Personal Approach Research Articles

Hepatocellular Carcinoma risk scores for non-viral liver disease: a systematic review and meta-analysis

BackgroundHepatocellular carcinoma (HCC) risk prediction models may provide a more personalised approach to surveillance for HCC among patients with cirrhosis. This systematic review aims to summarise the performance of HCC prediction models in patients with non-viral chronic liver disease. MethodThe study was prospectively registered with PROSPERO (ID: CRD42022370078) and reported in accordance with PRISMA guidelines. MEDLINE and EMBASE databases were searched using a validated search filter for prediction model studies. Two reviewers independently assessed studies for inclusion and risk of bias. Model performance (discrimination and calibration) were identified to assess the risk of HCC at specified time points. A random effects meta-analysis was done on a subset of studies that reported performance of the same model. Results7,854 studies were identified. After review, 14 studies with a total of 94,014 participants were included. 45% of patients had viral hepatitis, 27% alcohol related liver disease (ArLD) and 19% metabolic associated steatotic liver disease (MASLD). Follow-up ranged from 15.1 - 138 months. Only one model was developed using a competing risk approach. Age (7 models) and sex (6 models) were the most frequently included predictors. Model discrimination (AUROC or c-statistic) ranged from 0.61 - 0.947. Only the ‘aMAP’ score (age, male sex, albumin,bilirubin, and platelets) had sufficient external validation for quantitative analysis, with a pooled c-statistic of 0.81 (95% CI 0.80-0.83). Calibration was reported in only 9 of 14 studies. All studies were rated high risk of bias. ConclusionStudies describing risk prediction of HCC in non-viral chronic liver disease are poorly reported, have a high risk of bias and do not account for competing risk events. Patients with ArLD and MASLD are underrepresented in development and validation cohorts. These factors remain barriers to the clinical utility and uptake of HCC risk models in persons with the commonest liver diseases. Impact and implicationsThe recent EASL policy statement emphasises the potential of risk-based surveillance to reduce both HCC-related deaths and surveillance costs. This study addresses the gap in understanding the performance of current HCC risk models in patients with non-viral liver diseases, reflecting the epidemiological landscape of liver disease in Western countries.In our review of these models, we identified several key concerns regarding reporting standards and risk of bias and confirmed that patients with alcohol-related liver disease (ArLD) and metabolic-associated steatotic liver disease (MASLD) are underrepresented in model development and validation cohorts. Additionally, most models fail to account for the significant risk of competing events, leading to potential overestimation of true HCC risk.This study highlights these critical issues that may hinder the implementation of risk models in clinical practice and offers key recommendations for future model development studies.

Expert Opinion on Refined and Extended Key Performance Indicators for Individualized Ovarian Stimulation for ART

ObjectiveTo assess the adequate ovarian follicular development and oocyte recovery between ovarian potential (antral follicle count [AFC]) before the start of ovarian stimulation (OS) and oocyte quantity and quality at oocyte retrieval. A holistic overview of the current key performance indicators (KPIs) was applied to identify the complementary strengths and identify where the current repertoire can be expanded. DesignExpert opinion. SubjectsNot applicable. InterventionNone. Main Outcome MeasuresTo formulate a proposal for a refined and expanded repertoire of KPIs for individualized OS for Assisted Reproductive Technology. ResultsThe performance and outcomes of OS on ovarian follicular development can be evaluated through the application of defined KPIs. Current KPIs for OS are the ovarian sensitivity index (OSI), the follicular output rate (FORT), the oocyte retrieval rate (ORR), and the follicle to oocyte index (FOI). Notably, there are no specific KPIs dedicated to the assessment of follicular development (i.e., recruitment, selection, growth and dominance). In light of this, we recommend expanding the current KPIs for OS to include “Early FORT” (accounting for the number of follicles measuring ≥10–11 mm on Day 5/6 of OS relative to AFC) and “Modified FORT” (the ratio between the number of follicles measuring ≥12 mm at the time of oocyte maturation triggering and AFC); the extension of ORR to include two discrete categories at oocyte retrieval: follicles ≥12 mm and follicles ≥16 mm, to ensure all responsive follicles are accounted for; and FOI to be measured at oocyte maturation triggering and oocyte retrieval ("Advanced FOI”). ConclusionsOnce validated and adopted in clinical practice, we envisage that the proposed expanded KPIs measuring the effect of OS on follicular development (recruitment, selection, growth and dominance) will increase the understanding of the relationship between ovarian reserve measured by AFC and oocyte quantity and quality at oocyte retrieval. This understanding will enable physicians to better evaluate the direct effect of different gonadotropins and doses on ovarian response, leading to a more personalized approach to OS in the context of ART treatment.

