Aging Clinical and Experimental Research最新文献

{"title":"Treatment of postmenopausal osteoporosis with recombinant human parathyroid hormone and electromagnetic field","authors":"Miao Xuan,&nbsp;Bo Wang,&nbsp;Wanrong Bi,&nbsp;Ying Li,&nbsp;Lige Song,&nbsp;Zhuangli Xie,&nbsp;Qi Liu,&nbsp;Xiuzhen Zhang","doi":"10.1007/s40520-025-02932-w","DOIUrl":"10.1007/s40520-025-02932-w","url":null,"abstract":"<div><h3>Objective</h3><p>This study aimed to investigate the effect of electromagnetic field (EMF) combined with recombinant human parathyroid hormone (rhPTH) on bone mineral density (BMD) and bone turnover indicators in postmenopausal osteoporosis (PMOP) patients.</p><h3>Methods</h3><p>A total of 336 PMOP patients were randomly assigned into three groups: EMF + rhPTH group (<i>n</i> = 115), rhPTHx group (<i>n</i> = 113) and EMF group (<i>n</i> = 108). The lumbar spine and femoral neck BMDs were measured before treatment and at 6, 12, and 18 months after treatment. Blood calcium, bone alkaline phosphatase (BSAP), type I procollagen N-terminal peptide (PINP), and type I collagen C-terminal peptide/creatinine ratio (CTX/Cr) levels were measured before treatment and at 3, 6, 12, and 18 months after treatment.</p><h3>Results</h3><p>The lumbar spine BMD was significantly increased at 6, 12, and 18 months after treatment, and the neck BMD was increased markedly at 18 months in both EMF + rhPTH group and rhPTH group as compared to those before treatment. There was significant difference in the lumbar spine BMD between EMF + rhPTH group and EMF group and between rhPTH group and EMF group at 6, 12, and 18 months after treatment. In the EMF + rhPTH group, at 3, 6, 12, and 18 months after treatment, blood calcium level was increased by 5.2%, 2.8%, 2.7%, and 3.1%, respectively; BASP level was increased by 80.9%, 120.3%, 84.1%, and 67.7%, respectively; PINP level was increased by 65.4%, 79.7%, 89.7%, and 74.5%, respectively; CTX/Cr was increased by 80.9%, 120.3%, 84.1%, and 67.7%, respectively; the bone metabolism indicators were markedly higher than those before treatment. In the rhPTH group, at 3, 6, 12, and 18 months after treatment, blood calcium level was increased by 5.1%, 3.3%, 3.0%, and 2.1%, respectively; BSAP level was increased by 51.6%, 81.4%, 101.1% and 56.3% respectively; PINP level was increased by 48.5%, 69.8%, 80.7% and 70.5% respectively; CTX/Cr was increased by 29.8%, 29.9%, 55.7%, and 44.8% respectively; the bone turnover indicators were significantly different from those before treatment (<i>P</i> &lt; 0.01).</p><h3>Conclusion</h3><p>The combination of EMF and rhPTH can significantly improve the bone turnover and BMD of PMOP patients, and may serve as a clinical treatment of PMOP.</p></div>","PeriodicalId":7720,"journal":{"name":"Aging Clinical and Experimental Research","volume":"37 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s40520-025-02932-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143466005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Musculoskeletal diseases, infections and vaccines: state of the art, research perspectives and educational needs","authors":"Fiona Ecarnot,&nbsp;Jotheeswaran Amuthavalli Thiyagarajan,&nbsp;Mario Barbagallo,&nbsp;Jane Barratt,&nbsp;Stefan Constantinescu,&nbsp;Ori Elkayam,&nbsp;Luigi Ferrucci,&nbsp;Mickaël Hiligsmann,&nbsp;Meliha Kapetanovic,&nbsp;Francesco Macchia,&nbsp;Jean-Pierre Michel,&nbsp;Alberto Migliore,&nbsp;Alberto Pilotto,&nbsp;Cornel Sieber,&nbsp;Anja Strangfeld,&nbsp;Nicola Veronese,&nbsp;Davide Liborio Vetrano,&nbsp;Stefania Maggi,&nbsp;René Rizzoli","doi":"10.1007/s40520-025-02940-w","DOIUrl":"10.1007/s40520-025-02940-w","url":null,"abstract":"<div><p>Musculoskeletal disorders are a significant public health burden concern, projected to increase in the coming decades, and will substantially contribute to the rising prevalence of functional impairment, frailty and disability in a growing global population. Since persons with musculoskeletal disorders tend to have immune dysfunction, inflammation or be taking immunosuppressive medication, prevention of vaccine-preventable diseases (VPDs) in this group is particularly important. The European Interdisciplinary Council for Aging (EICA) and the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO) jointly convened a 2-day in-person and virtual meeting on 26–27 September 2023, to review the state of the evidence on the link between