Researchers measured adherence to a Mediterranean lifestyle with a composite score ranging from 0 to 24. The score combined six domains: Mediterranean diet adherence, physical activity, water intake, sleep, social isolation and cooking activities. The investigators assessed the relationship between the lifestyle score and three cardiovascular outcomes: hypertension, myocardial infarction and stroke.

They used logistic regression models for both cross-sectional and longitudinal analyses, adjusting the models for age and sex. The cross-sectional models examined associations with existing hypertension, while the longitudinal models assessed associations with cardiovascular events occurring during follow-up. Higher adherence to the overall Mediterranean lifestyle score was significantly associated with lower odds of prevalent hypertension after adjustment for age and sex.

Because the finding was cross-sectional, it describes an association among participants who already had hypertension rather than demonstrating that the lifestyle pattern prevented, reversed or improved the condition. For the longitudinal analysis, however, the composite lifestyle score was not significantly associated with incident hypertension, myocardial infarction or stroke. This means the study did not find evidence of a statistically significant prospective relationship between the broad lifestyle score and those outcomes in the model presented.

It does not establish that no such relationship exists, because a nonsignificant result is not equivalent to proof of no association. The component-level analysis produced a more specific result: higher Mediterranean diet adherence was prospectively associated with lower odds of incident myocardial infarction. The study’s summary describes this as supporting the potential relevance of Mediterranean dietary habits for cardiovascular health in older age.

By contrast, the other individual lifestyle components examined—physical activity, water intake, sleep, social isolation and cooking activities—did not show significant adjusted associations with the cardiovascular outcomes analyzed. The distinction between the two forms of analysis is central to the results. The cross-sectional hypertension finding concerns the prevalence of an existing condition, whereas the myocardial infarction finding concerns the occurrence of a new event during follow-up.

The analysis of individual components also should not be conflated with the overall lifestyle score: the prospective association was reported for Mediterranean diet adherence, not for the full six-domain Mediterranean lifestyle pattern. As an observational study, the research can identify associations but cannot establish that following a Mediterranean lifestyle or a specific component caused better cardiovascular outcomes. The use of logistic regression and adjustment for age and sex also leaves the findings subject to the influence of other factors, while the sample of 565 older adults limits the conclusions that can be generalized.

Overall, the study offers a mixed rather than uniformly protective picture. Stronger adherence to the combined Mediterranean lifestyle score was linked to lower odds of existing hypertension, but the score was not significantly associated with new hypertension, myocardial infarction or stroke during follow-up. Within the individual lifestyle components, Mediterranean diet adherence alone was associated with lower odds of a subsequent myocardial infarction, a result that warrants attention while remaining observational rather than causal.

Subject of Research: Observational associations of Mediterranean lifestyle and diet adherence with cardiovascular outcomes in older adults

Article Title: Associations between Mediterranean lifestyle and its components with cardiovascular outcomes among community-dwelling older adults

Article References: Coelho Júnior, H. J., & Marzetti, E. (2026). Associations Between Mediterranean Lifestyle and Its Components With Cardiovascular Outcomes Among Community-Dwelling Older Adults. Frontiers in Epidemiology, 6, 1933837. https://doi.org/10.3389/fepid.2026.1933837

Image Credits: AI Generated

DOI: 10.3389/fepid.2026.1933837

Keywords: Mediterranean lifestyle, Mediterranean diet, older adults, hypertension, myocardial infarction, stroke, cardiovascular outcomes, observational study, England, ELSA, Associations, between

The model, named DROID-RV — short for Dimensional Reconstruction of Imaging Data-Right Ventricle — was trained on an extraordinary volume of real-world clinical data: 17,141 ambulatory cardiology patients, spanning 51,188 echocardiographic studies and 383,881 individual video clips. Each of those clips captured the beating heart from the standard windows used in transthoracic echocardiography, the ubiquitous ultrasound scan performed millions of times a year worldwide. By learning from hundreds of thousands of labeled examples, DROID-RV absorbed the visual grammar of the right ventricle in a way no single human reader ever could.

Technically, the model is built on a MoViNet backbone, an efficient video-recognition neural network architecture originally designed for mobile video analysis. The researchers cut the network at its final convolutional layer, flattened the resulting feature maps, and passed them through a dense layer of 256 nodes connected to multiple output heads. Three classification heads predict patient sex, right ventricular systolic function category and right ventricular cavity size category, while a regression head outputs two continuous values: age and right ventricular end-diastolic diameter, the key linear measurement of chamber size taken at the moment the ventricle is most relaxed and full. Dropout layers between the dense connections help prevent the network from simply memorizing its training data.

An interesting wrinkle in the training strategy is that the model was first pre-trained with an identical architecture but only a single regression output — age. This kind of auxiliary task forces the network to learn general features of cardiac anatomy and image quality before being asked to tackle the harder, more clinically specific problem of measuring the right ventricle. It is a form of curriculum learning: master the easy, ubiquitous signal first, then refine toward the target measurement. The team also leveraged RVENet, a large public echocardiographic dataset for right ventricular assessment, whose creators they explicitly credit in the paper.

Validation was deliberately broad. The researchers tested DROID-RV in 9,112 patients drawn from primary care — a very different population from the cardiology clinics where the training data came from — and in 831 patients whose right ventricular ejection fraction had been measured by three-dimensional echocardiography, a more demanding and quantitative technique that is rarely used in routine practice. Across these test samples, the model accurately estimated right ventricular end-diastolic diameter and correctly identified right ventricular systolic dysfunction. The authors are candid about the model’s limits: prediction error grows at the extremes of right ventricular size and function, precisely where the most abnormal hearts live and where clinical judgment matters most.

Why has the right ventricle been so hard to measure in the first place? Unlike the thick-walled, bullet-shaped left ventricle, the right ventricle is a thin-walled, crescent-shaped structure wrapped around the left side of the heart. Its complex geometry defies the simple prolate-ellipse assumptions that make left ventricular volume estimation relatively straightforward from two-dimensional images. Professional guidelines acknowledge the problem, and prior studies have documented poor interobserver concordance even among experienced echocardiographers asked to grade right ventricular size and systolic function. Measurements that vary from reader to reader are measurements that vary from lab to lab — and that undermines their prognostic value.

This is where the deep learning approach changes the calculus. A neural network applies exactly the same visual criteria to every clip it sees, producing measurements with perfect reproducibility even if its absolute accuracy is bounded by the quality of two-dimensional imaging. The team demonstrated this consistency using saliency maps based on gradient-weighted class activation mapping, a technique that highlights the image regions driving the network’s predictions. The saliency videos published with the paper show the model focusing on the right ventricular free wall and cavity in ways that correspond to how a trained sonographer would assess dilation and hypokinesis — evidence that the network learned anatomically meaningful features rather than exploiting spurious correlations.

The most consequential finding, however, is prognostic. When the researchers stratified patients by the model’s predicted right ventricular size and function, they observed clear differences in the cumulative incidence of major outcomes: mortality, incident atrial fibrillation and incident heart failure all clustered according to the AI’s assessment of this one chamber. This aligns with a growing body of literature linking right ventricular ejection fraction to major adverse cardiovascular events and linking right ventricular structure to new-onset atrial fibrillation, but it extends those associations to predictions generated automatically, at scale, from standard two-dimensional scans that already exist in electronic health records by the hundreds of thousands.

The work also fits into a broader arc of cardiovascular AI research from the same ecosystem. Previous efforts from this group showed that deep learning assessment of left heart structure and function predicts cardiovascular outcomes, and other teams have demonstrated video-based AI for beat-to-beat assessment of cardiac function and automated interpretation of systolic and diastolic performance. What distinguishes the new study is its focus on the right side of the heart — the chamber that two-dimensional echocardiography handles worst — and its dual validation strategy spanning both a general primary care population and a three-dimensional echocardiography reference standard. The researchers followed reporting guidelines for observational studies and for machine learning evaluation in cardiovascular imaging, and they used natural language processing methods previously validated for cohort construction in electronic health records.

The practical implications are striking. Because the model runs on standard transthoracic echo videos, it could in principle retrofit quantitative right ventricular assessment onto the enormous existing archive of echocardiograms, extracting prognostic information from studies performed years ago without a single new scan. The team has released model code and data processing scripts through the Broad Institute’s machine learning for health repository, along with synthetic test data demonstrating the training and inference pipelines, and limited de-identified source data sufficient to recreate the published figures. Real clinical deployment will require prospective validation, regulatory review and careful attention to the model’s degraded performance at the extremes of right ventricular pathology — but the direction of travel is unmistakable. An measurement that was once subjective, inconsistent and often skipped can now be generated automatically for every patient, every study, every time. And as this study shows, that measurement carries real information about who will live, who will develop atrial fibrillation, and who will develop heart failure. The forgotten chamber of the heart has finally found its voice, and it is speaking through the mathematics of deep neural networks.

