Medical archives (Sarajevo, Bosnia and Herzegovina)最新文献

{"title":"Clozapine Withdrawal-Induced Catatonia with Overlapping Features of Neuroleptic Malignant Syndrome: a Case Report.","authors":"Rusmir Softic, Almerisa Tufekcic, Jasmina Klebic, Aida Sehanovic","doi":"10.5455/medarh.2026.80.94-95","DOIUrl":"10.5455/medarh.2026.80.94-95","url":null,"abstract":"<p><strong>Background: </strong>Clozapine is the most effective antipsychotic for treatment-resistant schizophrenia, and abrupt discontinuation can lead to severe neuropsychiatric destabilization, including withdrawal catatonia. High-potency dopamine D2 receptor antagonists may further precipitate neuroleptic malignant syndrome (NMS), a condition with substantial clinical overlap with malignant catatonia.</p><p><strong>Objective: </strong>This report follows CARE guidelines to provide a structured and transparent description of a complex case involving abrupt clozapine withdrawal and rapid antipsychotic transition.</p><p><strong>Case presentation: </strong>This report describes a male patient with schizophrenia who developed malignant catatonia with overlapping NMS features following abrupt clozapine withdrawal and initiation of fluphenazine.</p><p><strong>Conclusion: </strong>The case underscores the importance of cautious antipsychotic transitions and early recognition of catatonia and NMS.</p>","PeriodicalId":94135,"journal":{"name":"Medical archives (Sarajevo, Bosnia and Herzegovina)","volume":"80 1","pages":"94-95"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13049473/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147625391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of COVID-19 Pandemic on Pediatrics Primary Healthcare Visits in a University Based Family and Community Medicine Center in Saudi Arabia.","authors":"Haneen A Yousef, Mohammed M Alismail, Moataza M Abdel Wahab, Naheel A AlAmer, Mohammad H Al-Qahtani, Beshaier Almulhem, Ruba K Alnajim, Faisal O AlQurashi","doi":"10.5455/medarh.2026.80.33-39","DOIUrl":"10.5455/medarh.2026.80.33-39","url":null,"abstract":"<p><strong>Background: </strong>The COVID-19 pandemic has significantly impacted many aspects of healthcare, particularly pediatric visits to primary healthcare (PHC). Difficulties associated with PHC in this delicate age group can result in substantial complications.</p><p><strong>Objective: </strong>This study aims to determine the impact of the COVID-19 pandemic on pediatric primary care delivery by examining patient characteristics, the number and types of visits, and their relationships both before and after the pandemic.</p><p><strong>Methods: </strong>This comparative cross-sectional study (pre-COVID-19 and COVID-19) utilized register-based data of children aged ≤14 years old, including both Saudi and non-Saudi females and males. Data collection spanned from 2016 to 2021. Sampling was conducted using a stratified random sampling method based on age groups, followed by a simple random sampling technique with proportional allocation to each age group.</p><p><strong>Results: </strong>A total of 1,439 pediatric visits were included in this study, with males accounting for 52.2% of the sample. The most highly represented age group was toddlers, and 60% of the sample were Saudis. Vaccination was the most common reason for visits, accounting for 32% of the cases, followed by general and well-baby checkups, constituting 25.4%. During the COVID-19 pandemic, there was an increase in visits related to general and well-baby checkups, vaccinations, and psychiatry compared to the pre-COVID-19 period. Conversely, visits for fever, dermatology, ENT (ear, nose, and throat), gastrointestinal (GI), and respiratory conditions decreased during the COVID-19 pandemic compared to the pre-COVID-19 period. Moreover, there was a statistically significant increase in referrals to the ophthalmology department in contrast to a decrease in referrals to the emergency department (ED) compared to the pre-COVID-19 period.</p><p><strong>Conclusion: </strong>The COVID-19 pandemic resulted in a significant impact on pediatric visits to PHC. Awareness of families regarding the well-baby clinic and vaccination visits reflects a positive attitude, emphasizing the importance of this during and after the pandemic will contribute to the overall wellbeing of the pediatric population. In addition, greater effort should be made to provide mental health PHC visits to protect and support this age group in future pandemics.</p>","PeriodicalId":94135,"journal":{"name":"Medical archives (Sarajevo, Bosnia and Herzegovina)","volume":"80 1","pages":"33-39"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13049476/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147625360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Liability for Damage Caused by the Use of Artificial Intelligence (AI) in Medicine.","authors":"Blanka Matesa, Izet Masic","doi":"10.5455/medarh.2026.80.74-81","DOIUrl":"10.5455/medarh.2026.80.74-81","url":null,"abstract":"<p><strong>Background: </strong>Artificial intelligence (AI) is applied in numerous areas of society and has also led to significant changes in the field of medicine. Medicine is a branch of science of exceptional importance, and it is therefore necessary to ensure a high level of patient protection. The quality of healthcare has significantly improved through the use of artificial intelligence in various stages of the medical process, from the analysis of medical data and diagnostics, through therapy planning, to patient monitoring and the management of healthcare systems.