Predicting the effectiveness of binaural beats on working memory.

Working memory is vital for short-term information processing. Binaural beats can enhance working memory by improving attention and memory consolidation through neural synchronization. However, individual differences in cognitive and neuronal functioning affect effectiveness of binaural beats, necessitating personalized approaches. This study aimed to develop a machine learning model to predict binaural beats's effectiveness on working memory using electroencephalography. Sixty healthy participants underwent a 5-min electroencephalography recording, an initial working memory evaluation, 15 min of binaural beats stimulation, and a subsequent working memory evaluation using digit span tests of increasing difficulty. Recall accuracy and response times were measured. Differential scores from pre-evaluation and post-evaluation labeled participants as active or inactive to binaural beats stimulation. electroencephalography data, recorded using 14 electrodes, provided brain activity estimates across theta, alpha, beta, and gamma frequency bands, resulting in 56 features (14 channels × 4 bands) for the machine learning model. Several classifiers were tested to identify the most effective model. The weighted K-nearest neighbors model achieved the highest accuracy (90.0%) and area under the receiver operating characteristic curve (92.24%). Frontal and parietal electroencephalography channels in theta and alpha bands were crucial for classification. This study's findings offer significant clinical insights, enabling informed interventions and preventing resource inefficiency.

COMPARATIVE ANALYSIS OF FOREIGN EXPERIENCE IN IMPLEMENTING PSYCHOLOGICAL AND PEDAGOGICAL GUIDANCEFOR SOFT SKILLS DEVELOPMENT OF UNIVERSITY STUDENTS

The article discusses modern methods and practices of psychological and pedagogical guidanceforthe soft skills development of students in higher educational institutions. With globalization and rapid technological progress, traditional teaching methods are becoming insufficient. The purpose of this study is to conduct a comparative analysis of modern methods and practices used in different countries, with the aim of adapting and introducing them into the higher education system of the Republic of Kazakhstan. The methodological basis of our research is a personal approach, which involves considering the individual characteristics of each student.The analysis of international experience revealed effective methods, such as emotional intelligence development, active learning, coaching and mentoring, project-based and problem-based learning, gamificationand the flipped classroom. These approaches demonstrate high effectiveness and can be adapted for use in the higher education system of the Republic of Kazakhstan. The introduction of these methods helps to improve the quality of education, improve the employment of graduates and their competitiveness in the labor market. Successful integration of these practices will require adaptation to local conditions and training of teachers, which will significantly increase the level of specialists’training in Kazakhstan.

Alterations in Immune Parameters ADP, ANA, IL-1, IL-6, IL-8, STAT-4, and TNF Alpha in Patients with Rheumatoid Arthritis and Osteoarthritis

Background: Rheumatoid arthritis (RA) and osteoarthritis (OA) are chronic joint diseases with distinct pathophysiological mechanisms, but both involve alterations in immune parameters. This research investigates the alterations in several immune parameters, specifically adiponectin (ADP), antinuclear antibodies (ANA), interleukin-1 (IL-1), interleukin-6 (IL-6), interleukin-8 (IL-8), signal transducer and activator of transcription 4 (STAT-4), and tumor necrosis factor-alpha (TNF Alpha), in patients with rheumatoid arthritis (RA) and osteoarthritis (OA). Also, the current study aims to identify the changes occurring in the physiological and immune parameters of people suffering from rheumatic diseases, as Evaluation of Immunological Inflammatory biomarkers levels ADP, ANA, IL1, IL6, IL8, STAT-4 and TNF-α. Material & Methods: A cross-sectional laboratory-based study with 90 patient’s participant was conducted. Using ELISA kits and laboratory tests, various biomarkers (Immunological Inflammatory biomarkers levels ADP, ANA, IL1, IL6, IL8, STAT-4 and TNF-α were measured among rheumatoid arthritis and Osteoarthritis patients. Results: The findings revealed elevated levels of IL-1, IL-6, IL-8, STAT-4, and TNF Alpha in RA patients, reflecting a heightened inflammatory state. In contrast, OA patients exhibited a more moderate increase in these parameters, suggesting differing immune activation pathways. ADP and ANA levels showed distinct variations between the two patient groups, indicating their potential roles in the pathogenesis and progression of RA and OA. Conclusion: These results contribute to a better understanding of the immune mechanisms underlying RA and OA, highlighting the importance of targeted therapeutic strategies to manage these conditions effectively. Further research is recommended to explore the clinical implications of these findings and develop personalized treatment approaches.