Subject of Research: Deep learning assessment of right ventricular size and function from echocardiography for cardiovascular risk prediction

Article Title: Deep learning-enabled assessment of right ventricular size and function is associated with cardiovascular outcomes

Article References: Al-Alusi, M. A., Kopparapu, K., Singh, P., di Achille, P., Reeder, C., Lau, E. S., Shnitzer, T., Andrews, C. T., Kany, S., Rämö, J. T., Haimovich, J. S., Khurshid, S., Picard, M. H., Ho, J. E., Batra, P., Maddah, M., Lubitz, S. A., & Ellinor, P. T. (2026). Deep learning-enabled assessment of right ventricular size and function is associated with cardiovascular outcomes. Nature Cardiovascular Research. https://doi.org/10.1038/s44161-026-00886-4

Image Credits: AI Generated

DOI: 10.1038/s44161-026-00886-4

Keywords: deep learning, echocardiography, right ventricle, cardiovascular outcomes, artificial intelligence, medical imaging, heart failure, atrial fibrillation, risk prediction, cardiology, neural networks, Nature Cardiovascular Research

To understand how a diabetes drug touches the vascular system, it helps to start with the hormone it mimics. GLP-1 is an incretin hormone released by enteroendocrine L-cells in the distal ileum and colon after a meal. When glucose or other nutrients arrive in the gut, these cells close ATP-dependent potassium channels, depolarize the membrane, open L-type calcium channels and secrete GLP-1 into the bloodstream. The hormone then amplifies insulin secretion from pancreatic beta cells by two- to three-fold compared with intravenous glucose, a phenomenon known as the incretin effect. It also delays gastric emptying and suppresses glucagon release. In type 2 diabetes, this incretin effect is blunted, partly through impaired GLP-1 function and reduced receptor expression, which is precisely why pharmacological boosting of the pathway has proven so effective.

Native GLP-1, however, is a fleeting molecule. The enzyme dipeptidyl peptidase-4 cleaves it within minutes, leaving a circulating half-life of roughly ninety seconds, so a substantial fraction of the hormone is inactivated before it ever reaches its targets. Therapeutic agonists were engineered to escape this fate. Exenatide, derived from a peptide found in the saliva of the Gila monster, survives for about 2.4 hours and was approved in 2005 for twice-daily injection. Liraglutide carries a fatty-acid side chain that binds reversibly to serum albumin, extending its half-life to 13 to 15 hours after subcutaneous injection. Semaglutide, dulaglutide and albiglutide push persistence further still, with half-lives long enough to permit once-weekly dosing. Tirzepatide adds a second layer of sophistication by engaging the receptor for the other incretin hormone, GIP, as well as GLP-1.

All of these molecules converge on a single target: the GLP-1 receptor, a class B G protein-coupled receptor of 463 amino acids found in the pancreas, gastrointestinal tract, lungs, kidneys, central nervous system and, in mice, monkeys and humans, the heart. When activated, the receptor can couple to the Gs protein to raise cyclic AMP, to Gq/11 to elevate intracellular calcium, and to beta-arrestin to trigger ERK1/2 signaling. Crucially, different ligands bias the receptor toward different downstream cascades, a property known as biased agonism. The review highlights this as one plausible explanation for why structurally distinct agonists do not lower blood pressure to the same degree: they are not simply switching the receptor on, they are steering it toward different intracellular programs.

The vascular story begins in the endothelium. In human umbilical vein endothelial cells exposed to GLP-1, receptor activation recruits the phosphatidylinositol 3-kinase/Akt pathway, which phosphorylates and activates endothelial nitric oxide synthase, raising the bioavailability of nitric oxide, the principal relaxing factor of the vessel wall. A parallel protein kinase A-dependent route to nitric oxide production operates alongside it. Together these converging pathways relax vascular smooth muscle and reduce peripheral resistance. Downstream, activation of AMP-activated protein kinase and suppression of nuclear factor-kappa B signaling cut vascular oxidative stress, adhesion molecule expression and inflammatory cytokine release, linking the acute vasoactive effects of the receptor to the slower, anti-atherosclerotic remodeling of the vessel wall.

The heart and kidneys contribute their own mechanisms. In atrial cardiomyocytes, GLP-1 receptor activation couples to Epac2, triggering the secretion of atrial natriuretic peptide, which raises cyclic GMP and promotes both vasodilation and renal sodium excretion. Direct natriuresis has been documented in healthy, obese and type 2 diabetic individuals, offering a plausible route by which plasma volume, and with it blood pressure, is reduced. Evidence from mouse studies further suggests that exendin-4 can dampen angiotensin II signaling in the kidney, inhibiting the transforming growth factor beta1 and Smad3 pathway that drives fibrosis. Yet here the literature fractures: a clinical study of dulaglutide found no significant changes in plasma renin activity, serum aldosterone or related neurohormonal markers, leaving the role of the renin-angiotensin-aldosterone system unresolved and flagged by the review as a priority for further investigation.

The clinical data, drawn from cardiovascular outcome trials and pooled analyses, paint a picture of modest but persistent effect. Exenatide at 10 micrograms twice daily reduced systolic pressure by a least-squares mean of 2.8 mmHg across 2,171 patients, with the largest difference, 8.2 mmHg versus placebo, seen in people whose baseline systolic pressure exceeded 150 mmHg. Once-weekly exenatide lowered systolic pressure by 1.6 mmHg in the EXSCEL trial of nearly 14,752 patients. Dulaglutide at 1.5 milligrams produced a 2 to 3 mmHg reduction evident within four weeks and sustained through 26 weeks, accompanied by a fall in 24-hour pulse pressure. Semaglutide at 1.0 milligram weekly lowered systolic pressure by 2.6 mmHg in SUSTAIN-6, and oral semaglutide matched that figure at week 83 in PIONEER-6. Liraglutide managed 1.2 mmHg over 36 months in LEADER, while lixisenatide achieved only 0.8 mmHg in ELIXA. Diastolic pressure, by contrast, was largely untouched.

Two patterns emerge from those numbers. First, the effect is drug-specific: agents differ by more than threefold in the magnitude of systolic reduction they deliver, consistent with the biased agonism observed at the receptor. Second, the benefit is conditional. People with normal blood pressure at baseline showed no between-group differences in the trials, suggesting that GLP-1 receptor agonists act as regulators of an elevated system rather than as blanket antihypertensives. The review also draws a careful temporal distinction that has muddied the literature. Acutely, GLP-1 receptor stimulation of sinoatrial node pacemaker cells and brainstem autonomic neurons raises heart rate and can transiently nudge mean arterial pressure upward, particularly after dose escalation. Chronically, sustained therapy produces a net systolic reduction as weight loss, improved glycemic control and the vascular, renal and anti-inflammatory mechanisms accumulate and outweigh the initial pressor response. The two effects operate on different timescales and are not contradictory, but conflating them has fueled apparent inconsistencies across studies.

What the mechanisms cannot yet claim is firm human validation. Aside from the natriuresis and endothelial function data, most of the mechanistic evidence comes from animal models and in vitro systems, and blood pressure was rarely a pre-specified primary endpoint in the major cardiovascular outcome trials from which the clinical numbers are extracted. That makes it difficult to determine whether the observed 1 to 3 mmHg reductions translate into meaningful antihypertensive benefit independent of glycemic control or weight loss, and head-to-head comparisons between agents are lacking. The review calls for trials that place blood pressure at the center of the design, translational studies in human subjects to confirm the proposed nitric oxide, atrial natriuretic peptide and renin-angiotensin pathways, and stratified analyses to identify which patients, most plausibly those with elevated baseline pressure and coexisting type 2 diabetes, stand to gain the most.

Even within those limits, the synthesis carries a striking implication. A drug class developed to restore a gut hormone signal has turned out to engage nearly every major axis of cardiovascular regulation: endothelial nitric oxide signaling, natriuretic peptide release, renal sodium handling, vascular inflammation and atherosclerotic plaque biology. Liraglutide has been shown to suppress angiotensin II-induced inflammatory cascades in vessel walls, preventing the expression of ICAM-1, VCAM-1 and P-selectin on endothelial cells and restoring nitric oxide levels. Exenatide modulates matrix metalloproteinases in human coronary artery cells and shifts macrophages from a pro-inflammatory M1 state toward a reparative M2 phenotype, stabilizing atherosclerotic lesions. Semaglutide and liraglutide reduce plaque development in mice through AMPK activation and lowered proinflammatory cytokines. The blood pressure effect, small as it is, may be the visible surface of a much deeper vascular reprogramming, and understanding it fully could determine how these blockbuster drugs are positioned in the broader campaign against cardiovascular disease.

Subject of Research: Blood pressure regulation by glucagon-like peptide-1 receptor agonists and its cardiovascular mechanisms

Article Title: Glucagon‐Like Peptide‐1 Agonists and Blood Pressure Regulation: Molecular Mechanisms and Cardiovascular Implications

Article References: Alharbi, N. H. J. (2026). Glucagon‐Like Peptide‐1 Agonists and Blood Pressure Regulation: Molecular Mechanisms and Cardiovascular Implications. Pharmacology Research & Perspectives, 14(5), Article e70329. https://doi.org/10.1002/prp2.70329

Image Credits: AI Generated

DOI: 10.1002/prp2.70329

Keywords: GLP-1 receptor agonists, blood pressure, hypertension, type 2 diabetes, nitric oxide, endothelial function, natriuresis, atrial natriuretic peptide, cardiovascular outcomes, semaglutide, liraglutide, incretin effect

The scale of the underlying clinical problem explains the intensity of the research effort. In 2024, an estimated 588.7 million adults worldwide were living with diabetes, more than 90 percent of them with the type 2 form, and prevalence is projected to reach 852.5 million by 2050. Type 2 diabetes is not merely a disorder of blood sugar: cardiovascular disease was reported in roughly a third of patients in a 13-country study, diabetic kidney disease affects up to 35 percent of patients and remains a leading cause of end-stage renal disease, and the frequent coexistence of obesity accelerates disease progression. These realities have pushed therapeutic priorities beyond short-term glycemic targets toward durable metabolic control, reduction of cardiovascular and renal risk, weight management and long-term treatment sustainability.

