Search Results (394)

Background/Objectives: Biological ageing is accompanied by progressive alterations in mitochondrial metabolism, microvascular function, and thermoregulation. These processes collectively influence tissue heat production and dissipation, reflecting integrated metabolic, vascular, and thermoregulatory activity measurable at the physiological level. Passive microwave radiometry (MWR) provides a non-invasive, radiation-free method for detecting deep-tissue bioenergy emissions, complementing surface infrared thermography. To evaluate a thermophysiological Bioenergetic Index (BEI), derived from deep-tissue microwave emission, surface temperature, and their spatial and deep–surface relationships, as a candidate age-referenced thermophysiological marker associated with chronological ageing. Methods: Breast thermophysiology measurements from 36,391 women aged 20–80 years were analysed using data collected during routine clinical assessments. Supervised machine-learning models were trained exclusively on thermal features, with chronological age used only as the prediction target. Model performance was assessed using mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R²). In addition, data were aggregated into 5-year age bins to evaluate population-level ageing trajectories. Results: At the individual level, models predicted chronological age with MAE ≈ 3.5 years, RMSE ≈ 5.4 years, and R² ≈ 0.76. Aggregation into 5-year age bins revealed a robust nonlinear ageing trajectory characterised by midlife decline and late-life stabilisation. The increased correspondence at the grouped level reflects reconstruction of the population-level ageing trajectory rather than improved individual-level prediction accuracy, as averaging reduces inter-individual variability. Conclusions: These findings demonstrate a strong ageing-related signal in female breast thermophysiology and support thermophysiology as a candidate age-referenced physiological marker, pending longitudinal and outcome-based validation. The present analysis is cross-sectional and requires longitudinal validation before diagnostic or prognostic interpretation. Full article

Background/Objectives: Against the background of the rapid aging of the population, the symptoms of depression are a major health problem for middle-aged and older adults. This study analyzes the relationship between social participation and the trajectory of depressive symptoms and whether this association varies by gender. Methods: The data comes from five rounds of surveys conducted by the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2020, including a total of 5796 participants aged 45 or above. The depressive symptoms of each wave are measured using the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10). Social participation was defined as the number of reported activities (0, 1, or ≥2). The development trajectory of depressive symptoms was analyzed through Group-Based Trajectory Modeling (GBTM), and their links with social participation level were subsequently quantified using multinomial logistic regression. Gender differences were assessed via interaction tests and stratified models. Results: GBTM identified four distinct depressive symptom trajectories: low (29.71%), moderate (42.72%), increasing (22.07%), and high (5.50%). Compared with no participation, engaging in one activity was linked to lower odds of falling into the moderate, increasing, and high trajectories; the association was stronger for ≥2 activities. Gender-stratified analyses revealed substantial heterogeneity (all interaction p < 0.01). Among women, single-activity participation was associated with lower odds across all three adverse trajectories. Among men, similar associations required ≥2 activities, with single-activity participation linked only to lower odds of the high trajectory. Conclusions: Higher levels of social participation have significantly reduced the depressive symptoms of middle-aged and older adults, and the gender differences are pronounced. Interventions should improve access to social participation for older women and promote activity diversity for older men. Full article