HYPERTENSION IN THE ELDERLY: CHALLENGES IN MANAGEMENT AND TREATMENT

Hypertension is a prevalent and significant health issue among the elderly, contributing to increased risks of cardiovascular diseases, stroke, and kidney failure. Managing hypertension in older adults poses unique challenges due to age-related physiological changes, comorbidities, and polypharmacy. This review explores the complex pathophysiology of hypertension in the elderly, including age-related changes in vascular function and the impact of comorbid conditions. It examines the difficulties in diagnosing hypertension, such as variability in blood pressure readings, white coat syndrome, and masked hypertension, highlighting the need for accurate monitoring through home and ambulatory techniques. The review discusses current management strategies, emphasizing the importance of setting appropriate treatment goals, implementing lifestyle modifications, and utilizing pharmacological treatments, including new antihypertensive drugs and combination therapies. It also addresses challenges such as adverse drug reactions, medication adherence, and the management of polypharmacy. Recent advances, including innovations in drug delivery systems and digital health technologies, offer promising solutions for improving hypertension management. Future research directions include exploring precision medicine, understanding the role of the gut microbiome, and addressing health disparities. Clinicians are advised to adopt personalized treatment approaches, integrate technological tools, and address socioeconomic barriers to optimize hypertension management in the elderly. This review underscores the need for ongoing research and tailored strategies to improve outcomes and quality of life for older patients with hypertension.

The Impact of Postgraduate Leadership Development Fellowships for Doctors-in-Training: Reflections from a Fellow's Experience and a Narrative Literature Review.

Postgraduate leadership fellowships are becoming more popular among doctors-in-training. The author completed a one-year leadership fellowship with the Health Education England (HEE), East Midlands. A personal reflective approach was used to present the experiences of the author following the completion of the fellowship programme. Using the PubMed database, a narrative literature review on the impact of postgraduate leadership development programmes on doctors-in-training was also performed, with a focus on published randomised controlled trials (RCTs) and systematic reviews. Personal benefits for the author were seen in the areas of improved leadership skills; completion of a postgraduate academic qualification; improvement of teaching skills; and honing of major trauma clinical skills. Furthermore, the literature review showed that there was high grade evidence from two randomised controlled trials, for the impact of such programmes in obstetrics/gynaecology simulation, and on team leadership for major trauma resuscitation. In addition, three systematic reviews reported positive impacts of such programmes at an individual level for participants' attitudes, knowledge and skills, with minimal evidence for the overall impacts on healthcare institutions.

Analyzing demand for virtual reality based adaptive learning design in engineering faculty of universitas negeri Makassar Indonesia

This research aims to analyze the needs of students regarding the application of Virtual Reality (VR) technology in learning at the Faculty of Engineering. The main focus is to understand how VR can support adaptive learning and improve students' practical ability according to individual ability. This research uses a needs analysis method involving a survey of engineering students. Data collection was conducted through questionnaires and observations to identify students' constraints, needs, and interests in VR-based learning. The collected data were then analyzed quantitatively and qualitatively. The results show that 85% of students struggle to understand complex engineering concepts, and 90% show high interest in using VR for skills practice in a safe environment. In addition, students expected a more interactive and personalized learning approach. Important features they expected included automatic adjustment of difficulty levels and immediate feedback during practice. The findings of this study confirm the importance of integrating VR into engineering education, especially in creating an adaptive learning environment that meets individual needs. VR has the potential to improve students' understanding of concepts and practical skills, as well as to support the development of curriculum that are more relevant to the needs of modern industry.