musculoskeletal diseases, infections and vaccines. We present here the Executive Summary of the proceedings of this meeting. We review the importance of physical activity in preventing or mitigating both musculoskeletal diseases and risk of infection. We summarize current knowledge of the impact of common VPDs on the development and progression of musculoskeletal diseases, and the role of selected vaccines in preventing onset and worsening of frailty and disability in these individuals. This report summarizes the evidence presented at the two-day meeting, highlighting the need to raise awareness among scientists, healthcare professionals, decision-makers, civil society and the general public about the long-term sequelae of VPDs, with focus on the health status of older patients with musculoskeletal diseases.</p></div>","PeriodicalId":7720,"journal":{"name":"Aging Clinical and Experimental Research","volume":"37 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s40520-025-02940-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143471950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning based on nutritional assessment to predict adverse events in older inpatients with possible sarcopenia","authors":"Chengyu Liu,&nbsp;Hongyun Huang,&nbsp;Moxi Chen,&nbsp;Mingwei Zhu,&nbsp;Jianchun Yu","doi":"10.1007/s40520-024-02916-2","DOIUrl":"10.1007/s40520-024-02916-2","url":null,"abstract":"<div><h3>Background</h3><p>The accuracy of current tools for predicting adverse events in older inpatients with possible sarcopenia is still insufficient to develop individualized nutrition-related management strategies. The objectives were to develop a machine learning model based on nutritional assessment for the prediction of all-cause death and infectious complications.</p><h3>Methods</h3><p>A cohort of older patients with possible sarcopenia (divided into training group [70%] and validation group [30%]) from 30 hospitals in 14 major cities in China was retrospectively analyzed. Clinical characteristics, laboratory examination, Nutritional risk Screening-2002 (NRS-2002) and mini-nutritional Assessment-Short form (MNA-SF) were used to construct machine learning models to predict in-hospital adverse events, including all-cause mortality and infectious complications. The applied algorithms included decision tree, random forest, gradient boosting machine (GBM), LightGBM, extreme gradient boosting and neural network. Model performance was assessed according to learning a series of learning metrics including area under the receiver operating characteristic curve (AUC) and accuracy.</p><h3>Results</h3><p>Among 3 999 participants (mean age 75.89 years [SD 7.14]; 1 805 [45.1%] were female), 373 (9.7%) had adverse events, including 62 (1.6%) of in-hospital death and 330 (8.5%) of infectious complications. The decision tree model showed a better AUC of 0.7072 (95% CI 0.6558–0.7586) in the validation cohort, using the five most important variables (i.e., mobility, reduced food intake, white blood cell count, upper arm circumference, and hypoalbuminemia).</p><h3>Conclusions</h3><p>Machine learning prediction models are feasible and effective for identifying adverse events, and may be helpful to guide clinical nutrition decision-making in older inpatients with possible sarcopenia.</p></div>","PeriodicalId":7720,"journal":{"name":"Aging Clinical and Experimental Research","volume":"37 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s40520-024-02916-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143471952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Phenotyping to predict 12-month health outcomes of older general medicine patients","authors":"Richard John Woodman,&nbsp;Kimberly Bryant,&nbsp;Michael J. Sorich,&nbsp;Campbell H. Thompson,&nbsp;Patrick Russell,&nbsp;Alberto Pilotto,&nbsp;Aleksander A. Mangoni","doi":"10.1007/s40520-024-02924-2","DOIUrl":"10.1007/s40520-024-02924-2","url":null,"abstract":"<div><h3>Background</h3><p>A variety of unsupervised learning algorithms have been used to phenotype older patients, enabling directed care and personalised treatment plans. However, the ability of the clusters to accurately discriminate for the risk of older patients, may vary depending on the methods employed.</p><h3>Aims</h3><p>To compare seven clustering algorithms in their ability to develop patient phenotypes that accurately predict health outcomes.