Objective: To evaluate the adherence of large language model (LLM)-based healthcare research to the Minimum Reporting Items for Clear Evaluation of Accuracy Reports of Large Language Models in Healthcare (MI-CLEAR-LLM) checklist, a framework designed to enhance the transparency and reproducibility of studies on the accuracy of LLMs for medical applications. Materials and Methods: A systematic PubMed search was conducted to identify articles on LLM performance published in high-ranking clinical medicine journals (the top 10% in each of the 59 specialties according to the 2023 Journal Impact Factor) from November 30, 2022, through June 25, 2024. Data on the six MI-CLEAR-LLM checklist items: 1) identification and specification of the LLM used, 2) stochasticity handling, 3) prompt wording and syntax, 4) prompt structuring, 5) prompt testing and optimization, and 6) independence of the test data—were independently extracted by two reviewers, and adherence was calculated for each item. Results: Of 159 studies, 100% (159/159) reported the name of the LLM, 96.9% (154/159) reported the version, and 91.8% (146/159) reported the manufacturer. However, only 54.1% (86/159) reported the training data cutoff date, 6.3% (10/159) documented access to web-based information, and 50.9% (81/159) provided the date of the query attempts. Clear documentation regarding stochasticity management was provided in 15.1% (24/159) of the studies. Regarding prompt details, 49.1% (78/159) provided exact prompt wording and syntax but only 34.0% (54/159) documented prompt-structuring practices. While 46.5% (74/159) of the studies detailed prompt testing, only 15.7% (25/159) explained the rationale for specific word choices. Test data independence was reported for only 13.2% (21/159) of the studies, and 56.6% (43/76) provided URLs for internet-sourced test data. Conclusion Although basic LLM identification details were relatively well reported, other key aspects, including stochasticity, prompts, and test data, were frequently underreported. Enhancing adherence to the MI-CLEAR-LLM checklist will allow LLM research to achieve greater transparency and will foster more credible and reliable future studies.

Background: Acute eosinophilic pneumonia (AEP) is a rare and severe lung condition characterized by a rapid accumulation of eosinophils in the alveoli, leading to respiratory distress. This study analyzed the clinical characteristics of affected patients, aiming to shed light on the relationship between cigarette smoking and AEP. Methods: This retrospective study analyzed 17 cases of AEP, focusing on patients' smoking habits, clinical symptoms, diagnostic findings, and treatment outcomes. Data were collected from medical records, imaging studies, and bronchoalveolar lavage (BAL) findings. Results: The study cohort consisted primarily of male military personnel (94.1%), with a mean age of 20.8 years. Symptoms generally appeared approximately 2.82 days prior to hospitalization, with a mean body temperature at admission of 37.6 °C. The mean initial peripheral blood white blood cell count was 15.3×103/μL, with eosinophil percentages starting at 0.2%, peaking at a mean of 16.1%, and reaching as high as 32.4%. BAL fluid analysis showed a mean eosinophil level of 46.6%±15.1% (range, 17%–67%). In most cases, radiological examinations revealed bilateral ground-glass opacities, interlobular septal thickening, various degrees of airspace consolidation, and bilateral pleural effusions. Steroid treatment was administered to 70.5% of patients, lasting a mean of 8.3 days and resulting in significant improvements. Conclusions These cases reinforce the strong link between cigarette smoking and AEP. Additionally, these cases demonstrate the importance of obtaining a detailed smoking history and thorough diagnostic assessments, including BAL, in order to facilitate a more rapid diagnosis and early initiation of corticosteroid treatment.

Background: The significance of risk modification in patients with acute coronary syndrome (ACS) is well recognized; however, the optimal timing for adminstering PCSK9 inhibitors remains unclear. Additionally, the lipid-lowering efficacy of evolocumab and alirocumab has not been fully established. This study evaluated the lipid-lowering effects of these two PCSK9 inhibitors. Methods: Patients diagnosed with ACS, including unstable angina, ST-segment elevation myocardial infarction, and non-ST-segment elevation myocardial infarction, who were treated with a PCSK9 inhibitor (evolocumab or alirocumab) during hospitalization for ACS between 2021 and 2023 were retrospectively analyzed. Baseline low-density lipoprotein cholesterol (LDL-C) levels were assessed, and changes in LDL-C levels during the acute and subacute phases after PCSK9 inhibitor administration were compared between the evolocumab and alirocumab groups. Results: Among 80 patients diagnosed with ACS, 36 received evolocumab, while 44 were treated with alirocumab. The mean baseline LDL-C level was 123 mg/dL in the evolocumab group and 128 mg/dL in the alirocumab group (p=0.456). In the subacute phase, the mean follow-up LDL-C levels were 47.05 mg/dL in the evolocumab group and 49.5 mg/dL in the alirocumab group (p=0.585). The mean percentage reduction in LDL-C levels during the subacute phase was 60.41% in the evolocumab group and 58.51% in the alirocumab group (p=0.431). These differences were not statistically significant. Conclusions No significant differences were observed between evolocumab and alirocumab. LDL-C levels exhibited a similar trend, characterized by a rapid decline in the acute phase, followed by a slight rebound in the subacute phase.