Background/Objectives: Childhood overweight and obesity represent a major global public health challenge, with increasing prevalence and significant long-term metabolic, cardiovascular, and psychosocial consequences. Standard pediatric weight-management strategies based on lifestyle modification often achieve modest and variable results, highlighting the need for more personalized and scalable approaches. Artificial intelligence (AI) has emerged as a promising tool to enhance prevention, early risk stratification, and management of pediatric overweight and obesity. Methods: This narrative review was conducted through a structured search of PubMed, Scopus, and Web of Science for English-language studies published up to January 2026. The main search terms included “artificial intelligence”, “machine learning”, and “deep learning”, combined with “child”, “adolescent”, “pediatric”, “childhood obesity”, “pediatric overweight”, “body mass index”, “weight management”, “nutrition”, “diet”, “physical activity”, “lifestyle”, and “behavior change”. After title/abstract and full-text screening according to predefined eligibility criteria, the included studies were qualitatively synthesized and grouped by main application domains. The initial database search identified 412 records. After removal of 96 duplicates, 316 records were screened by title and abstract. Full-text assessment was subsequently performed for 175 potentially eligible articles. Following this evaluation, 51 studies met the eligibility criteria and were retained from the database search. Additional relevant articles were identified through manual screening of reference lists and related reviews, resulting in the final set of studies included in the narrative synthesis. Results: The review identified five main domains of AI application in pediatric weight management: risk assessment and prediction, dietary assessment and nutritional support, physical activity and lifestyle monitoring, behavioral and psychological support, and clinical decision support. Across the included literature, AI-based approaches were most frequently applied to predictive modeling using longitudinal BMI or growth trajectories, birth characteristics, parental BMI, sleep duration, physical activity, sedentary behavior, and family or socioeconomic factors. However, the evidence base was largely composed of observational and predictive-modeling studies, whereas interventional studies, real-world implementation studies, and long-term pediatric weight-outcome data remained limited. Conclusions: This narrative review indicates that AI has potential as a complementary tool within multidisciplinary, family-centered pediatric weight-management pathways, particularly for early risk stratification, personalized monitoring, and behavioral support. However, the findings also highlight that current evidence remains mainly exploratory and predictive rather than interventional. Further longitudinal, real-world, and ethically grounded research is required to confirm effectiveness, safety, clinical usefulness, and equitable implementation in pediatric populations. Full article

As the largest inter-basin water diversion project in eastern China, the Eastern Route of China’s South-to-North Water Diversion Project (ER-SNWDP) plays a crucial role in alleviating water shortages and ensuring regional ecological security. However, large-scale water diversion that uses natural lakes as impounded lakes across different basins has impacted on the structure and function of the original ecosystems. To explore the changes in the food web and ecosystem structure of the impounded lakes during different operation periods of the ER-SNWDP, we constructed Ecopath models for Hongze Lake in 2010–2011 (pre-operation), 2017–2018 (initial operation), and 2023–2024 (operational period). Our results showed that the trophic energy flow in Hongze Lake was dominated by the detrital food chain, with the highest trophic level ranging from 3.06 to 3.50. Energy flows at trophic levels I and II accounted for a high proportion of the total throughput, and the interactions between trophic levels were relatively simple, indicating that Hongze Lake is approaching a mature ecosystem. Compared with the pre-operation period, the average trophic level, food chain length, and energy conversion efficiency of Hongze Lake declined during the initial operation period, but rebounded during the operational period, though still remaining lower than the pre-operation period. Ecosystem stability followed a similar trajectory: the total primary production/total respiration (TPP/TR) and the system omnivory index (SOI) indicated that ecosystem maturity decreased during the initial operation and increased during the operational period. Fishing activities had negative effects on most functional groups during the pre-operation and initial operation periods, whereas the negative effects from zooplankton and non-native species groups increased during the operational period. Based on changes in the food web structure and ecosystem of Hongze Lake across different water diversion periods, we suggest that the management of Hongze Lake should establish precautionary fishing management measures targeting the effects of filter-feeding functional groups and non-native species, optimize the species and quantities of restocking initiatives, prioritize the protection of critical habitat integrity, and implement long-term ecological monitoring. Full article

