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BackgroundWhile the associations of low-density lipoprotein cholesterol (LDL-C) and the triglyceride-to-high-density lipoprotein cholesterol ratio (TG/HDL-C) with carotid atherosclerosis are known, their age-varying trajectories remain unclear. This study aimed to characterize the age-specific heterogeneity in these associations using a large Chinese health check-up cohort.MethodsWe retrospectively enrolled 23,058 adults undergoing carotid ultrasonography. After exclusions, 21,227 participants were included. Multivariate logistic regression evaluated the independent associations of LDL-C and TG/HDL-C with carotid plaque. Age-stratified analyses (<40, 40–49, 50–59, 60–69, ≥70 years) and interaction tests were performed. Sensitivity analyses included substituting non-HDL-C for LDL-C and the triglyceride-glucose index (TyG index) for TG/HDL-C. Associations with hypoechoic plaques were also assessed.ResultsThe carotid plaque detection rate was 31.4% (6,657/21,227). Both LDL-C (OR = 1.12, 95% CI: 1.08–1.17, P < 0.001) and TG/HDL-C (OR = 1.11, 95% CI: 1.07–1.15, P < 0.001) were independently associated with plaque. However, their age patterns diverged significantly. The association of LDL-C was strongest in participants aged <40 years (OR = 1.51, 95% CI: 1.30–1.76) but attenuated with age, becoming non-significant in those ≥60 years (P for interaction <0.001). Conversely, the TG/HDL-C association remained stable across age groups, with the numerically highest ORs observed in the <40 and 50–59 age groups (OR = 1.20 and 1.15, respectively), though the age interaction was not significant (P = 0.544). Within the plaque population, LDL-C correlated with hypoechoic plaques (OR = 1.23, 95% CI: 1.16–1.30), while the TyG index did not.ConclusionLDL-C and TG/HDL-C exhibit distinct age-modified patterns of association with carotid plaque. The LDL-C association is most pronounced in younger individuals, whereas the TG/HDL-C association remains relatively stable across age strata. These cross-sectional findings generate the hypothesis that age-specific lipid assessment strategies may warrant prospective evaluation.

Background Multimorbidity is associated with mortality and service use, with specific types of multimorbidity having differential effects. Additionally, multimorbidity is often negatively associated with participation in research cohorts. Therefore, we set out to identify clusters of multimorbidity patients and how they are differentially associated with mortality and service use across age groups in a population-representative sample. Methods Linked primary and secondary care electronic health records contributed by 382 general practices in England to the Clinical Practice Research Datalink (CPRD) were used. The study included a representative set of multimorbid adults (18 years old or more, N  = 113,211) with two or more long-term conditions (a total of 38 conditions were included). A random set of 80% of the multimorbid patients ( N  = 90,571) were stratified by age groups and clustered using latent class analysis. Consistency between obtained multimorbidity phenotypes, classification quality and associations with demographic characteristics and primary outcomes (GP consultations, hospitalisations, regular medications and mortality) was validated in the remaining 20% of multimorbid patients ( N  = 22,640). Results We identified 20 patient clusters across four age strata. The clusters with the highest mortality comprised psychoactive substance and alcohol misuse (aged 18–64); coronary heart disease, depression and pain (aged 65–84); and coronary heart disease, heart failure and atrial fibrillation (aged 85+). The clusters with the highest service use coincided with those with the highest mortality for people aged over 65. For people aged 18–64, the cluster with the highest service use comprised depression, anxiety and pain. The majority of 85+-year-old multimorbid patients belonged to the cluster with the lowest service use and mortality for that age range. Pain featured in 13 clusters. Conclusions This work has highlighted patterns of multimorbidity that have implications for health services. These include the importance of psychoactive substance and alcohol misuse in people under the age of 65, of co-morbid depression and coronary heart disease in people aged 65–84 and of cardiovascular disease in people aged 85+.

Background/Aims: To compare the influence of stroke risk factors between different stroke types and age groups in Taiwan. Materials and Methods: During the study period, March 2007 to August 2008, 1,161 patients with acute ischemic stroke were admitted to the neurological ward. All the patients had risk factors work up and stroke subtype categorization. Results: The study cohort included 736 men and 425 women. Patients were grouped into three age groups: below 50 years (153, 13.2%); 50-75 years, (702, 60.5%) and above 75 years (306, 26.4%). Stroke subtypes included: (1) large-artery atherosclerosis (14.6%), cardioembolism (12%), small-artery occlusion (39.4%), stroke of other determined etiology (1.5%) and stroke of undetermined etiology (32.6%). Older patient group had higher frequency of hypertension and diabetes mellitus. Younger age group of patients had high frequency of obesity and elevated serum triglyceride levels. Smoking and alcohol consumption were strongly related to men, and heart disease and obesity were related to women. Conclusions: The influence of risk factors at different ages is different. Awareness of the stroke risk factors before stroke and treatment with appropriate therapies or life modifications may have a bearing on the outcomes.

Abstract Purpose Age and sex are known to influence outcomes in neuroendocrine neoplasms (NENs), yet their molecular determinants remain poorly defined. We queried a real-world dataset of gastrointestinal (GI) tract and pancreatic (P) NENs and characterized their clinical, molecular, and immune profiles. Methods One thousand nine hundred thirty-five cases (GI: n = 1431, P: n = 504) of NENs were analyzed using Next Generation or Whole Exome Sequencing of DNA, and 1211/1935 cases (GI: n = 917, P: n = 294) underwent Whole Transcriptome Sequencing. We compared the molecular and immune profile with respect to age and sex. Results Older age at diagnosis was associated with worse survival in both GI- and P-NENs. In patients with GI-NENs, there was decreased survival in males compared to females. In GI-NENs, TP53, RB1, FAT1, and KMT2D mutations, as well as immune checkpoint gene (ICG) expressions of LAG3, CD80, and HAVCR2 and M1 macrophages increased with increasing age while APC mutations and M2 macrophages decreased with increasing age. In P-NENs, TP53, RB1, KRAS, and SMAD4 mutations and CD4+ T cells increased with increasing age while MUTYH and NTHL1 mutations and M2 macrophages decreased with increasing age. In GI-NENs, TP53, FBXW7, and TERT (promoter) mutations and genomic loss of heterozygosity (gLOH) were increased in males. In P-NENs, PIK3CA mutations and dMMR/MSI-H were increased in females. Conclusion Our study queries one of the largest datasets of GI- and P-NENs to date and highlights distinct age- and sex-specific molecular and immune profiles. Given the exploratory nature of these analyses and borderline significance, these results remain hypothesis-generating, providing an initial framework for future validation studies.

Maxillary supernumerary teeth (ST) frequently induce complications (e.g., dental irregularities, bone destruction), but precise risk stratification remains challenging. This retrospective study analysed cone-beam computed tomography (CBCT) data from 217 patients, stratified into childhood (6–12 years) and adulthood (≥ 19 years). Morphological assessment showed that 77.1% of ST were conical, with a significantly higher proportion in females (88.3% vs. 73.4% in males). Age-stratified risk modelling revealed that root curvature was strongly associated with adult bone destruction (adjusted odds ratio [OR] = 3.5), while ST number drove childhood dental anomalies (adjusted OR = 4.2). The adult bone destruction model achieved an area under the curve (AUC) of 0.80 (outperforming non-stratified models), whereas the childhood dental anomaly model had modest performance (AUC = 0.69). These findings support age-specific clinical strategies: early extraction for high-risk children and prioritised surgical intervention for adults with ≥ 2 ST plus root curvature, thereby enhancing precision and reducing unnecessary treatments.

BackgroundLiterature on 30-day readmission in adults with sickle cell disease (SCD) is limited. This study examined the overall and age-stratified rates, risk factors, and healthcare resource utilization associated with 30-day readmission in this population.MethodsUsing the Nationwide Readmissions Database, a retrospective cohort study was conducted to identify adult patients (aged ≥ 18) with SCD in 2016. Patients were stratified by age and followed for 30 days to assess readmission following an index discharge. The primary outcome was 30-day unplanned all-cause readmission. Secondary outcomes included index hospitalization costs and readmission outcomes (e.g., time to readmission, readmission costs, and readmission lengths of stay). Separate generalized linear mixed models estimated the adjusted odds ratios (aORs) for associations of readmission with patient and hospital characteristics, overall and by age.ResultsOf 15,167 adults with SCD, 2,863 (18.9%) experienced readmission. Both the rates and odds of readmission decreased with increasing age. The SCD complications vaso-occlusive crisis and end-stage renal disease (ESRD) were significantly associated with increased likelihood of readmission (p < 0.05). Age-stratified analyses demonstrated that diagnosis of depression significantly increased risk of readmission among patients aged 18-to-29 years (aOR = 1.537, 95%CI: 1.215–1.945) but not among patients of other ages. All secondary outcomes significantly differed by age (p < 0.05).ConclusionThis study demonstrates that patients with SCD are at very high risk of 30-day readmission and that younger adults and those with vaso-occlusive crisis and ESRD are among those at highest risk. Multifaceted, age-specific interventions targeting individuals with SCD on disease management are needed to prevent readmissions.

This study aims to employ machine learning for automated age stratification in patients with polycystic ovary morphology (PCOM) and to clarify the age-specific contributions of key clinical characteristics, thereby improving diagnostic accuracy. A total of 192 ovaries with corresponding clinical and ultrasound data were analyzed. Automated age stratification was performed using the K-means unsupervised clustering model along with the elbow method. XGBoost, Random Forest (RF), Support Vector Machine (SVM), and Artificial Neural Network (ANN) algorithms were applied to compare full and selected feature sets. Model performance was evaluated using five-fold cross-validation with metrics including accuracy, sensitivity, F1-score, and area under the curve (AUC), validating the stratification robustness and feature selection strategy. Automated age stratification categorized PCOM patients into three distinct age groups. A stable positive correlation was observed between ovarian volume and follicle count across all strata; however, key diagnostic drivers varied significantly by age. Beyond ovarian volume, follicle count, and BMI, the 18-22 years group was primarily influenced by menstrual cycle phase. The 23-29 years group was characterized by the number of pregnancies and the ovarian stromal artery blood flow RI. In the 30-40 years group, the ovarian stromal artery blood flow S/D ratio and the number of live births showed increasing importance. This study highlights the differential role of age-sensitive indicators in ultrasound-based diagnosis of PCOM and provides a framework for more personalized diagnostic assessment.

To evaluate the efficacy of vaginal misoprostol for labor induction in intrauterine fetal death (IUFD) at ≥20 weeks' gestation. This retrospective cohort study reviewed medical records of IUFD cases between 2021 and 2023 at Dr. Hasan Sadikin General Hospital, Bandung, Indonesia. Women with IUFD at ≥20 weeks' gestation who underwent vaginal misoprostol induction were included, and cases with incomplete key data were excluded. Outcomes included induction-to-contraction interval, induction-to-delivery interval, and cumulative misoprostol dose. Comparisons across gestational age groups (21-27, 28-36, and ≥37 weeks) were performed using the Kruskal-Wallis test; categorical variables were analyzed using the chi-square test. Of 155 IUFD cases, 71 received misoprostol-only induction and were analyzed. Median induction-to-contraction intervals were 12 hours, 6 hours, and 3 hours in the 21-27, 28-36, and ≥37 weeks groups, respectively (p<0.001). Median induction-to-delivery intervals were 13 hours, 10 hours, and 6 hours, respectively (p=0.010). Median cumulative misoprostol doses decreased significantly with advancing gestational age: 200 µg, 100 µg, and 50 µg, respectively (p<0.001). Maternal age and parity did not differ significantly among groups. Vaginal misoprostol was associated with shorter induction intervals and lower cumulative dose requirements at later gestational ages in IUFD. Prospective multicenter studies are needed to confirm optimal regimens and safety.

Systemic lupus erythematosus (SLE) is a highly heterogeneous autoimmune disorder, and lupus nephritis (LN) is one of its most severe organ manifestations. The age at disease onset is a critical factor influencing the clinical phenotype, disease progression, and prognosis of SLE. However, few studies have specifically focused on the age-stratified risk of developing LN. This review examines the age-related clinical and immunological features of SLE and the risk factors associated with progression to LN. In addition, it systematically evaluates how current LN risk prediction models incorporate age as a variable. Although many existing models include age, a significant gap remains-no tools have been specifically designed to assess LN risk across different age groups. Therefore, developing age-specific LN risk prediction models and tailored management strategies is crucial to improving patient outcomes. Such approaches would enable the early identification of high-risk patients and facilitate individualized interventions, ultimately leading to improved long-term renal outcomes for patients with SLE.

This study develops an age–stratified SEIR framework with dose–dependent recovery to explore how therapeutic allocation across age groups can mitigate epidemic spread. The susceptible and exposed classes are modeled as a single homogeneous pool, while infectious and recovered individuals are partitioned into four age groups (infants, children, adolescents, adults) with distinct recovery rates. Recovery in each age class is governed by a sigmoid dose–response relationship, representing age–specific pharmacodynamic efficacy as a function of administered dose. We derive an explicit expression for the basic reproduction number , identify the corresponding transmission threshold , and characterize the forward threshold at separating disease-free extinction from transient epidemic waves with age-stratified quasi-steady plateaus. Numerical simulations, including time series and low–dimensional phase portraits, illustrate how improving recovery in high–contribution age groups (particularly infants and children) can reduce and suppress epidemic peaks under a range of initial conditions. The results provide a conceptual quantitative framework for assessing age–specific dosing strategies and highlight the need for disease – and setting–specific calibration before drawing operational policy conclusions. Clinical trial Not applicable.