</p><p><strong>Objective: </strong>The aim of this paper is to analyze the civil law aspects of artificial intelligence in medicine, with a particular focus on questions of liability for damage resulting from the use of such systems.</p><p><strong>Methods: </strong>The paper will first present the basic characteristics and areas of application of artificial intelligence in medicine, and then examine potential sources of damage and the legal basis for the liability of various stakeholders, including AI system manufacturers, software developers and data providers, healthcare institutions, and healthcare professionals. Special attention will be given to the challenges of proving causation and allocating liability in situations where decisions are made or supported by autonomous algorithmic systems.</p><p><strong>Results and discussion: </strong>However, at the same time, numerous legal issues arise, particularly in the field of civil liability in cases where the application of artificial intelligence results in harm to a patient. Given the great importance of medicine and the need to ensure a high level of patient protection, the application of artificial intelligence must be accompanied by appropriate legal protection. The paper gives answers to a number of questions, with particular emphasis on the question of who may be held liable for damage caused by the use of artificial intelligence in medicine, as well as under which regulations and in what manner such liability is determined.</p><p><strong>Conclusion: </strong>Artificial intelligence has the potential to significantly enhance medical practice, its application must be accompanied by appropriate legal mechanisms that ensure patient protection and clearly define the responsibility of all participants in the system. Future legal development in this area will likely focus on further adapting existing civil law institutions to the specificities of artificial intelligence, while simultaneously strengthening preventive risk management mechanisms and transparency of AI systems in medicine.</p>","PeriodicalId":94135,"journal":{"name":"Medical archives (Sarajevo, Bosnia and Herzegovina)","volume":"80 1","pages":"74-81"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13049468/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147624956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Perioperative Nutritional Support in Gastrointestinal Surgical Patients with Severe Malnutrition.","authors":"Pham Van Nhan, Luu Ngan Tam, Nguyen Tan Cuong","doi":"10.5455/medarh.2026.80.52-56","DOIUrl":"10.5455/medarh.2026.80.52-56","url":null,"abstract":"<p><strong>Background: </strong>Severely malnourished patients undergoing major gastrointestinal surgery are at high risk of postoperative complications, increasing costs and length of hospital stay.</p><p><strong>Objective: </strong>This study aimed to evaluate the impact of perioperative nutritional support on nutritional and surgical outcomes in these patients.</p><p><strong>Methods: </strong>This was a prospective before-after study. Perioperative nutritional support in severely malnourished patients based on at least one of the following criteria: SGA.C, weight loss > 10% within 6 months, BMI < 18 kg/m2, serum albumin < 30 g/l. Once the patients were nourished achieving target energy continuously for at least 7 days and improved nutritional conditions, they were operated. Postoperative nutritional support lasted until hospital discharge. The preoperative and postoperative target energy intake was 30 and 25 kcal/kg, respectively. Enteral and parenteral feeding was combined perioperatively.</p><p><strong>Results: </strong>A total of 53 patients underwent perioperative nutritional support combining one-stage surgery. Preoperative nutritional conditions improved. Postoperative catabolism was inevitable but patients early restored anabolism before hospital discharge. Overall and malnutrition-related postoperative complication rates were 11.3% and 7.5%, respectively, with no mortality or anastomotic leakage. The postoperative and perioperative average durations were 9 and 17.3 days, respectively. Nutritional and hospitalization costs were not high.</p><p><strong>Conclusion: </strong>Perioperative nutritional support for severely malnourished patients undergoing major gastrointestinal surgery improved preoperative nutritional conditions, early restored anabolism postoperatively, provided positive surgical outcomes on postoperative complications, costs and length of hospitalization.