Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.2
3.3
Journals
JCM
Special Issues
From Biology to Bedside: Novel Clinical Strategies in Obesity-Linked Cardiometabolic...
jcm-logo
Submit to Special Issue Submit Abstract to Special Issue Review for JCM Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

From Biology to Bedside: Novel Clinical Strategies in Obesity-Linked Cardiometabolic Disease

A Special Issue of Journal of Clinical Medicine (ISSN 2077-0383) belonging to the section "Cardiovascular Medicine".

Deadline for manuscript submissions: 28 December 2026 | Viewed by 2142

Editors

Dr. Matilda Florentin

E-Mail Website
Guest Editor
Internal Medicine, Faculty of Medicine, School of Health Sciences, University of Ioannina, 45110 Ioannina, Greece
Interests: dyslipidemias; diabetes mellitus; cardio–renal–metabolic syndrome; metabolic dysfunction-associated steatotic liver disease; obesity
Dr. Theocharis Koufakis

E-Mail Website
Guest Editor
Second Propaedeutic Department of Internal Medicine, Hippokration General Hospital, Aristotle University of Thessaloniki, 54642 Thessaloniki, Greece
Interests: diabetes mellitus; obesity; cardiovascular risk; modern diabetes pharmacotherapy; cardio–renal–metabolic syndrome; obesity pharmacotherapy; precision medicine
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Obesity has emerged as one of the most pressing global health challenges, affecting over one billion individuals worldwide and acting as a major driver of metabolic and cardiovascular disease. Far from being a simple consequence of lifestyle imbalance, obesity is now recognized as a complex, chronic and biologically regulated condition involving neuroendocrine pathways, adipose tissue dysfunction, systemic inflammation and metabolic dysregulation. Its close links with type 2 diabetes, atherosclerotic cardiovascular disease, heart failure and chronic kidney disease underscore its central role within the cardiometabolic continuum.

Despite significant advances in our understanding of obesity pathophysiology, important gaps remain in translating this knowledge into effective, individualized clinical care. Traditional reliance on body mass index (BMI) alone fails to capture the heterogeneity of adiposity distribution, metabolic risk and disease burden. At the same time, rapidly evolving therapeutic options—including novel pharmacotherapies and combination approaches—are reshaping the management landscape, challenging long-standing paradigms that prioritized lifestyle interventions as the primary treatment modality.

This Special Issue aims to present and disseminate the most recent advances in the clinical understanding and management of obesity-linked metabolic and cardiovascular disease. We welcome contributions that explore mechanistic insights, innovative biomarkers and emerging therapeutic strategies, with particular emphasis on precision medicine approaches and risk stratification beyond conventional anthropometric measures.

Topics of interest include, but are not limited to, the following:

  • Clinical manifestations and management linking obesity with cardiometabolic disease
  • Novel biomarkers and composite indices of metabolic and inflammatory burden
  • Role of adipose tissue distribution and ectopic fat in disease risk
  • Advances in obesity pharmacotherapy and combination treatment strategies
  • Cardiovascular and renal outcomes of weight-loss interventions
  • Integration of obesity management into cardiometabolic care pathways
  • Limitations of BMI and alternative approaches to risk assessment

By bringing together cutting-edge research and clinically relevant perspectives, this Special Issue seeks to advance a more nuanced and effective approach to obesity as a central determinant of cardiometabolic health.

Dr. Matilda Florentin
Dr. Theocharis Koufakis
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Clinical Medicine is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • obesity
  • cardiometabolic disease
  • type 2 diabetes
  • cardiovascular risk
  • adipose tissue dysfunction
  • inflammation
  • biomarkers
  • precision medicine