To chart the field’s development, the researchers searched the Web of Science Core Collection from January 2004 to December 2025, using a strategy that combined drug-class terms, generic and brand names of individual agents and disease-specific terms refined with proximity operators. Only original research articles in English were included, and two investigators independently screened all records against a predefined eligibility manual. The team then cleaned and standardized the data meticulously: country and institutional affiliations were harmonized, author keywords were consolidated across spelling and synonym variants, and drug names were standardized at two levels, merging formulations of the same agent for co-occurrence analyses while retaining regimen-level terms such as oral semaglutide for timeline and burst analyses. VOSviewer, CiteSpace and R handled the network construction, burst detection and statistical processing, and an independent PubMed search confirmed that more than 97 percent of the most-cited Web of Science articles were recoverable across databases.

The headline finding is explosive growth. Annual output rose from just 7 articles in 2004 to 589 in 2025. Studies restricted to selective GLP-1 receptor agonists accounted for 94.86 percent of the entire corpus, but studies involving GLP-1-based multi-receptor agonists, which engage additional metabolic hormone receptors, first appeared in 2020 and by 2025 together with mixed comparative studies made up 14.09 percent of that year’s output. The subject-category breakdown shows a literature spanning far beyond endocrinology and metabolism, which dominated at 55.03 percent, into pharmacology, general medicine, experimental medicine and cardiac and cardiovascular systems, reflecting the drugs’ widening clinical footprint.

Geographically, 80 countries and regions contributed, but the distribution was strikingly unequal. Under fractional counting, the ten most productive countries accounted for 79.01 percent of output, with the United States and China alone contributing 43.11 percent, and a country-level Gini coefficient of 0.837 signaled profound inequality. The United States led on nearly every measure, with 1,558 articles, 112,863 citations and the strongest collaboration links, while the United Kingdom and Denmark achieved higher citations per publication than the United States despite smaller outputs. China ranked second in publication volume but only tenth in total collaboration strength, and its multiple-country publication proportion was markedly lower than those of Germany, the United Kingdom, Canada and the Netherlands, illustrating that output, citation influence and collaboration intensity are distinct dimensions of national research performance.

The institutional analysis revealed a research ecosystem built around both pharmaceutical and academic hubs. Novo Nordisk and Eli Lilly ranked first and second in both full-counted publication output and total citations, with 426 and 343 articles and 43,640 and 32,211 citations respectively, and they remained the top two contributors even after fractional allocation of multi-institutional papers. Among academic centers, the University of Toronto, the University of Texas Southwestern Medical Center and the University of North Carolina stood out for citation impact. Institutional output followed a long-tailed distribution with a Gini coefficient of 0.682, yet the top ten institutions captured only 11.26 percent of fractional output, meaning no small group monopolized the field. At the author level, dispersion was even greater: the ten most productive researchers, led by Julio Rosenstock with 75 articles and a dataset-specific h-index of 41, accounted for just 1.62 percent of total fractional output, and 82 of 83 threshold-eligible authors formed a single connected co-authorship network of ten clusters.

The thematic evolution tells perhaps the most compelling story. Keyword co-occurrence analysis grouped the 100 most frequent author keywords into six clusters spanning incretin biology, individual therapies, glycemic management, obesity, cardiorenal complications and real-world evaluation. Timeline and burst analyses then revealed four developmental stages: a foundational period from 2004 to 2008 centered on incretin physiology and early exenatide trials; a therapeutic expansion phase from 2009 to 2015 dominated by liraglutide and the LEAD program; a cardiovascular-outcomes period from 2016 to 2020 shaped by landmark trials within a regulatory environment created by the 2008 US Food and Drug Administration cardiovascular-risk guidance; and, from 2021 onward, a phase of cardiovascular-kidney-metabolic integration featuring semaglutide, the dual GIP/GLP-1 agonist tirzepatide, obesity, chronic kidney disease, oral formulations and real-world evidence. Burst detection captured this shift quantitatively, with the strongest keyword burst belonging to GLP-1 itself from 2008 to 2018, and recent bursts for chronic kidney disease, fixed-ratio combination therapy and oral semaglutide extending through 2025.

Citation analysis confirmed which individual studies drove these transitions. When citations were normalized within publication year to remove the advantage of older papers, the LEADER trial of liraglutide by Marso and colleagues ranked first, with 6,891 total citations and a normalized score of 62.94, meaning it received nearly 63 times the mean citations of publications from the same year. The 2024 trial of semaglutide in patients with type 2 diabetes and chronic kidney disease ranked second despite its short citation window, followed by the REWIND dulaglutide trial and the head-to-head comparison of tirzepatide with semaglutide. Six of the top ten appeared in the New England Journal of Medicine and four in The Lancet. Among cited references, LEADER also produced the strongest citation burst, and the analysis showed influence migrating from early exenatide trials through the LEAD program and ADA/EASD consensus statements toward cardiorenal outcome trials and clinical guidance, with seven references still bursting through 2025.

The journal landscape added a further layer of nuance. The 3,736 articles were spread across 627 journals, but a recognizable specialty core emerged, led by Diabetes, Obesity and Metabolism with 494 articles, followed by Diabetes Therapy and Diabetes Care. Co-citation rankings told a different story: Diabetes Care was the most co-cited journal, but the New England Journal of Medicine and The Lancet were highly co-cited despite publishing few of the included articles, suggesting that landmark trials achieve their widest influence through general medical journals while the cumulative development of the evidence remains anchored in specialist outlets. Dual-map overlay analysis showed clinically oriented articles drawing on both molecular-biological and health-services literature, consistent with bidirectional translation between incretin biology, therapeutic development and outcomes research.

The authors are careful about what these bibliometric signals do and do not mean. Citation counts measure scholarly attention, not methodological quality or clinical benefit, and institutional prominence based on affiliations should not be read as evidence of funding involvement or commercial influence. They also note that the evidence base remains uneven: multi-receptor agonists other than tirzepatide, such as retatrutide and survodutide, have been studied mainly for short- to intermediate-term glycemic and weight outcomes, real-world data document substantial discontinuation and reinitiation, patient-experience research is strikingly thin, and racial, ethnic and socioeconomic disparities in trial participation and drug use persist. Combined with the geographic concentration documented here, these gaps suggest that the next phase of GLP-1 research will need to extend beyond efficacy and cardiovascular outcomes into long-term effectiveness, treatment persistence, equity and the populations and care settings that the current literature has largely left behind.

Subject of Research: Bibliometric analysis of research on GLP-1 receptor agonists and GLP-1-based multi-receptor agonists in type 2 diabetes mellitus

Article Title: Global Landscape and Thematic Evolution of Selective GLP‐1 Receptor Agonists and GLP‐1–Based Multi‐Receptor Agonists in Type 2 Diabetes Mellitus: A Bibliometric Analysis

Article References: Wang, Y., Liu, Z., Wang, S., Lv, C., El‐Seedi, H. R., Khalifa, S. A. M., & Wang, H. (2026). Global Landscape and Thematic Evolution of Selective GLP ‐1 Receptor Agonists and GLP ‐1–Based Multi‐Receptor Agonists in Type 2 Diabetes Mellitus: A Bibliometric Analysis. Endocrinology, Diabetes & Metabolism, 9(6), Article e70351. https://doi.org/10.1002/edm2.70351

Image Credits: AI Generated

DOI: 10.1002/edm2.70351

Keywords: GLP-1 receptor agonists, type 2 diabetes, bibliometrics, semaglutide, tirzepatide, liraglutide, cardiovascular outcomes, chronic kidney disease, obesity, incretin biology, research collaboration, citation analysis

The study, led by Jorge Dahdal of Amsterdam University Medical Center together with colleagues from Turku University Hospital in Finland and several European institutions, is notable for its technical rigor. Every patient underwent both coronary computed tomography angiography (CCTA) and positron emission tomography (PET) myocardial perfusion imaging using oxygen-15 labeled water, a tracer considered the gold standard for quantifying absolute blood flow to the heart muscle. Rather than relying on the subjective, visual assessments that have long dominated clinical practice, the team deployed an FDA-cleared AI software platform to measure plaque volume in every coronary segment larger than 1.5 millimeters in diameter. The software distinguishes atherosclerotic tissue from epicardial fat and the vessel lumen, sums the volume of every lesion, and normalizes that total to the overall volume of the vessel tree. The resulting metric, percent atheroma volume or PAV, expresses the proportion of the coronary artery wall occupied by plaque — a continuous, quantitative measure of how much atherosclerosis a patient carries.