Background: Aerobic exercise training and drug therapy are well-established interventions for the prevention and treatment of hypertension and dyslipidemia. We investigated the synergistic effects of aerobic exercise and olmesartan/rosuvastatin on epicardial fat thickness (EFT) and endothelial function in patients with hypertension and dyslipidemia. Methods: A sample of 75 participants with hypertension and dyslipidemia was evaluated for multifactorial cardiovascular risk at baseline and at 6 months of intervention according to anthropometric and hemodynamic components, lipid profile, glycemia, brachial artery flow-mediated dilation (FMD), and EFT. After 3 months of drug therapy only, participants were allocated to one of three conditions: treadmill (n=22), exergame (n=29), or control (n=24). Results: After 12 weeks of drug therapy only, systolic and diastolic blood pressure (3% and 2%, both p<0.05), total cholesterol (6.3%, p<0.01), low-density lipoprotein cholesterol (4.9%, p<0.05), triglycerides (11.1%, p<0.05), fasting blood glucose (10.2%, p<0.01), and glycosylated hemoglobin (3%, p<0.01) were significantly reduced. After 12 weeks of combined aerobic exercise and drug therapy, both the treadmill and exergame groups showed a significant improvement in FMD (both p<0.001) and reduction in EFT (both p<0.001). Systolic and diastolic blood pressures decreased in the treadmill group only (1.9% and 2.7%, respectively, p<0.05). Conclusions Incorporating aerobic exercise into drug therapy regimens can yield synergistic effects, particularly in improving endothelial function and reducing EFT, providing a comprehensive approach to managing cardiovascular risk in patients with hypertension and dyslipidemia.

Artificial intelligence (AI) is revolutionizing stroke care by enhancing diagnosis, treatment, and outcome prediction. This review examines 505 original studies on AI applications in ischemic stroke, categorized into outcome prediction, stroke risk prediction, diagnosis, etiology prediction, and complication and comorbidity prediction. Outcome prediction, the most explored category, includes studies predicting functional outcomes, mortality, and recurrence, often achieving high accuracy and outperforming traditional methods. Stroke risk prediction models effectively integrate clinical and imaging data, improving assessments of both first-time and recurrent stroke risks. Diagnostic tools, such as automated imaging analysis and lesion segmentation, streamline acute stroke workflows, while AI models for large vessel occlusion detection demonstrate clinical utility. Etiology prediction focuses on identifying causes such as atrial fibrillation or cancer-associated thrombi, using imaging and thrombus analysis. Complication and comorbidity prediction models address stroke-associated pneumonia and acute kidney injury, aiding in risk stratification and resource allocation. While significant advancements have been made, challenges such as limited validation, ethical considerations, and the need for better data collection persist. This review highlights the advancements in AI applications for addressing key challenges in stroke care, demonstrating its potential to enhance precision medicine and improve patient outcomes.

RESULTS: Resveratrol significantly reduced cardiac hypertrophy and remodeling in aging hearts. In addition, resveratrol significantly ameliorated aging-induced mitochondrial dysfunction (e.g., decreased oxygen respiration and increased hydrogen peroxide emission) and mitochondria-dependent apoptotic signaling (the Bax/Bcl-2 ratio, mitochondrial permeability transition pore opening sensitivity, and cleaved caspase-3 protein levels).Resveratrol also significantly attenuated aging-induced apoptosis (determined via cleaved caspase-3 staining and TUNEL-positive myonuclei) in cardiac muscles. CONCLUSION This study demonstrates that resveratrol treatment has a beneficial effect on aging-induced cardiac remodeling by ameliorating mitochondrial dysfunction and inhibiting mitochondria-mediated apoptosis in the heart.

