Search Results (776)

Background and Objectives: Pneumonia is a leading cause of intensive care unit (ICU) admission and is associated with high mortality, particularly among patients with multiple comorbidities. Accurate early risk stratification is essential for guiding clinical decision-making in critically ill patients. However, the prognostic benefit of combining clinical scoring systems with nutritional and endothelial stress indices in ICU patients with pneumonia remains unclear. Materials and Methods: This retrospective, single-center cohort study included adult patients admitted to the ICU with a diagnosis of pneumonia between 1 January 2023 and 1 July 2025. Demographic characteristics, comorbidities, clinical variables, laboratory parameters, and prognostic scores were obtained from electronic medical records. The National Early Warning Score (NEWS), Prognostic Nutritional Index (PNI), and Endothelial Activation and Stress Index (EASIX) were calculated at ICU admission. The primary outcome was in-hospital mortality. Univariate and multivariate logistic regression analyses were performed to examine variables associated with in-hospital mortality. The discriminative performance of individual and combined prognostic models was evaluated using receiver operating characteristic (ROC) curve analysis. Results: A total of 221 patients were included; 79 (35.7%) survived and 142 (64.3%) died during hospitalization. Non-survivors had significantly higher NEWS and EASIX values and lower PNI values compared with survivors (all p < 0.05). In multivariate analysis, endotracheal intubation (OR: 12.46; p < 0.001), inotropic use (OR: 5.14; p = 0.001), and serum lactate levels (OR: 1.75; p = 0.003) were identified as being independently associated with in-hospital mortality. Models combining NEWS with PNI or EASIX demonstrated improved discriminatory performance. Conclusions: In critically ill patients with pneumonia, integrating NEWS with nutritional and endothelial stress indices provides numerically improved discrimination compared with NEWS alone, although the incremental gain did not reach statistical significance. Full article

Background: Persistent liver pathology despite a sustained virologic response (SVR) to hepatitis C virus (HCV) therapy is a major clinical concern. This is particularly relevant for people with HIV (PWH) with HCV coinfection, a population prone to accelerated liver disease progression. This study aimed to characterize the plasma miRNA profile in PWH with cirrhosis one year after successful completion of HCV therapy, and to explore their relationship with metabolite alterations. Methods: This cross-sectional study enrolled 47 PWH who achieved HCV clearance with antiviral therapy. Using plasma samples collected approximately one year after completion of HCV therapy, participants were stratified into two groups based on liver stiffness measurement (LSM): compensated cirrhosis (n = 32, LSM ≥ 12.5 kPa) and non-cirrhosis (n = 15, LSM < 12.5 kPa). Plasma miRNAs and metabolites were determined using small RNA sequencing and untargeted capillary electrophoresis-mass spectrometry (CE-MS), respectively. Significantly differentially expressed (SDE) miRNAs were identified using generalized linear models (GLM) with a negative binomial distribution, and their correlation with metabolite levels was quantified using Spearman’s correlation. Results: In the cirrhosis group (n = 32), we identified a distinct signature of 15 SDE miRNAs (9 upregulated, 6 downregulated) compared to the non-cirrhotic group (n = 15), showing hsa-miR-10401-3p, hsa-miR-548ak, hsa-miR-141-3p, and hsa-miR-3940-3p the largest expression changes. miRNA-gene interaction and pathway enrichment analysis suggested that these 15 SDE miRNAs potentially regulate multiple genes involved in immune response and amino acid metabolism. In addition, correlation analyses with our metabolomic data revealed significant associations between specific SDE miRNAs and amino acids and their derivatives. Specifically, the expression of upregulated miRNAs (e.g., hsa-miR-10401-3p and hsa-miR-16-5p) was positively correlated with plasma levels of L-methionine and its derivatives, while downregulated miRNAs (e.g., hsa-miR-625-5p) were inversely correlated with L-tryptophan. Conclusions: In cirrhotic PWH with history of HCV coinfection, a distinct plasma miRNA signature linked to dysregulated amino acid metabolism is found one year after completion of HCV therapy. This underscores that the HCV cure does not equate to complete hepatic recovery, highlighting the critical need for long-term monitoring in this high-risk population. Full article

