Search Results (1,545)

Background/Objectives: Cardiac rehabilitation (CR) is a cornerstone of secondary prevention, traditionally delivered through supervised center-based models. However, significant logistical barriers and high healthcare costs necessitate a paradigm shift. This review aims to assess the impact of emerging digital frontiers, specifically telerehabilitation (CTR) and artificial intelligence (AI), on overcoming these challenges and improving clinical outcomes. Methods: This study is a narrative, clinically oriented review informed by a structured search of PubMed/MEDLINE and EMBASE for literature published between January 2015 and January 2026. Results: Evidence indicates that CTR is non-inferior to center-based programs in terms of exercise capacity and quality of life (QoL). Digital tools, such as wearable devices and mobile health (mHealth) applications, have significantly increased program participation and improved adherence to lifestyle modifications. Furthermore, the integration of AI facilitates early detection of cardiac events and personalized exercise prescription, while prehabilitation models have been shown to reduce postoperative hospital stays. Conclusions: Digitalization of CR may represent a cost-effective alternative that bridges the gap in global access. While technology serves as an essential diagnostic partner, a robust regulatory and privacy framework is required to protect data sovereignty. Ultimately, multidisciplinary synergy between human expertise and digital innovation is important for providing an equitable and personalized pathway to recovery. Full article

Background/Objectives: Risk stratification in asymptomatic carotid stenosis has traditionally relied on the degree of luminal narrowing; however, plaque vulnerability may better predict cerebrovascular events. Ipsilateral silent brain lesions (SBLs) are considered surrogate markers of stroke risk. This study aimed to identify carotid plaque features on duplex ultrasound (DUS) and computed tomography angiography (CTA), as well as circulating biomarkers, associated with ipsilateral SBL in patients with clinically asymptomatic ≥70% internal carotid artery stenosis. Methods: This prospective observational study with cross-sectional imaging analysis included 316 clinically asymptomatic patients with ≥70% carotid stenosis treated between January 2022 and October 2024. All patients underwent cranial non-contrast CT for SBL detection, DUS plaque characterization (according to the Gray–Weale classification and plaque surface morphology), and CTA analysis, including plaque surface, composition, length, and attenuation values categorized according to Schroeder’s criteria (<50 HU lipid-rich; 51–120 HU fibrous; >120 HU calcified). Demographic, clinical, and laboratory parameters, including inflammatory biomarkers, were recorded. Multivariate logistic regression was performed to identify independent predictors of SBL. Results: SBL were detected in 72 patients (22.8%). On DUS, SBL were significantly associated with Gray–Weale class II plaques, heterogeneous composition, and irregular or ulcerated surfaces (all p < 0.001). On CTA, lipid-rich plaques (<50 HU), ulcerated surfaces, heterogeneous morphology, and lower median plaque density were significantly more frequent in the SBL group (all p < 0.001). In multivariate analysis, independent predictors of SBL were male sex (OR 2.2; 95% CI 1.2–5.7; p = 0.029), Gray–Weale class II plaques (p = 0.002), lipid-rich plaque morphology (OR 21.39; 95% CI 6.86–66.76; p < 0.001), and ulcerated plaque surface on CTA (OR 20.62; 95% CI 7.37–57.68; p < 0.001). Conclusions: Specific ultrasound and CT plaque characteristics were associated with ipsilateral silent brain lesions in patients with asymptomatic ≥70% carotid stenosis. A multiparametric imaging approach may improve risk stratification beyond stenosis severity alone. Full article

Open and reusable road-safety microdata remain scarce in Latin America, particularly when incident records combine detailed temporal information, geocoded event locations, and a clear pathway for extracting fatal outcomes. This article documents a curated administrative dataset for Medellín, Colombia, containing 702,540 reported road-traffic incidents recorded between 1 January 2008 and 31 August 2025. The dataset includes 13 variables describing incident identifier, date, time, incident class, severity, interpolated address, geographic coordinates (latitude and longitude), and planning-unit identifiers. Although the complete dataset contains three severity levels—property damage only, injured, and fatal—it also enables the construction of a fully reproducible fatality subset by filtering incidents classified as fatal, yielding 2762 records. The database covers 21 planning units (communes) in Medellín and includes named neighborhood information for 394 neighborhoods in the complete dataset and 274 neighborhoods in the fatal subset. Spatial completeness is high for administrative data: geographic coordinates are available for 93.63% of all records and 90.77% of fatal incidents. To keep the emphasis on dataset documentation, this data descriptor focuses on compact statistical tables and an illustrative grouped logistic regression model of fatal outcomes. The dataset, accompanied by a complete data dictionary and reproducible R script, is intended to support secondary research in road-traffic safety, spatial epidemiology, transportation planning, urban mobility, and public health. Full article

