Regional Prevalence, Stage Distribution, and Temporal Trends of Cardiovascular-Kidney-Metabolic Syndrome in the Americas, Europe and Western Pacific: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Abstract Background The cardiovascular-kidney-metabolic (CKM) syndrome, first proposed by the American Heart Association (AHA) in 2023, represents a groundbreaking conceptual framework that integrates these three interrelated conditions into a unified clinical entity. Despite growing research on its prevalence, risk factors, and clinical management, the regional burden of CKM syndrome remains poorly characterized. To address this gap, we aimed to estimate the prevalence of CKM syndrome, providing critical insights into the regional impact of this novel disease definition. Methods In this study, we conducted literature retrieval in both English (PubMed, Web of Science and Wiley Online Library) and Chinese databases (CNKI and Wangfang), as well as the journal official websites (e.g. American Heart Association (AHA) and American Society of Nephrology (ASN)) from database inception until January 20, 2025, followed by an update search until April 1, 2025. Grey literature such as posters and preprint articles, and citations from the identified reviews were also searched for. Cross sectional and cohort studies were included without language limitation. Studies employing other study designs or were done in people who were not representative of the general population (e.g. people with specific diseases) were excluded. Summary data were obtained from included studies. The primary outcomes were the prevalence of CKM syndrome and its different stages (stages 0 - 4) among general population. The combined prevalence was obtained with Freeman-Tukey Double Arcsine Transformation method. The estimated annuls percentage change (EAPC) was employed to explore the trend of CKM syndrome. This study is registered with PROSPERO (CRD420251037912). Findings From 2,708 identified 2,708 related articles, 28 studies with 29 datapoints, encompassing 1,561,209 individuals, were included. The overall pooled prevalence of CKM syndrome (Stages 1–4) in the general population was 0.88 [95% CI 0.86–0.91]. This estimate was 0.85 [95% CI 0.76–0.91] in a sensitivity analysis selecting one representative study per database to test the magnitude of potential duplicate bias. The combined prevalence of stages 1, 2, 3 and 4 was 0.23 [95% CI 0.19–0.27], 0.46 [95% CI 0.41–0.51], 0.08 [95% CI 0.05–0.11], 0.07 [95% CI 0.04–0.12], respectively, displaying as the Stage 2 patients were the majority of CKM syndrome. The EAPC of CKM syndrome in the period of 1991-2021 was (-0.55% [95% CI -0.90 to 0.21], p=0.0024), displaying a significant decreased trend. Stratified by countries, the pooled estimates were 0.91 [95% CI 0.90–0.93] for USA, 0.90 [95% CI 0.87–0.93] for China, and 0.77 [95% CI 0.69–0.84] for other countries (UK, Italy and South Korea). CKM syndrome prevalence demonstrated an increasing trend with a higher proportion of males (male/female ratio <0.98) and with increasing mean age (up to 56.5 years). Statistically significant disparities were observed across social development index (SDI) level, data source and countries. Interpretation This study provides the pooled regional prevalence of CKM syndrome in the general population; these findings are valuable for understanding the current burden of CKM syndrome and facilitating more research into the clinical management and prevention. While a slight decreasing temporal trend was observed based on the included studies, the relatively high combined prevalence suggests more epidemiological research into missing regions, such as Africa and South America, to verify this finding. Research In Context Evidence before this study Cardiovascular-Kidney-Metabolic (CKM) syndrome has drawn substantial attention to the complex interactions among cardiovascular, kidney and metabolic diseases. Previous studies reported a heavy burden of CKM syndrome in certain jurisdictions, for example, the weighted prevalence was 83.7% in China in 2019 and 79.5% in the USA in 2023 nationwide. However, the epidemiological studies reporting the burden of CKM syndrome regionally remain inadequate. Thus, we did a meta-analysis to map the prevalence of CKM syndrome globally. We searched PubMed from database inception to April 1, 2025, using terms (with variants) like “meta-analysis”, “CKM syndrome” and “prevalence”, and did not find any other meta-analysis reporting this topic. Added value of this study This study provides a comprehensive regional view of the prevalence of CKM syndrome in the general population, with additional temporal trend analysis based on study period, male/female ratio and average age. Our analysis indicated a significant but slight downward trend of the prevalence of CKM syndrome from 1991 to 2021. The pooled prevalence of CKM syndrome was between 0.85 [95% CI 0.76–0.91] and 0.88 [95% CI 0.86–0.91], with stage 2 patients taking the highest proportion. Significant differences were observed across sociodemographic index (SDI), data source and countries. Middle level SDI, population-based design and USA showed the highest prevalence of CKM syndrome compared to their counterparts. Implications of all the available evidence This study provides up-to-date estimates of regional burden of CKM syndrome and can be referred to future public health promotion planning, as well as to explore the risk factors and locate the high-risk population. The relatively high pooled prevalence of CKM syndrome, nearly close to 90%, highlights the urgent need for developing risk stratification and prevention strategies for CKM syndrome patients, especially preventing staging progress among substantial stage 2 patients. The significant disparities in the prevalence of CKM syndrome across SDI, data source of the study and countries necessitating targeted strategies and further study design of this topic. Both developed and developing countries are facing heavy burden of CKM syndrome, where public health policies to reduce risk factors of CKM syndrome might be effective in alleviating the burden. Although the reported prevalence of CKM syndrome has declined from 1991 to 2021, this trend may be influenced by publication bias, as key regions with potentially higher CKM syndrome risks, such as Africa and South America, lack sufficient prevalence data. Therefore, more studies need to be conducted in these regions for more accurate estimate of global prevalence. Besides, more population-specific prevalence (such as sex, age group, different groups of patients) are also needed to help with risk factors determination.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.030 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".