</p><h3>Methods</h3><p>Data was collected for <i>N</i> = 737 older medical inpatients during their hospital stay for five different types of medical data (ICD-10 codes, ATC drug codes, laboratory, clinic and frailty data). We trialled five unsupervised learning algorithms (K-means, K-modes, hierarchical clustering, latent class analysis (LCA), and DBSCAN) and two graph-based approaches to create separate clusters for each method and datatype. These were used as input for a random forest classifier to predict eleven health outcomes: mortality at one, three, six and 12 months, in-hospital falls and delirium, length-of-stay, outpatient visits, and readmissions at one, three and six months.</p><h3>Results</h3><p>The overall median area-under-the-curve (AUC) across the eleven outcomes for the seven methods were (from highest to lowest) 0.758 (hierarchical), 0.739 (K-means), 0.722 (KG-Louvain), 0.704 (KNN-Louvain), 0.698 (LCA), 0.694 (DBSCAN) and 0.656 (K-modes). Overall, frailty data was most important data type for predicting mortality, ICD-10 disease codes for predicting readmissions, and laboratory data the most important for predicting falls.</p><h3>Conclusions</h3><p>Clusters created using hierarchical, K-means and Louvain community detection algorithms identified well-separated patient phenotypes that were consistently associated with age-related adverse health outcomes. Frailty data was the most valuable data type for predicting most health outcomes.</p></div>","PeriodicalId":7720,"journal":{"name":"Aging Clinical and Experimental Research","volume":"37 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s40520-024-02924-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143466009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Group exercise in long-term care facilities, alignment with World Health Organization recommendations: a cross-sectional survey","authors":"Salud Poveda-López,&nbsp;Carmen Lillo-Navarro,&nbsp;Joaquina Montilla-Herrador","doi":"10.1007/s40520-025-02954-4","DOIUrl":"10.1007/s40520-025-02954-4","url":null,"abstract":"<div><h3>Background</h3><p>Maintaining functional status in institutionalized older people is a challenge for long-term care (LTC) institutions. In this regard, exercise may have positive effects. The World Health Organization (WHO) has issued guidelines which include recommendations of exercise for each population group. Nonetheless, the literature shows that the levels of exercise among institutionalized population are still low.</p><h3>Aims</h3><p>This study sought to determine: (1) the characteristics of exercise programs for older people performed by health professionals in LTC facilities, (2) the knowledge and use of the WHO recommendations and guidelines for exercising among older people in LTC facilities; (3) the limitations identified by health professionals regarding the application of the WHO guidelines.</p><h3>Materials and methods</h3><p>A cross-sectional national survey following STROBE guideline was performed. Sample: professionals developing exercise programs for institutionalized older people. A Delphi study was conducted to create the survey which included sociodemographic data, exercise characteristics, knowledge about WHO recommendations and limitations regarding their application. Descriptive statistics were used on the data, such as Pearson’s χ2 and independent t- test.</p><h3>Results</h3><p>Many professionals do not know (27,5%) or do not follow (52%) the guidelines proposed by the WHO. There is a low weekly frequency for strength exercises (30%) and aerobic exercise (51%). The professional contract influences the weekly frequency of exercise. Most identified limitations for using the WHO recommendations were the lack of time and large groups.</p><h3>Discussion and conclusions</h3><p>Recommendations of WHO guidelines are familiar to many professionals, however, some are difficult to implement in exercise programs in LTC facilities.