Diffusion models for 3D genome structures make inference an ensemble-generation and tiling problem. In the released ChromoGen workflow, millions of independent denoising trajectories are executed through a single-GPU path, while overlapping genomic windows are sampled without enforcing consistency of their shared physical interval. We introduce ParaChromo, a parallel inference framework for conditioned, tiled 3D genome diffusion workloads built around the trained diffusion U-Net and distance-map interface. ParaChromo organizes the workload into three inference-layer modules: a workload-dispatch module schedules region, guidance, and sample chunks across worker groups; an encoder-aware sharded-conditioning module scales and shards the EPCOT front end with FSDP while keeping the inner-loop U-Net replicated; and a seam-coherent tiled-synchronization module projects the shared 12-bead overlap of adjacent reverse chains in distance-map space. On eight A6000 GPUs, the combined reduced-step and task-parallel systems path raises throughput from $2.356\pm 0.003$ to $235.71\pm 1.120$ samples/s, a $100.04\pm 0.486$-fold gain over the released single-GPU baseline. The reduced-step setting is supported by a sweep from 50 to 1000 DDIM steps, where distance-distribution and Hi-C-based metrics remain stable across four chromosomes. For the synchronization module, the chr22 seam discrepancy falls from 150.9 pm to 7.9 pm, while matched internal and Hi-C-based quality metrics are preserved. The synchronized chr22 run also gives a chromosome-scale coordinate rendering over 32 paper-aligned tiles. Together, these results show that conditioned, tiled 3D genome diffusion can be executed as a scalable workload when throughput parallelism, sampler length, encoder placement, and spatial consistency are treated as separate but compatible constraints. Full article

Vocational integration (VI) services aim to support sustainable employment for persons with disabilities. However, in individuals with spinal cord injury, evidence on effective intervention targets and the evaluation of sustainable integration remains limited. The Work–Life Study aims to build an evidence base for supporting sustainable employment in Switzerland by (1) identifying typical work–life trajectories; (2) examining key work–life transitions and their predictors; (3) establishing a multi-state model for intervention targets; (4) exploring individual work–life narratives; and (5) developing guidelines for personalized VI practice. The study combines a mixed methods design with a collaborative Integrated Knowledge Translation approach, actively involving VI professionals and individuals with spinal cord injury. Participants are recruited from the Swiss Spinal Cord Injury Cohort Study (SwiSCI). Work–life history data are collected through a Biographical Survey and Biographical Interviews and analyzed alongside SwiSCI data. Guideline development includes a stakeholder meeting with representatives from the Swiss Paraplegic Group, spinal cord injury clinics, individuals with spinal cord injury, employers, and disability insurers. Of 2041 eligible SwiSCI participants, 478 (23.4%) completed the Biographical Survey (median age 57.5 years; median time since injury 19.1 years), with responders and non-responders showing comparable characteristics. Work–life data closely matched existing SwiSCI data (rho > 0.8), indicating good recall. The resulting guidelines will help VI providers coordinate rehabilitation services to optimally promote sustainable employment for individuals with spinal cord injury. Full article

Background/Objectives: To analyse postoperative pain trajectories after anterior cruciate ligament (ACL) reconstruction using data from a digital rehabilitation system, and to determine (i) whether combined ligament injuries are perceived as more painful than isolated ACL tears, (ii) which patient characteristics are associated with clinically relevant pain (visual analogue scale [VAS] > 5), and (iii) whether higher early pain is associated with later discontinuation of digital monitoring. Methods: This retrospective cohort study used routine data recorded by a validated sensor-based home rehabilitation system in patients after ACL reconstruction. This approach has previously been used to analyse functional recovery trajectories. All patients with ACL-related indications who performed at least one postoperative test were included and classified into four groups: isolated ACL rupture, ACL + meniscus, ACL + collateral ligament, and ACL + collateral ligament + meniscus. Pain during exercises and tests was recorded on a 0–10 VAS. High pain was defined as VAS > 5. Group comparison between indication types, anthropometric and activity-related variables and the proportion of high-pain events were performed using chi-square tests. Early pain (first postoperative month) was analysed in relation to the presence of later tests (≥3 months) to explore associations with discontinuation of digital monitoring. Results: Combined ligament injuries showed a significantly higher proportion of high-pain events during rehabilitation compared with isolated ACL ruptures (5.8% vs. 2.4%, overall p < 0.001). In particular, combined ligament injuries with ACL + collateral ligament rupture were associated with a greater share of VAS > 5 ratings in the early rehabilitation phases. No relevant association was observed between sex or BMI category and the occurrence of high pain, while age group showed an overall association without a consistent directional pattern. Sport activity level showed a strong relationship with high pain (p < 0.001). Early pain demonstrated a small but statistically significant negative correlation with later test participation (r = −0.15, approximately 2% of variance, p = 0.0076); however, this association was attenuated and no longer statistically significant when analysed using mixed-effects models accounting for within-patient clustering, indicating that patients with higher early pain tended to discontinue digital monitoring. Conclusions: Digital routine data after ACL reconstruction suggest that (i) combined ACL–collateral ligament injuries are perceived as more painful than isolated ACL tears, (ii) high postoperative pain is more closely related to activity level and injury pattern than to sex or BMI, while age group shows an overall but non-directional association, and (iii) higher early pain shows a weak bivariate correlation with digital disengagement that was not confirmed in mixed-effects models. Pain is therefore an exploratory marker warranting further investigation, rather than a confirmed independent predictor of adherence in app-based rehabilitation. Full article