Background: Gastrointestinal (GI) symptoms are common in endurance and ultra-endurance sports and may impair performance or lead to race withdrawal. While nutritional strategies are frequently emphasized, the respective roles of baseline digestive susceptibility and cumulative exercise exposure remain insufficiently characterized. Methods: Two complementary cross-sectional questionnaire-based studies were conducted in endurance athletes. Study 1 included 230 ultra-trail runners and examined determinants of systematic GI symptoms during competition using a composite digestive vulnerability (DV) score reflecting susceptibility indicators. Study 2 included 497 endurance and ultra-endurance athletes from multiple disciplines and investigated multivariable correlates of GI symptoms and GI-related race withdrawal, integrating training-related GI symptoms (proxy of digestive vulnerability), habitual competition duration (≥6 h), sport category and specific digestive symptoms. Logistic regression models were adjusted for age and sex. Results: In Study 1, the DV score was independently associated with systematic GI symptoms during competition (adjusted OR per point = 1.93, 95% CI 1.33–2.80). In Study 2, athletes reporting GI symptoms during training had markedly higher odds of experiencing GI symptoms during competition (adjusted OR = 3.96, 95% CI 2.67–5.87). Habitual exposure to events lasting ≥6 h was independently associated with increased odds of GI-related race withdrawal (adjusted OR = 2.25, 95% CI 1.35–3.78). GI symptoms during competition represented the strongest proximal correlate of withdrawal (adjusted OR = 7.04, 95% CI 4.00–12.30), indicating a sequential relationship between baseline digestive vulnerability, symptom expression during competition and race termination. After adjustment for digestive vulnerability and exercise exposure, no individual nutritional category remained independently associated with GI outcomes. Conclusions: Gastrointestinal symptoms and race withdrawal in endurance athletes were more consistently associated with digestive vulnerability expressed during training and cumulative exercise exposure than with isolated nutritional items. These findings support a vulnerability–exposure framework in which individual digestive susceptibility interacts with prolonged physiological stress during endurance exercise. Identifying athletes with elevated digestive vulnerability during training may represent a practical strategy to improve individualized nutritional preparation and reduce GI-related race interruption. Full article

Background: High recurrence rates for non-muscle-invasive bladder cancer (NMIBC) remain a clinical challenge. Recommended post-operative treatments are underutilized, highlighting the need for alternative strategies. Given the variability in bladder cancer prognosis, personalized treatment approaches are highly relevant. In this study, we evaluated post-operative two-hour continuous sterile water bladder irrigation (CSWBI) regarding recurrence and safety, as a potential addition to the treatment arsenal for bladder cancer. Method: In 2018, two-hour CSWBI was implemented as routine treatment after all transurethral resection procedures of the bladder (TURB), at the urology department of Sundsvall Hospital. All patients who underwent TURBs four years prior (control group) and four years after the implementation of CSWBI (intervention group) were analyzed. Primary NMIBC were included, MIBC and CIS were excluded. Data were collected retrospectively from patient records, including baseline characteristics, adverse events, and recurrence rates within 12 months follow-up. Statistical analyses included Chi-squared test, Wilcoxon rank-sum test, univariate and multivariate logistic regression analyses, Kaplan–Meier curves and log-rank test. Results: A total of 168 patients were included (control group n = 90, irrigation group n = 78). Median age was 73 years, 23% were female, 77% were male, and 74% were active or previous smokers. The recurrence rate within twelve months for the intervention group vs. the control group was: 27% vs. 21% (p = 0.4) respectively. CSWBI had no statistically significant impact on recurrence (OR 1.25, 95% CI 0.58–2.68, p = 0.6). Adverse effects were limited and equal between groups. Conclusions: Post-operative two-hour CSWBI did not significantly reduce NMIBC recurrence within twelve months in this cohort. Full article