Background and Objectives: Subclinical paroxysmal atrial fibrillation (AF) is often undetected by conventional screening strategies, until complications emerge. Artificial intelligence (AI) applied to sinus rhythm electrocardiograms has emerged as a promising tool to identify individuals with occult AF and to predict the risk of future incident AF. This scoping review synthesizes evidence from original studies evaluating AI models trained on sinus rhythm ECGs for AF detection or AF prediction. Materials and Methods: A comprehensive search of MEDLINE, Embase, Web of Science, Scopus, and IEEE Xplore was conducted to identify peer-reviewed studies from inception to November 2025. Eligible studies included original investigations in which the model input was a sinus rhythm ECG and the outcome was either paroxysmal AF or new-onset AF. Extracted variables included cohort characteristics, ECG acquisition parameters, AI architecture, model predictive performance, AF prediction horizon, clinical outcomes, and validation strategy. Risk of bias was assessed using PROBAST. Results: Nineteen studies met the inclusion criteria. Retrospective datasets ranging from several thousand to over one million ECGs and convolutional or deep neural network AI architectures were used in most studies. AI-ECG models demonstrated high diagnostic accuracy for detecting subclinical AF (ten studies; AUROC 0.75–0.90) and for predicting long-term new-onset AF (six studies; AUROC 0.69–0.85) from a single sinus rhythm ECG. Robust external validation was reported in eleven studies. Combining AI-ECG models with clinical risk factors improved AF predictive performance in several reports. Key limitations across studies included retrospective design, patient selection, limited calibration reporting, and sparse prospective impact data. Conclusions: AI-based analysis of sinus rhythm ECGs can detect occult AF and stratify future AF risk with moderate-to-high accuracy across multiple populations and healthcare systems. However, rigorous prospective trials, evaluating clinical benefit, cost-effectiveness, calibration across demographic groups, and real-world implementation, are required before broad adoption in clinical practice. Full article

Background/Objectives: Type 2 diabetes (T2D) is a chronic metabolic disorder closely linked to cardiovascular disease and obesity and notably influenced by lifestyle and dietary patterns. The Mediterranean diet has well-established benefits across multiple cardiometabolic risk factors, including those relevant to diabetes. This study aimed to investigate the degree to which adults with T2D adhere to a Mediterranean dietary pattern and to examine how such adherence relates to glycemic and lipidemic regulation. Methods: This cross-sectional study included 100 adults with T2D (54 men and 46 women). Adherence to the Mediterranean diet was assessed using the Mediterranean Diet Score (MDS). Demographic, anthropometric, lifestyle, and clinical data were collected, and glycemic and lipid parameters were analyzed. Associations between Mediterranean diet adherence and metabolic outcomes were examined using correlation analyses and multivariable regression models adjusted for relevant confounders. Results: Most participants showed low adherence to the Mediterranean diet. A significant inverse association was observed between Mediterranean diet adherence and hemoglobin A1c (HbA1c) levels, with individuals scoring ≤35 on the MDS demonstrating higher HbA1c levels. Similar trends were observed in the lowest tertile of adherence. Notably, each one-point increase in MDS predicted a 0.13% reduction in HbA1c. In multivariable regression analyses, Mediterranean diet adherence remained the strongest predictor of glycemic control, independent of age, body mass index (BMI), sex, smoking status, physical activity and the number of antidiabetic treatments. Higher adherence was also significantly associated with lower low-density lipoprotein cholesterol (LDL-C) and triglyceride (TG) levels, as well as higher high-density lipoprotein cholesterol (HDL) concentrations. Conclusions: Greater adherence to the Mediterranean diet is independently associated with improved glycemic regulation and a more favorable lipid profile in adults with T2D. These findings support the Mediterranean diet as a valuable non-pharmacologic strategy for optimizing metabolic outcomes in people with T2D. Full article