On the functional side, the researchers quantified hyperemic myocardial blood flow, or hMBF, the rate at which blood reaches the heart muscle when it is pushed to its maximum demand. Patients abstained from caffeine for at least 24 hours before their scans, and pharmacologic hyperemia was induced with intravenous adenosine at 140 micrograms per kilogram per minute. Dedicated software packages at the two centers, CardiacVUer in Amsterdam and Carimas in Turku, generated parametric flow maps across the standard 17-segment model of the left ventricle. The team defined regional hMBF as the lowest mean flow across two contiguous myocardial segments, a deliberately conservative measure that captures focal flow reductions without diluting them in a whole-heart average. Perfusion was classified as normal above 2.3 milliliters per minute per gram and graded as mildly, moderately, or severely reduced below that threshold. The two measures were, unsurprisingly, related: patients with more plaque tended to have lower hyperemic flow, with a moderate inverse correlation (Spearman’s rho of -0.47).

The cohort itself reflected the messy reality of real-world cardiology. Between 2007 and 2016, symptomatic patients with suspected coronary artery disease and no prior cardiac history were enrolled at two centers with different imaging philosophies. In Amsterdam, combined CCTA and PET perfusion imaging was performed routinely in all referred patients, while in Turku, PET was performed selectively when CCTA suggested obstructive disease. The patients had a mean age of 62 years, 54 percent were male, 58 percent had hypertension, and 18 percent had diabetes. Median percent atheroma volume was 7.9 percent, with nearly 28 percent of patients showing extensive plaque burden, and impaired regional perfusion was detected in roughly half the cohort. Twenty percent of patients underwent early revascularization — stenting or bypass surgery within six months of imaging — a fact that would prove central to interpreting the results.

Over a median follow-up of 7.1 years, extending as far as 13.3 years, 185 patients — 13.4 percent of the cohort — experienced the composite outcome of all-cause death, non-fatal myocardial infarction, or unstable angina. Deaths accounted for just over half of these events, followed by heart attacks and unstable angina. The cumulative event rate climbed from 5.2 percent at three years to 9.5 percent at six years and 12.1 percent at nine years. Patients who suffered events had dramatically higher plaque burden than those who did not — a median PAV of 15.4 percent versus 7.0 percent — and significantly lower regional blood flow, 1.85 versus 2.38 milliliters per minute per gram. Kaplan-Meier survival curves showed a stepwise deterioration in event-free survival with each increasing stage of plaque burden and each grade of perfusion impairment, a visual gradient that foreshadowed the statistical findings to come.

The heart of the analysis lay in a series of multivariable Cox regression models that pitted the two imaging metrics against each other while adjusting for age, sex, hypertension, diabetes, and early revascularization. When each measure was considered alone, both predicted events at every timepoint. But when both were entered into the same model — a head-to-head test of independent prognostic value — a clear division of labor emerged. Each 1 percent increase in percent atheroma volume raised the hazard of an event by roughly 3.5 to 4.7 percent at all three timepoints, with adjusted hazard ratios of 1.047, 1.035, and 1.036 at three, six, and nine years respectively, all highly statistically significant. Regional hMBF, by contrast, remained independently predictive at three years (a hazard ratio of 1.050 per 0.1 milliliter per minute per gram decrease, p = 0.004) and six years (1.028, p = 0.024), but the association weakened to statistical insignificance by nine years (1.020, p = 0.063).

Why would ischemia’s predictive power fade while plaque burden’s endured? The answer, the researchers argue, lies largely in what happened after the scans were taken. Interaction analysis revealed that early revascularization significantly modified the prognostic associations of both metrics, suggesting that opening blocked arteries changes the natural history that the imaging had captured. When the team repeated the analysis after excluding the 281 patients who underwent early revascularization, the picture transformed: both plaque burden and regional blood flow were significantly associated with outcomes at all three timepoints, including nine years. In other words, untreated ischemia retains its full prognostic force over the long term, but once clinicians relieve it with stents or bypass grafts, the flow measurement no longer reflects the risk it once did — the risk has been, at least partly, defused. Plaque burden, by contrast, is not so easily erased; it represents the cumulative atherosclerotic substrate that continues to generate risk regardless of any single intervention.

These findings land in the middle of an ongoing and often heated debate about the value of ischemia detection. Landmark randomized trials such as COURAGE and ISCHEMIA showed that revascularization guided by ischemia, while effective at relieving symptoms, does not reliably improve hard clinical outcomes compared with guideline-directed medical therapy in stable coronary disease. Skeptics have used those results to question whether ischemia imaging is worth the cost and radiation. But the authors of the new study point out that those trials relied on earlier-generation perfusion techniques or even non-imaging exercise testing, which may have failed to fully characterize the burden and complexity of ischemia. Quantitative PET perfusion imaging offers a continuous, precise measurement rather than a binary yes-or-no answer, and observational studies have consistently shown it adds prognostic information beyond anatomy. This study is among the first to demonstrate that PET-derived ischemia remains independently predictive even when integrated with AI-based quantitative plaque analysis, a technique rapidly entering clinical practice.

The clinical implications are correspondingly two-pronged. Recent scientific statements from the American College of Cardiology and the American Heart Association now endorse AI-based quantitative plaque analysis to enhance risk assessment and guide preventive therapy in patients with plaque visible on CCTA. The new data suggest that percent atheroma volume may be particularly valuable for long-term risk stratification, especially in patients with non-obstructive disease whose anatomic risk is otherwise underestimated, potentially justifying more intensive lipid-lowering and preventive strategies. Regional hyperemic blood flow, meanwhile, identifies patients at elevated near-term risk and may inform symptom-directed management and closer short-term follow-up. The two measurements, in effect, answer different questions: plaque burden describes the size of the reservoir of future risk, while ischemia signals how much of that risk is about to be expressed. Staging frameworks linking plaque volume to preventive treatment targets have been proposed, though optimal thresholds remain under active investigation.

The authors are careful to acknowledge the study’s limitations. As a retrospective observational analysis, it lacked comprehensive data on post-imaging medical therapy, used all-cause rather than cardiovascular-specific mortality, and involved different scanner hardware across the two centers. The findings pertain specifically to absolute flow measurements from oxygen-15 water PET and may not extend directly to flow reserve indices or other tracers. Residual confounding is an inherent risk, particularly around the selection of patients for early revascularization. Yet the consistency of the results across alternative plaque and perfusion metrics, different revascularization definitions, and both imaging protocols strengthens the central conclusion: anatomy and function are not rivals but complementary windows onto coronary disease, each with its own temporal signature. For a field still deciding how best to deploy its increasingly powerful imaging arsenal, that temporal map — plaque for the long game, ischemia for the near term — may prove one of the most actionable findings yet.

Subject of Research: Time-dependent prognostic value of coronary plaque burden and hyperemic myocardial blood flow in suspected coronary artery disease

Article Title: Time-dependent prognostic value of coronary plaque burden and hyperemic myocardial blood flow

Article References: Dahdal, J., Maaniitty, T., Jukema, R. A., Nurmohamed, N. S., Raijmakers, P. G., Driessen, R. S., Mäenpää, M., Bär, S., Planken, R. N., van Royen, N., Bax, J. J., Saraste, A., Messaoudi, S. E., Knuuti, J., Knaapen, P., & Danad, I. (2026). Time-dependent prognostic value of coronary plaque burden and hyperemic myocardial blood flow. European Journal of Nuclear Medicine and Molecular Imaging. https://doi.org/10.1007/s00259-026-08135-3

Image Credits: AI Generated

DOI: 10.1007/s00259-026-08135-3

Keywords: coronary artery disease, CCTA, PET imaging, plaque burden, myocardial ischemia, percent atheroma volume, hyperemic myocardial blood flow, risk stratification, artificial intelligence, revascularization, cardiovascular outcomes, nuclear medicine

The research, led by Tasneem Al-Namshah and colleagues at Sana’a University with collaborators at Al-Razi University, enrolled 216 patients diagnosed with STEMI who received streptokinase at a tertiary hospital in Sana’a between 2024 and 2025. Yemen, devastated by years of armed conflict, offers a rare and sobering window into how cardiovascular care functions when resources are scarce and infrastructure is shattered. The team assessed each patient’s socioeconomic status using a composite score adapted to the local context, capturing the realities of income, education, and living conditions in a country where conventional measures of wealth may not translate cleanly. Patients were then followed through their hospital stay to track whether the drug succeeded in reopening the infarct-related artery and how they fared clinically.

The technical definition of success was rigorous. Reperfusion failure was defined as failure to achieve at least 50 percent resolution of the elevated ST segments on the electrocardiogram at 90 minutes after thrombolysis, a standard surrogate indicating that the occluded coronary artery has not been adequately reopened and that myocardial tissue remains starved of blood. By this measure, the socioeconomic gradient was dramatic. Successful reperfusion was achieved in only 27.0 percent of patients in the low socioeconomic group, compared with 65.8 percent of those of intermediate status and 80.6 percent of high-status patients, a difference that was highly statistically significant. In other words, the poorest patients failed thrombolysis nearly three times as often as the wealthiest, and more than twice as often as those in the middle tier.