Education occupies an important place among the 17 Sustainable Development Goals. It plays a role in the process of spreading awareness of the concept—its directions, meaning, and goals. According to the idea of the SDG, it is to be universally available to the world’s communities, with the aim of bridging social inequalities, as well as increasing the capacity for responsible functioning and development. The authors of this study believe that knowledge about sustainable development is crucial for shaping social attitudes that determine the uninterrupted development of the world’s economies towards sustainability. In their opinion, it is essential to pay particular attention to ensuring sustainable competences in the education process, which is aimed at preparing staff to perform professional roles in the socio-economic sphere and to be competent in the field of sustainable development. Hence, the aim of this study is to examine the level of awareness of students from selected higher education schools in Poland in this area. The study was conducted on the basis of a diagnostic survey, and the analysis of the results was carried out using qualitative methods, as well as quantitative methods in an in-depth study (logistic regression, supported by PQStat software version 1.8.4.164. The research results indicated that the surveyed students’ knowledge of sustainable development is good, as confirmed by 91% of responses. A key factor in strengthening this knowledge is the educational process implemented as part of their studies (64% of responses). Events supporting the teaching process, such as conferences or meetings with experts, are particularly important for shaping this knowledge. This indicates a high level of student motivation to explore this knowledge and apply it to a model of social behavior, which is rated as responsible by 94% of respondents. In-depth research confirms the above. The odds ratio of 12.994 with a confidence interval of −95% CI: 1.894–+95% CI: 3.238 for the factor of scientific events in the process of supporting green education demonstrates the significance of the findings. Strengthening green education with thematic scientific events is, therefore, an attractive and anticipated form of gaining knowledge on the SDGs by students, and undertaking these events is a recommendation resulting from the presented research. These results are important for modeling sustainable education in terms of the development potential of human resources. Full article

Background: Gestational diabetes mellitus (GDM) affects many pregnancies worldwide and is associated with adverse maternal and fetal outcomes. Current screening at 24–28 weeks limits opportunities for early intervention. We evaluated whether machine learning (ML) models using first-trimester clinical and dietary data can predict GDM risk before the standard oral glucose tolerance test. Methods: We analyzed data from 797 pregnant women enrolled in the BORN2020 prospective cohort study (Thessaloniki, Greece). Ten ML algorithms were evaluated across five class-imbalance handling strategies using stratified 5-fold cross-validation, with final evaluation on an independent 20% held-out test set. Features included maternal demographics, obstetric history, lifestyle factors, and 22 dietary micronutrient intakes from the pre-pregnancy period assessed by Food Frequency Questionnaire. Results: The best-performing model (Logistic Regression without resampling) achieved an AUC-ROC of 0.664 (95% CI: 0.542–0.777), with sensitivity of 0.783 and NPV of 0.932 at the pre-specified threshold. The high NPV should be interpreted in the context of the low GDM prevalence (14.7%), as NPV is mathematically dependent on disease prevalence. A reduced nine-feature model using only routine clinical and demographic variables achieved a numerically higher AUC of 0.712 (95% CI: 0.589–0.825), with overlapping confidence intervals, indicating that detailed FFQ-derived micronutrient data did not improve prediction. Maternal age and pre-pregnancy BMI were the strongest individual predictors by SHAP analysis. No model reached the AUC >0.80 threshold for good discrimination. Substantial miscalibration was observed (slope: 0.56; intercept: −1.83), limiting use for absolute risk estimation. Conclusions: This exploratory study demonstrates that first-trimester ML models achieve modest discriminative ability for early GDM prediction, with routine clinical variables performing comparably to models incorporating detailed dietary assessment. These findings should be interpreted with caution, as no external validation cohort was available and the low events-per-variable ratio (~3.8) constrains the reliability of individual model estimates. Substantial miscalibration further limits use for absolute risk estimation. Accordingly, these models should be regarded as exploratory risk-ranking tools only and require external validation and recalibration before any clinical implementation. Full article

Background: Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) are the first-line treatment for patients with non-small cell lung cancer (NSCLC) harboring EGFR mutations. Although EGFR-TKIs can cause various adverse events (AEs), their profiles have not been fully elucidated in Thai patients. This study aimed to determine the incidence, characteristics, severity, and duration of the first AEs and to evaluate their association with tumor response in patients with NSCLC receiving EGFR-TKIs. Method: This retrospective cohort study was conducted at a super-tertiary care hospital in Thailand. Patients with NSCLC who received EGFR-TKIs between August 2021 and July 2024 were included. Descriptive statistics were used to summarize safety profiles and tumor response. The association between AEs and objective response was assessed using logistic regression. Results: A total of 187 patients were included in this study. Overall, 177 AEs were observed in patients receiving erlotinib, osimertinib, or gefitinib. The most common cutaneous AEs were rash (30.7%), xerosis (24.1%), and acneiform rash (19.3%), while diarrhea (20.3%) was the most frequent gastrointestinal toxicity. Most AEs were grade 1–2 and occurred within 1 month after treatment initiation. In multivariable logistic regression analysis, pruritus (OR 8.26, 95% CI: 1.00–67.75, p = 0.049) and treatment line (OR 0.27, 95% CI: 0.10–0.68, p = 0.006) were independently associated with objective response. Conclusion: Most of the AEs occurred early during EGFR-TKI therapy, with cutaneous reactions being the most common and generally mild to moderate. Pruritus and treatment line were independently associated with objective response, suggesting that pruritus may serve as a potential clinical indicator of treatment response and highlighting the importance of monitoring of the EGFR-TKI-related AEs during therapy. Full article