Novel biomarkers and drug correlations of non-canonical WNT signaling in prostate and breast cancer

Prostate cancer (PCa) and breast cancer (BC) present formidable challenges in global cancer-related mortality, necessitating effective management strategies. The present study explores non-canonical Wnt signaling in PCa and BC, aiming to identify biomarkers and assess their clinical and therapeutic implications. Co-expression analyses reveal distinct gene patterns, with five overlapping genes (SULF1, ALG3, IL16, PLXNA2 and RASGFR2) exhibiting divergent expression in both cancers. Clinical relevance investigations demonstrate correlations with TNM stages and biochemical recurrence. Drug correlation analyses unveil potential therapeutic avenues, indicating that Wnt5a and ROR2 expressions are related to MEK inhibitor sensitivity in cancers. Meanwhile, further correlation analyses were conducted between drugs and the other novel non-canonical WNT genes (ALG3, IL16, SULF1, PLXNA2, and RASGRF2). Our findings contribute to understanding non-canonical Wnt signaling, offering insights into cancer progression and potential personalized treatment approaches.

Seminal Malondialdehyde (MDA) Levels in Iraqi Males with Infertility: Exploring the Relationship with Body Mass Index (BMI)

Background: The investigation of the relationship between BMI and MDA levels in male infertility is pivotal for comprehending the underlying mechanisms of infertility, pinpointing potential therapeutic targets, and devising personalized approaches to enhance fertility outcomes in men. Therefore, the primary objective of this study was to explore the correlation between MDA levels in seminal fluid and infertility in Iraqi males, along with its potential association with Body Mass Index (BMI). Methodology: Ninety males aged between twenty and forty-five were included in this cross-sectional study, all diagnosed with infertility by specialists at the infertility unit of Al-Batool Teaching Hospital between February 2022 and February 2023. The participants were categorized into three groups: the Normozoospermic Group (G1), the Asthenospermia Group (G2), and the Oligozoospermic Group (G3). Results: The distribution of age and BMI across the study groups (G1, G2, and G3) appeared to be uniform and not statistically significant, indicating more noticeable variations among the groups. However, waist circumference (WC) analysis suggested statistically significant differences among the groups, highlighting a non-negligible change in the frequency of obesity within the groups participating in the study. Between the study groups, there was no statistically significant difference in smoking habits. The seminal fluid MDA levels for G1 were significantly lower than those for G2 and G3. Additionally, Seminal plasma MDA levels and BMI showed a non-significant positive correlation. Conclusion: There is no correlation between BMI and MDA levels in male infertility.

Acute Levodopa Challenge in Atypical Parkinsonism: Comprehensive Analysis of Individual Motor Responses.

The acute levodopa challenge is widely used to distinguish Parkinson's disease (PD) from atypical parkinsonian syndromes (APSs) such as multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). In APSs, very few patients present a clinically relevant response to levodopa. The aim of this study was to determine whether patients with atypical parkinsonism benefit from levodopa in any aspect of their multiple motor deficits despite the generally poor response. This retrospective study analyzed individual motor responses to the acute levodopa challenge using the MDS-UPDRS III in 47 PSP, 26 MSA, and 71 PD patients at Hannover Medical School. Despite the generally poor levodopa response in both PSP and MSA patients, bradykinesia and rigidity were the symptoms most notably affected by levodopa in PSP patients, while MSA patients experienced significant improvements in bradykinesia and action tremor. These findings underscore the variability in levodopa response among PSP and MSA patients and highlight the need for personalized treatment approaches in atypical parkinsonism.

Managing the rehabilitation of patients following joint replacement using remote support tools

The article considers the approach to the development of an intelligent decision support system based on artificial intelligence technologies to manage the rehabilitation process in patients who have undergone joint endoprosthetic surgery. The paper focuses on the advantages of using complex intelligent systems in various industries requiring personalised approaches to the object, including medicine. The prospects for their further development are considered. The creation of a digital twin reflecting the key parameters of the object and its development trajectory from the moment of the first interaction with the system is proposed. The system, developed on the basis of software and instrumental environments, provides the possibility of remote observation and correction of the recovery plan by specialists, which represents a significant advantage compared to traditional methods. In order to ensure the adaptability of the system and the actualisation of the proposed solutions, control over the patient's condition and adaptation of treatment programmes is achieved by means of periodic and unscheduled checking of the object indicators. This is achieved by comparing the indicators obtained as a result of video data analysis with the normalised indicators of the system. The developed system analyses video recordings, performs movement analysis and adapts rehabilitation measures depending on the obtained data on the patient's motor activity in real time. The proposed method offers the potential to enhance the precision and personalisation of rehabilitation approaches, thereby facilitating greater accessibility and efficacy in treatment. The integration of artificial intelligence elements into clinical practice presents a promising avenue for optimising rehabilitation processes.