Part of the explanation lies in time. The study documented that low-socioeconomic-status patients arrived at the hospital far later after symptom onset, with a median symptom-to-door time of 360 minutes compared with 240 minutes for their higher-status counterparts, a difference that was statistically significant. Total ischemic times, which encompass the entire duration from the first symptom to reperfusion, followed the same pattern at 434 versus 330 minutes. This matters because thrombolytic efficacy is strongly time-dependent: the longer a clot has matured and the more myocardium has been jeopardized, the less likely fibrinolysis is to achieve complete and sustained reperfusion. Six hours of delay, as seen in the poorest group, pushes patients well beyond the window in which streptokinase performs optimally.

The downstream clinical consequences were equally stark. In-hospital mortality climbed along the socioeconomic gradient, from zero percent among high-status patients to 0.9 percent in the intermediate group and 6.8 percent among the poorest. Major adverse cardiovascular events, a composite endpoint typically encompassing death, reinfarction, and other serious cardiac complications, affected 18.9 percent of low-status patients versus 9.9 percent of intermediate and 6.5 percent of high-status patients. Both gradients were statistically significant, painting a coherent picture in which poverty was associated not only with failed reperfusion but with worse survival and more complications during the same hospital admission.

Crucially, the investigators did not stop at simple associations. They employed multivariable logistic regression, adjusting for potential confounders, and found that low socioeconomic status remained independently associated with markedly higher odds of reperfusion failure, with an odds ratio of 16.19 and a 95 percent confidence interval of 4.92 to 53.29. To probe the robustness of this finding against unmeasured confounding, the team calculated an E-value, a quantitative sensitivity metric indicating how strong an unmeasured factor would need to be to explain away the observed association. The E-value of 31.88 is extraordinarily high, suggesting that no plausible unmeasured variable, short of an implausibly powerful one, could plausibly account for the entire effect. This analytical rigor strengthens the argument that the socioeconomic gradient reflects a genuine causal pathway rather than statistical artifact.

One particularly informative finding concerns what did not differ. Rates of post-thrombolysis percutaneous coronary intervention, the rescue or adjunctive procedure performed after clot-dissolving drugs, were similar across socioeconomic groups. This suggests that the disparity was not driven by unequal access to mechanical revascularization once patients were inside the hospital. Instead, the damage appears to be done before patients ever reach the hospital doors, in the hours lost to delayed recognition of symptoms, lack of transportation, financial barriers to seeking care, and the logistical chaos of a conflict zone. The authors argue that context-appropriate interventions, including subsidized emergency transport and pharmaco-invasive networks that link thrombolysis in peripheral settings to timely angiography, are essential to mitigate these prehospital delays and promote equitable STEMI care.

The Yemeni findings resonate with a broader literature linking socioeconomic position to cardiovascular outcomes, but they sharpen the picture in an important way. Most prior studies have examined disparities in access to advanced procedures or in long-term outcomes shaped by secondary prevention and rehabilitation. This study isolates a more fundamental inequity: the biological efficacy of the initial reperfusion therapy itself. If the clot-dissolving drug fails more often in poor patients largely because they arrive later, then the intervention point is prehospital, encompassing public awareness of heart attack symptoms, affordable and rapid transport, and streamlined triage. In a conflict-affected setting where ambulances are scarce, fuel is expensive, and roads are dangerous, each of these steps becomes a formidable barrier for families with the fewest resources.

The study does carry limitations inherent to its design and setting. As a single-center prospective observational study of 216 patients, its findings require replication in other conflict-affected and resource-limited environments before broad generalization. The composite socioeconomic score, while context-adapted, cannot capture every dimension of disadvantage, and observational designs can never fully exclude residual confounding, however reassuring the E-value may be. Streptokinase itself is an older thrombolytic with known limitations, including antigenicity and a relatively high failure rate even under ideal circumstances, which may have amplified the observed gradients. Nevertheless, the internal consistency of the data, spanning delay times, reperfusion success, mortality, and composite adverse events, lends the conclusions considerable weight.

For global health, the message is uncomfortable but clear. Cardiovascular disease is no longer a affliction confined to wealthy nations, and the tools available to poorer countries must be made to work for everyone within them. Streptokinase costs only a few dollars per dose, yet its effectiveness in Yemen appears to be rationed by circumstance as much as by biology. The authors’ call for subsidized emergency transport and pharmaco-invasive networks represents a pragmatic, achievable agenda: rather than waiting for catheterization laboratories that may take decades to build, health systems can invest in the unglamorous logistics of getting patients through the door faster and connecting fibrinolysis to follow-up angiography. In a world where conflict and poverty increasingly shape disease outcomes, this study demonstrates that the fight for health equity begins not in the operating theater but on the road to the hospital.

Subject of Research: Socioeconomic disparities in thrombolytic reperfusion success and outcomes after ST-elevation myocardial infarction in conflict-affected Yemen

Article Title: Association of socioeconomic status with streptokinase reperfusion failure and in-hospital outcomes in STEMI: evidence from conflict-affected Yemen

Article References: Al-Namshah, T., Al-Kebsi, M., Alradi, A., Al-Habeet, A., Al-Motarreb, A., Al-Wather, N., Alodhari, R., & Al-Jalal, A. (2026). Association of socioeconomic status with streptokinase reperfusion failure and in-hospital outcomes in STEMI: evidence from conflict-affected Yemen. International Journal for Equity in Health. https://doi.org/10.1186/s12939-026-03047-y

Image Credits: AI Generated

DOI: 10.1186/s12939-026-03047-y

Keywords: socioeconomic status, STEMI, streptokinase, reperfusion failure, Yemen, thrombolysis, health equity, conflict-affected settings, in-hospital mortality, MACE, prehospital delay, cardiovascular outcomes

The numbers behind that headline are precise. Across all included trials, treatment with one of the three drug classes was associated with a pooled hazard ratio of 0.72 for renal adverse outcomes, with a 95 percent confidence interval of 0.67 to 0.78. For cardiovascular events, the pooled hazard ratio was 0.85, with a confidence interval of 0.82 to 0.88. In the language of epidemiology, hazard ratios below 1.0 indicate that the treated group experienced fewer events over time than the control group, and the fact that both confidence intervals sit entirely below 1.0 means the findings are statistically significant at the conventional threshold. The renal effect is particularly striking: a hazard ratio of 0.72 implies that, at any given point during follow-up, the instantaneous risk of a kidney-related adverse outcome was about 28 percent lower among treated patients.

What makes this analysis noteworthy is not the discovery of a new drug but the deliberate decision to look across three pharmacological families that could hardly be more different in mechanism. SGLT2 inhibitors work in the proximal tubule of the kidney, blocking the sodium–glucose cotransporter-2 protein that normally reabsorbs filtered glucose back into the bloodstream. By forcing the kidneys to excrete glucose in the urine, they lower blood sugar, but their cardiorenal benefits appear to extend well beyond glucose control, involving shifts in renal hemodynamics, reduced tubular workload, and effects on sodium handling that ease pressure on the filtering units of the kidney. GLP-1 receptor agonists, by contrast, mimic the incretin hormone glucagon-like peptide-1, enhancing insulin secretion in a glucose-dependent manner, suppressing inappropriate glucagon release, slowing gastric emptying, and acting on appetite centers in the brain, with downstream anti-inflammatory and vascular effects thought to contribute to cardiovascular protection.

The third class, nonsteroidal mineralocorticoid receptor antagonists, represents the newest arrival among the three. Traditional steroidal mineralocorticoid receptor antagonists such as spironolactone have long been used in heart failure, but their use in diabetic kidney disease has been limited by hyperkalemia risk. The nonsteroidal agents, of which finerenone is the prototype, bind the mineralocorticoid receptor with greater selectivity and less off-target activity, dampening the inflammatory and fibrotic signaling driven by aldosterone activation in both the heart and the kidney while maintaining a more manageable potassium safety profile. Large outcome trials of finerenone in patients with chronic kidney disease and type 2 diabetes demonstrated meaningful reductions in kidney failure progression and cardiovascular events, securing the class a place in contemporary treatment algorithms.

Conducted according to the PRISMA 2020 reporting framework, the review systematically searched PubMed, Embase, Web of Science, the Cochrane Library, and Google Scholar for randomized controlled trials published between January 2010 and March 2024. The eligibility criteria were deliberately broad: adult patients with type 2 diabetes, exposure to one of the three drug classes, and reported renal or cardiovascular outcomes. The investigators extracted hazard ratios with their corresponding 95 percent confidence intervals and pooled them using inverse-variance random-effects models, the standard approach when the true effect size may plausibly vary across trials because of differences in populations, comparators, and follow-up durations. Random-effects weighting assigns relatively more influence to smaller studies than a fixed-effects model would, which guards against letting a handful of mega-trials dominate the pooled estimate.

Heterogeneity—the degree to which individual trials disagree beyond what chance would predict—was assessed and found to be moderate for renal outcomes, with an I² statistic of 43.7 percent, and low for cardiovascular outcomes, at 26.3 percent. The I² statistic describes the percentage of variability in effect estimates that is attributable to true heterogeneity rather than sampling error; values below 25 percent are typically considered low, 25 to 50 percent moderate, and above 50 percent substantial. The relatively tame heterogeneity figures are reassuring for a pooled analysis that deliberately mixes drug classes, trial designs, and outcome definitions, and they suggest the direction of benefit is consistent even if its magnitude varies. Sensitivity analyses, in which the pooled estimates are recalculated under alternative assumptions or with individual studies excluded, confirmed that the results were robust rather than driven by any single influential trial.