The selective detection of small, highly hydrophilic metabolites differing only in stereochemistry represents a major challenge in biosensor development. Here, we present a computational investigation to elucidate the molecular basis of the experimentally observed selectivity of a protein-based electrochemical biosensor toward myo-inositol over D-chiro-inositol. Although the two stereoisomers differ only in the orientation of a single hydroxyl group, they induce distinct dynamic effects on the protein recognition element. Molecular docking revealed comparable binding regions and similar affinity scores, indicating that selectivity does not arise from differences in binding site or docking energy. To investigate dynamic contributions, all-atom molecular dynamics simulations were performed in triplicate (3 × 100 ns) using the AMBER99SB force field and explicit TIP3P water. Trajectory analyses showed that myo-inositol forms a more persistent hydrogen bond network, resulting in reduced residue-level flexibility, more stable ligand–protein interactions, and enhanced local structural stabilization. Overall, these findings support a dynamic model of stereoselective recognition in which ligand-induced modulation of protein conformational ensembles, rather than static affinity, governs biosensor performance. This work highlights the value of molecular dynamics simulations in the rational design of biosensors targeting structurally similar analytes. Full article

The Hsp20 protein family, essential in heat stress responses across all organisms, is part of the heat shock protein (Hsp) superfamily, recognized for its conserved alpha-crystallin domain (ACD). Hsp20s are the smallest proteins in the superfamily and primarily assist in protein refolding during stress and developmental processes. We present an in silico characterization of the Hsp20 gene family in Chenopodium quinoa (2n = 4x = 36) using an integrative approach. Quinoa is well known for its global contributions to food production and tolerance to various abiotic stresses. We identified 69 CqHsp20 genes that exhibit a well-conserved evolutionary pattern, characterized by a balanced copy number distributed symmetrically across 19 homeologous pairs in both subgenomes (A and B), with localized expansions driven by tandem duplications on eight chromosomes. High sequence identity in contiguous gene pairs and Ka/Ks ratios consistently below 1 (0.14–0.84) mathematically demonstrate that strict purifying selection has maintained the structural and sequence integrity of these genes since the ancestral polyploidization event. The phylogenetic analysis grouped CqHsp20 into two main clusters, splitted into four sub-clusters based on peptides’ cellular localization, consistent with a characteristic gene structure and conserved motif analysis, which may reflect the evolutionary trajectory and functional specialization of the Hsp20 family in plants. The integration of transcriptomic data from published experiments enabled us to detect a cluster of putatively ubiquitously expressed CqHsp20, as well as other groups that showed differential responses across abiotic stress conditions. The pattern shows that more genes exhibit higher transcription abundance under drought and salinity than under heat, key adaptive traits underlying quinoa’s known ecological versatility. Some of these genes, which are undetectable or have low abundance under heat stress, encode organelle-targeting peptides, a phenomenon not reported in other model plant studies. Differential expression analysis revealed a highly transcribed sub-cluster where six out of seven of nuclear CqHsp20 genes were active in aerial tissue during initial heat stress, with a specific cohort of four genes (CQ025082, CQ031384, CQ041158, and CQ055373) maintaining significant upregulation ($|{log}_2\mathrm{Fold}\mathrm{Change}|\ge 1.0$, $\mathrm{padj}<0.05$) under prolonged and simultaneous shoot/root exposure. Varying expression within CqHsp20 homologous and paralogs supports the idea that gene duplication creates genomic diversity, facilitating adaptation to variable extreme environments. However, while theoretical and in silico analysis provide valuable insight into quinoa Hsp20 response, empirical data are essential to unequivocally understand how these gene expression variations affect quinoa response to abiotic stressors. Full article

