Abstract
Background
Few studies have explored the relationship between cardiometabolic index (CMI) and the risk of death from dialysis. This study aimed to investigates whether the CMI values correlates with cardiovascular and all-cause mortality in patients undergoing dialysis. The study population included patients undergoing maintenance hemodialysis (MHD) and maintenance peritoneal dialysis (MPD).
Method
This retrospective cohort study included patients undergoing dialysis (MHD and MPD) from January 2022 to and June 2025. Patients were divided into tertiles based on the CMI measured at the start of follow-up. Restricted Cubic Splines (RCS) were used to model the association between elevated CMI and the risk of adverse outcomes. The Kaplan-Meier curve was used to compare survival differences among the three groups. Additionally, a subgroup analysis identified and confirmed the risk factors.
Results
A total of 551 patients were included in this study. The risks of cardiovascular and all-cause mortality increased gradually across the CMI tertiles (13%, 19%, and 35% for cardiovascular mortality; 15%, 27%, and 50% for all-cause mortality; trend p < 0.001). RCS analysis was used to evaluate the association between elevated CMI and the risk of adverse outcomes. As CMI increased, the risk of all-cause mortality showed a significant increase (hazard ratio [HR] = 2.16, p < 0.001), as did the risk of cardiovascular mortality (HR = 1.82, p < 0.001) among all dialysis patients. After adjusting for various potential confounders, CMI remained a risk factor for cardiovascular and all-cause mortality among patients undergoing dialysis.
Conclusion
Increased CMI was positively correlated with a higher risk of cardiovascular mortality and all-cause mortality in patients undergoing dialysis.
Keywords: Cardiometabolic index, Maintenance hemodialysis, Maintenance peritoneal dialysis, Cardiovascular mortality, All-cause mortality
Introduction
The median global prevalence of chronic kidney disease (CKD) is 10%, with prevalence rates varying across regions owing to economic disparities and differences in screening methodologies [1]. Without effective control, CKD may progress to end-stage renal disease (ESRD), ultimately necessitating dialysis. The number of patients undergoing dialysis is increasing annually, and projections indicate that the dialysis population will double between 2010 and 2030 [2]. At the 2025 Annual Conference on Blood Purification of the Chinese Medical Association on July 3, Academician Chen Xiangmei reported that the dialysis population in China reached 1,183,000 in 2024, representing a net increase of 114,000 patients compared to 2023. This figure includes 1,027,000 patients undergoing hemodialysis, with 220,000 new admissions in 2024. Moreover, the peritoneal dialysis population increased by 156,000 during the same year, including 23,000 new admissions for peritoneal dialysis [3].
With an increasing number of patients undergoing dialysis, prognosis has become a critical concern. Cardiovascular disease (CVD) remains the primary cause of death among patients undergoing dialysis [4]. The cardiometabolic index (CMI), which consists of clinical parameters such as high-density lipoprotein cholesterol (HDL-C), triglyceride (TG), and waist-to-height ratio (WHtR) [5–7], is associated with a significantly increased risk of cardiovascular mortality in patients with elevated CMI levels. Previous studies have revealed that CMI values can be used to identify obesity-related disorders and cardiovascular dysfunctions, including diabetes, hyperuricemia, nonalcoholic fatty liver disease, hypertension, stroke, kidney disease, erectile dysfunction, and peripheral arterial disease [8–14]. However, few studies have explored the association between CMI and dialysis outcomes. Therefore, this study aimed to investigate whether the CMI correlates with cardiovascular and all-cause mortality in patients undergoing maintenance hemodialysis (MHD) or maintenance peritoneal dialysis (MPD).
Method
Participants
This retrospective cohort study enrolled 551 patients who were receiving maintenance hemodialysis or peritoneal dialysis in Shishi Municipal Hospital in Quanzhou City, Fujian Province, from January 2022 to June 2025. The requirement for patient consent was waived by the medical ethics committee. The inclusion criteria required patients to be over 18 years old and have received regular dialysis for more than 3 months. Exclusion criteria were as follows: (1) age < 18 years, (2) dialysis duration < 3 months, (3) presence of malignant tumors, and (4) survival period < 6 months after calculating the CMI value. Regular hemodialysis patients received treatments 2–3 times weekly, whereas peritoneal dialysis patients underwent continuous ambulatory peritoneal dialysis with 3–5 bags daily, depending on their residual renal function.
Data collection and definition
Demographic and clinical data were extracted from the medical information system of Shishi Municipal Hospital for all patients undergoing dialysis. These data included sex, age, dialysis mode, dialysis duration, comorbidities, and clinical test results. The parameters included are as follows: (1) General biochemical indicators: blood urea nitrogen (BUN), serum creatinine (Scr), TG, HDL-C, hemoglobin (Hb), C-reactive protein (CRP), serum calcium (Ca), serum phosphate (P), serum potassium (K), and parathyroid hormone (PTH). (2) Special renal function indicator: Kt/V (single pool). This indicator was calculated using the urea kinetics modeling formula: Kt/V = -ln(R − 0.008T) + (4–3.5R) × (UF/W), where R = post-dialysis urea/pre-dialysis urea, T = dialysis duration (h), UF = ultrafiltration volume (L), and W = post-dialysis patient weight (kg).
