José Luis Pérez-Castrillón

Background/Objective: Given the high prevalence of vitamin D deficiency, particularly among older women, this post hoc analysis was conducted to evaluate the long-term efficacy and safety of weekly calcifediol 100 µg in women with vitamin D deficiency participating in a randomised, double-blind, phase II/III trial. Methods: A total of 261 women were included (calcifediol, n = 192; placebo, n = 69). The primary objective was to compare the proportions of women achieving serum 25(OH)D concentrations ≥20 ng/mL or ≥30 ng/mL over the 12-month treatment period. Exploratory analyses of body mass index (BMI) and menopausal status were performed. Results: Weekly calcifediol 100 µg demonstrated superior efficacy versus placebo from week 4 in women achieving ≥20 ng/mL (68.2% vs. 5.8%; p < 0.001) or ≥30 ng/mL (21.4% vs. 0%; p < 0.001), and consistently higher proportions were maintained through week 52. Mean 25(OH)D concentrations increased from 12.21 ng/mL at baseline to 39.47 ng/mL at week 16, and remained stable (41–43 ng/mL) thereafter. No significant differences were observed across BMI or menopausal status subgroups. The safety profile of weekly calcifediol 100 µg was similar to placebo, with no evidence of toxicity. Conclusions: Weekly calcifediol 100 µg is a safe and effective option for achieving and maintaining adequate vitamin D levels in vitamin D-deficient women over a period of 12 months, and is associated with consistent effects across BMI and menopausal status.

Purpose: Osteoporosis and associated hip fractures are a major public health concern. Dualenergy X-ray Absorptiometry (DXA) remains the diagnostic gold standard, but its areal (a) bone mineral density (BMD) measurements have limited sensitivity, as many fractures occur at T-scores above −2.5. Three-dimensional (3D) DXA provides compartment-specific volumetric parameters of the hip, potentially improving osteoporosis management. This study aimed to establish reference data for 3D-DXA parameters to improve osteoporosis management and investigate potential compartmental imbalances at the hip. Method: This multicenter, cross-sectional, population-based observational study (SEIOMM-3D-DXA project), supported by the Spanish Society for Bone and Mineral Metabolism (SEIOMM), analyzed hip DXA scans from 1366 Spanish men and women across six centers. 3D-DXA analyses were conducted using the 3D-Shaper software (3D-Shaper Medical, Barcelona, Spain), producing estimates of trabecular volumetric (v) BMD and cortical surface (s) BMD. Age- and sex-specific reference curves were generated using the LMS method, and thresholds were established based on regression with T-score values. Moreover, trabecular vBMD and cortical sBMD Z-scores were calculated to evaluate potential compartmental imbalances. Results: The derived aBMD curves closely aligned with the NHANES III Caucasian reference. Sex-specific thresholds for trabecular vBMD and cortical sBMD were established for patient stratification. Z-score comparisons revealed significant discrepancies between trabecular and cortical compartments in 52.0% of females and 48.7% of males, underlining the importance of compartment-specific bone assessment. Conclusions: This study establishes reference curves for clinical interpretation of 3D-DXA parameters and demonstrates the potential of 3D-DXA to capture compartmental imbalances at the hip. Mini In this study, hip scans from over a thousand men and women in Spain were analyzed to create normative reference values for 3D-DXA parameters. These results can help doctors better stratify people based on the status of each part of the bone and improve the management of osteoporosis.

The main objective of osteoporosis management is to prevent osteoporotic fractures. Using machine learning methods, new risk variables can be identified to enhance the ability to identify women with osteoporosis who are at an increased risk of bone fracture. A multicenter study using machine learning-based methods was conducted in two independent cohorts of postmenopausal women (HURH and Camargo Cohorts), with clinical follow-up periods ranging from 8 to 10 years. The prediction models were developed in the HURH Cohort and validated using the Camargo Cohort, an independent external group of postmenopausal women. This study developed machine learning models to predict the risk of osteoporotic bone fractures. One is for postmenopausal women with osteoporosis, and the other is for general postmenopausal women. For each of these, two variable grouping options were used. The aggregation with the most predictive power included variables that are generally most accessible in medical practice. For postmenopausal women with osteoporosis, the AUC was 0.92, and for general postmenopausal women, it was 0.88. The results highlighted the significance of the previous fracture, DXA data, vitamin D levels, and PTH levels in predicting future fractures. Machine learning should be used to identify postmenopausal women at increased risk of fractures. This study summarizes that previous fractures, DXA, PTH, and vitamin D play crucial roles in identifying these women.