Internet-of-Things (IoT) sensing can improve traceability, safety, and efficiency of medical waste handling, yet many deployments remain fragmented, lack an end-to-end system architecture, and do not provide the structured data pipelines needed for artificial intelligence (AI) analytics. This paper presents a layered IoT-based system design for medical waste management that integrates: (i) Espressif Systems 32 (ESP32)-based edge devices for fill-level and Global Positioning System (GPS) telemetry; (ii) secure network communication; (iii) a cloud backend for data ingestion, storage, and analytics; and (iv) operator dashboards with event-driven alerting. The architecture extends our prior GPS-enabled tracking and route optimization by adding sensor-driven state monitoring, threshold-based decision support, and a time-series data pipeline designed for future AI-driven predictive analytics. In a 30-day pilot with five containers, the system collected one reading every 15 min (14,400 total readings). The backend demonstrated efficient processing with an average Application Programming Interface (API) response time of 45 ms, sub-50 ms database write latency, and high uptime; alerts were delivered promptly upon threshold violations. Compared with a fixed-schedule baseline, the system enabled condition-based collection scheduling with zero data loss. The proposed design emphasizes modularity, fault tolerance, and integration readiness for hospital information systems, providing a practical blueprint for scalable smart-healthcare waste logistics and a foundation for machine learning-based predictive waste management. Full article

This study presents the development of a Python-based flood-susceptibility risk-mapping tool, implemented in Jupyter Notebook, applied to Rwanda. A Flood Susceptibility Index (FSI) was developed by integrating 20 causal factors associated with flood occurrences, including topographic, hydrological, geological, and anthropogenic variables. Logistic regression, and Variance Inflation Factor were implemented in Python using libraries such as Numpy, Arcpy, traceback, scipy, Pandas, Seaborn, and statsmodel to assign weights to each factor, and to address multicollinearity. The model was validated against flood extent data derived from Sentinel-1 satellite imagery for the major historical flood event that occurred from 2014 to 2024, ensuring spatial consistency and predictive reliability. To project future flood susceptibility for 2030, precipitation data from the Institut Pierre Simon Laplace Coupled Model, version 5A, Medium Resolution (IPSL-CM5A-MR) climate model under the Representative Concentration Pathway 8.5 (RCP 8.5) scenario were utilized. The resulting FSI was classified into five susceptibility levels, from very low to very high, and visualized using Python’s geospatial and plotting tools within Jupyter Notebook in ArcGIS Pro 3.5. It indicates that areas with high amounts of rainfall, and proximity to wetlands and rivers reveal the highest flood risk. The automated and reproducible approach offered by Python enhances transparency and scalability, providing a decision-support tool for disaster risk reduction and climate adaptation planning in Rwanda. Full article

Background: Acute kidney injury (AKI) is a common and high-risk complication of hospitalization that frequently occurs in patients with chronic cardiometabolic disease. Although heart failure (HF) and diabetes mellitus (DM) are prevalent among hospitalized adults and may differentially modify AKI-associated outcomes, their joint impact on in-hospital risk profiles and cumulative burden remains incompletely characterized. Methods: We conducted a retrospective analysis of adult hospitalizations complicated by AKI using a nationally representative inpatient database. Hospitalizations were classified into four cardiorenal metabolic phenotypes: AKI alone, AKI with HF, AKI with DM, and AKI with both HF and DM. Primary outcomes included in-hospital mortality, dialysis initiation, and mechanical ventilation. Survey-weighted multivariable logistic regression models incorporating HF, DM, and their interaction were used to estimate adjusted associations and model-based predicted probabilities. Adjusted risks were visualized across outcomes, and a composite burden metric was constructed to summarize cumulative in-hospital adverse events. Results: AKI outcomes varied substantially across cardiorenal metabolic phenotypes. HF was consistently associated with higher adjusted mortality and mechanical ventilation risk, whereas DM alone was associated with lower adjusted mortality. A significant interaction between HF and DM was observed regarding dialysis initiation, with a disproportionately higher adjusted risk when both conditions coexisted. Integrated visualization across outcomes demonstrated distinct risk profiles by phenotype, with the combined HF and DM group exhibiting the highest cumulative burden of adverse in-hospital events. Conclusions: Among hospitalizations complicated by AKI, the underlying cardiorenal metabolic status is associated with marked heterogeneity in in-hospital outcomes. HF appears to be a dominant modifier of AKI-associated risk, while DM exerts outcome-specific effects and synergistically increases the risk of dialysis initiation when combined with HF. These findings highlight the importance of incorporating cardiometabolic context into AKI risk stratification approaches and underscore the value of multidimensional in-hospital assessments. Full article