Bone-A-Fide Breakthrough: Machine Learning Cracks the Code on Osteoporosis Treatment Using the Irish Hip Fracture Database

Abstract Background Osteoporosis is a metabolic bone disorder characterised by decreased bone mineral density and mass. Due to its asymptomatic nature, it often remains undiagnosed and untreated until a fracture occurs. Traditionally, treatment decisions for osteoporosis are based on clinical appropriateness while balancing the treatment's risks and benefits. Machine learning (ML) is revolutionising healthcare domains through pattern recognition of previously “unseen” observations. Presently, its application in osteoporosis is limited to early diagnosis. More research is needed to examine its role in guiding osteoporosis treatment. This study aims to identify new predictive attributes for osteoporosis treatment using ML techniques on data from the Irish Hip Fracture Database (IHFD). Methods Datasets from January to March 2023 in University Hospital Waterford were sourced from the IHFD. Osteoporosis treatment decisions were obtained from discharge letters. Preliminary data cleaning was performed in Excel with zero-variance and near-zero predictor. Attributes excluded. The dataset was entered into the WEKA 3.8.6 environment for ML processing. Results The initial dataset containing 141 instances and 32 attributes was refined using the Correlation Feature Selection and Ranker Search Method, identifying key osteoporosis treatment predictors. The highest correlation attributes are pre-fracture total score, pre-fracture indoor score, and age. Moderately positive correlations are discharge destination, pre-fracture outdoor and shopping score, ASA grade, Length-of-stay, admission code, Admission 4AT score, Frailty scale, and fracture type. The implemented J48 Tree ML-trained model revealed Correctly Classified Instances and Incorrectly Classified Instances of 98.24% and 1.7%, respectively, indicating a high prediction accuracy rate. Conclusion This study demonstrates the potential of ML in enhancing osteoporosis treatment decision-making by leveraging datasets from the IHFD. Integrating ML algorithms with traditional approaches can provide a comprehensive, nuanced and personal approach to osteoporosis treatment and patient care. The study opens avenues for future research in applying big data and advanced analytics in healthcare, underscoring the evolving landscape of medical decision-making.

Exploration of potential drug targets for Glaucoma by plasma proteome screening

BackgroundGlaucoma is the leading cause of irreversible blindness. However, the current available treatment methods are still unsatisfactory. Therefore, the exploration of new drug targets for the treatment of glaucoma is of paramount importance. MethodsWe conducted two-sample Mendelian randomization (MR) using plasma protein quantitative trait loci (pQTL) data from two datasets (n = 734, n = 4907) and their instrumental variables to investigate the causal relationship between plasma proteins and glaucoma. The analysis was validated by replacing the exposure and outcome cohorts. Additionally, we utilized protein-protein interaction networks to assess the associations between these potential drug targets and existing drug targets. ResultsThrough two-sample Mendelian randomization analysis, we identified causal relationships between Glaucoma and the following proteins: AZU1, OBP2B, ENPP5, INPP5B, KREMEN1, LYPLAL1, and PTPRJ. External validation confirmed the protective effect of LYPLAL1 on Glaucoma, while ENPP5, KREMEN1, and PTPRJ increased the risk of Glaucoma. Reverse MR and Steiger filtering did not indicate any reverse causal associations of the aforementioned proteins with Glaucoma. ConclusionOur study demonstrates a causal impact of ENPP5, KREMEN1, PTPRJ, and LYPLAL1 on the risk of Glaucoma. These findings suggest that these four proteins may serve as promising drug targets for Glaucoma treatment. SignificanceCurrently, the pharmacological treatment of glaucoma primarily focuses on lowering intraocular pressure, which has its limitations. Targeted therapy is a personalized treatment approach that aims to inhibit or block the development and progression of diseases such as cancer and inflammation by selectively acting on specific biomolecules or signaling pathways. Our research employs a two-sample Mendelian randomization (MR) method, integrating a large amount of GWAS and pQTL data to perform MR analysis. This has enabled us to explore several plasma proteins as potential drug targets for glaucoma, providing direction and a research foundation for future investigations into glaucoma drug targets.

Exploring the Interconnection between Metabolic Dysfunction and Gut Microbiome Dysbiosis in Osteoarthritis: A Narrative Review.