The genetic background influences the outcomes of COVID-19. This study aimed to evaluate the incidence of polymorphisms in genes linked to the RAAS system, cytokine production, and vitamin D on COVID-19 severity, with the goal of gaining a deeper understanding of the genetic etiology related to COVID-19. This study involved 338 COVID-19 patients and employed machine learning methods to identify the genetic variants that most significantly affect COVID-19 severity. The results revealed that polymorphisms in the IL6, IL6R, IL1α, IL1R, IFNγ, TNFα, CRP, VDR, VDBP, and ACE2 genes are the most significant genetic factors influencing COVID-19 prognosis, particularly in terms of the risks of COVID-19 pneumonia, mortality, rehospitalization, and associated mortality. The machine learning methods achieved an AUC of 0.86 for predicting COVID-19 pneumonia, mortality, and mortality related to rehospitalization, as well as an AUC of 0.85 for rehospitalization within the first year. These results confirm the crucial role of genetic background in COVID-19 prognosis, facilitating the identification of patients at increased risk. In summary, this research demonstrates that genetics-driven machine learning models can pinpoint patients at heightened risk by primarily focusing on genetic variants associated with ACE2, inflammation, and vitamin D.

Background/Objectives: Adequate vitamin D levels are critical for overall health, yet vitamin D deficiency remains prevalent. This study aims to evaluate the efficacy and safety of a standardized weekly supplementation regimen of 100 μg calcifediol for patients with varying degrees of vitamin D deficiency. Methods: A post hoc pool analysis was conducted from a randomized, double-blind, placebo-controlled, multicenter, two-cohort trial. Cohort 1 included vitamin D mild deficiency patients (25(OH)D levels > 10 < 20 ng/mL) and Cohort 2 severe deficiency patients (25(OH)D levels ≤ 10 ng/mL). As both had placebo and weekly calcifediol 100 μg arms (ratio 1:2), a pooled analysis of safety and efficacy was conducted. The primary outcome was the percentage of subjects achieving 25(OH)D levels ≥ 20 ng/mL and/or ≥30 ng/mL at various time points. Results: A total of 401 participants across both cohorts were included in the analysis, 130 who received a placebo and 271 calcifediol 100 µg weekly. By week 52, 94.5% of individuals in the calcifediol group achieved 25(OH)D levels ≥ 20 ng/mL, compared to 25.3% in the placebo group (p < 0.0001). At this same week, 80.5% of subjects in the calcifediol group, but none in the placebo group (p < 0.0001), had 25(OH)D levels ≥ 30 ng/mL. The mean 25(OH)D level plateaued around 40.7 ng/mL from weeks 16 to 52. The frequency of treatment-emergent adverse events was similar in both groups, placebo and calcifediol. Conclusions: Weekly supplementation of 100 μg calcifediol effectively restores vitamin D levels in individuals with both mild and severe deficiencies, demonstrating a favourable safety profile.

La pancreatitis aguda se caracteriza por un proceso inflamatorio reversible del páncreas. Las causas más frecuentes son la obstrucción de la vía biliar y el consumo de alcohol. No obstante, 4% a 10% de los episodios están asociados a hipertrigliceridemia con niveles séricos superiores a 1000 mg/dL. Aunque la fisiopatología exacta no está claramente establecida, las hipótesis predominantes incluyen el efecto tóxico directo de los ácidos grasos libres sobre el tejido pancreático y la obstrucción vascular provocada por los quilomicrones debido a la reducción de la expresión genética de la lipoproteína lipasa (LPL). El tratamiento se enfoca en reducir los niveles de triglicéridos a menos de 500 mg/dL; pocas intervenciones han demostrado ser efectivas, pero se recomienda el uso de insulina y de anticoagulantes. Se presenta el caso clínico de un paciente masculino joven con pancreatitis aguda asociada a hipertrigliceridemia, y se realiza una revisión de la fisiopatología y del manejo de esta entidad.

Introduction: This study aimed to evaluate the impact of infographics and social media threads (SMT) on academic performance in the Musculoskeletal Medical and Surgical Pathology (MMSP) course. Additionally, gender differences in the effectiveness of these tools were examined. Methods: A within-subject educational intervention study was conducted over three academic years, involving 459 fifth-year medical students. Infographics and SMT were exclusively provided for the rheumatology section of the MMSP course, while no additional tools were offered for the traumatology section, serving as a control. Students completed a final exam comprising multiple-choice questions (MCQs) for both sections. Survey data were collected to assess tool usage and perceptions (completed by 84.1%). Statistical analysis included Mann–Whitney U , Kruskal–Wallis, and Jonckheere-Terpstra tests with Z -score standardization. Results: The use of infographics significantly improved standardized scores in rheumatology MCQs ( p = 0.035), particularly among male students ( p = 0.046), while no impact was observed for traumatology section. SMT showed limited association with improved performance. Surveys indicated that 86% of students found infographics helpful for studying, and 85% would recommend them. In contrast, SMT received lower ratings, with 44% of students finding them useful for studying. Conclusions: Infographics effectively enhanced academic performance, with gender-specific variations in impact. In contrast, SMT had limited influence. These findings suggest that infographics are effective supplementary tools in medical education, especially when designed to align with diverse learning preferences. Further exploration of SMT’s potential and development of gender-inclusive teaching strategies is warranted. Graphical