The authors also confronted the problem of publication bias, the well-documented tendency for studies showing positive results to be published more readily than null findings, which can inflate pooled effect estimates. They deployed Egger’s regression test, which examines whether smaller studies show disproportionately larger effects, and trim-and-fill analysis, which estimates how many hypothetical missing studies would be needed to restore symmetry to a funnel plot. Both approaches were interpreted cautiously given the limited number of included studies, a candid acknowledgment that formal bias tests lose statistical power when fewer than about ten trials contribute to a comparison. This transparency matters for clinicians weighing the findings at the bedside, because the true magnitude of benefit could in principle be somewhat smaller than the headline hazard ratios suggest.

The clinical stakes of this synthesis are enormous. Type 2 diabetes remains the leading cause of chronic kidney disease worldwide, and it carries a markedly elevated risk of cardiovascular morbidity and mortality; a large fraction of people with diabetes will eventually die of cardiovascular causes rather than of hyperglycemia itself. For decades, the therapeutic arsenal against diabetic kidney disease consisted essentially of blood pressure control, blockade of the renin–angiotensin–aldosterone system, and glycemic management, yet progression to end-stage renal disease continued relentlessly in many patients. The arrival of SGLT2 inhibitors, GLP-1 receptor agonists, and nonsteroidal mineralocorticoid receptor antagonists—each validated in dedicated cardiovascular or renal outcome trials—has been described as the most consequential expansion of cardiorenal protection in a generation, and the new meta-analysis quantifies just how much those trials have moved the needle in aggregate.

Importantly, the authors are careful about what pooling across distinct drug classes can and cannot tell us. Combining pharmacologically unrelated agents into a single pooled estimate is a statistical convenience that answers the question of whether contemporary cardiorenal therapy, broadly defined, works; it does not answer which drug works best for which patient, or whether combining them yields additive or synergistic benefit. The moderate heterogeneity observed for renal outcomes hints at genuine differences among the classes and among the trials. The researchers explicitly call for future head-to-head trials and individual patient-data meta-analyses, in which raw participant-level data from multiple studies are harmonized and reanalyzed, as the tools needed to define comparative effectiveness and identify subgroups who stand to gain the most from each agent.

For now, the findings land as a strong endorsement of existing guidance. The authors conclude that the evidence supports current recommendations from the American Diabetes Association and KDIGO, the global kidney disease guideline body, which advocate individualized use of these agents as complementary rather than competing pillars of cardiorenal protection in type 2 diabetes. In practical terms, the message reaching clinicians is that the choice is increasingly not whether to deploy one of these therapies but which combination and sequence best fits a given patient’s kidney function, cardiovascular risk profile, and tolerability. As the population of people living with diabetes continues to grow worldwide, a reliable 28 percent reduction in renal risk and 15 percent reduction in cardiovascular risk, replicated across three independent drug mechanisms, represents one of the most consequential shifts in chronic disease medicine of the modern era.

Subject of Research: Cardiorenal outcomes of SGLT2 inhibitors, GLP-1 receptor agonists, and nonsteroidal mineralocorticoid receptor antagonists in type 2 diabetes

Article Title: Cardiorenal effects of SGLT2 inhibitors, GLP-1 receptor agonists, and nonsteroidal mineralocorticoid receptor antagonists in type 2 diabetes: a systematic review and meta-analysis

Article References: Ayar, Y., Kahveci̇oglu, S., Aktas, N., Akarsu, O., & Bilen, N. (2026). Cardiorenal effects of SGLT2 inhibitors, GLP-1 receptor agonists, and nonsteroidal mineralocorticoid receptor antagonists in type 2 diabetes: a systematic review and meta-analysis. BMC Endocrine Disorders. https://doi.org/10.1186/s12902-026-02586-3

Image Credits: AI Generated

DOI: 10.1186/s12902-026-02586-3

Keywords: type 2 diabetes, SGLT2 inhibitors, GLP-1 receptor agonists, nonsteroidal mineralocorticoid receptor antagonists, finerenone, chronic kidney disease, cardiovascular outcomes, meta-analysis, diabetic nephropathy, cardiorenal protection, KDIGO guidelines, randomized controlled trials

The stakes of this comparison could hardly be higher. According to the World Obesity Atlas 2023, 38 percent of the global population is currently overweight or living with obesity, a figure projected to climb to 51 percent by 2035. The World Health Organization reports that adult obesity rates have doubled since 1990, while adolescent rates have quadrupled. Obesity is not merely a matter of weight; it is a metabolic engine that drives dyslipidemia, hypertension, sleep apnea and a prothrombotic state, each of which compounds cardiovascular danger. Evidence cited in the analysis shows that individuals with both obesity and diabetes face a 96 percent higher risk of cardiovascular mortality than people of normal weight without diabetes, and obesity alone raises the likelihood of myocardial infarction by approximately 10 percent compared with normal-weight individuals.

Both interventions have individually demonstrated impressive cardiovascular credentials. Previous meta-analytic work summarized in the study indicates that GLP-1 receptor agonists reduce major adverse cardiovascular events by 14 percent, heart failure by 11 percent, myocardial infarction by 10 percent, stroke by 17 percent and cardiovascular mortality by 13 percent. Bariatric surgery, by comparison, has been associated with a 50 percent decrease in heart failure, 42 percent in myocardial infarction, 36 percent in stroke and 41 percent in cardiovascular mortality. What was missing was a rigorous head-to-head verdict, because large randomized trials directly comparing the two approaches simply do not exist. The research team, led by Erfan Shirmohammadi and colleagues, turned to network meta-analysis, a statistical framework that combines direct comparisons, such as surgery versus control, with indirect ones, allowing surgery and drugs to be ranked through their shared comparator.

The methodological architecture of the study is worth appreciating, because its conclusions rest on it. The researchers searched PubMed/MEDLINE, Ovid/Embase, Google Scholar and the Cochrane Library for publications from January 2000 to September 30, 2024, screening 932 records down to 43 included studies reported under PRISMA guidelines. The evidence network contained three nodes: bariatric surgery, GLP-1 receptor agonists and control. Twenty-eight cohort studies supplied the surgical evidence, eleven randomized controlled trials supplied the pharmacological evidence, and four observational cohorts provided direct surgery-versus-drug comparisons. Risk of bias was assessed with the Cochrane Risk of Bias Tool for the randomized trials and the Newcastle-Ottawa Scale for the observational studies, with the surgical cohorts generally rated as good quality and the drug trials as low risk.

The headline numbers come from the random-effects hazard ratio models, which are considered the more conservative reading because they account for variability between studies. Bariatric surgery versus control yielded a hazard ratio of 0.66 for major adverse cardiovascular events, meaning a 34 percent risk reduction, while GLP-1 receptor agonists versus control produced a hazard ratio of 0.85, a 15 percent reduction. For heart failure, surgery achieved a hazard ratio of 0.45, a 55 percent reduction, whereas the drugs showed a non-significant hazard ratio of 0.87. For myocardial infarction, surgery delivered a hazard ratio of 0.53, cutting risk by 47 percent, while the drug class showed a non-significant 0.91. Fixed-effects models told a similar story with somewhat smaller effect sizes, and parallel analyses using risk ratios rather than hazard ratios reproduced the same directional pattern, an internal consistency check the authors describe as validation of their trends.

Because network meta-analysis lives or dies by the coherence of its evidence web, the team ran node-splitting analyses to test whether direct and indirect estimates disagreed. They did not. For major adverse cardiovascular events, the network estimate for surgery versus GLP-1 receptor agonists was 0.54 in the common-effects model, with direct evidence at 0.50 and indirect evidence at 0.56, and the ratio of odds ratios produced p-values ranging from 0.62 to 0.94, far from any threshold of inconsistency. Heart failure showed the same harmony, with inconsistency p-values between 0.42 and 0.60. Funnel plots displayed largely symmetrical distributions, suggesting low likelihood of publication bias. For myocardial infarction, no node-splitting was possible because no direct comparative evidence existed for that outcome, a gap the authors flag as a limit on the precision of that particular indirect estimate.

Why would surgery so decisively outpace a drug class celebrated as one of the great cardiovascular breakthroughs of the decade? The authors point to weight loss-dependent and weight loss-independent mechanisms. Bariatric surgery induces broader and more durable metabolic remodelling: meta-analytic evidence shows it enhances the cholesterol efflux capacity of high-density lipoprotein particles and significantly lowers low-density lipoprotein and lipoprotein(a) concentrations, modifying atherogenic lipoprotein pathways in ways that persist for years. GLP-1 receptor agonists, for their part, exert direct effects on natriuresis, vascular tissue, myocardium and endothelium, but they produce a smaller magnitude of weight loss through sustained pharmacological modulation of metabolic, inflammatory and atherosclerotic pathways. In essence, the scalpel appears to reset the metabolic system more profoundly than the injection fine-tunes it.