BACKGROUND/OBJECTIVES: Green Citrus junos (yuja) peel extract has higher naringin and hesperidin contents and antioxidant activity than yellow yuja peel extract, but its anti-obesity effects are unclear. This study examined the anti-obesity properties of green yuja peel ethanol extract (GYE) in 3T3-L1 cells and high-fat diet (HFD)-induced obese mice.MATERIALS/METHODS: The effects of GYE on adipocyte differentiation were assessed by measuring Oil red O staining, mRNA and protein expression. The beneficial effects of GYE on HFD-induced obese mice were evaluated using the body weight, body composition, visceral fat size, and biochemical analysis. RESULTS: GYE inhibited adipocyte differentiation and lipid accumulation compared to the control cells, as evidenced by Oil red O staining and the triglyceride level, respectively.GYE down-regulated the adipogenic genes CCAAT/enhancer binding protein α (C/EBPα) and peroxisome proliferator-activated receptor γ (PPARγ), and lipogenic gene diacylglycerol O-acyltransferase 2 (DGAT2). GYE at 100 μg/mL downregulated the phosphorylation levels of phosphoinositide 3-kinase (PI3K) and protein kinase B (Akt), and their downstream targets PPARγ and sterol regulatory element-binding protein-1 (SREBP-1c) compared to the control group. In obese mice, GYE (100 mg/kg/day) reduced the body weight, body weight gain, and serum lipid level compared to the control group. Analysis using dual-energy X-ray absorptiometry showed that GYE decreased the fat percentage, fat in tissue, and abdominal circumference, while it increased the lean percentage compared to control group.Furthermore, GYE significantly reduced the visceral fat weight and size compared to the control group. CONCLUSION GYE suppressed adipocyte differentiation by inhibiting the PI3K-Akt pathway in vitro and reduced the body fat mass and visceral adiposity in HFD-induced obese mice.These findings suggest that GYE is a viable natural option for combating obesity.

Objective: In this study, we aimed to investigate how fetal head and abdominal circumferences are related to the incidence of neonatal complications in mothers with gestational diabetes mellitus (GDM) and pre-gestational diabetes mellitus (PGDM) compared to normal pregnancies. Methods: We retrospectively analyzed data of expectant mothers with GDM, PGDM, and normal pregnancies who delivered singleton full-term infants (≥37 weeks) at a tertiary center from January 2013 to December 2022. Ultrasonography-measured fetal weight, fetal head circumference, fetal abdominal circumference, difference between head and abdominal circumference, and head-to-abdominal circumference ratio were assessed. Neonatal outcomes were evaluated based on the rates of admission to the neonatal intensive care unit, intubation, and hypoglycemia. Statistical analyses, including univariate and multivariate analyses, were performed using the SPSS software (IBM Corp., Armonk, NY, USA). Results: Among the 473 participants, 175 (37.0%) were mothers with diabetes (DM). A head-to-abdominal circumference ratio <0.95 and a difference of ≥2.5 cm were significantly associated with neonatal hypoglycemia in all mothers with DM, with statistical significance noted only in the PGDM group. No significant association was observed in normal pregnancies. Conclusion Our findings indicate that a head-to-abdominal circumference ratio <0.95 and a ≥2.5 cm difference in circumferences are associated with neonatal hypoglycemia in mothers with DM.

Objectives: This study aimed to explore factors influencing satisfaction with medical services among medically underserved populations at the free medical clinic, providing data to improve free medical services for these populations. Methods: We employed a descriptive correlational study design involving 112 individuals (aged 19 years and older) from medically underserved populations who visited the clinic. Data were collected through face-to-face surveys from September to October 2023, and statistical analyses (t-tests, analysis of variance, Pearson correlation, and hierarchical multiple regression) were used to identify key predictors of satisfaction. Results: Perceived support from healthcare providers emerged as the strongest predictor ofsatisfaction with medical services, demonstrating a significant positive association. While socialsupport was positively correlated with perceived support from healthcare providers, it did not independently predict satisfaction. Conclusion These findings underscore the importance of healthcare provider and social supportin increasing satisfaction with medical services among medically underserved populations.Developing tailored healthcare programs and specialized healthcare provider training are essential strategies to improve healthcare access and outcomes for these vulnerable groups.