, and a digital RPD (D-RPD) module, under the framework of the certified Objective Manipulative Skill Examination of Dental Technicians (OMEDT) system reported in our previous work, may improve on existing RPD training models for students. We aimed to determine the efficacy of a virtual 3D simulation-based progressive digital training module for RPD design compared to traditional training. We developed a prospective cohort study including dental technology students at the Stomatology College of Chongqing Medical University. Cohort 1 received traditional RPD design training (7 wk). Cohort 2 received D-RPD module training based on text and 2D sketches (7 wk). Cohort 3 received D-RPD module pilot training based on text and 2D sketches (4 wk) and continued to receive training based on 3D virtual casts of real patients (3 wk). RPD design tests based on virtual casts were conducted at 1 month and 1 year after training. We collected RPD design scores and the time spent to perform each assessment. We collected the RPD design scores and the time spent to perform each assessment at 1 month and 1 year after training. The study recruited 109 students, including 58 (53.2%) female and 51 male (56.8%) students. Cohort 1 scored the lowest and cohort 3 scored the highest in both tests (cohorts 1-3 at 1 mo: mean score 65.8, SD 21.5; mean score 81.9, SD 6.88; and mean score 85.3, SD 8.55, respectively; P<.001; cohorts 1-3 at 1 y: mean score 60.3, SD 16.7; mean score 75.5, SD 3.90; and mean score 90.9, SD 4.3, respectively; P<.001). The difference between cohorts in the time spent was not statistically significant at 1 month (cohorts 1-3: mean 2407.8, SD 1370.3 s; mean 1835.0, SD 1329.2 s; and mean 1790.3, SD 1195.5 s, respectively; P=.06) but was statistically significant at 1 year (cohorts 1-3: mean 2049.16, SD 1099.0 s; mean 1857.33, SD 587.39 s; and mean 2524.3, SD 566.37 s, respectively; P<.001). Intracohort comparisons indicated that the differences in scores at 1 month and 1 year were not statistically significant for cohort 1 (95% CI -2.1 to 13.0; P=.16), while cohort 3 obtained significantly higher scores 1 year later (95% CI 2.5-8.7; P=.001), and cohort 2 obtained significantly lower scores 1 year later (95% CI -8.8 to -3.9; P<.001). Cohort 3 obtained the highest score at both time points with retention of competency at 1 year, indicating that progressive D-RPD training including virtual 3D simulation facilitated improved competency in RPD design. The adoption of D-RPD training may benefit learning outcomes.

Audiology Students' Clinical Communication During Simulated Peer Role Play Consultations: An Exploratory Study.

The objectives of this study were to describe the clinical communication practices of student audiologists during case history taking and feedback giving using simulated peer role play consultations and to explore whether clinical communication skills outcomes can be achieved through simulated peer role play. An exploratory, qualitative research design was used for this pilot study. A total of four simulated peer role play consultations were video-recorded, comprising two adult diagnostic audiology case scenarios. Eight online interviews were conducted with the student participants following the simulated audiological consultation. Analysis of the video-recorded sessions incorporated an interactional sociolinguistic focus, and interviews were analyzed using inductive thematic analysis. Findings from the video analysis and interviews were triangulated, with a specific focus on establishing commonalities in terms of communication skills of student clinicians, reflections of their own skills, and the simulated peer patient's reflections on the student clinician's skills. Although variation was noted in terms of case history taking skills, feedback giving was similar among all student clinicians. These communication practices are consistent with findings from related literature on consultations with real patients. Student clinicians reflected on feedback giving as more challenging than case history taking, with room for improvement suggested by the simulated peer patients. Our findings highlight key questions regarding the use of peer simulation in facilitating the development of communication skills for audiological consultations among student audiologists. We discuss some considerations for using this approach to clinical training more effectively. https://doi.org/10.23641/asha.25492804.