European Geriatric Medicine最新文献

Background: In frail older adults, the incidence of postoperative delirium (POD) is markedly increased, leading to greater morbidity, prolonged length of stay, and higher healthcare costs. An accurate POD prediction model can direct preventive strategies and improve patient outcomes. Employing advanced machine-learning techniques, this study develops a POD prediction model using comprehensive preoperative and intraoperative data.

Methods: We enrolled 2,089 frail patients aged ≥ 65 years undergoing general anesthesia for noncardiac surgery at Fuyang People's Hospital between February 2023 and February 2025. Thirty-eight baseline, anesthetic, and laboratory variables were extracted; missing data were handled by multiple imputation using chained equations (MICE). The dataset was randomly split 7:3 into training and validation sets. After feature selection with Boruta and LASSO, eight machine-learning models-logistic regression, random forest, support-vector classifier, XGBoost, artificial neural network, naïve Bayes, k-nearest neighbors, and decision tree-were trained and compared, with ROC-AUC as the primary metric, accompanied by accuracy, precision, recall, and F1 score. Model interpretability was achieved using SHAP analysis for the best-performing algorithm.

Results: Among 2,089 frail elderly patients, the incidence of POD was 16.52%. After Boruta and LASSO identified 15 key predictors, the XGBoost model achieved an AUC of 0.813, outperforming the other seven algorithms. SHAP analysis identified MMSE score, Charlson Comorbidity Index, and age as the strongest predictors. External validation demonstrated high clinical utility on decision-curve analysis, with an ROC-derived sensitivity of 0.813 and specificity of 0.793, confirming robust performance without overfitting.

Conclusions: This study presents a robust XGBoost-based model for predicting postoperative delirium in frail elderly patients undergoing noncardiac surgery, demonstrating the potential of machine learning for clinical risk stratification. With its balanced performance and high accuracy, the model enables clinicians to identify high-risk patients and initiate timely interventions. Future work should focus on integration into clinical workflows and further external validation.

The term "muscle quality" is widely used in both research and clinical settings, yet a universally accepted definition currently does not exist. Studies addressing "muscle quality" encompass a broad range of functional and morphological characteristics of skeletal muscle, leading to inconsistent interpretations. Aligning with global efforts to adopt standardized and precise terminology, this paper aims to clarify the most frequently assessed parameters under the umbrella of "muscle quality", describe the accurate definitions, and emphasize their clinical significance. Establishing a future unified framework and terminology will be essential for advancing research, ensuring comparability across studies, and reinforcing the clinical applicability of muscle health assessments. Until then, muscle composition, muscle architecture, and muscle-specific strength may serve as appropriate terms to describe the morphological and functional aspects, respectively.

Background: Cognitive trajectories in older adults classified as cognitively normal are poorly characterized, and it is unclear whether their cognitive function has improved or worsened over the past decade, including the COVID-19 pandemic.

Methods: We recruited 343 adults aged ≥ 60 years who visited a memory clinic with various complaints, including subjective or objective memory problems, but were classified as cognitively normal after comprehensive evaluations by specialists between 2013 and 2022. Participants were categorized into four age groups: 60 s, early 70 s, late 70 s, and 80 s. A cross-sectional analysis of covariance (ANCOVA) was conducted to identify which cognitive function tests exhibited earlier declines. To further investigate temporal trends in cognitive performance from 2013 to 2022, linear regression analyses were performed using the year of assessment as an explanatory variable. Additionally, ANCOVA was employed to compare cognitive function during three distinct periods: 2013-2016, 2017-2019, and 2020-2022.

Results: Advancing age was associated with poorer performance across all cognitive domains. Processing speed and executive indices declined earliest, with significant decrements evident in the early 70 s. Neither linear regression nor ANCOVA using test year revealed any improvement in neuropsychological test performance; instead, significant deterioration across multiple domains was observed.