This study aimed to investigate the relationship between water intake and post-race gastrointestinal illness in triathletes. Following a post-event survey approach, we evaluated the association between water intake and gastrointestinal illness in triathletes. We collected data among participants of six different triathlons in the Netherlands using an online questionnaire about personal characteristics (age, sex, swimming experience, chronic illness, and athletic level), the completed triathlon (length and duration), water intake, and illnesses during the 7 days following the triathlon. The associations between water intake and gastrointestinal illness were analyzed using generalized estimating equations logistic regression. In total, 1294 athletes participated in this study. The average rate of gastrointestinal illnesses per triathlon was 5.1%. In total, 75.3% of the athletes reported water intake during the race. The associations between water intake and gastrointestinal illnesses were significant. Triathletes with one to three sips of water intake reported 3.7 times more gastrointestinal illnesses (OR = 3.672, 95%CI: 1.316–10.242, p = 0.013) compared to those who did not ingest water. Triathletes with four or more sips of water intake reported 5.1 times more gastrointestinal illnesses (OR = 5.070, 95%CI: 1.740–14.767, p = 0.003). In conclusion, water intake was associated with an increased risk of post-race gastrointestinal illness. The results advocate for improved water quality monitoring and preventive measures in triathlon. Full article

Background/Objective: The most common hemoglobin disorder in the world is SCD. The majority of SCD cases come from Africa, accounting for up to two-thirds of the 300,000 annual births of individuals with SCD worldwide. In Tanzania, 11,000–14,000 babies are born with SCD each year. Despite treatment advancement, pain is still an attributable cause of admissions among patients with SCD. However, data are still lacking regarding the adequacy of pain control in patients with SCD in Tanzania. The aim of this study was to determine factors affecting pain control among patients with SCD presenting with painful events at Mwananyamala Regional Referral Hospital (MRRH) and Muhimbili National Hospital (MNH) in Dar es Salaam, Tanzania. Methods: This was a cross-sectional study conducted at MRRH and MNH, which are tertiary referral hospitals in Dar es Salaam, Tanzania. Patients with SCD aged 8 years and above who presented at the hospitals with painful events (from August 2022 to February 2023) were enrolled in the study. We used a structured questionnaire to collect data on participants’ socio-demographic characteristics and clinical parameters. The adequacy of pain control was assessed using the WHO Pain Management Index. Multivariable binary logistic regression was used to determine factors associated with pain control. Differences were considered statistically significant when the p-value was <0.05. Results: A total of 390 patients with SCD were analyzed. The mean age (±SD) was 15 (±6) years. Most patients were recruited from outpatient clinics (88.2%). The male-to-female ratio was 1:1. The majority of patients had less than three pain episodes per year (77.9%), and about 64.6% presented to the hospital with mild pain. The proportion of patients on hydroxyurea was 62.3%. Furthermore, one-third of patients had inadequate pain control. Factors associated with inadequate pain control included receiving initial pain management in other health facilities (adjusted odds ratio [aOR] and 95% confidence interval [CI] = 2.5 (1.5–4.5), p = 0.001), presenting to the hospital with moderate pain (aOR = 2.2, 95% CI [1.3–3.8], p = 0.0060), and presenting to the hospital with a fever (aOR = 3.8, 95% CI [1.1–13.9], p = 0.04). Having severe pain and receiving initial treatment at MRRH and MNH seemed to be protective factors (aOR = 0.33, 95% CI [0.11–0.97], p = 0.04, and aOR = 0.29, 95% CI [0.14–0.61], p = 0.001, respectively). Conclusions: A considerable proportion of patients with SCD receive suboptimal pain control. Receiving initial pain management from another healthcare facility, presenting to the hospital with moderate pain, and having a fever were associated with inadequate pain control. Further research is warranted to elucidate ways of optimizing the management of pain in patients with SCD in Tanzania. Full article