</p></div>","PeriodicalId":7720,"journal":{"name":"Aging Clinical and Experimental Research","volume":"37 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s40520-025-02954-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143471949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Opportunistic muscle density assay during CT lung cancer screening for low muscle quality evaluation in older adults: a multicenter study","authors":"Xin Chen,&nbsp;Xifa Gao,&nbsp;Rongzhou Wang,&nbsp;Zicheng Wei,&nbsp;Jiangchuan Wang,&nbsp;Miaomiao Wang,&nbsp;Chao Xie,&nbsp;Xiao Chen","doi":"10.1007/s40520-025-02933-9","DOIUrl":"10.1007/s40520-025-02933-9","url":null,"abstract":"<div><h3>Background</h3><p>Intramuscular adiposity, which can be reflected by muscle computed tomography (CT) attenuation, may be a marker of sarcopenia. This study aimed to investigate muscle attenuation across the life course and thresholds of muscle attenuation for evaluating low muscle quality in older adults.</p><h3>Methods</h3><p>This retrospective multicenter study included 9701 subjects aged 20 years and older who underwent CT lung cancer screening from 2019 to 2021 at our institutions in cohort 1. Muscle attenuation (Hounsfield units [HUs]) of the bilateral erector spinae and spleen attenuation at the middle level of the T11 vertebra were measured. The T score, which is analogous to that used to define osteoporosis, was calculated on the basis of absolute muscle attenuation and the muscle‒spleen ratio (M/S). A T score &lt; -2.5 was used to define low muscle density. The cutoff points for muscle CT attenuation and M/S were subsequently calculated to define low muscle density. Another cohort (cohort 2) of 2006 subjects aged 50 years or older was included to explore the association between low muscle quality and vertebral compression fracture (VCF).</p><h3>Results</h3><p>The mean [SD] age of cohort 1 was 51.8 [15.5] years, and 5896 [60.8%] men were included. The mean [SD] age of cohort 2 was 62.4 [9.6] years, and 1162 [57.9%] men were included. Multiple linear regression analysis revealed that age was associated with muscle CT attenuation (β = -0.19, 95% confidence interval (CI): -0.21 to -0.18) and the M/S ratio (β = -0.004, 95% CI: -0.004 to -0.003). The prevalence of low muscle density was dependent on the cutoff point and increased with age. A cutoff point of 32 HU for women and 37 HU for men and an M/S of 0.65 for women and 0.75 for men were used to define low muscle density. Low muscle density defined by those cutoff points was associated with the risk of VCF [muscle attenuation: adjusted hazard ratio (aHR) = 0.422 (95% CI: 0.256–0.696) for women; aHR = 0.391 (95% CI: 0.173–0.883) for men; M/S: aHR = 0.40 (95% CI: 0.23–0.68) for women; aHR = 0.23 (95% CI: 0.09–0.58) for men].</p><h3>Conclusion</h3><p>Muscle density decreases with age. The muscle attenuation of 32 HU for women and 37 HU for men, an M/S of 0.65 for women and 0.75 for men, may be used to define low muscle density.</p></div>","PeriodicalId":7720,"journal":{"name":"Aging Clinical and Experimental Research","volume":"37 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s40520-025-02933-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143466010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing in-hospital mortality prediction in older patients with sepsis: the role of frailty indices and multidrug-resistance status in non-ICU wards—a proof-of-concept study","authors":"Chukwuma Okoye,&nbsp;Andrea Piazzoli,&nbsp;Maria Cristina Ferrara,&nbsp;Alberto Finazzi,&nbsp;Alice Margherita Ornago,&nbsp;Elena Pinardi,&nbsp;Beatrice Tonus,&nbsp;Paolo Mazzola,&nbsp;Andrea Ticinesi,&nbsp;Giuseppe Bellelli","doi":"10.1007/s40520-025-02955-3","DOIUrl":"10.1007/s40520-025-02955-3","url":null,"abstract":"<div><h3>Background</h3><p>Prognostic stratification in older patients with sepsis is challenging due to frailty and the role of multidrug-resistant (MDR) infections.</p><h3>Aims</h3><p>To test the predictive accuracy of different frailty measures, blood routine tests and MDR infection status for in-hospital mortality among older patients with sepsis.</p><h3>Methods</h3><p>Consecutive patients aged ≥ 65 years with qSOFA ≥ 2 and positive cultures admitted to a tertiary care hospital were enrolled. Frailty was assessed using the Clinical Frailty Scale (CFS), the Primary Care–Frailty Index (PC-FI), and a 50-item FI. A base logistic regression model including age, sex, WBC count, platelets, creatinine, hs-CRP, and lactate predicted mortality. Frailty indices and MDR status were sequentially added, and model performance was compared using the area under the Receiver Operating Characteristics (AUROC). A nomogram was developed to visualize mortality probabilities.