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

24 pages, 3014 KB  
Article
Duplicate-Aware Internal Validation of Machine-Learning Models for Classifying a Tanita BIA-Derived High-Adiposity Phenotype Using Simple Anthropometric Predictors
by Rukiye Çiftçi, İpek Atik, Neşe Bülbül, Özgür Eken and Monira I. Aldhahi
J. Clin. Med. 2026, 15(16), 6164; https://doi.org/10.3390/jcm15166164 - 8 Aug 2026
Viewed by 290
Abstract
Background/Objectives: Anthropometric machine-learning models may approximate body-composition classifications, but performance can be inflated by inconsistent preprocessing, non-independent validation records, and incomplete calibration reporting. This study evaluated a sex-specific bioelectrical impedance analysis (BIA)-defined high-adiposity phenotype using simple anthropometric variables in adults with and without [...] Read more.
Background/Objectives: Anthropometric machine-learning models may approximate body-composition classifications, but performance can be inflated by inconsistent preprocessing, non-independent validation records, and incomplete calibration reporting. This study evaluated a sex-specific bioelectrical impedance analysis (BIA)-defined high-adiposity phenotype using simple anthropometric variables in adults with and without hypertension. Methods: Of 583 prespecified records, 11 with invalid placeholder-coded values in required anthropometric or body-composition fields were excluded, leaving 572 participants (385 normotensive and 187 hypertensive). A high-adiposity phenotype was defined as BIA-derived body fat ≥ 25% in males or ≥35% in females. Predictors were sex, height, body weight, waist circumference, and hypertension status; body mass index and body-fat percentage were excluded. Eight algorithms were assessed using 10 repetitions of stratified five-fold group cross-validation, with identical predictor profiles kept within the same fold. Continuous predictors were standardized within training folds. Performance was estimated from averaged out-of-fold probabilities with 2000 stratified bootstrap confidence intervals, calibration measures, and SHAP analysis. Results: A high-adiposity phenotype was present in 441 participants (77.1%). Random forest achieved the highest discrimination (ROC AUC = 0.959, PR AUC = 0.980). Gradient boosting provided the strongest threshold-dependent performance (accuracy = 0.937, balanced accuracy = 0.895, sensitivity = 0.973, specificity = 0.817, precision = 0.947, F1 score = 0.960, MCC = 0.817) and the lowest Brier score (0.057), but its calibration slope was 0.462, indicating overconfident probabilities. SHAP analysis identified waist circumference as the largest attribution within the fitted gradient-boosting model; this result must be interpreted jointly with the ablation analysis because sex, height, and body weight are inputs to the proprietary Tanita equation. Conclusions: Simple anthropometric variables classified the prespecified Tanita BIA-derived high-adiposity threshold with strong internal performance after duplicate-aware validation. Sex, height, and body weight alone achieved a ROC AUC of 0.920; adding waist circumference produced a small and uncertain increase in discrimination (ΔROC AUC = 0.0054, 95% CI −0.0060 to 0.0153), whereas hypertension status added a negligible value. The findings represent internal validation of a device-defined outcome, not prediction of an independent biological reference, and require external validation against criterion body-composition methods before clinical application. Full article
(This article belongs to the Special Issue From Biology to Bedside: Novel Clinical Strategies in Obesity-Linked Cardiometabolic Disease)
►▼ Show Figures

Figure 1

12 pages, 372 KB  
Article
Comparative Effects of SGLT2 Inhibitors and GLP-1 Receptor Agonists on Composite Surrogate Markers of Insulin Resistance: A Real-World Study Using METS-IR and SPISE
by Dimitra Voziki, Ioannis Stergiou, Ioanna Zografou, Maria Mavridou, Lefteris Teperikidis, Michael Doumas, Evangelos N. Liberopoulos, Kalliopi Kotsa, Matilda Florentin and Theocharis Koufakis
J. Clin. Med. 2026, 15(12), 4403; https://doi.org/10.3390/jcm15124403 - 6 Jun 2026
Viewed by 1473
Abstract
Objective: Insulin resistance is a key pathophysiological driver linking obesity and type 2 diabetes (T2D) with cardiovascular risk. Composite surrogate indices derived from routine clinical parameters, such as the Metabolic Score for Insulin Resistance (METS-IR) and the Single Point Insulin Sensitivity Estimator (SPISE), [...] Read more.
Objective: Insulin resistance is a key pathophysiological driver linking obesity and type 2 diabetes (T2D) with cardiovascular risk. Composite surrogate indices derived from routine clinical parameters, such as the Metabolic Score for Insulin Resistance (METS-IR) and the Single Point Insulin Sensitivity Estimator (SPISE), may provide a practical means of capturing multidimensional metabolic changes. Given that comparative data are limited, we aimed to evaluate the effects of sodium–glucose cotransporter-2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP-1RA) on these indices in individuals with T2D and overweight or obesity. Methods: In this retrospective observational study, 100 individuals with T2D treated with either GLP-1RA (n = 54) or SGLT2i (n = 46) were evaluated over 6 months. Strict inclusion criteria ensured treatment stability without initiation or modification of concomitant pharmacotherapy. Changes in METS-IR and SPISE were assessed alongside body mass index (BMI) and glycated hemoglobin (HbA1c). Multivariable regression and exploratory analyses, including stratification by BMI and correlation analyses, were performed. Results: Both treatment groups demonstrated significant improvements in METS-IR (GLP-1RA: −3.9 ± 5.9; SGLT2i: −2.5 ± 2.6; both p < 0.001) and SPISE (GLP-1RA: +0.46 ± 0.52; SGLT2i: +0.44 ± 0.61; both p < 0.001), with no significant between-group differences. In the GLP-1RA group, changes in METS-IR correlated with changes in BMI (r = 0.48, p < 0.001) and HbA1c (r = 0.29, p = 0.030), whereas no significant correlations were observed in the SGLT2i group. Stratified analyses indicated greater reductions in METS-IR among individuals with BMI ≥30 kg/m2 treated with GLP-1RA. Conclusions: Both SGLT2i and GLP-1RA improve composite surrogate markers of insulin resistance, with distinct associations with weight and glycemic changes. METS-IR and SPISE may serve as practical tools for monitoring multidimensional metabolic responses in clinical practice. Full article
(This article belongs to the Special Issue From Biology to Bedside: Novel Clinical Strategies in Obesity-Linked Cardiometabolic Disease)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop