Rapid global population ageing is accelerating the burden of cardiometabolic disease, and inflammageing-the chronic, low-grade, sterile inflammation that accompanies advancing age-has emerged as a shared pathological substrate linking cardiovascular disease, metabolic syndrome, and type 2 diabetes mellitus in older adults. Increasing evidence identifies the gut microbiota as an upstream driver of this process, forming a modifiable feedback loop with the intestinal barrier, the immune system, and cardiometabolic homeostasis. With advancing age, beneficial taxa such as Bifidobacterium and Faecalibacterium prausnitzii decline in abundance, whereas pro-inflammatory taxa expand; this dysbiosis compromises tight-junction integrity, producing the "leaky gut" phenotype and permitting translocation of lipopolysaccharide and other pathogen-associated molecular patterns into the portal circulation. The resulting metabolic endotoxaemia activates TLR4/NF-κB signalling and sustains systemic elevations of IL-6, TNF-α, and IL-1β, which converge on insulin resistance, endothelial dysfunction, oxidative stress, and vascular injury. Microbiota-derived metabolites further shape this trajectory: trimethylamine-N-oxide (TMAO) has been implicated in the acceleration of atherosclerosis, foam-cell formation, and platelet reactivity-largely on the basis of rodent studies and observational human data-whereas short-chain fatty acids reinforce barrier function and induce regulatory T cells. This review systematically synthesises current mechanistic and clinical evidence on the gut microbiota-inflammageing axis and its contribution to cardiometabolic deterioration during ageing, and critically appraises dietary intervention strategies as the most direct and actionable entry point into this feedback loop. The Mediterranean, Green-Mediterranean, and plant-based dietary patterns, together with intermittent fasting, have been shown to remodel the gut microbiota, reduce systemic inflammatory tone, and improve cardiometabolic risk profiles. Key dietary components-fibre-derived short-chain fatty acids, polyphenols and their microbial metabolites, omega-3 polyunsaturated fatty acids together with specialised pro-resolving mediators, and age-appropriate protein intake-act through distinct but converging molecular mechanisms to preserve barrier integrity, restore immunometabolic balance, and support healthy vascular ageing. Emerging translational approaches, including precision nutrition guided by individual microbiome profiles, next-generation probiotics, prebiotics and postbiotics, and small-molecule inhibitors targeting TMAO biosynthesis, are also examined, alongside their current translational limitations-including the absence of standardised microbiome analytical pipelines, strain-specific heterogeneity of probiotic effects, and the lack of formal recommendations in current cardiovascular and diabetes guidelines. Safety considerations relevant to frail older adults-such as hypoglycaemia risk during intermittent fasting, bleeding risk with high-dose omega-3 supplementation, and rare bacteraemia associated with probiotic use in immunocompromised individuals-are also highlighted. Research gaps such as scarce long-term follow-up, under-representation of non-Western populations, and heterogeneity across ageing stages are discussed. By integrating mechanistic insight with translational evidence, this review provides a theoretical foundation for the development of individualised nutritional strategies aimed at extending cardiometabolic healthspan in older adults.

Height is inversely associated with risk of cardiovascular and metabolic conditions in nonpregnant populations. Whether maternal height is independently associated with pregnancy complications, after accounting for prepregnancy weight, remains less clear.

To investigate associations of maternal height with pregnancy complications, independent of prepregnancy weight, and to examine the role of infant sex and race/ethnicity in these associations.

We conducted a secondary analysis of data from the Omega and Hyperglycemia and Adverse Pregnancy Outcome (HAPO) prospective cohort studies of pregnant women (total N = 8763). Cohort-specific short (<20th percentile), average (20th-80th percentile), and tall (≥80th percentile) height categories were defined. Gestational diabetes mellitus (GDM), preterm birth (PTB; Omega only), and preeclampsia were considered outcomes. We fit cohort-specific unadjusted and adjusted modified Poisson regression models with robust standard errors and estimated relative risks (RRs) and 95% confidence intervals (CIs) associated with each 5-cm greater maternal height. We fit similar models to examine risks among women with short or tall height compared with average height. We evaluated race/ethnicity and infant sex as potential modifiers of height-GDM associations using interaction models.