</p><h3>Results</h3><p>Among 93 patients (median age 80, IQR [72–84] years, 63.4% males), in-hospital mortality was 16.1%. Deceased patients were frailer and had a higher number of comorbidities. By logistic multivariable regression, the base model achieved an AUROC of 0.771 for predicting in-hospital mortality. Adding frailty indices improved model performance to 0.800 (PC-FI), 0.817 (CFS), and 0.823 (FI). Incorporating MDR status further increased AUROC to 0.890 (PC-FI + MDR), 0.907 (CFS + MDR), and 0.922 (FI + MDR), outperforming the base model (<i>p</i> &lt; 0.05 for all).</p><h3>Conclusions</h3><p>Incorporating frailty indices and MDR status of culture isolates into traditional prognostic parameters improves mortality prediction in older patients admitted with sepsis, enabling more accurate risk stratification and personalized treatment strategies.</p></div>","PeriodicalId":7720,"journal":{"name":"Aging Clinical and Experimental Research","volume":"37 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s40520-025-02955-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143471951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Personalised screening tool for early detection of sarcopenia in stroke patients: a machine learning-based comparative study","authors":"Huan Yan,&nbsp;Juan Li,&nbsp;Yujie Li,&nbsp;Lihong Xian,&nbsp;Huan Tang,&nbsp;Xuejiao Zhao,&nbsp;Ting Lu","doi":"10.1007/s40520-025-02945-5","DOIUrl":"10.1007/s40520-025-02945-5","url":null,"abstract":"<div><h3>Background</h3><p>Sarcopenia is a common complication in patients with stroke, adversely affecting recovery and increasing mortality risk. However, no standardised tool exists for its screening in this population. This study aims to identify factors influencing sarcopenia in patients with stroke, develop a risk prediction model and evaluate its predictive performance.</p><h3>Methods</h3><p>Data from 794 patients with stroke were analysed to assess demographic and clinical characteristics. Variable selection was performed using least absolute shrinkage and selection operator (LASSO) regression, followed by multivariate regression analysis. Logistic regression (LR), random forest (RF) and XGBoost algorithms were used to construct prediction models, with the optimal model subjected to external validation. Internal validation was conducted via bootstrap resampling, and external validation involved an additional cohort of 159 patients with stroke. Model performance was assessed using the area under the curve (AUC), calibration curves and decision curve analysis (DCA).</p><h3>Results</h3><p>Seven variables were identified through LASSO and multivariate regression analysis. The LR model achieved the highest AUC (0.805), outperforming the RF (0.796) and XGBoost (0.780) models. Additionally, the LR model exhibited superior accuracy, precision, recall, specificity and F1-score. External validation confirmed the LR model’s robustness, with an AUC of 0.816. Calibration and DCA curves demonstrated their accuracy and clinical applicability.</p><h3>Conclusions</h3><p>A predictive model, presented as a nomogram and an online risk calculator, was developed to assess sarcopenia risk in patients with stroke. Early screening using this model may facilitate timely interventions and improve patient outcomes.</p></div>","PeriodicalId":7720,"journal":{"name":"Aging Clinical and Experimental Research","volume":"37 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s40520-025-02945-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143455454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical implication of anemia in older patients with dementia with lewy bodies","authors":"Abdulkadir Karismaz,&nbsp;Pinar Soysal,&nbsp;Rafet Eren,&nbsp;Istemi Serin,&nbsp;Irem Bilgic,&nbsp;Irem Tanriverdi,&nbsp;Lee Smith","doi":"10.1007/s40520-025-02958-0","DOIUrl":"10.1007/s40520-025-02958-0","url":null,"abstract":"<div><h3>Aim</h3><p>This research sought to investigate the possible connection between anemia and various parameters of comprehensive geriatric assessment in elderly individuals diagnosed with Dementia with Lewy Bodies (DLB). To our knowledge, this investigation represents the first attempt to examine how anemia impacts patients suffering from DLB.</p><h3>Methods</h3><p>This cross-sectional study encompassed 147 DLB patients from a single geriatric outpatient clinic. The study defined anemia as hemoglobin levels under 12 g/dL for women and 13 g/dL for men. Patients’ demographic information, coexisting medical conditions, and results from comprehensive geriatric evaluations were also recorded.