Osteoarthritis (OA) is a prevalent joint disorder and the most common form of arthritis, affecting approximately 500 million people worldwide, or about 7% of the global population. Its pathogenesis involves a complex interplay between metabolic dysfunction and gut microbiome (GM) alterations. This review explores the relationship between metabolic disorders-such as obesity, diabetes, and dyslipidemia-and OA, highlighting their shared risk factors, including aging, sedentary lifestyle, and dietary habits. We further explore the role of GM dysbiosis in OA, elucidating how systemic inflammation, oxidative stress, and immune dysregulation driven by metabolic dysfunction and altered microbial metabolites contribute to OA progression. Additionally, the concept of "leaky gut syndrome" is discussed, illustrating how compromised gut barrier function exacerbates systemic and local joint inflammation. Therapeutic strategies targeting metabolic dysfunction and GM composition, including lifestyle interventions, pharmacological and non-pharmacological factors, and microbiota-targeted therapies, are reviewed for their potential to mitigate OA progression. Future research directions emphasize the importance of identifying novel biomarkers for OA risk and treatment response, adopting personalized treatment approaches, and integrating multiomics data to enhance our understanding of the metabolic-GM-OA connection and advance precision medicine in OA management.

Efficacy and prognosis of neoadjuvant chemotherapy in HER2 low-expressing breast cancer: a retrospective single-center study.

Human epidermal growth factor receptor 2 (HER2) is vital for breast cancer prognosis. The aim of this study was to analyze the clinicopathological data of HER2-negative breast cancer patients receiving neoadjuvant chemotherapy and the associated factors affecting the pathological complete response rate (pCR) and prognosis. Clinical data of 173 patients with primary HER2-negative breast cancer, who initially received neoadjuvant chemotherapy followed by surgical treatment at the Breast Surgery Department of Bethune Hospital in Shanxi Province from January 2012 to December 2022, were collected. Compared to HER2-0 patients, HER2-low patients had higher T staging (p = 0.008), higher Ki67 proliferation index (p < 0.001), lower N staging (p = 0.001), and lower pCR rate (p < 0.001). Univariate analysis revealed that T stage, TNM stage, HR status, HER2 status, and Ki67 are risk factors that affect the pCR rate in HER-2 negative. Multivariate analysis identified HR status as an independent predictor of pCR rate. Kaplan-Meier survival curves showed that menstrual status, N staging, T staging, TNM staging, and pCR status affected the prognosis of HER2-low breast cancer patients (p < 0.05). HER2-low breast cancer exhibits distinct biological behaviors, suggesting personalized treatment approaches.

Exploring cariprazine as a treatment option for varied depression symptom clusters.

Major depressive disorder (MDD) is among the most prevalent psychiatric conditions and a leading cause of disability worldwide. MDD presents a diverse range of symptoms that significantly impact personal, societal, and economic dimensions. Despite the availability of numerous antidepressant treatments (ADTs) targeting different molecular mechanisms, a substantial proportion of patients experience inadequate response, presenting a considerable challenge in MDD management. As a result, adjunctive strategies, particularly involving atypical antipsychotics, are often employed to enhance treatment efficacy. Cariprazine, a D2/D3 partial agonist, is distinguished from other atypical antipsychotics by its selective action on the D3 receptor and its modulation of 5-HT1A, 5-HT2A, and alpha 1B receptors. This distinctive pharmacological profile warrants investigation into its potential effectiveness and tolerability across various symptom domains of MDD, including pleasure, interest, and motivation; mood and suicidality; sleep and appetite; fatigue; psychomotor activity and anxiety; and cognitive function. Preliminary evidence from animal studies and clinical trials suggests that cariprazine may improve motivation, anhedonia, and cognitive function symptoms. Cariprazine shows promise in alleviating mood-related symptoms, though its impact on anxiety and its effects on agitation and psychomotor retardation remains uncertain. Cariprazine may be particularly beneficial for patients with MDD exhibiting anhedonia, cognitive deficits, and possibly fatigue and hypersomnia. Evaluating cariprazine's efficacy across these symptom domains could reveal patterns that support more personalized treatment approaches for depression. Further research is essential to elucidate the role of cariprazine as an adjunctive therapy for adults with major depressive disorder who have an inadequate response to antidepressant monotherapy.