Background: A sedentary lifestyle contributes to chronic disease risk in adults and may predict unfavourable body composition in adolescents. Declining physical activity and rising sedentary behaviour are linked to increasing global obesity rates. Given the scarcity of longitudinal studies examining how participation in organized sports and screen device use relate to body composition in early adolescence, this study aims to address this gap by analyzing temporal trends in both sexes. Methods: A sample of 158 Italian students, 38% of whom were female, was followed longitudinally from ages 11 to 13. Annual anthropometric assessments were conducted, and self-reported data on screen time and organised sports participation were collected. Fat mass (FM), fat-free mass (FFM), fat mass index (FMI), fat-free mass index (FFMI), body mass index (BMI), and waist-to-height ratio (WHtR) were subsequently calculated, along with annual increments. Repeated-measures ANOVA assessed age and sex effects, while multiple regression models evaluated associations between behavioural variables or sex and body composition indices. Results: Significant differences in %F, FM, FFM and its increment, WHtR and its increment, FMI, and FFMI (all p < 0.01) were observed by age and sex interaction. At age 13, weekly sports participation was negatively associated with annual increments in %F (β = −0.204, p = 0.04) and FMI (β = −0.227, p = 0.03). Female sex was associated with greater increments in %F (β = 0.188, p < 0.05) and WHtR (β = 0.323, p < 0.01), and with smaller increments in FFM (β = −0.421, p < 0.01). No significant associations were found for screen time (p > 0.05). Conclusions: Sporting during early adolescence seems to have positive effects on body composition changes, while sex-specific patterns warrant further attention. A deeper understanding of how early adolescent lifestyle factors, such as physical activity and sedentary behaviour, shape body composition is essential for promoting long-term health. Full article

Background: Type 2 diabetes (T2D) has been linked to impairments in skeletal muscle performance, encompassing reductions in both muscle strength and muscle quality. While malnutrition is a known modifiable factor contributing to muscle quality deterioration, its specific relationship with the Geriatric Nutritional Risk Index (GNRI) in T2D remains underexplored. Using data from 743 participants in the KAMOGAWA-A cohort, this cross-sectional study evaluated the association between muscle quality and GNRI in individuals with type 2 diabetes. Methods: Muscle quality was defined as handgrip strength divided by arm lean mass. GNRI was calculated using serum albumin and body mass index. Multiple linear regression models were used to assess associations between GNRI and muscle quality. To account for BMI-related dependency in muscle quality measurements, we derived BMI-adjusted GNRI residuals and performed the same regression analysis to evaluate the stability of the observed relationship beyond BMI-induced confounding. Results: In the overall population, GNRI was inversely associated with muscle quality (β = −0.17, p < 0.001). Conversely, residual GNRI demonstrated a significant positive association with muscle quality (β = 0.13, p < 0.001), especially among men, individuals under 65 years of age, and across all BMI categories. Stratified analyses suggested that the strength and direction of associations varied by age, sex, and glycemic control status. Conclusions: The GNRI showed an inverse correlation with muscle quality, whereas residual GNRI showed a consistent positive relationship. These findings suggest that improving nutritional status may support muscle function in T2D, but BMI confounds the interpretation of GNRI in this context. Full article

Background/Objectives: Osteoporosis is a major global health concern, and early risk assessment plays a crucial role in fracture prevention. Although demographic, clinical, and lifestyle factors are commonly incorporated into screening tools, their relative importance within data-driven prediction frameworks can vary substantially across datasets. Rather than aiming to identify novel predictors, this study evaluates the stability and behavior of established osteoporosis risk factors using statistical inference and machine learning-based feature selection methods across heterogeneous data sources. We further examine whether simplified and near-minimal models can achieve predictive performances comparable to that of full-feature configurations. Methods: An open-access Kaggle dataset (n = 1958) and a retrospective clinical dataset from the University of Phayao Hospital (n = 176) were analyzed. Feature relevance was assessed using logistic regression, likelihood ratio testing, MRMR, ReliefF, and unified importance scoring. Multiple predictor configurations, ranging from full-feature to minimal and near-minimal models, were evaluated using decision tree, support vector machine, k-nearest neighbor, naïve Bayes, and efficient linear classifiers. External validation was performed using hospital-based records. Results: Across all analyses, age consistently emerged as the dominant predictor, followed by corticosteroid use, while other variables showed limited incremental predictive contributions. Simplified models based on age alone or age combined with medication-related variables achieved performances comparable to full-feature models (accuracy ≈91% and AUC ≈ 0.95). In addition, near-minimal models incorporating gender alongside age and medications demonstrated a favorable balance between discrimination and computational efficiency under external validation. Although overall performance declined under distributional shift, naïve Bayes and efficient linear classifiers showed the most stable external behavior (AUC = 0.728–0.787). Conclusions: These findings indicate that stability-driven feature selection primarily reproduces well-established epidemiological risk patterns rather than identifying novel predictors. Minimal and near-minimal models—including those incorporating gender—retain acceptable performances under external validation and are methodologically efficient. Given the limited size and single-center nature of the external cohort, the results should be interpreted as preliminary methodological evidence rather than definitive support for clinical screening deployment. Further multi-center studies are required to assess generalizability and clinical relevance. Full article