The authors are careful, however, to attach substantial caveats to their verdict. The evidence base is fundamentally asymmetric: nearly all surgical data come from observational cohorts, while nearly all drug data come from randomized trials, a design mismatch that can introduce residual confounding into the surgical arm, since patients selected for surgery may differ systematically from those who are not. Heterogeneity across the analyses was moderate to high, with I-squared values reaching 92.5 percent in some risk-ratio models, reflecting variation in follow-up duration, intervention type, baseline diabetes prevalence and obesity severity. The randomized trials included mostly first-generation GLP-1 receptor agonists rather than newer agents such as tirzepatide, and subgroup analyses or meta-regression could not be performed due to data limitations. The absence of large-scale head-to-head randomized trials remains the central constraint on the field.

Those caveats shape, but do not erase, the clinical message. The authors suggest that bariatric surgery may be the preferred intervention for patients with obesity who are surgical candidates and carry high cardiovascular risk, particularly those with established heart failure or prior myocardial infarction. GLP-1 receptor agonists remain an effective and far less invasive alternative for reducing major adverse cardiovascular events when surgery is contraindicated, declined or inaccessible, and the choice between the two should be individualized according to surgical risk, patient preference, comorbidity profile and healthcare access. With obesity projected to encompass half of humanity within a decade, and cardiovascular disease its deadliest shadow, the analysis signals that the next frontier is not choosing a winner but mapping which patient profiles benefit most from which intervention, through trials stratified by surgery type, drug generation, diabetes status and baseline risk.

Subject of Research: Comparative cardiovascular outcomes of bariatric surgery versus GLP-1 receptor agonist therapy in people with obesity

Article Title: Comparative Cardiovascular Outcomes of GLP‐1 Receptor Agonists Versus Bariatric Surgery: A Systematic Review and Network Meta‐Analysis

Article References: Shirmohammadi, E., Ghasemloo, N., Ebrahimi, N., Mohammadzadeh, N., Ehtemami, A., Babaei, M., & Fardoost, S. (2026). Comparative Cardiovascular Outcomes of GLP ‐1 Receptor Agonists Versus Bariatric Surgery: A Systematic Review and Network Meta‐Analysis. Endocrinology, Diabetes & Metabolism, 9(5), Article e70311. https://doi.org/10.1002/edm2.70311

Image Credits: AI Generated

DOI: 10.1002/edm2.70311

Keywords: bariatric surgery, GLP-1 receptor agonists, cardiovascular outcomes, major adverse cardiovascular events, heart failure, myocardial infarction, network meta-analysis, obesity, semaglutide, systematic review, metabolic surgery, cardiovascular risk

The study, led by Anastasios Mavridis and colleagues at Sahlgrenska University Hospital and the University of Gothenburg, drew on the Swedish National Diabetes Register, a national quality registry that captures the vast majority of diabetes care in the country. The researchers followed 171,917 individuals who were registered for the first time between January 2013 and December 2019, accumulating more than 1.6 million clinical registrations and up to seven years of follow-up per person. During that window, 2,734 people suffered an ischemic stroke and 428 a hemorrhagic stroke. Because Sweden links its health registries through unique personal identity numbers, the team could connect each patient’s laboratory values, prescriptions, comorbidities and stroke outcomes into a single longitudinal record of routine clinical care.

What sets the analysis apart from most real-world studies is how it handled the messy dynamics of actual treatment. In clinical practice, patients switch drugs, stop and restart, and their blood pressure, weight, kidney function and cholesterol evolve alongside those decisions. Standard observational analyses typically adjust for characteristics measured once, at baseline, an approach that can badly distort estimates when treatment and risk factors influence each other over time. The Swedish team instead used inverse probability of treatment weighting within a marginal structural model, a statistical framework designed precisely for this treatment-confounder feedback. Each patient’s exposure status was updated at every registry visit, drawing on pharmacy dispensing records to reconstruct when drugs were actually in use, and weights were recalculated to balance clinical characteristics across treated and untreated intervals.

The headline result concerns GLP-1 receptor agonists. Across weighted time-varying Cox models, use of these drugs was associated with a 54 percent lower hazard of ischemic stroke (hazard ratio 0.46, 95 percent confidence interval 0.29 to 0.72) and a 49 percent lower hazard of total stroke (hazard ratio 0.51, 95 percent confidence interval 0.33 to 0.79). For hemorrhagic stroke the point estimate pointed in the same direction but the confidence interval was wide, spanning 0.28 to 2.28, reflecting the small number of bleeding events. By contrast, SGLT2 inhibitors showed no clear association with any stroke subtype, with an ischemic stroke hazard ratio of 0.94, and DPP-4 inhibitors were likewise neutral, at 1.17 for ischemic stroke.

To place these numbers in context, the authors systematically searched PubMed for meta-analyses of both randomized trials and observational studies, screening 274 abstracts and 102 full texts. The picture that emerged explains why the field has been so confused. For SGLT2 inhibitors, meta-analyses of randomized controlled trials consistently reported no effect on stroke, with effect sizes between 0.84 and 1.30, while observational meta-analyses suggested a protective association between 0.75 and 0.87. For GLP-1 receptor agonists, both trial and observational syntheses agreed on a protective effect, roughly a 10 to 20 percent risk reduction. DPP-4 inhibitors were neutral in trials. The new Swedish findings align with the randomized trial evidence for all three classes, and they do so using a method that many earlier observational studies lacked.

Why did previous real-world studies so often disagree with the trials? The authors argue that the answer lies largely in methodology. Most prior observational work adjusted only for baseline variables, which is appropriate for estimating the effect of initial treatment assignment but poorly suited to dynamic treatment patterns. When patients frequently switch or discontinue therapy, an intention-to-treat style estimator loses information about whether prescriptions are actually filled and says little about the hazard at any given moment of drug use. By updating exposure, covariates and concomitant medications throughout follow-up, the marginal structural model approach directly targets the question of what happens while patients are on treatment, which may partly explain why the GLP-1 association observed here was stronger than the 10 to 20 percent reductions typically reported in randomized trials.

The authors are careful to caution against over-interpreting that larger magnitude. Their estimates reflect treatment use during follow-up, not the effect of starting a drug in a treatment-naive patient, and the two estimands are not directly comparable. Differences in adherence, persistence, study populations and residual confounding may all contribute. As with any observational study, unmeasured confounding remains a possibility, and the team acknowledges that substantial missing data in several clinical variables, handled through two-level multiple imputation, means the results depend on the adequacy of the imputation models. The hemorrhagic stroke analyses were also limited by small event counts, and the comparison with published meta-analyses was explicitly contextual rather than a formal evidence synthesis.

Biologically, the divergence between drug classes makes considerable sense. Beyond lowering glucose, GLP-1 receptor agonists reduce systolic blood pressure, body weight and post-meal lipaemia, improve endothelial function and dampen vascular inflammation. Experimental work suggests anti-atherosclerotic effects through reduced oxidative stress, better nitric oxide bioavailability and modulation of macrophage activity within plaques, potentially stabilizing the vulnerable lesions that cause ischemic strokes. Intriguingly, GLP-1 receptors are also expressed in the central nervous system, and preclinical models hint at direct neuroprotective properties, including reduced excitotoxicity, less neuroinflammation and diminished apoptotic signalling. SGLT2 inhibitors, by contrast, deliver their cardiovascular and renal benefits largely through osmotic diuresis, natriuresis and improved cardiac loading, mechanisms that may not target the atherosclerotic and thromboembolic pathways most relevant to ischemic stroke. Some researchers have even hypothesized that SGLT2 inhibition raises hematocrit and blood viscosity, potentially offsetting cerebrovascular gains.

The clinical implications are nuanced rather than revolutionary. The authors suggest that GLP-1 receptor agonists may reasonably be considered part of a stroke-prevention strategy in type 2 diabetes, but they are emphatic that the established benefits of SGLT2 inhibitors and DPP-4 inhibitors for heart failure, kidney disease and other outcomes must remain central to prescribing decisions. Treatment choices, they argue, should be informed by the totality of evidence for each individual patient, weighing the distinct benefit profiles of each class. Because the study drew on Sweden’s universal healthcare system, the findings are most applicable to settings with similar care structures, and the cohort, restricted to people newly registered from 2013 onward, may not fully represent those with long-standing diabetes.

For a field wrestling with how to translate landmark cardiovascular outcome trials into everyday practice, this study offers a methodological template as much as a clinical finding. By embracing the time-varying chaos of real-world care rather than freezing patients at their baseline characteristics, the Swedish team produced observational estimates that line up with the randomized evidence, resolving a discordance that has persisted across dozens of published syntheses. Future work, the authors note, should focus on how these findings can feed into personalized glucose-lowering strategies that optimize stroke prevention, a goal that becomes more attainable when trial data and real-world data finally tell the same story.

