Ioakeim-Skoufa Ignatios, Ledesma-Calvo Rubén, Moreno-Juste Aida, Roque Fátima, Atkins Kerry, Hernández-Rodríguez Miguel Ángel, Aza-Pascual-Salcedo Mercedes, González-Rubio Francisca, Lasala-Aza Carmen, Esteban-Jiménez Óscar, Avedillo-Salas Ana, Cebollada-Herrera Celeste, Gimeno-Miguel Antonio, Vicente-Romero Jorge
Department of Drug Statistics, Division of Health Data and Digitalisation, Norwegian Institute of Public Health, 0213 Oslo, Norway.
Department of Pharmacology, Physiology, and Legal and Forensic Medicine, Faculty of Medicine, University of Zaragoza, 50009 Zaragoza, Spain.
J Clin Med. 2025 Apr 11;14(8):2615. doi: 10.3390/jcm14082615.
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. This systematic review synthesises evidence from longitudinal studies on the incidence and progression of CMM, exploring transitions between multimorbidity clusters and their clinical implications. 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. 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. 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.
管理多重疾病是医疗系统面临的一项重大挑战。心脏代谢多重疾病（CMM）非常普遍，且与疾病负担增加、功能衰退和死亡率上升有关。虽然大多数研究侧重于横断面分析，但纵向研究方法对于理解疾病进展和识别可能从针对性干预中受益的患者群体至关重要。本系统综述综合了关于CMM发病率和进展的纵向研究证据，探讨了多重疾病集群之间的转变及其临床意义。按照PRISMA指南在MEDLINE和EMBASE中进行了系统检索。如果研究采用纵向设计和聚类技术来评估多重疾病的演变，则将其纳入。使用GRADE系统评估证据质量。十项研究符合纳入标准。CMM在所有年龄组和男女中均有发生，死亡率和功能衰退率最高。患有CMM的患者经常会出现其他心脏代谢疾病或转变为相关集群。许多人还会经历神经退行性疾病和心理健康障碍。来自呼吸多重疾病集群的个体经常会转变为CMM。此外，CMM在社会经济地位较低的人群中更为普遍。了解多重疾病轨迹有助于制定有针对性的预防策略。识别具有可预测进展的患者有助于设计适当有效的干预措施，减少健康差距，并改善医疗结果。