Background: Non-syndromic cleft lip/palate (NCL/P) is a prevalent congenital anomaly. Despite an unclear epidemiological link between orofacial clefts and dental caries, genetic studies suggest that polymorphisms in taste receptor genes may influence caries risk. Objectives: This study had two primary objectives: (1) to compare SNPs in NCL/P-associated genes (IRF6, FOXE1) between Kuwaiti NCL/P cases and controls, and (2) to explore whether variants in caries-associated (KLK4, DSPP) and taste receptor (TAS1R2, TAS2R38) genes are associated with dental caries susceptibility in individuals with NCL/P, independent of overall caries prevalence. Methods: A case–control design was employed, with 25 NCL/P cases and 25 unaffected controls recruited from a Dental Craniofacial Clinic in Kuwait. Genomic DNA was extracted from buccal swabs, and SNP genotyping was performed using real-time PCR for genes related to NCL/P, dental caries, and taste perception. Caries status was assessed using the dmft/DMFT scoring system. The genotyped genes included NCL/P-related (IRF6, FOXE1), caries-related (KLK4, DSPP), and taste receptor genes (TAS1R2, TAS2R38). Results: At nominal significance, KLK4, DSPP, and TAS1R2 showed associations with NCL/P status, while IRF6 and FOXE1 did not. After applying Benjamini–Hochberg FDR correction across 10 SNPs, no allele- or genotype-level association remained significant (q < 0.05). The strongest signal was KLK4 rs2235091 (allele-level p = 0.016; q = 0.159). An exploratory age- and sex-adjusted logistic model for KLK4 suggested a possible effect (aOR 0.40; 95% CI 0.18–0.87; p = 0.021). Within-group analyses of caries burden revealed no associations that survived FDR control (lowest q = 0.056 for FOXE1 in controls). Conclusions: After controlling for multiple testing, no SNP showed a statistically significant association with NCL/P or caries burden. Nominal signals for KLK4, DSPP, and TAS1R2 did not survive FDR correction; an exploratory adjusted model suggested a possible KLK4 effect, but this requires cautious interpretation. The small sample size is a key limitation, and the findings highlight the need for larger, well-powered studies to clarify genetic contributions to NCL/P and caries risk. Full article

Background: Left ventricular systolic dysfunction (LVSD) is a major determinant of prognosis in patients with ischemic heart disease. Electrocardiography (ECG) is widely available, inexpensive, and may aid in identifying patients at risk. We hypothesized that a composite score derived from multiple established ECG markers could improve the detection of LVSD in patients with stable angina. Methods: In this single-center, cross-sectional study, 177 patients undergoing elective coronary angiography for stable angina were included. Patients were classified as LVSD-negative (n = 123) or LVSD-positive (n = 54) based on echocardiographic ejection fraction. ECG parameters, including fragmented QRS, pathologic Q waves, R-wave peak time, QRS duration, and frontal QRS–T angle, were assessed. Independent predictors of LVSD were identified using multivariate logistic regression. A composite ECG score was constructed by assigning one point to each abnormal parameter. Model robustness was evaluated using bootstrap resampling (1000 iterations) and 10-fold cross-validation. Results: Multivariable analysis identified prior stent implantation, fragmented QRS, pathological Q waves, R-wave peak time, frontal QRS–T angle (log-transformed), and QRS duration as independent predictors of LVSD. ROC analysis demonstrated good discriminatory performance for R-wave peak time (AUC 0.804), QRS duration (AUC 0.649), and frontal QRS–T angle (AUC 0.825) measurements. The composite ECG score showed a stepwise association with LVSD: a score of ≥2 yielded high sensitivity (88%) and negative predictive value (97%), whereas a score of ≥3 provided high specificity (100%) and positive predictive value (100%). Bootstrap resampling and cross-validation confirmed model stability and strong discriminatory performance (mean AUC, 0.964; accuracy, 0.91). Conclusions: A simple composite ECG score integrating multiple established ECG markers is associated with the robust detection of LVSD in patients with stable angina. Although not a substitute for echocardiography, this score may support early risk stratification and help identify patients who warrant further imaging evaluations. External validation in larger and more diverse populations is required before routine clinical implementation of this model. Full article