</p>","PeriodicalId":94135,"journal":{"name":"Medical archives (Sarajevo, Bosnia and Herzegovina)","volume":"80 1","pages":"52-56"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13049465/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147625340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical Artificial Intelligence (AI) Liability in the MENA Region: a Comparative Analysis of Hospital, Physician, Suppliers, and Vendor Responsibility.","authors":"Mohammad Alsalamat Mohammad Assaf, Hisham Jadallah Mansour Shakhatreh, Khaled Khalaf Abed Rabbo Aldrou, Nasir Mohammad Albalawee, Mohammad Saad Mousa Al-Zboon, Zaid Ibrahim Yousef Gharaibeh, Farouq Ahmad Faleh Alazzam","doi":"10.5455/medarh.2026.80.82-88","DOIUrl":"10.5455/medarh.2026.80.82-88","url":null,"abstract":"<p><strong>Background: </strong>Clinical artificial intelligence (Clinical AI) is now a commonplace tool being used for administrative, diagnostic and therapeutic purposes. However, it gives rise to novel and complex liability questions that will involve multiple actors including physicians, hospitals, suppliers, vendors and more.</p><p><strong>Objective: </strong>The paper compares the relevant laws in nine jurisdictions in the MENA region - including the United Arab Emirates (UAE) and the other GCC states alongside Algeria, Egypt, and Morocco - to understand how evolving legislation, regulation and ethical codes impact fault and damages.</p><p><strong>Methods: </strong>The Clinical AI ecosystem roles are defined, and core legal duties related to consent, data protection, patient rights and safety oversight mapped. The text critiqued (i) the hospital's selection, governance, training, and ongoing post-deployment monitoring responsibilities; (ii) the accountability of clinicians in mixed \"decision-support\" workflows, including disclosure of the use of AI to patients and standard-of-care implications of accepting or override AI output; and (iii) supplier/vendor exposure through product liability, performance warranties, cybersecurity obligations, licensing/clearance and ongoing post-market updates and supervision.</p><p><strong>Results: </strong>The comparative section shows significant differences between MENA liability models. It also highlights the need for facility-wide incident response proper process that encompasses model drift, cyber events and data-quality failures, which more often cause the harm than algorithm malfunction.</p><p><strong>Conclusion: </strong>In conclusion, improved risk allocation through governance, documentation, contracting and incident reporting, can aid in reducing uncertainty, enhancing patient safety, and facilitating more scalable cross-border deployment of Clinical AI in the region.</p>","PeriodicalId":94135,"journal":{"name":"Medical archives (Sarajevo, Bosnia and Herzegovina)","volume":"80 1","pages":"82-88"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13049466/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147625412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predictors of a Depression Indicator in a Large Public Dataset: Logistic Regression and Neural Network Comparison.","authors":"Ibrahim Abdul Jaleel Yamani, Izzeldeen Abdullah Alnaimi, Ahed J Alkhatib","doi":"10.5455/medarh.2026.80.63-67","DOIUrl":"10.5455/medarh.2026.80.63-67","url":null,"abstract":"<p><strong>Background: </strong>Depression ranks among the five leading disability causes. The research associations with depression include many demographic, lifestyle and health-related measures. These factors and depression probably interact with each other.</p><p><strong>Objectives: </strong>The objectives of the study are to describe the characteristics of the participants, to examine the bivariate association between a proxy of depression and the study variables, to identify independent predictors with the help of a logistic regression model, and to evaluate a neural network classification model.</p><p><strong>Methods: </strong>A cross-sectional secondary analysis of a publicly available dataset N = 50000 was conducted. Depression indicator (Yes/No) is outcome variable. A neural network of the multilayer perceptron type (15 inputs, a hidden layer with.</p><p><strong>Results: </strong>Depression indicator in 40.7% of participants. In bivariable analyses, physical activity, alcohol consumption, dietary habits, family history of depression, and chronic medical conditions showed statistically significant but small differences. Income (p = 0.239) and number of children (p = 0.078) did not differ between groups.</p><p><strong>Conclusion: </strong>There was a modest association with depression index and poor discrimination by neural networks. In performing a classification relating to depression using machine learning one must use assessments with validated outcomes and employ class-sensitive performance assessment.</p>","PeriodicalId":94135,"journal":{"name":"Medical archives (Sarajevo, Bosnia and Herzegovina)","volume":"80 1","pages":"63-67"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13049475/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147624881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Paroxysmal Supraventricular Tachicardia (PSVT) Attacks in Correlation With Age, Gender, Residence, Diseases and Triggering Factors.","authors":"Halit Bajraktari, Edmond Haliti, Blerim Krasniqi, Naser Ramadani, Elizana Pertrela-Zaimi, Agim Krasniqi, Krenar Zenelaj","doi":"10.5455/medarh.2026.80.21-26","DOIUrl":"10.5455/medarh.2026.80.21-26","url":null,"abstract":"<p><strong>Background: </strong>Paroxysmal supraventricular tachycardia (PSVT) is a heart rhythm disorder that occurs due to the presence of aberrant cardiac conduction pathways, where the phenomenon of circular conduction of the electrical phenomenon - \"reentry\" occurs. PSVT presents as: AV nodal tachycardia with reentry, AV reentry tachycardia and focal atrial tachycardia.</p><p><strong>Objective: </strong>The aim of the study was to investigate the causes, age group, gender, place of residence, causative factors, various and cardiac diseases and the role of non-use/use of therapy in the occurrence of PSVT attacks.</p><p><strong>Methods: </strong>In the cross-sectional study, 203 patients were evaluated, of whom 43.35% (88 cases) were male and 56.65% (115) were female.</p><p><strong>Results: </strong>The mean age of the patients included in the study was 40.16±16.13 years. The largest number of patients who sought treatment for PSVT belonged to the group of patients without any diagnosed cardiac condition. The mean age differences reflected in the number of attacks in patients were analyzed and it was concluded that there was a statistically significant difference (p=0.01) in the mean age of patients who had only one attack (37.0±16.1 years) compared to those with three or more attacks (40.2±15.4) years.</p><p><strong>Conclusion: </strong>PSVT is often a heart rhythm disorder with onset ranging from early age to old age. Once present, it tends to recur. Diagnosing and treating PSVT attacks is important for both the quality of life of patients and for the prevention of congestive heart failure.</p>","PeriodicalId":94135,"journal":{"name":"Medical archives (Sarajevo, Bosnia and Herzegovina)","volume":"80 1","pages":"21-26"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13049478/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147625337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cone Beam Computed Tomography (CBCT) Image Based Volumetric and Dimension Measurements of Maxillary Sinus in Correlation to the Age and Gender of a Lebanese Population Sample.","authors":"Fidele Nabbout, Elie Hayek, Wadih Nassif, Georges Aoun","doi":"10.5455/medarh.2026.80.68-73","DOIUrl":"10.5455/medarh.2026.80.68-73","url":null,"abstract":"<p><strong>Background: </strong>The integration of Cone Beam Computed Tomography (CBCT) in the dental field has enhanced the capacity to identify remnants of skeletal and decomposing human parts in forensic medicine. Gender classification plays a crucial role in identification, as it can effectively eliminate a significant percentage of possibilities.</p><p><strong>Objective: </strong>The current study aimed to assess the utility of maxillary sinus volumes and dimensions, including ostium positioning, in determining gender among a sample of the Lebanese population.</p><p><strong>Methods: </strong>Data from 140 maxillary sinuses were investigated by means of CBCT images from 70 patients. Three radiologists measured the volume, width, depth, height, and ostium-floor distance of the sinuses using computer software tools. The maxillary sinus volumes with a mean patient age of 58 years were calculated using a mathematically validated formula and compared across left and right sides, genders, dentate and edentulous patients, and various age groups.</p><p><strong>Results: </strong>Statistical analysis of maxillary sinus measurements revealed that both the volume and dimensions of the sinuses were greater in males than in females. Additionally, these measurements tended to decrease with advancing age. Notably, significant differences were observed among patients with natural teeth and those who are edentulous, particularly in the height of the sinuses, which was significantly greater in edentulous individuals, resulting in larger maxillary sinus volumes for both genders. The ostium-floor distance measurements demonstrated high bilateral symmetry, with mean values of 3.54 cm (SD 0.57) for the right side and 3.58 cm (SD 0.52) for the left side, suggesting consistent ostium positioning across the population sample.</p><p><strong>Conclusion: </strong>This retrospective study, which assessed the volume, dimensions, and ostium positioning of the maxillary sinus using CBCT images from 70 patients, revealed that males possess larger maxillary sinuses than females, with a trend towards reduction in size with increasing age. The bilateral symmetry in ostium-floor distance provides additional anatomical reference data for clinical and forensic applications. Thus, the determination of age and gender in forensic medicine utilizing CBCT may prove to be both useful and advantageous.</p>","PeriodicalId":94135,"journal":{"name":"Medical archives (Sarajevo, Bosnia and Herzegovina)","volume":"80 1","pages":"68-73"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13049467/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147625389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing Medical Education With 3D Skin Models: a Quasi-Experimental Study of Their Impact Among Medical Students in Alkhobar, Saudi Arabia.","authors":"Hamad Almutlaq, Sarah Albreiki, Nasser M Alzoabi, Khalid M Al-Husain, Dana H Alkhudair, Maryam M Alfaraj","doi":"10.5455/medarh.2026.80.46-51","DOIUrl":"10.5455/medarh.2026.80.46-51","url":null,"abstract":"<p><strong>Background: </strong>Three dimensional (3D) models have shown promise in enhancing medical education across various specialties. However, the application of 3D-silicone skin models in dermatology education remains underexplored, particularly in Saudi Arabia. To our knowledge, this is the first study in Saudi Arabia to evaluate 3D skin models as a teaching tool for undergraduate medical students.</p><p><strong>Objective: </strong>To evaluate the effectiveness of 3D-silicone skin models as a teaching tool in dermatology education for undergraduate medical students.</p><p><strong>Methods: </strong>This quasi-experimental study was conducted at Imam Abdulrahman Bin Faisal University (2024-2025) and included 97 fourth year medical students, of whom 75 completed both pre- and post-intervention surveys. Following a dermatology lecture, students completed diagnostic assessments using two-dimensional (2D) photographs and subsequently 3D silicone models (Simu-Skin™, Mater Transformation). Outcomes included diagnostic accuracy, satisfaction, confidence, and perceived realism. Statistical analyses were performed using IBM SPSS v26.0 employing McNemar's test, t-tests, Chi-square tests, Cohen's kappa, and effect size calculations.</p><p><strong>Results: </strong>A total of 97 participants (53 females and 44 males) were included, with the majority reporting previous exposure to dermatology. No significant differences were found based on gender or prior dermatology experience (p > 0.05). Diagnostic accuracy using 2D models was initially high, with over 90% correct lesion and category identifications. Although diagnostic accuracy improved after exposure to the 3D models, the change was not statistically significant (p > 0.05). The 3D models were highly rated for satisfaction (mean 4.60-4.88/5), confidence in clinical application (mean 4.68-4.81), and perceived realism.</p><p><strong>Conclusion: </strong>3D-silicone based models produced modest but consistent improvements in diagnostic accuracy and were highly rated for satisfaction and realism. These findings support the integration of tactile simulation into dermatology education and underscore the need for further validation through larger, more diverse cohorts.</p>","PeriodicalId":94135,"journal":{"name":"Medical archives (Sarajevo, Bosnia and Herzegovina)","volume":"80 1","pages":"46-51"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13049470/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147625414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MEESSI-AHF Score for Predicting In-Hospital Mortality in Vietnamese Acute Heart Failure.","authors":"Tran Nguyen Phuong Hai, Nguyen Minh Kha, Bui Huu Dang Khoa, Hoang Van Sy","doi":"10.5455/medarh.2026.80.27-32","DOIUrl":"10.5455/medarh.2026.80.27-32","url":null,"abstract":"<p><strong>Background: </strong>The MEESSI-AHF score is widely recommended for 30-day risk stratification in acute heart failure (AHF), but its ability to predict in-hospital mortality - an endpoint with immediate implications for triage and resource allocation - has not been evaluated in Vietnam.</p><p><strong>Objective: </strong>This study externally validated MEESSI-AHF for in-hospital mortality in Vietnamese patients hospitalized with AHF, assessing both discrimination and calibration.</p><p><strong>Methods: </strong>A prospective cohort of adults hospitalized with AHF (Sep 2024 - Mar 2025; n = 241) was analyzed. The endpoint was in-hospital mortality; performance was assessed by AUC and calibration (CITL, slope, Brier, HL g=6, plots), with minimal recalibration (intercept/slope) if needed.</p><p><strong>Results: </strong>In-hospital mortality was 10.8% (26/241). MEESSI-AHF scores were higher in non-survivors than survivors (median 0.49 vs - 2.17; p<0.001) and showed excellent discrimination (AUC 0.886, 95% CI 0.832 - 0.940). Observed mortality increased stepwise across six pre-specified strata (p for trend < 0.001). Overall calibration suggested over-prediction (CITL -1.201, 95% CI -1.665 to -0.737; slope 1.118, 95% CI 0.734 - 1.502), with Brier score 0.092 (Brier skill 0.042) and poor HL fit (g=6: χ²=28.44, p < 0.001), mainly in the highest-risk stratum. Relative to low-intermediate risk, mortality was higher in high-risk (OR 17.55, 95% CI 1.89 - 162.51) and very-high-risk groups (OR 57.12, 95% CI 7.49 - 435.83).</p><p><strong>Conclusion: </strong>In Vietnamese patients hospitalized with AHF, MEESSI-AHF shows excellent discrimination for in-hospital mortality but systematically overpredicts risk; minimal recalibration corrects this and supports its use for bedside triage with local adjustment.</p>","PeriodicalId":94135,"journal":{"name":"Medical archives (Sarajevo, Bosnia and Herzegovina)","volume":"80 1","pages":"27-32"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13049477/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147625410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}