Each 5-cm greater maternal height was associated with lower GDM risk in both cohorts, with a modest association in Omega and a larger association in HAPO (Omega: adjusted RR [aRR], 0.99; 95% CI, 0.98, 0.99; HAPO: aRR, 0.84; 95% CI, 0.78, 0.90). Short women had higher GDM risk (Omega: aRR, 1.05; 95% CI, 1.03, 1.07; HAPO: aRR, 1.44; 95% CI, 1.18, 1.75), and tall women had lower GDM risk (Omega: aRR, 0.98; 95% CI, 0.96, 0.99; HAPO: aRR, 0.71; 95% CI, 0.56, 0.89), compared with women with average height. In Omega, linear height was associated with slightly lower preeclampsia risk (aRR, 0.99; 95% CI, 0.99, 0.99) and slightly greater PTB risk (aRR, 1.01; 95% CI, 1.00, 1.01). Infant sex or race/ethnicity did not meaningfully modify the association between height and GDM in either cohort.

Maternal height was inversely associated with GDM risk in both cohorts. We also observed small, cohort-specific associations of height with PTB and preeclampsia in Omega. These findings suggest that maternal height may provide modest information beyond conventional maternal body-size measures, although its clinical utility for individual risk prediction or targeted monitoring may be limited and requires further evaluation.

Nausea or vomiting are common adverse events (AEs) associated with glucagon-like peptide-1 receptor agonists and often decline over time despite continued exposure, suggesting tolerance development. However, the longitudinal dynamics of recurrent events and tolerance have not been quantitatively characterized for efpeglenatide. This study aimed to characterize efpeglenatide-induced nausea/vomiting in non-diabetic patients with obesity using repeated time-to-event (RTTE) modeling and to explore its implications for dose-escalation strategies.

Data from six clinical trials were pooled, and 678 participants with obesity and/or type 2 diabetes mellitus were included in the analysis. A total of 672 nausea or vomiting events were analyzed using a sequential PK-AE approach based on a previously developed population pharmacokinetic model. Separate RTTE models were developed for an obesity population and a pooled total population. The models incorporated baseline hazard, a time-decaying non-drug effect, and an exposure-driven drug effect with tolerance linked to cumulative exposure (AUC). Model performance was evaluated using bootstrap and visual predictive checks, and Monte Carlo simulations were performed to assess nine dose-escalation scenarios. The obesity model served as the primary model for predicting dosing regimen-dependent AE patterns, whereas the pooled total model was used as an exploratory model to assess the concentration-AE response relationship.

Among the 678 participants, 247 (36.4%) experienced at least one episode of nausea or vomiting. In the obesity model, the exposure-hazard relationship was best described by a log-linear function. The estimated AUC associated with 50% tolerance development was 109,872 h ng/mL in the obesity model. Among the nine dosing scenarios, the Case 1-4 titration regimens achieved approximately 50% tolerance within 3-4 weeks while maintaining a lower early AE burden than high fixed-dose regimens. Low fixed-dose regimens delayed tolerance development, whereas high fixed-dose regimens increased the early AE burden.

Efpeglenatide-associated nausea or vomiting was well characterized using an exposure-driven RTTE framework, and early cumulative exposure appeared to play a central role in tolerance development. These findings suggest that, in non-diabetic patients with obesity, stepwise titration of efpeglenatide may help optimize tolerability by mitigating early AE burden while allowing sufficient cumulative exposure for tolerance development.