Background/Objectives: Breast cancer is the most common malignancy among women, and early detection is critical for improving outcomes. The Breast Imaging Reporting and Data System (BI-RADS) standardizes reporting, but the BI-RADS 4 category presents a major challenge, with malignancy risk ranging from 2% to 95%. Consequently, most women in this category undergo biopsies that ultimately prove unnecessary. This study evaluated whether exhaled breath analysis could distinguish malignant from benign findings in BI-RADS 4 patients. Methods: Participants referred to the McGill University Health Centre Breast Center with BI-RADS 3–5 findings provided multiple breath specimens. Breathprints were captured using an electronic nose (eNose) powered breathalyzer, and diagnoses were confirmed by imaging and pathology. An autoencoder-based model fused the breath data with BI-RADS scores to predict malignancy. Model performance was assessed using repeated cross-validation with ensemble voting, prioritizing sensitivity to minimize false negatives. Results: The breath specimens of eighty-five participants, including sixty-eight patients with biopsy-confirmed benign lesions and seventeen patients with biopsy-confirmed breast cancer within the BI-RADS 4 cohort were analyzed. The model achieved a mean sensitivity of 88%, specificity of 75%, and a negative predictive value (NPV) of 97%. Results were consistent across BI-RADS 4 subcategories, with particularly strong sensitivity in higher-risk groups. Conclusions: This proof-of-concept study shows that exhaled breath analysis can reliably differentiate malignant from benign findings in BI-RADS 4 patients. With its high negative predictive value, this approach may serve as a non-invasive rule-out tool to reduce unnecessary biopsies, lessen patient burden, and improve diagnostic decision-making. Larger, multi-center studies are warranted. Full article

Background: Site-specific long-term outcomes, including neurofibromatosis type 1 (NF1), Ki-67 prognostic value, and very late recurrences of small bowel gastrointestinal stromal tumors (GISTs), remain inadequately defined. Methods: This retrospective cohort study investigated the clinical characteristics, diagnostic challenges, and long-term outcomes of patients with small bowel GISTs. This retrospective, single-center study (2008–2024) analyzed 27 consecutive patients (average age: 62.2 years) with jejunal/ileal GISTs. Clinicopathologic features, diagnostic yield of balloon-assisted enteroscopy (BAE), treatments, and outcomes were evaluated during a 10.2-year median follow-up period. Recurrence-free survival (RFS) and overall survival (OS) were estimated by Kaplan–Meier with log-rank testing. Ki-67 was assessed using MIB-1; a prespecified 5% cut-off was chosen based on prior evidence. Results: Tumor (mean size, 62.4 mm) sites included the jejunum (74.1%) and ileum (25.9%). NF1 was present in 3/27 (11.1%) patients, all with multiple jejunal tumors. Among the 14 patients who underwent BAE, biopsy was attempted in six and yielded a histological diagnosis in one (16.7%). Six patients had recurrence; two died from disease >10 years postoperatively. Five-year OS and RFS were 91.3% and 68.7%, respectively. Adverse RFS was associated with ileal location (p = 0.03), size ≥ 10 cm (p < 0.001), mitoses > 5/50 high-power fields (p = 0.002), and Ki-67 ≥ 5% (p < 0.001). One patient labeled low risk by conventional models had recurrence with Ki-67 = 10%. Another classified as low risk by conventional models experienced recurrence >10 years after surgery, with a Ki-67 index of 10%. Conclusions: Extended, risk-adapted surveillance may be reasonable for small-bowel GISTs, and it may be beneficial to incorporate Ki-67 (≥5%) into site-based risk stratification. These observations remain hypothesis-generating and require validation in larger, multicenter cohorts and prospective studies. Full article

Background: As a newly recognized type of cell death implicated in cancer, ferroptosis plays multiple roles in tumor biology. Here, we sought to construct a prognostic framework for EC on the basis of ferroptosis-related long non-coding RNAs (FerlncRNAs), microRNAs (FermiRNAs), and mRNAs (FRGs) for endometrial cancer (EC). Methods: Transcriptomic profiles of tumors and matched clinical data for 544 EC patients were retrieved from TCGA-UCEC. A prognostic framework was generated through Cox regression, integrating ferroptosis-linked lncRNAs, miRNAs, and mRNAs. EC cases were stratified into groups with high or low predicted risk based on ferroptosis-related gene expression. The model’s prognostic utility was examined through Kaplan–Meier (K–M) analysis and receiver operating characteristic curves. Results: A prognostic model based on 16 RNAs, including 10 FerlncRNAs, 2 FermiRNAs, and 4 FRGs, was developed. Analysis using K–M plots showed that high-risk patients experienced shorter overall survival than their low-risk counterparts (p < 0.001). The model’s area under curve (AUC) values were 0.731, 0.749, and 0.768 at 1-, 3-, and 5-year time points, surpassing those of standard clinical parameters. Furthermore, in an external validation cohort, these signature RNAs were associated with EC prognosis. Conclusions: The novel ferroptosis-related lncRNA–miRNA–mRNA prognostic model provides a basis to assess clinical prognosis in EC patients. Full article

Background: Irisin, an exercise-induced myokine, has emerged as a potent neuroprotective factor, though a systematic synthesis of its role across neurological disorders is lacking. This review systematically evaluates clinical and preclinical evidence on irisin’s association with neurological diseases and its underlying mechanisms. Methods: Following PRISMA 2020 guidelines, a systematic search of PubMed/MEDLINE, Scopus, Web of Science, Embase, and Cochrane Library was conducted. The review protocol was prospectively registered in PROSPERO. Twenty-one studies were included, comprising predominantly preclinical evidence (n = 14), alongside clinical observational studies (n = 6), and a single randomized controlled trial (RCT) investigating irisin in cerebrovascular diseases, Parkinson’s disease (PD), Alzheimer’s disease (AD), and other neurological conditions. Eligible studies were original English-language research on irisin or FNDC5 and their neuroprotective effects, excluding reviews and studies without direct neuronal outcomes. Risk of bias was independently assessed using SYRCLE, the Newcastle–Ottawa Scale, and RoB 2, where disagreements between reviewers were resolved through discussion and consensus. Results were synthesized narratively, integrating mechanistic, pre-clinical, and clinical evidence to highlight consistent neuroprotective patterns of irisin across disease categories. Results: Clinical studies consistently demonstrated that reduced circulating irisin levels predict poorer outcomes. Lower serum irisin was associated with worse functional recovery and post-stroke depression after ischemic stroke, while decreased plasma irisin in PD correlated with greater motor severity, higher α-synuclein, and reduced dopamine uptake. In AD, cerebrospinal fluid irisin levels were significantly correlated with global cognitive efficiency and specific domain performance, and correlation analyses within studies suggested a closer association with amyloid-β pathology than with markers of general neurodegeneration. However, diagnostic accuracy metrics (e.g., AUC, sensitivity, specificity) for irisin as a standalone biomarker are not yet established. Preclinical findings revealed that irisin exerts neuroprotection through multiple mechanisms: modulating microglial polarization from pro-inflammatory M1 to anti-inflammatory M2 phenotype, suppressing NLRP3 inflammasome activation, enhancing autophagy, activating integrin αVβ5/AMPK/SIRT1 signaling, improving mitochondrial function, and reducing neuronal apoptosis. Irisin administration improved outcomes across models of stroke, PD, AD, postoperative cognitive dysfunction, and epilepsy. Conclusions: Irisin represents a critical mediator linking exercise to brain health, with consistent neuroprotective effects across diverse neurological conditions. Its dual ability to combat neuroinflammation and directly protect neurons, demonstrated in preclinical models, positions it as a promising therapeutic candidate for future investigation. Future research must prioritize the resolution of fundamental methodological challenges in irisin measurement, alongside investigating pharmacokinetics and sex-specific effects, to advance irisin toward rigorous clinical evaluation. Full article