Protease inhibitors (PIs) remain important components of HIV-2 treatment, but resistance genotyping is frequently challenging in individuals with low or undetectable plasma viremia. Proviral DNA sequencing may provide access to archived viral variants and improve understanding of long-term resistance and clinical evolution. In this retrospective longitudinal study, 27 individuals with HIV-2, both ART-experienced and ART-naïve, followed at a hospital in Lisbon, were analyzed. The HIV-2 protease gene was amplified from peripheral blood mononuclear cell-derived proviral DNA, cloned, and sequenced (Sanger sequencing) at baseline and, for ART-treated participants, after eight years of follow-up. Resistance profiles were interpreted using the Stanford HIVdb, HIV-2EU, and Rega algorithms. Clinical data, including ART history, CD4 counts, and plasma viral load, were collected longitudinally. Amino acid diversity was assessed using Shannon entropy, and longitudinal CD4 dynamics were evaluated using mixed-effects models with time-varying ART exposure. Sensitivity analyses were performed using generalized estimating equations (GEE). A total of 222 clonal HIV-2 protease sequences clustered within group A. Major PI resistance mutations were detected in 21.4% of ART-experienced and 23.1% of ART-naïve individuals at baseline. Longitudinal resistance trajectories varied across participants, including persistence, apparent emergence, and non-detection of previously identified mutations. Mixed-effects modeling revealed substantial inter-individual variability in CD4 trajectories, with no statistically significant associations observed between CD4 evolution and ART status, time, or their interaction. GEE analyses yielded consistent results, supporting robustness across modeling frameworks. Entropy analysis identified localized sequence diversity changes restricted to a small number of protease residues, with positions 60 and 75 differing between groups at baseline and position 21 showing longitudinal variation among treated participants. This study demonstrates that proviral DNA sequencing captures archived HIV-2 protease diversity and reveals persistent and dynamic resistance patterns within the viral reservoir. While no population-level association between ART exposure and CD4 trajectory was observed, marked inter-individual variability highlights the complexity of longitudinal immune recovery in HIV-2 infection. These findings support the value of proviral sequencing as a complementary research tool for characterizing long-term viral evolution in settings where plasma-based genotyping is limited. Full article

Background: Congenital heart defects (CHD) are prevalent, affecting 1% of live births globally. Despite improved survival rates, adults with CHD face increased risks of psychological distress and neurocognitive deficits. The P-BAHn study (P-BAHn = “Psyche Bei Angeborenen Herzfehlern”, Psyche for congenital heart defects) evaluates the mental health status and psychosocial challenges of German children and adolescents with CHD, focusing on retrospectively assessed COVID-19-related burden and patient-/parent-rated experiences with psychological, psychotherapeutic, or psychiatric treatment (PST). Methods: A cross-sectional, online-based survey was conducted using the National Register for Congenital Heart Defects (NRCHD). The final dataset comprised 1567 respondent-level records from 1310 families, including 992 parent reports and 575 self-reports from children/adolescents aged 6 to <18 years. The survey assessed mental health, emotional well-being, psychosocial status, demographics, medical history, and psychological treatment. Data were analyzed descriptively using chi-square tests and t-tests for exploratory unadjusted group comparisons. In addition, exploratory multivariable logistic regression analyses were performed for selected key outcomes. Results: School-related stress was common in young CHD patients (45.3%) and was associated with older age and female sex (51.5% female vs. 35.6% male) in adjusted analyses. Overall, 17.0% of patients reported having a mental illness, most commonly anxiety (6.8%), eating disorders (5.6%), and depression (4.7%); neither sex nor CHD severity was significantly associated with self-reported mental illness in adjusted analyses. Less good/poor self-rated health was associated with older age and complex CHD in both patient and parent reports. Retrospectively assessed pandemic-related changes were perceived as quite or extremely stressful by 23.9% of patients. High COVID-19-related burden was associated with female sex, whereas CHD severity was not significant after adjustment. Among patients with previous or current PST, patient- and parent-rated treatment benefit varied by patient sex and CHD complexity. Previous/current PST was reported by 25.9% of patients and 23.8% of parents and was associated with older age in both respondent groups and with complex CHD in parent reports. Among patients with previous/current PST, 56.4% reported high perceived support. Conclusions: The P-BAHn study highlights the need for targeted psychosocial support for children and adolescents with CHD, including female patients, those with complex conditions, and patients reporting school- or crisis-related burden. Retrospectively reported pandemic-related burden underscores the importance of integrating crisis-sensitive strategies into psychosocial care frameworks. Longitudinal studies are essential to understand mental health trajectories and to evaluate the sustained patient- and parent-perceived benefit as well as clinical effectiveness of PST use. Enhancing support services and refining intervention models will improve the well-being and quality of life for young CHD patients. Full article