Subject of Research: Effects of SGLT2 inhibitors, GLP-1 receptor agonists, and DPP-4 inhibitors on stroke risk in type 2 diabetes

Article Title: The effect of SGLT2 inhibitors, GLP-1 receptor agonists, or DPP-4 inhibitors on stroke risk in type 2 diabetes: a nationwide longitudinal cohort study in Sweden with contextualisation analysis

Article References: Mavridis, A., Abzhandadze, T., Buvarp, D., Simons, K., Eliasson, B., von Euler, M., Viktorisson, A., & Sunnerhagen, K. S. (2026). The effect of SGLT2 inhibitors, GLP-1 receptor agonists, or DPP-4 inhibitors on stroke risk in type 2 diabetes: a nationwide longitudinal cohort study in Sweden with contextualisation analysis. eClinicalMedicine, 100, Article 104220. https://doi.org/10.1016/j.eclinm.2026.104220

Image Credits: AI Generated

DOI: 10.1016/j.eclinm.2026.104220

Keywords: type 2 diabetes, stroke, GLP-1 receptor agonists, SGLT2 inhibitors, DPP-4 inhibitors, Swedish National Diabetes Register, marginal structural models, ischemic stroke, hemorrhagic stroke, pharmacoepidemiology, cardiovascular outcomes, real-world evidence

The stakes of this comparison are enormous. Type 2 diabetes now affects an estimated 589 million adults worldwide as of 2024, a figure projected to climb to 853 million by 2050. Because the disease drives complications through both chronic hyperglycemia and the twin burdens of obesity and cardiovascular disease, contemporary treatment guidelines no longer ask simply whether a drug lowers glucose. They demand sustained reductions in hemoglobin A1c, meaningful weight reduction, cardiovascular safety, and tolerability that patients can live with for decades. Both tirzepatide and dulaglutide are once-weekly subcutaneous injections, but they work differently at the molecular level, and until now no trial had ever compared all clinically relevant doses of the two drugs simultaneously.

Dulaglutide is a selective glucagon-like peptide-1 receptor agonist, a class of drugs that mimics an intestinal hormone to boost glucose-dependent insulin secretion, suppress glucagon, slow gastric emptying, and reduce appetite. It carries hard cardiovascular outcome evidence: in the landmark REWIND trial, dulaglutide reduced major adverse cardiovascular events compared with placebo in people with type 2 diabetes. Tirzepatide, by contrast, is a first-in-class dual agonist that engages both the GIP and GLP-1 receptors, amplifying the incretin effect through two complementary hormonal pathways. Head-to-head trials had already hinted that tirzepatide’s dual mechanism translated into greater reductions in HbA1c and body weight, but individual studies compared only selected dose pairs, leaving clinicians without a comprehensive map of which specific dose delivers which specific benefit.

The research team, following Cochrane Handbook methodology and PRISMA reporting guidelines with a prospectively registered protocol, searched four major databases through the end of 2025 and identified four eligible randomized trials. Three of these were judged to carry low risk of bias across all assessed domains; the fourth, an open-label switching study, raised some concerns because participants and clinicians knew which treatment was being given. The largest trial by far was the SURPASS-CVOT cardiovascular outcomes study, which enrolled 13,165 patients with established atherosclerotic cardiovascular disease and demonstrated that tirzepatide titrated up to 15 milligrams was noninferior to dulaglutide 1.5 milligrams for the composite of cardiovascular death, myocardial infarction, or stroke over a median follow-up of roughly four years.

Using a frequentist random-effects network model, the analysts computed treatment effects and SUCRA rankings, a statistical measure of each dose’s cumulative probability of being among the most effective options. The results formed a clean dose-response gradient. For glycemic control, tirzepatide 15 milligrams ranked highest at both 12 and 24 weeks, achieving SUCRA values of 0.95 and 0.99 respectively, while dulaglutide 1.5 milligrams sat near the bottom of the efficacy rankings. At 24 weeks, tirzepatide 15 milligrams reduced HbA1c significantly more than tirzepatide 5 milligrams, and both dulaglutide 0.75 and 1.5 milligrams were associated with meaningfully smaller reductions. The differences of 0.2 to 0.4 percentage points between higher and lower tirzepatide doses are clinically meaningful, because shifts of that magnitude can move patients across standard treatment targets and delay the need for therapy intensification.

The weight findings followed the same pattern with even sharper separation. By week 16, tirzepatide 15 milligrams outperformed tirzepatide 5 milligrams by an additional 2.68 kilograms of weight loss, and the contrast against the weakest doses was dramatic: dulaglutide 0.75 milligrams and tirzepatide 1 milligram trailed the top dose by roughly 5 to 8 kilograms. Tirzepatide 15 milligrams earned a SUCRA of 0.95 for weight reduction, with the 10 milligram dose close behind, while tirzepatide 1 milligram ranked nearly last. Notably, the early weight outcomes showed substantial statistical heterogeneity, which the authors attribute to the sensitivity of short-term weight trajectories to titration schedules, baseline body mass index, diabetes duration, and transient gastrointestinal symptoms that can temporarily suppress food intake during dose escalation.

Safety told the mirror-image story. Tirzepatide 1 milligram carried the lowest risk of any treatment-emergent adverse event and of nausea, while dulaglutide 0.75 milligrams showed the lowest risks of diarrhea and vomiting. At the other end of the spectrum, both tirzepatide 15 milligrams and dulaglutide 1.5 milligrams were associated with significantly higher nausea risk compared with tirzepatide 5 milligrams. This gradient is biologically coherent: higher incretin receptor engagement intensifies slowed gastric emptying and central satiety signaling, which are precisely the mechanisms that drive both the metabolic benefits and the gastrointestinal complaints. Encouragingly, no significant differences emerged between any dose pairs for all-cause death, severe hypoglycemia, serious adverse events, pancreatitis, treatment discontinuation, or the composite cardiovascular endpoint, although the authors caution that wide confidence intervals for these rare outcomes mean the absence of statistical differences cannot be read as proof of equivalent safety.

The team stress-tested their findings with a battery of sensitivity analyses, including one that removed the dominant SURPASS-CVOT trial entirely to check whether its enormous statistical weight was distorting the network. The core conclusions held. Some outcomes, notably HbA1c at 12 weeks, early body weight change, and nausea and vomiting, proved sensitive to the inclusion of the Japanese SURPASS J-mono trial, which compared tirzepatide against the 0.75 milligram dulaglutide dose approved in Japan rather than the 1.5 milligram standard used elsewhere. Inconsistency testing using both design-by-treatment interaction models and node-splitting found no meaningful disagreement between direct and indirect evidence for most outcomes, lending credibility to the network’s internal structure.

The clinical implications are refreshingly practical. For patients whose primary goals are maximal HbA1c reduction and weight loss, the data support escalating to tirzepatide 10 or 15 milligrams when tolerability permits, with an expected stepwise advantage over lower doses and over any dulaglutide regimen. For patients whose priority is gastrointestinal tolerability, starting at lower doses such as dulaglutide 0.75 milligrams or tirzepatide 1 milligram remains a reasonable strategy, accepting more modest metabolic gains and possible later intensification. The findings also reinforce the results of the SURPASS-SWITCH trial, which showed that patients inadequately controlled on submaximal dulaglutide achieved greater HbA1c and weight improvements by switching to tirzepatide than by pushing the dulaglutide dose higher. An important interpretive caveat applies to the early time points: many participants assigned to the highest tirzepatide doses were still in protocol-mandated dose escalation at weeks 12 and 16, meaning the full maintenance-dose effects may be even larger than these figures suggest.

The authors are candid about the limitations. Only four trials informed the network, several dose nodes rested on sparse comparisons, and long-term durability, late adverse events, and sustained discontinuation could not be assessed because later time points were not consistently reported across trials. Some data were digitized from published figures, introducing the possibility of minor extraction error despite independent double-checking. Still, within those constraints, the analysis delivers something no single trial could: a unified, dose-level ranking of the two most widely used once-weekly injectable therapies for type 2 diabetes. The message for the millions of patients and their clinicians navigating this decision is one of individualized titration, balancing the escalating metabolic rewards of higher tirzepatide doses against the dose-related gastrointestinal costs, with the reassurance that cardiovascular safety appears preserved across the spectrum.

Subject of Research: Comparative efficacy and safety of tirzepatide versus dulaglutide doses in type 2 diabetes

Article Title: Efficacy and Safety of Tirzepatide Versus Dulaglutide in Type 2 Diabetes With or Without Established Atherosclerotic Cardiovascular Disease: A Network Meta‐Analysis of Randomized Clinical Trials

Article References: Hageen, A. W., Gadelmawla, A. F., Saleh, A. O., Bahnasy, S., Eladawi, S., Abdelaziz, M., Iyad, K., Kandil, A. H., Zinhom, K., Mohamed, M. R., Abdulhay, H., Turkman, M., Abdelazeem, B., & Fonarow, G. C. (2026). Efficacy and Safety of Tirzepatide Versus Dulaglutide in Type 2 Diabetes With or Without Established Atherosclerotic Cardiovascular Disease: A Network Meta‐Analysis of Randomized Clinical Trials. Endocrinology, Diabetes & Metabolism, 9(5), Article e70313. https://doi.org/10.1002/edm2.70313

Image Credits: AI Generated

DOI: 10.1002/edm2.70313

Keywords: tirzepatide, dulaglutide, type 2 diabetes, network meta-analysis, HbA1c, weight loss, GLP-1 receptor agonist, GIP, cardiovascular outcomes, gastrointestinal adverse events, dose-response, incretin therapy