Background and Objectives: Diffusion models, as a recent advancement in generative modeling, have become central to high-resolution image synthesis and reconstruction. Their rapid progress has notably shaped computer vision and health informatics, particularly by enhancing medical imaging and diagnostic workflows. However, despite these developments, researchers continue to face challenges due to the absence of a structured and comprehensive discussion on the use of diffusion models within clinical imaging. Methods: This systematic review investigates the application of diffusion models in medical imaging for diagnostic purposes. It provides an integrated overview of their underlying principles, major application areas, and existing research limitations. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines and included peer-reviewed studies published between 2013 and 2024. Studies were eligible if they employed diffusion models for diagnostic tasks in medical imaging; non-medical studies and those not involving diffusion-based methods were excluded. Searches were conducted across major scientific databases prior to the review. Risk of bias was assessed based on methodological rigor and reporting quality. Given the heterogeneity of study designs, a narrative synthesis approach was used. Results: A total of 68 studies met the inclusion criteria, spanning multiple imaging modalities and falling into eight major application categories: anomaly detection, classification, denoising, generation, reconstruction, segmentation, super-resolution, and image-to-image translation. Explainable AI components were present in 22.06% of the studies, clinician engagement in 57.35%, and real-time implementation in 10.30%. Overall, the findings highlight the strong diagnostic potential of diffusion models but also emphasize the variability in reporting standards, methodological inconsistencies, and the limited validation in real-world clinical settings. Conclusions: Diffusion models offer significant promise for diagnostic imaging, yet their reliable clinical deployment requires advances in explainability, clinician integration, and real-time performance. This review identifies twelve key research directions that can guide future developments and support the translation of diffusion-based approaches into routine medical practice. Full article

Background/Objectives: Multiple myeloma (MM) patients receiving immunomodulatory drugs (IMiDs) are at increased risk of venous thromboembolism (VTE). Standard prophylaxis typically involves aspirin or low-molecular-weight heparin (LMWH), guided by risk assessment tools such as SAVED and IMPEDE-VTE. However, these models have practical limitations, and real-world evidence supporting novel oral anticoagulants (NOACs) as primary prophylaxis remains limited. Methods: In this retrospective, single-center study, we analyzed 101 MM patients treated with IMiD-based therapy between January 2020 and December 2024. All patients received NOAC prophylaxis (apixaban 2.5 mg twice daily or rivaroxaban 10–20 mg once daily), irrespective of baseline thrombotic risk. Clinical characteristics, comorbidities, and treatment details were collected. The primary outcome was objectively confirmed VTE, while secondary outcomes included bleeding events and treatment feasibility, assessed by treatment continuation without clinically significant bleeding. Results: Median age was 63 years (range 35–89); 36.6% were female. Lenalidomide and pomalidomide were used in 86.1% and 13.9%, respectively. Twenty-eight patients (27.7%) had relapsed/refractory disease, while 72.3% were newly diagnosed. Over a median NOAC exposure of 6 months, two patients (2.0%) developed VTE (both deep vein thrombosis). One major bleeding event (1.0%) occurred. Conclusions: Universal NOAC prophylaxis in MM patients receiving IMiD-based therapy was associated with a low incidence of thromboembolic events and an acceptable safety profile. These real-world findings suggest that NOACs may represent a practical and effective alternative to aspirin or LMWH, potentially overcoming the limitations of score-based prophylaxis strategies. Full article