Background/Objectives: Bone is the most common organ affected by distant metastasis in advanced breast cancer, and the development of skeletal-related events (SREs) often leads to significant deterioration in patients’ quality of life and survival outcomes. In this study, we aimed to explore the risk factors associated with bone metastasis in breast cancer and to develop a predictive nomogram for identifying high-risk patients, which may facilitate timely preventive interventions and improve clinical prognosis. Methods: A retrospective analysis was conducted on 672 patients with breast cancer who underwent surgery at the Fourth Hospital of Hebei Medical University (Shijiazhuang, China) between 2013 and 2023; this cohort served as the training set. Clinical and pathological characteristics potentially influencing bone metastasis—including age, menopausal status, histological grade, affected side, maximum tumor diameter, lymph node staging, TNM staging, ER status, PR status, HER-2 status, Ki-67, molecular subtypes, vascular tumor thrombus, nerve infiltration and visceral metastasis—were collected. The median follow-up time was 42 months. Patients were stratified into two cohorts based on whether postoperative bone metastasis occurred, with groups matched according to Tumor–Node–Metastasis (TNM) stage. Univariate and multivariate logistic regression models were applied to identify independent factors associated with breast cancer bone metastasis, and a nomogram prediction model was constructed using the variables retained in the final analysis. For external validation, data from 2814 patients with breast cancer who underwent surgery between 2013 and 2021 were extracted from the U.S. Surveillance, Epidemiology, and End Results database. Results: The multivariate logistic regression analysis revealed that histological grade (p = 0.002), progesterone receptor (PR) negativity (p = 0.001), human epidermal growth factor receptor 2 (HER-2) negativity (p = 0.002) and visceral metastasis (p < 0.001) were identified as independent predictors of bone metastasis in breast cancer. A nomogram predictive model was established using these four factors. The area under the receiver operating characteristic curve was 0.720 (95% confidence interval (CI): 0.6797–0.7607) for the training cohort and 0.701 (95% CI: 0.6813–0.7205) for the external validation cohort. Decision curve analysis further confirmed the clinical applicability of the model. Conclusions: The present study confirms that histological grade, PR status, HER-2 status and visceral metastasis are independent factors associated with bone metastasis in breast cancer. The constructed nomogram may effectively predict breast cancer-related bone metastasis and could serve as a practical tool for clinical decision-making. Full article

Background/Objectives: Eliglustat is an oral therapy for Gaucher disease type 1 (GD1) that may reduce infusion-related logistical burden, particularly in resource-constrained settings. Post-approval evidence from routine clinical practice in China remains limited. This study evaluated its real-world effectiveness and safety in Chinese adults with GD1. Methods: This retrospective, multicenter study included adults with GD1 receiving eliglustat monotherapy for ≥6 months. Outcomes included plasma glucosylsphingosine (lyso-Gb1), hemoglobin (HGB), platelet count (PLT), liver and spleen volumes, and adverse events (AEs). Depending on distribution, paired changes were analyzed using paired t tests or Wilcoxon signed-rank tests. p < 0.05 was considered statistically significant. Results: Nineteen patients were included in the effectiveness analysis, with a median follow-up of 7 months (range, 6–9). Lyso-Gb1 decreased from 468 to 210 ng/mL (p < 0.0001). HGB increased from 123 to 131 g/L (p = 0.147); among six patients with baseline anemia, 83.3% improved and 33.3% normalized. PLT increased from 109 to 132 × 10⁹/L (p = 0.019); among 12 patients with baseline thrombocytopenia, 58.3% improved. Liver volume decreased from 1808 to 1747 mL (p = 0.016) (1.22 to 1.01 multiples of normal; p < 0.001). Spleen volume decreased from 473 to 452 mL (p = 0.016) (4.69 to 5.17 multiples of normal; p = 0.015). Lyso-Gb1 reduction was greater in patients without prior enzyme replacement therapy (ERT) exposure than in those with prior ERT exposure (−55.1% vs. −43.1%; p = 0.049). In the safety analysis group (n = 90), suspected drug-related AEs occurred in 27.8% of patients, mainly gastrointestinal or skin-related, and were limited to grade I/II. No serious AE or treatment discontinuation occurred. Conclusions: In routine clinical practice in China, eliglustat was associated with rapid substantial reductions in plasma lyso-Gb1, early improvements in hematologic and visceral parameters, and favorable short-term tolerability in adults with GD1. Full article