Shared decision-making and detection of comorbidities in an online acromegaly consultation with and without the Acromegaly Disease Activity Tool ACRODAT® using the simulated person approach

ObjectiveA patient-centered approach to the management of acromegaly includes disease activity control, shared decision-making and identification of comorbidities. The Acromegaly Disease Activity Tool (ACRODAT®) is intended to assist physicians in providing such holistic management. The present study investigated this claim using the simulated person (SP) approach.MethodsWe studied patient-doctor interaction via online video consultation in a randomized prospective study design with SPs trained to simulate a specific acromegaly profile. We analyzed the proportion of conversation time devoted to health content and the specific acromegaly and comorbidity relevant categories mentioned in the conversation. We collected physicians’ feedback on the usefulness of ACRODAT®, SPs subjective perception of the quality of the conversation and compared consultations with and without ACRODAT® using a qualitative approach.ResultsThe sample (N = 30) consisted of endocrinologists treating patients with acromegaly in Germany. For SP-physician interactions (N = 60), the proportion of time spent on conversation content (e.g. IGF-I, quality of life) was distributed according to the focus of the patient profile. Comorbidities were less well identified than the need for a change in therapy. Only 18.3% of the SPs were actively asked to participate in the decision-making process. ACRODAT® did not lead to any significant differences in the course of the discussion.ConclusionsShared decision-making was underrepresented in this SP-physician interaction in acromegaly management. Physicians adapted the content of the discussion to the SP’s needs, but did not adequately address comorbidities. According to the analysis criteria used, ACRODAT® did not contribute to a more holistic patient management in the present study.

Ethnicity in neuro-oncology research: How are we doing and how can we do better?

This study systematically reviews and meta-analyses the extent of ethnic minority representation in neuro-oncology Phase III and IV clinical trials, explores the effect of ethnicity on outcomes, and identifies predictors for the inclusion of ethnicity data in publications. Adhering to PRISMA guidelines, we conducted a comprehensive literature search across multiple databases, on Phase III and IV trials in neuro-oncology that reported on adult and/or paediatric subjects. Through meta-analysis, we synthesized information on overall survival, event-free survival, and the incidence of adverse outcomes across ethnicities. From 448 identified articles, a fraction reported ethnicity data, with an even smaller number providing outcome data stratified by ethnicity. Most study participants were identified as White, underscoring a significant underrepresentation of minorities. Our meta-analysis did not reveal significant outcome differences by ethnicity, which may be attributed to the limited and inadequate reporting of data. Predictors for including ethnicity data were identified, including trials in North America(OR2.39, 95%CI 1.18-5.12, p < 0.02),trials of drugs or biologic agents(OR 5.28, 95%CI 1.43-3.42, p < 0.05),and trials funded by charities(OR 2.28, 95% CI 1.04-5.27, p < 0.05) or pharmaceutical companies(OR 3.98, 95% CI 1.60-10.0, p < 0.005). The underrepresentation of minorities in neuro-oncology clinical trials and the inadequately characterized impact of ethnicity on treatment outcomes highlight a critical need for more inclusive recruitment strategies and improved reporting standards. Change is necessary to ensure trials reflect the diversity of the patient population, which is essential for developing tailored strategies and improving outcomes. Future research should prioritize understanding the role of ethnicity in neuro-oncology to facilitate personalized treatment approaches.

English Foreign Language Teachers’ Strategy in Teaching Speaking Classes: A Case Study at the Rumah Inggris Jogja

This research aims to find out English teachers' strategies in teaching English-speaking classes at the Rumah English Jogja, explore the challenges faced by two English teachers in teaching speaking classes, and how they solve these problems. The present study utilized qualitative design with descriptive analysis, and the respondents were two teachers who teach English speaking classes. Observations and semi-structured interviews were employed to obtain the data. All data gathered were gone through several analysis steps: data reduction, data display, and conclusion. The findings revealed that the teaching strategies used by Mr. A were the question &amp; answer, conversation, drilling, storytelling, and conversation strategy. Meanwhile, Mr. M, applied translation, repeating, group work, drilling, role play, reporting, game, story completion, interview, and question &amp; answer. The result of the interview with Mr. A, and Mr M, revealed that they found it difficult to deal with new students as they were not well prepared to join the speaking class. Mr. A found it hard to stimulate and motivate his students who were not familiar with the topic discussed. Meanwhile, Mr. M, pointed out some of his difficulties, including the difference in learners' characteristics, and the variety of learners' needs, wants, and lacks in the class. Having a personal approach to students, being good friends, and creating an enjoyable learning atmosphere are several good efforts to do.