Conclusions: In cognitively normal older adults, attention, processing speed, and executive abilities begin to decline in the early 70 s. The cognitive function of individuals classified as cognitively normal may deteriorate over time. These findings highlight that a diagnosis of "normal cognition" in a memory clinic does not ensure long-term cognitive stability.

Introduction: Several chronic disease combinations (i.e., multimorbidity [MM] patterns) have been linked to poor mental health. This systematic review aimed to synthesize evidence on the longitudinal association between MM patterns and several mental health conditions in later life, including depression, anxiety, suicidality, cognitive decline, and dementia.

Methods: Following PRISMA guidelines (PROSPERO: CRD42024537617), we included longitudinal studies of middle-to-older individuals (45 +) that examined baseline MM patterns and the incidence or trajectories of depression, anxiety, dementia, cognitive decline, or suicidality. The search was conducted in MEDLINE and Web of Science from inception to March 2024, and involved independent screening and quality assessment using a modified Newcastle-Ottawa Scale.

Results: From 13,771 retrieved records, 17 studies were included, ranging from 1209 to 447,888 participants. Fourteen studies were population-based, with follow-ups between 2 and 16 years. Most studies investigated depression (n = 7) and dementia/cognitive decline (n = 9). MM pattern definitions varied, most often relying on data-driven methods (e.g., latent class analysis) and encompassing different numbers and types of diseases. Methodological quality was high across studies. MM patterns featuring cardiometabolic diseases were associated with higher risk of depression, anxiety, cognitive decline, and dementia. Patterns characterized by musculoskeletal, gastrointestinal, and pain-related conditions also showed associations with depression and anxiety. Two studies examined suicidality, with greater multimorbidity burden linked to increased suicidal ideation.

Conclusion: MM patterns linked to higher clinical complexity present poorer mental health trajectories. Validation of MM patterns within and across populations is key for identifying older adults with complex health profiles who may benefit from targeted care strategies.

Purpose: To evaluate whether a geriatric-focused, ChatGPT-based chatbot (PEGAssist) provides clinically adequate and comprehensible guidance for percutaneous endoscopic gastrostomy (PEG) aftercare in older adults. We examined whether its answers met expert expectations for depth/clinical usefulness, clarity/actionability, and scientific accuracy, with emphasis on complication recognition and triage.

Methods: A multidisciplinary panel (geriatrics, nursing, surgery) independently rated chatbot responses to a curated set of common PEG aftercare questions spanning education, routine care, troubleshooting, and complications. Ratings addressed depth, clarity, and accuracy; inter-rater reliability was calculated. Free-text comments were analyzed to identify safety-critical omissions and practical improvements.

Results: Overall answer quality was considered clinically appropriate, with good inter-rater agreement. Performance was strongest in complication management, where responses consistently highlighted clear red-flag signs (e.g., infection, tube dislodgement, and persistent pain) and specified escalation pathways (self-care, 24-48 h contact, urgent evaluation). No unsafe recommendations were identified. Needed refinements included frailty-aware tailoring and more stepwise, caregiver-oriented instructions.

Conclusions: A geriatric-focused LLM chatbot can deliver clinically useful, understandable PEG aftercare guidance aligned with expert expectations, particularly for recognizing complications and directing timely care. This clinician-informed evaluation assessed expert perceptions of chatbot responses; patient or caregiver usability and comprehension were not examined in this phase. Integrating such tools into discharge education may enhance safety and caregiver confidence. Prospective usability and effectiveness studies in older adults and caregivers are warranted.

Purpose: This study aimed to investigate the use of antihypertensive, lipid-lowering, antithrombotic, and glucose-lowering medication among the FINGER (Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability) population during a 9-year follow-up. Also, the effects of the FINGER intervention on and differences between sexes and age groups in medication use were studied.

Methods: Medication data for FINGER participants were retrieved from a national register annually, starting from the study baseline. FINGER was a two-year randomized controlled trial for older adults (n = 1259) at risk of cognitive impairment, who were randomly allocated to a multidomain lifestyle intervention or a control group. The intervention aimed at enhancing healthy lifestyle and to manage and monitor cardiovascular and metabolic risk factors. Generalized Estimation Equations were used to assess longitudinal changes in medication use.