Against the backdrop of the digital transformation in engineering education, this study developed and implemented a Learning Analytics (LA)-driven and Artificial Intelligence (AI)-supported blended learning model to address structural challenges in the “Combustion” course, including highly abstract theories, experimental safety risks, and compressed instructional hours. Moving beyond mere technical stacking, the model establishes a closed-loop data ecosystem that integrates “pre-class adaptive diagnosis, in-class contextualized internalization, and post-class personalized transfer,” while deeply embedding engineering ethics and sustainability issues related to carbon neutrality. A one-semester quasi-experimental study (Experimental N = 60, Control N = 60) was conducted, utilizing a triangulated assessment of final exam scores, platform-based behavioral trajectories, and semi-structured interviews. The results showed that the experimental group achieved significantly higher final assessment scores than the control group (82.4 ± 5.7 vs. 73.2 ± 6.9), with normality tests supporting the use of parametric analysis and Analysis of Covariance (ANCOVA) indicating a significant instructional effect after controlling for Grade Point Average (GPA) and pre-test scores. Furthermore, behavioral analysis confirms that the LA mechanism significantly enhances students’ self-regulated learning and engagement by increasing the visibility of the learning process. This study provides an evidence-based reform paradigm for engineering curricula to achieve the synergistic cultivation of knowledge acquisition, competency development, and value alignment within constrained instructional timeframes. Full article

Background: This pilot study investigated the potential effects of an individualized home-based cognitive training program delivered through the Neurotablet^® in individuals with Mild Cognitive Impairment (MCI). Methods: Fourteen outpatients were assigned to the experimental group (n = 7) or to the waiting-list control group (n = 7). Standardized neuropsychological and psychological measures were collected at baseline and follow-up. Outpatients of the experimental group completed an eight-week personalized home-based digital rehabilitation protocol targeting multiple cognitive domains. Longitudinal changes in standardized outcomes were analyzed using generalized linear mixed models. In addition, individual MCI trajectories were examined qualitatively by comparing MCI subtype between baseline and follow-up, whereas training performance was analyzed using within-participant linear regression models. Results: Standardized neuropsychological outcomes remained overall stable over time, with no significant differences between groups. By contrast, analyses of training performance revealed heterogeneous patterns across participants, with significant session-related changes emerging in some individuals. In particular, some tasks showed reductions in reaction times across sessions, suggesting changes in task efficiency with repeated practice. These findings highlight the heterogeneity of cognitive trajectories in MCI and suggest that individualized digital training may be associated with measurable changes in task performance, even in the absence of detectable changes in standardized neuropsychological measures. Conclusions: Despite the presence of limitations, digital cognitive interventions may offer a feasible approach to support the delivery of individualized cognitive rehabilitation in individuals reporting cognitive complaints. Further studies with larger samples, more detailed monitoring of training variables and engagement are needed to better clarify the potential cognitive impact of such interventions. Full article

Background/Objectives: In standardized low-event surgery such as laparoscopic cholecystectomy (LC), discharge-based outcomes may be insufficiently sensitive to capture differences in recovery trajectory. We investigated whether early gastrointestinal recovery after standardized LC differed according to anesthetic maintenance strategy. Methods: This single-center retrospective cohort study included consecutive adults who underwent scheduled LC between September 2023 and December 2025 within a standardized perioperative pathway. The primary exposure was anesthetic maintenance strategy, comparing remimazolam-based with desflurane-based maintenance. The primary outcome was time to first flatus. Key secondary outcomes included postoperative day 1 (POD 1) high-sensitivity C-reactive protein (hs-CRP), C-reactive protein-to-albumin ratio (CAR), diet delay, prolonged hospital stay, postoperative nausea and vomiting, and 30-day readmission. Associations were evaluated using a log-normal accelerated failure time model, multivariable logistic regression, and log-transformed linear models for inflammatory markers. Results: A total of 316 patients were included (remimazolam, n = 171; desflurane, n = 145). Time to first flatus was shorter in the remimazolam group, with an unadjusted median difference of 8 h (28.0 [24.0–37.0] vs. 36.0 [28.0–52.0] h). After adjustment, remimazolam-based maintenance remained associated with a 21% shorter time to first flatus (time ratio, 0.79; 95% confidence interval [CI], 0.72–0.86; p < 0.001), corresponding to an adjusted median reduction of 8.0 h. The remimazolam group also showed earlier flatus recovery across predefined time windows and lower POD 1 hs-CRP and CAR, whereas later outcomes were largely similar. Conclusions: In standardized LC, early gastrointestinal recovery appeared more sensitive to anesthetic maintenance strategy than discharge-based outcomes. These findings support the use of early functional recovery measures, in addition to discharge timing, when evaluating perioperative recovery in low-event short-stay surgery. Full article

Background: Chronological age remains deeply embedded in perioperative risk assessment because it is readily available and intuitively associated with adverse outcomes. In clinical practice, however, patients of similar age frequently experience markedly different postoperative trajectories, suggesting that physiological reserve may more accurately reflect vulnerability to surgical stress than years lived alone. We therefore investigated whether age-based stratification inadequately captures perioperative vulnerability when compared with functional phenotyping based on frailty status and baseline handgrip strength (HGS). Methods: We conducted a prospective multicenter observational cohort study including 223 adults undergoing elective abdominal surgery between January 2023 and June 2025. Chronological age was evaluated both continuously and using a conventional threshold (<70 vs. ≥70 years). Physiological reserve was characterized using a phenotype-based frailty model (fit, pre-frail, frail) and baseline HGS measured at hospital admission. Prolonged hospitalization, defined a priori as length of stay (LOS) > 10 days, was used as a pragmatic clinical benchmark. Cross-classification analyses, logistic regression, and receiver operating characteristic (ROC) curve analyses were performed to compare the discriminatory performance of chronological age, frailty phenotype, and HGS. Results: Substantial discordance was observed between chronological age and frailty phenotype. Among patients younger than 70 years, 7.7% met criteria for frailty, whereas 58.0% of patients aged ≥70 years were classified as fit or pre-frail. Prolonged hospitalization occurred in 48 patients (21.5%) and varied markedly according to frailty status within each age group. Frail patients younger than 70 years demonstrated higher rates of prolonged LOS than fit older patients (40.0% vs. 10.5%). Chronological age demonstrated limited discrimination for prolonged hospitalization (AUC 0.579), while the ≥70-year threshold showed poor discriminatory performance (AUC 0.541). Frailty phenotype demonstrated improved discrimination (AUC 0.679), whereas the combined multivariable model integrating age, frailty, HGS, sex, and oncologic indication achieved good discriminatory performance (AUC 0.810). In multivariable analyses, frailty remained independently associated with prolonged LOS, whereas chronological age did not. Conclusions: Chronological age alone demonstrated limited discriminatory performance for perioperative risk stratification. Functional phenotyping based primarily on frailty status, complemented by objective functional measures such as HGS, may better capture physiological reserve and support more individualized, function-centered perioperative assessment in abdominal surgery. Full article