Chronic kidney disease (CKD) is a major global health concern characterized by progressive loss of kidney function and an increased risk of cardiovascular morbidity and mortality. Sodium-glucose cotransporter-2 (SGLT-2) inhibitors, initially developed as antihyperglycemic agents for the treatment of type 2 diabetes mellitus (T2DM), have subsequently demonstrated substantial renoprotective effects that extend beyond glycemic control. This systematic review aimed to evaluate current evidence regarding the effects of SGLT-2 inhibitors on CKD progression in adults with and without diabetes. A comprehensive literature search was conducted in PubMed/MEDLINE, Scopus, and Google Scholar from database inception through October 2025. Eligible studies included randomized controlled trials (RCTs), systematic reviews and meta-analyses, and prospective or retrospective observational cohort studies evaluating kidney outcomes, including CKD progression, changes in estimated glomerular filtration rate (eGFR), doubling of serum creatinine, and progression to end-stage kidney disease (ESKD). The review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. Thirty-two studies met the inclusion criteria, comprising 13 RCTs, eight systematic reviews and meta-analyses, and 11 observational cohort studies. Across randomized trials, SGLT-2 inhibitors consistently reduced CKD progression and major adverse kidney outcomes and slowed the decline in kidney function. Dedicated kidney outcome trials demonstrated substantial reductions in adverse kidney outcomes, while meta-analytic evidence confirmed preservation of kidney function across diverse CKD populations, including individuals without diabetes. Real-world observational studies further supported these findings, demonstrating slower eGFR decline and favorable kidney outcomes in routine clinical practice. SGLT-2 inhibitors were generally well tolerated, and meta-analytic evidence demonstrated a reduced risk of acute kidney injury among patients with CKD. Collectively, the available evidence indicates that SGLT-2 inhibitors substantially slow CKD progression and reduce adverse kidney outcomes across diverse CKD populations, including patients with and without diabetes. Their consistent efficacy and favorable safety profile support their role as cornerstone nephroprotective agents in contemporary CKD management. Further research is warranted to clarify their long-term efficacy and safety in underrepresented populations, particularly patients with advanced CKD and non-albuminuric disease.

Microvascular myocardial ischemia (MMI) in patients with T2DM may be influenced by the presence of concomitant obstructive coronary artery disease (OCAD). Our investigation focused on assessing the impact of OCAD on MMI and delineating the prognostic relevance of MMI.

This study included four groups: (1) control group without OCAD (n = 125), (2) control group with OCAD (n = 99); (3) T2DM patients without OCAD (n = 100); (4) T2DM patients with OCAD (n = 93). All patients received dynamic computed tomography myocardial perfusion imaging (CT-MPI) as well as coronary computed tomography angiography (CCTA). Univariate and multivariate linear regression analyses were performed to identify independent determinants of clinical characteristics and perfusion metrics related to MMI. Major adverse cardiovascular events (MACEs) were documented, and the prognostic significance of CT-MPI compared with clinical variables was assessed.

The myocardial blood flow (MBF) stepwise reduced from the control (OCAD-), T2DM (OCAD-), control (OCAD+) to T2DM (OCAD+) group (p < 0.05). Independent associations were observed between global MBF and OCAD or T2DM (OCAD: p < 0.05, R² = 0.154; T2DM: β = -11.96, p < 0.001, R² = 0.101). A significant association was observed between OCAD and global MBF in the circumstance of T2DM (R² = 0.176). An independent association was observed between the global MBF and MACEs (p < 0.05).

Dynamic CT-MPI combined with CCTA demonstrated that the presence of OCAD in T2DM patients is associated with a greater occurrence of MMI. MBF emerged as a robust predictor of cardiovascular outcomes in this population.

Women with pregestational diabetes mellitus (PGDM) are at increased risk of preeclampsia (PE) and are commonly prescribed aspirin prophylaxis based on clinical risk factors alone. First-trimester screening algorithms may allow a more individualized allocation of aspirin. We aimed to compare the association between three first-trimester aspirin allocation strategies and the incidence of preterm PE in women with PGDM in routine clinical practice.

This retrospective multicenter observational cohort study included 519 singleton pregnancies with PGDM managed at six tertiary hospitals in Spain between January 2017 and December 2022. Women were classified according to the strategy used to allocate aspirin prophylaxis: clinical risk factor-based prophylaxis, first-trimester algorithm-based screening without placental growth factor (PlGF), or algorithm-based screening including PlGF. The primary outcome was preterm PE (<37 weeks). Secondary outcomes included overall and severe PE, gestational age at delivery, spontaneous preterm birth, birthweight, small-for-gestational-age infants, and neonatal intensive care unit admission. Multivariable regression models were adjusted for prespecified maternal characteristics.

Among 519 pregnancies, 255 were managed using clinical risk factor-based prophylaxis, 119 using the algorithm without PlGF, and 145 using the algorithm with PlGF. Aspirin was prescribed to 100%, 16.8%, and 28.3% of women, respectively. Preterm PE rates were 4.7%, 5.9%, and 4.2%, respectively. After multivariable adjustment, no statistically significant differences in preterm PE were observed for the algorithm without PlGF (adjusted odds ratio [aOR] 1.89, 95% confidence interval [CI] 0.62-5.45) or with PlGF (aOR 1.33, 95% CI 0.41-3.91) compared with clinical risk factor-based prophylaxis. Secondary maternal and perinatal outcomes were also comparable across groups.

In women with PGDM, algorithm-based aspirin allocation strategies were associated with substantially lower aspirin exposure without evidence of increased preterm PE or adverse perinatal outcomes compared with clinical risk factor-based prophylaxis. However, given the observational design, baseline differences, and limited number of events, the study was not powered to demonstrate equivalence or exclude smaller clinically relevant differences. These findings should therefore be considered exploratory and require confirmation in adequately powered prospective studies.

TAPUR is a phase II basket trial evaluating the antitumor activity of commercially available targeted agents in patients with advanced cancer and genomic alterations. Results of two cohorts of patients with various solid tumors with FGFR1 or FGFR2 alterations treated with sunitinib are reported.

Eligible patients had measurable disease, Eastern Cooperative Oncology Group performance status 0-2, adequate organ function, and no remaining standard treatment options. The primary end point was disease control (DC), defined as objective response (OR) or stable disease (SD) of at least 16 weeks duration (SD16+). Low accruing histology-specific cohorts with FGFR1 or FGFR2 alterations treated with sunitinib were collapsed into two histology-pooled cohorts for this analysis. The hypothesized null DC rate of 15% was evaluated by a 1-sided exact binomial test (alpha .10; 82% power) per cohort. Secondary end points included OR, progression-free survival, overall survival, duration of response, duration of SD, and safety.

Sixty-four patients with 20 different cancer types with FGFR1 (N = 36) or FGFR2 (N = 28) alterations were enrolled from April 2016 to June 2024 and collapsed into two histology-pooled cohorts (FGFR1 and FGFR2) for analysis. Eight patients (all in the FGFR1 cohort) were not evaluable for efficacy. DC rates for the FGFR1 and FGFR2 cohorts were 21% (one-sided 90% CI, 12 to 100) and 39% (one-sided 90% CI, 27 to 100), respectively. The null hypothesis was not rejected for the FGFR1 cohort (P = .24) but was rejected for the FGFR2 cohort (P = .0015). Twenty patients had at least one treatment-related grade 3-5 adverse event (AE) or serious AE.

Sunitinib met the prespecified criteria to declare a signal of activity in patients with various solid tumors and FGFR2 alterations but not FGFR1 alterations.

Preoperative nodal assessment in colorectal cancer (CRC) remains imperfect, and uncertainty regarding pathological lymph node metastasis (LNM) may persist despite conventional imaging. Machine learning using routinely available preoperative information may provide complementary patient-level risk estimates without requiring radiomic feature extraction or molecular testing.

This study aimed to develop and externally validate machine learning models for preoperative estimation of pathologically confirmed LNM risk in patients with newly diagnosed CRC undergoing direct radical surgery without preoperative anticancer treatment, and to assess whether multivariable prediction adds information beyond clinical tumor stage (cT) alone.

This multicenter retrospective study included 2725 patients from 2 hospitals. The internal cohort (n=1074) was split into training (n=753) and internal test (n=321) sets, while 1651 patients from a second center formed the external validation cohort. Candidate predictors were routinely available preoperative clinical, laboratory, tumor-marker, imaging-based, and endoscopic biopsy variables. Predictors were selected using univariable and multivariable logistic regression (LR). Seven algorithms were evaluated: random forest (RF), support vector machine (SVM), LR, decision tree (DT), extreme gradient boosting (XGBoost), naive Bayes (NB), and light gradient boosting machine (LightGBM). Performance was assessed using discrimination, threshold-dependent classification metrics, calibration, and decision curve analysis (DCA). Shapley additive explanations (SHAP) were used for interpretation. Sensitivity analyses compared the selected predictors with all candidate predictors and cT alone.