Results: Cardiovascular and glucose-lowering medication use was common and increased over time among FINGER participants. The prevalences of medication use did not differ between the intervention and control groups. The use of cardiovascular and glucose-lowering medication was fairly similar between men and women. Older participants used more cardiovascular medication compared to younger participants throughout the follow-up.

Conclusion: The increasing use of cardiovascular and glucose-lowering medication in this older population at risk of cognitive impairment reflects increasing cardiovascular and diabetes morbidity, management of these risks and diseases through medication, and possible changes in medical practices. Before drawing further conclusions about the effect of the intervention on medication use, its effect on treatment adjustments should be studied.

Trial registration: ClinicalTrials.gov, NCT01041989, retrospectively registered 04/01/2010.

Purpose: Older persons frequently experience postoperative acute pain and delirium, however, there is little clinical data on their possible interrelationships.

Methods: A secondary analysis of multicenter prospective data, including tertiary hospitals in Five Chinese Regions, from April 2020 to April 2022. Older persons (≥ 65 years) scheduled for elective abdominal surgery under general anesthesia, without auditory, visual, or cognitive impairments, who completed assessments for postoperative delirium, anxiety, and depression. The impact of early postoperative acute pain on postoperative delirium in older persons undergoing abdominal surgery was evaluated using univariate and multivariate logistic regression, propensity score matching, and subgroup analysis.

Results: The study cohort included 2,674 patients. The median age was 70 years, and 66.5% of the patients were male. Delirium occurred in 13.2% (n = 354) of patients in postoperative 7 days (POD 7), with a significantly higher prevalence in the moderate-to-severe pain group (unadjusted: 16.3 vs. 9.6%, p < 0.001). Moderate-to-severe pain on POD1 showed a significant association with delirium occurrence in POD 7 according to univariate logistic regression (OR 1.83, 95% CI 1.445-2.319, p < 0.001), multivariable logistic regression (OR 1.63, 95% CI 1.274-2.084, p < 0.001), and propensity score matching (PSM) model (OR 1.44, 95% CI 1.108-1.879, p = 0.006).

Conclusion: In older persons undergoing elective abdominal surgery, moderate-to-severe pain on POD 1 was significantly associated with both delirium and depressive symptoms within 7 days of surgery. Improved early postoperative analgesic strategies may aid in preventing delirium.

Trial registration: ClinicalTrials.gov identifier: NCT06964893 (2025-05-07).

Purpose: The increased population of long-term care facility (LTCF) residents with complex care needs presents a growing challenge for healthcare systems. Besides multimorbidity, functional decline, and cognitive impairments, these residents often have a limited social network, making access to hospital-based medical specialists difficult. Our main aim is to identify the impact of interprofessional collaboration interventions between long-term care (LTC) physicians and medical specialists on the quality of life (QoL) and quality of care (QoC) of LTCF residents.

Methods: A systematic literature search in PubMed, EMBASE, Cochrane Library, Cinahl and a manual screening of the reference lists was performed on the impact of interprofessional collaboration between LTC physicians and medical specialists on the QoL and QoC for LTCF residents. The final search was performed on March 3, 2025 and according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines.

Results: The searches identified 10,364 studies of which ultimately 16 studies were included for analysis. Three ways of interprofessional collaboration were identified; teleconsultations, on-site consultation services, and multidisciplinary collaboration interventions.

Conclusions: This review suggests that interprofessional collaboration between LTC physicians and medical specialists holds potential to improve the QoL and QoC of LTCF residents. Multidisciplinary collaboration interventions that integrate tele- and on-site consultations with additional elements and support show promise for sustainable and positive impact. Given the heterogeneity in study designs and outcomes, further research is needed to identify which elements of multidisciplinary collaboration interventions have the greatest impact on the QoL and QoC of LTCF residents.