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Review
. 2025 Apr 11;14(8):2615.
doi: 10.3390/jcm14082615.

Charting the Pathways of Cardiometabolic Multimorbidity: A Systematic Review of Clinical Trajectories

Ignatios Ioakeim-Skoufa  1   2   3   4   5 , Rubén Ledesma-Calvo  2 , Aida Moreno-Juste  3   5   6 , Fátima Roque  7   8   9 , Kerry Atkins  10 , Miguel Ángel Hernández-Rodríguez  4   11 , Mercedes Aza-Pascual-Salcedo  3   5   6 , Francisca González-Rubio  3   4 , Carmen Lasala-Aza  12 , Óscar Esteban-Jiménez  4   6 , Ana Avedillo-Salas  2 , Celeste Cebollada-Herrera  2 , Antonio Gimeno-Miguel  3   5 , Jorge Vicente-Romero  2
Affiliations
Review

Charting the Pathways of Cardiometabolic Multimorbidity: A Systematic Review of Clinical Trajectories

Ignatios Ioakeim-Skoufa et al. J Clin Med. .

Abstract

Background: Managing multimorbidity is a major challenge for healthcare systems. Cardiometabolic multimorbidity (CMM) is highly prevalent and linked to increased disease burden, functional decline, and mortality. While most studies focus on cross-sectional analyses, longitudinal approaches are essential for understanding disease progression and identifying patient groups who may benefit from targeted interventions. Objectives: This systematic review synthesises evidence from longitudinal studies on the incidence and progression of CMM, exploring transitions between multimorbidity clusters and their clinical implications. Methods: A systematic search was conducted in MEDLINE and EMBASE following PRISMA guidelines. Studies were included if they employed longitudinal designs and clustering techniques to assess multimorbidity evolution. The quality of evidence was evaluated using the GRADE system. Results: Ten studies met the inclusion criteria. CMM occurs across all age groups and both sexes, showing the highest mortality and functional decline rates. Patients with CMM frequently develop additional cardiometabolic conditions or transition to related clusters. Many also experience neurodegenerative and mental health disorders. Individuals from respiratory multimorbidity clusters often transition to CMM. Moreover, CMM is more prevalent in lower socioeconomic populations. Conclusions: Understanding multimorbidity trajectories enables targeted preventive strategies. Identifying patients with predictable progression can help design adequate and effective interventions, reduce health disparities, and improve healthcare outcomes.

Keywords: cardiometabolic diseases; chronic disease; cluster analysis; comorbidity; disease progression; longitudinal studies; mortality; multimorbidity; quality of life; risk factors.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Application of the Patient/Population, Intervention, Comparison, and Outcomes (PICO) model to assess the suitability of the identified articles for inclusion in the systematic review.
Figure 2
Figure 2
PRISMA 2020 flow diagram.
See this image and copyright information in PMC

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