Six predictors were retained: BMI, preoperative carcinoembryonic antigen, primary tumor site, cT, histological type, and tumor differentiation. RF was selected based on internal test performance. The area under the receiver operating characteristic curve (AUROC) was 0.803 (95% CI 0.756-0.849) in the internal test set and 0.776 (95% CI 0.755-0.797) in external validation. In external validation, accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 0.687, 0.677, 0.693, 0.569, and 0.781, respectively. The Brier score was 0.190, and the calibration slope was 1.061. cT contributed most in SHAP analysis; however, the 6-predictor RF model showed significantly higher discrimination than cT alone in both the internal test set (AUROC 0.803 vs 0.712; ΔAUROC=0.091; P<.001) and external validation cohort (AUROC 0.776 vs 0.707; ΔAUROC=0.069; P<.001). Discrimination did not differ significantly between the 6-predictor and all-predictor RF models.

We developed and externally validated a 6-predictor RF model for preoperative LNM risk estimation in patients with newly diagnosed CRC undergoing radical resection with regional lymph node dissection without preoperative anticancer treatment. The model showed moderate external discrimination and provided predictive information beyond cT alone. It is intended for research-stage adjunctive risk stratification and should not replace imaging, pathological evaluation, or clinical judgment. Prospective validation in broader populations and clinical settings is required before implementation.

Inflammation-based biomarkers may refine prognostic stratification in patients with metastatic renal cell carcinoma (mRCC). This study evaluated the prognostic value of the pretreatment C-reactive protein-to-albumin ratio (CAR) and systemic immune-inflammation index (SII) in patients with mRCC receiving first-line systemic therapy.

We retrospectively analyzed 117 patients who received first-line systemic therapy between January 2001 and April 2022. Pretreatment CAR and SII were evaluated as readily available blood-based inflammatory biomarkers. Overall survival (OS) was defined as the primary outcome, and progression-free survival (PFS) was defined as the secondary outcome. Exploratory cutoffs were CAR 0.0731 and SII 533.81.

High CAR and high SII were independently associated with shorter OS after adjustment for IMDC risk classification and nephrectomy status. The adjusted HRs were 2.36 for high CAR (95% CI, 1.30-4.27; p = 0.005) and 2.58 for high SII (95% CI, 1.42-4.69; p = 0.002). Patients with concurrent elevation of both CAR and SII had the shortest OS compared with those with neither marker elevated (HR, 6.39; 95% CI, 2.76-14.77; p < 0.001). Adding CAR and SII to International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) improved the optimism-corrected C-index for OS from 0.641 to 0.733.

Pretreatment CAR and SII were associated with OS in patients with mRCC receiving first-line systemic therapy. These readily available biomarkers may help refine OS risk assessment when used alongside established clinical factors, but external validation is required before clinical implementation.

Red breast syndrome (RBS) is a challenging complication of acellular dermal matrix (ADM)-assisted breast reconstruction. Its incidence and hematologic predictors in patients receiving neoadjuvant chemotherapy (NAC) remain poorly characterized.

This retrospective cohort study included 70 patients who underwent skin-sparing mastectomy with immediate implant-based reconstruction following NAC (January 2011-May 2025) at a single tertiary institution. Patients were stratified into ADM (n = 47) and Non-ADM (n = 23) groups. Within the ADM group, Firth penalized logistic regression with backward elimination identified preoperative variables independently associated with RBS. Optimal cutoffs were determined by the Youden Index. A composite hematologic scoring model (WBC + PLT + Ki-67 High, cutoff ≥2) was developed and internally validated using bootstrap resampling (2,000 iterations).

RBS occurred in 31.9% (15/47) of ADM patients versus 0% in Non-ADM patients (p = 0.001). The final model identified WBC (OR 1.235, 95% CI 1.066-1.502, p = 0.004), PLT (OR 1.013, 95% CI 1.001-1.028, p = 0.037), and Ki-67 High (OR 8.975, 95% CI 1.356-155.173, p = 0.020) as independently associated with RBS. Individual biomarkers showed modest discrimination (AUC 0.605-0.641, all p > 0.10), while the composite score achieved AUC = 0.816 (p < 0.001; sensitivity 86.7%, specificity 71.9%, NPV 92.0%). Bootstrap-corrected AUC was 0.817 (95% CI 0.636-0.959; optimism=-0.001). No significant temporal trend in RBS incidence was observed (Cochran-Armitage, p = 0.527).

RBS incidence is substantially elevated in post-NAC ADM patients. This exploratory, single-center study develops a hypothesis-generating combination score for preoperative RBS risk stratification using routine laboratory and pathology assessment. External validation in prospective multi-institutional cohorts is required before clinical application.