</p><h3>Results</h3><p>Participants in the study had an average age of 85.4 ± 7.1 years. Anemia was present in 46.9% of the patients. Significant disparities were noted between individuals with and without anemia regarding the occurrence of congestive heart failure (CHF), polypharmacy, geriatric depression, and insomnia (all <i>p</i> &lt; 0.05). After controlling for age, gender, and CHF in the multivariate analysis, the association between anemia and both the quantity of medications used [OR: 1.15 (95% CI:1.01-1,31)] and Geriatric Depression Scale-15 scores [OR: 0.88, 95% CI: 0.78–0.98] remained statistically significant (<i>p</i> &lt; 0.05) when comparing anemic patients to non-anemic individuals.</p><h3>Conclusion</h3><p>In the present study almost one in two older patients with DLB were anemic. Anemia is associated with presence of CHF, higher number of drugs and depressive mood in DLB. It is recommended that healthcare providers should recognize the importance of anemia and its associated effects when treating older adults with DLB. This approach may lead to more effective management and treatment of this complex condition.</p></div>","PeriodicalId":7720,"journal":{"name":"Aging Clinical and Experimental Research","volume":"37 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s40520-025-02958-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143431081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Left atrial size and echocardiographic diastolic parameters as predictors of incident atrial fibrillation in older hospitalized patients","authors":"Yan Yin,&nbsp;Yanguang Li,&nbsp;Lili Wang,&nbsp;Qiaoyuan Li,&nbsp;Xu Liu,&nbsp;Zhipeng Hu,&nbsp;Jiawei Zhang,&nbsp;Tao Zhang,&nbsp;Zhuo Liang,&nbsp;ShaoMin Chen,&nbsp;Yunlong Wang","doi":"10.1007/s40520-025-02936-6","DOIUrl":"10.1007/s40520-025-02936-6","url":null,"abstract":"<div><h3>Background</h3><p>The associations between left atrial (LA) size, echocardiographic diastolic parameter (E/A ratio), and incident atrial fibrillation (AF) in older inpatients remain underexplored.</p><h3>Aims</h3><p>This study aimed to evaluate the relationship between LA size, E/A ratio, and AF risk in older hospitalized patients.</p><h3>Methods</h3><p>Between January 2015 and May 2023, a total of 2,615 older inpatients (aged ≥ 65 years) were enrolled in this retrospective longitudinal study. Left atrial diameter (LAD) and E/A ratio were measured using transthoracic echocardiography.</p><h3>Results</h3><p>Over a median follow-up of 844 days (IQR: 331–1355 days), 209 patients (8.0%) experienced at least one incident of AF. After adjusting for covariates, large LA and high E/A ratio were significantly associated with incident AF, with an 11% increase in risk for each 1 mm increase in LAD over 35 mm (adjusted HR: 1.11, 95% CI: 1.10–1.13) and a 30% increased risk per standard deviation increase in E/A ratio when E/A ratio exceeded 0.65 (adjusted HR: 1.30, 95% CI: 1.23–1.37), P &lt; 0.001. The influence of LA size and E/A ratio on incident AF was more pronounced in the younger subgroup of older adults. Incorporating LAD and E/A ratios into the CHA2DS2-VASc score improved its predictive accuracy (AUC _increase = 0.168, P &lt; 0.001).</p><h3>Discussion</h3><p>This study shows that LA size and E/A ratio are key predictors of AF in hospitalized older patients, with age influencing their predictive value. Incorporating these factors into the CHA2DS2-VASc score enhances risk stratification and highlights the need for early AF screening in this group.</p><h3>Conclusions</h3><p>In hospitalized older patients, large LA and high E/A ratio are associated with incident AF, and these associations are more pronounced in younger individuals. LAD and E/A ratios provide incremental predictive value for AF beyond the CHA2DS2-VASc score.</p><h3>Graphical Abstract</h3><p>LA, left atrium; ASE: American Society of Echocardiography; E, mitral inflow velocity in the early diastolic phase; A, mitral inflow velocity in the late diastolic phase; AF: Atrial Fibrillation.</p>\u0000<div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":7720,"journal":{"name":"Aging Clinical and Experimental Research","volume":"37 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s40520-025-02936-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143423471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}