CMI calculation method
The CMI was calculated at the start of follow-up. Waist circumference (WC) was measured using a nonelastic tape at the midpoint between the 12th rib and iliac crest. This measurement followed the cutoff criteria recommended by the International Diabetes Federation. In patients undergoing peritoneal dialysis, WC was measured after the drainage of the morning dialysis fluid. The triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C) was calculated by dividing serum triglyceride concentration by HDL-C concentration (both in mmol/L). The WHtR was calculated by dividing the WC (cm) by height (cm). The CMI was calculated according to a previously published formula: TG/HDL-C multiplied by WHtR.
The criteria for hypertension were: (1) two separate resting systolic blood pressure measurements ≥ 140 mmHg and/or diastolic blood pressure ≥ 90 mmHg; or (2) current use of anti-hypertensive therapy.
The criteria for diabetes mellitus (DM) included the following: (1) patients receiving insulin or oral hypoglycemic agents, (2) patients clinically diagnosed with type 1 or type 2 diabetes mellitus, (3) fasting blood glucose (FPG) ≥ 7.0 mmol/L (126 mg/dL) including values obtained during a 75 g oral glucose tolerance test (OGTT).and (4) HbA1c ≥ 6.5%.
Cardiovascular disease (CVD) was defined as the occurrence of initial cardiovascular events during patient follow-up or a documented history of prior cardiovascular incidents. Such incidents included non-fatal myocardial infarction, non-fatal stroke, hospitalization for congestive heart failure, coronary revascularization, and cardiovascular-related mortality..
Cardiovascular mortality was defined as fatalities attributable to cardiovascular conditions during the follow-up period. These conditions included arrhythmias, cardiac arrest, congestive heart failure, cerebrovascular accidents, ischemic brain injury, hypoxic encephalopathy, peripheral vascular disease, acute myocardial infarction, atherosclerotic heart disease, cardiomyopathy, and arterial dissection or rupture.
Patients undergoing MHD or MPD who experienced all-cause mortality were defined as those who succumbed to cardiovascular mortality, infection, multiple organ failure, or other causes of death.
End point of study
Primary endpoint events: all-cause and cardiovascular mortality in patients undergoing MHD or MPD.
The follow-up endpoints were defined as follows: death, renal transplantation, transfer to another hemodialysis center for continued treatment, loss to follow-up, or termination of the study.
Statistical analysis
Continuous variables with a normal distribution are presented as mean ± standard deviation (SD) and were compared using t-tests or one-way analysis of variance. Variables that did not follow a normal distribution are expressed as median (interquartile range, IQR) and were analyzed using the Mann–Whitney U test or Kruskal–Wallis H test. Categorical data were evaluated using the chi-squared test. A restricted cubic spline model was used to investigate the association between elevated CMI and the risk of adverse outcomes. Univariate Cox regression analysis was conducted to identify variables associated with cardiovascular and all-cause mortality. Subsequently, the key variables and common traditional risk factors were incorporated into a multivariate Cox proportional hazards regression model. The Kaplan–Meier curve was used to compare survival disparities between the groups.
All statistical tests were two-tailed, and statistical significance was set at p < 0.05. Analyses were performed using SPSS version 25.0 (IBM Corp., Armonk, NY) and R version 3.6.0 (R Core Team, Vienna, Austria). Graphics were generated using GraphPad Prism version 10.4.2 (GraphPad Software, San Diego, CA) and R version 3.6.0.
Results
Baseline characteristics of patients grouped based on CMI tertiles
This study recruited 551 patients undergoing hemodialysis or peritoneal dialysis. Their baseline characteristics are presented in Table 1. The patients were stratified into low, middle, and high CMI tertile groups (0.12–0.54, 0.55–1.05, and 1.06–6.57, respectively), and clinical baseline comparisons were conducted between the overall population and each subgroup. The mean age of the enrolled patients was 58 years (range 19–87 years), and 347 (63%) were males. Significant differences were observed among the groups in terms of age, dialysis modality, and sex; however, no statistically significant variations were identified in dialysis duration, comorbid hypertension, or diabetes (Table 1).
Table 1.
Comparison of the clinical characteristics of MHD and MPD patients in different cardiometabolic index group
| Characteristics | Total population N=551 | Low CMI group N=183 | Middle CMI group N=184 | High CMI group N=184 | p value |
|---|---|---|---|---|---|
| Gender male N(%) | 347(63) | 112(61) | 123(67) | 112(61) | 0.016 |
| Female N(%) | 204(37) | 72(39) | 62(33) | 70(39) | |
| Age (years) | 58 (19-87) | 57(19-87) | 57(20-83) | 60(21-85) | <0.001 |
| Maintenance hemodialysis N(%) | 322(58) | 101 (55) | 108 (59) | 113(61) | 0.037 |
| Maintenance peritoneal dialysis N(%) | 229 (42) | 82 (45) | 76 (41) | 71 (39) | |
| Dialysis duration(months) | 42 (7-164) | 43 (8-162) | 41 (7-164) | 43 (8-160) | 0.893 |
| CVD N(%) | 276 (50) | 71 (39) | 82 (45) | 123 (67) | <0.001 |
| Hypertension N(%) | 419(76) | 132(72) | 140(76) | 146(80) | 0.187 |
| Diabetes mellitus N(%) | 268(49) | 87(47) | 90(49) | 91(50) | 0.892 |
| Hemoglobin (g/L) | 104 (37-167) | 117 (56-139) | 107 (47-167) | 94 (37-154) | <0.001 |
| C-reactive protein(mg/L ) | 26.0(0.1-242) | 7.1(0.1-143) | 20.3(0.64-242) | 50.0(0.1-231) | <0.001 |
| Serum potassium (mmol/L) | 4.36(2.5-7.21) | 4.33(2.63-5.75) | 4.42(2.5-6.15) | 4.36(3.12-7.21) | 0.742 |
| Serum phosphate(mmol/L) | 1.79(0.85-3.89) | 1.69(0.85-3.41) | 1.79(1.01-3.23) | 1.91(0.89-3.89) | 0.003 |
| Serum calcium (mmol/L) | 2.29(0.94-3.89) | 2.29(1.42-3.35) | 2.28(0.97-2.6) | 2.31(0.94-3.89) | 0.156 |
| Parathyroid hormone (pg/ml) | 309(12-1581) | 300(17-995) | 300(15-581) | 329(12-1212) | 0.033 |
| Serum creatinine (μmol/L)) | 955(392-1920) | 995(392-1858) | 898(400-1706) | 972(592-1920) | 0.078 |
| Blood urea nitrogen (mmol/L) | 23.54(8-45.2) | 22.95(8-45.2) | 23.61(11.7-44.2) | 24.08(10.8-41.2) | 0.624 |
| Triglycerides (mmol/L) | 1.98 (0.09-14.95) | 0.98 (0.09-2.16) | 1.79 (0.8-3.54) | 2.7 (0.62-14.95) | <0.001 |
| HDL-C (mmol/L) | 0.94 (0.12-3.06) | 0.98 (0.18-3.06) | 0.98 (0.4-1.97) | 0.7 (0.12-2.14) | <0.001 |
| Kt/V | 1.64(0.78-4.16) | 1.78(0.86-4.16) | 1.64(0.78-2.9) | 1.50(1.02-2.93) | <0.001 |
| Cardiometabolic index | 1.10(0.12-6.57) | 0.38(0.12-0.54) | 0.78(0.55-1.05) | 2.17(1.06-6.57) | <0.001 |
| Cardiovascular mortality N(%) | 123(22) | 24(13) | 35(19) | 64(35) | <0.001 |
| All-cause mortality N(%) | 170(31) | 28(15) | 50(27) | 92(50) | <0.001 |
MHD, maintenance hemodialysis; MPD, maintenance peritoneal dialysis; HDL-C, high-density lipoprotein cholesterol; CMI, cardiometabolic index; CVD, cardiovascular disease; Statistical tests were performed using the Kruskal-Wallis H test; p < 0.05 was considered statistically significant
Clinical parameters showed notable differences in Hb, CRP, P, and PTH levels, and Kt/V. In contrast, K, Ca, Scr, and BUN levels did not vary significantly. Additionally, significant differences were observed in CMI, TG, and HDL-C levels. Importantly, cardiovascular and all-cause mortality rates varied substantially across the groups (p < 0.001).
Over a median follow-up period of 30 months (IQR, 7–42 months), 170 patients (31%) died from all causes, including 123 (22%) who died of cardiovascular causes. In the low CMI group, 28 patients (15%) died from all causes, including 24 (13%) from cardiovascular causes. In the middle-CMI group, 50 patients (27%) died from all causes, including 35 (19%) from cardiovascular causes. In the high-CMI group, 92 patients (50%) died from all causes, including 64 (35%) from cardiovascular causes.
Clinical characteristics between the MHD and MPD groups
During the 42-month follow-up period, we compared the baseline clinical data between the MHD and MPD groups. The MHD subgroup included 332 participants (201 males, 62%), and the MPD subgroup included 229 participants (146 males, 64%). No significant sex differences were detected between the groups. No significant differences were observed in dialysis duration (p = 0.823). The two groups with combined hypertension did not differ significantly (p = 0.052); however, a statistically significant difference was observed in the incidence of diabetes (p = 0.038).
Clinical parameters showed notable differences in Hb, CRP, P, and PTH levels, and Kt/V. In contrast, the K, Ca, Scr, and BUN levels did not vary significantly. Significant differences were also found in the CMI, TG, and HDL-C levels. No statistically significant differences were observed between the two groups in terms of cardiovascular or all-cause mortality. (Table 2).
Table 2.
Differences in clinical characteristics between the MHD and MPD subgroups
| Characteristics | MHD (N = 322) | MPD (N = 229) | p value |
|---|---|---|---|
| Gender male N (%) | 201(62) | 146(64) | 0.431 |
| Female N (%) | 121(38) | 83(36) | |
| Age (years) | 59(19–87) | 57(21–85) | 0.02 |
| Dialysis duration(months) | 43(7-164) | 41(7-145) | 0.823 |
| Hypertension N (%) | 254(79) | 165(72) | 0.052 |
| Diabetes mellitus N (%) | 170(53) | 98(43) | 0.038 |
| Hemoglobin (g/L) | 100(37–167) | 110(51–159) | 0.021 |
| C-reactive protein(mg/L) | 28.5(0.09–242) | 22.34(0.1–218) | 0.001 |
| Serum potassium (mmol/L) | 4.26(2.5–6.15) | 4.42(2.63–5.75) | 0.892 |
| Serum phosphate (mmol/L) | 1.85(0.85–3.89) | 1.71(1.01–2.52) | 0.004 |
| Serum calcium (mmol/L) | 2.32 (1.42–2.7) | 2.3(1.73–3.35) | 0.082 |
| Parathyroid hormone(pg/ml) | 317 (12-1581) | 277(53-1212) | < 0.001 |
| Serum creatinine (µmol/L)) | 982 (382–1858) | 955(392–1920) | 0.083 |
| Blood urea nitrogen (mmol/L) | 23.54(8-45.2) | 24.08(10.8–41.2) | 0.357 |
| Triglycerides (mmol/L) | 2.2(0.61–14.95) | 0.97 (0.09–2.16) | < 0.001 |
| HDL-C (mmol/L) | 0.86(012-2.14) | 1.26 (0.18–3.06) | < 0.001 |
| Kt/V | 1.41(0.78–1.97) | 1.91(1.04–3.01) | 0.032 |
| cardiometabolic index | 1.6(0.64–6.57) | 0.42 (0.16–0.64) | < 0.001 |
| Cardiovascular mortality N (%) | 70(22) | 53 (23) | 0.573 |
| All-cause mortality N (%) | 98(30) | 72 (31) | 0.513 |
MHD, maintenance hemodialysis; MPD, maintenance peritoneal dialysis; HDL-C, high - density lipoprotein cholesterol; statistical tests are using the Mann-Whitney U test, p < 0.05 was considered statistically significant
Elevated CMI was associated with an increased risk of cardiovascular and all-cause mortality
To evaluate the association between CMI and cardiovascular and all-cause mortalities. The results presented in Table 1 show the clinical characteristics of patients classified into tertiles based on CMI. As the CMI increased, the risks of cardiovascular and all-cause mortality showed a gradual upward trend (13% vs. 19% vs. 35%, p < 0.001; 15% vs. 27% vs. 50%, p < 0.001). Conversely, the percentage of surviving patients decreased (85% vs. 73% vs. 50%; p < 0.001) (Fig. 1).
Fig. 1.
Patients were divided into low, middle, and high CMI groups, and cardiovascular mortality (A), all-cause mortality (B), and survival (C) were analyzed in each group. As CMI values increased, cardiovascular and all-cause mortality rates in patients undergoing dialysis increased, while the number of survivors decreased. Among these groups, *** indicates a statistically significant difference with p < 0.001
Restricted cubic splines were used to visualize the relationship between CMI and adverse outcomes. In all patients, when CMI was ≥ 2.07, and the risk of all-cause mortality increased significantly, when CMI was ≥ 2, and the risk of cardiovascular mortality increased significantly (Fig. 2).
Fig. 2.
Restricted cubic spline (RCS) curves illustrate the association between CMI and the risk of all-cause mortality (A) and cardiovascular mortality (B). CI, confidence interval; CMI, cardiometabolic index
In the MHD subgroup, which included 322 patients, 224 (70%) survived, and 98 (30%) experienced all-cause mortality. Among the deceased patients, 70 (71%) died from cardiovascular causes. The MPD subgroup included 229 patients, of whom 157 (69%) survived, 72 (31%) died from all causes, and 53 (74%) died from cardiovascular causes (Fig. 3).
Fig. 3.
Distribution of survival, all-cause mortality, and cardiovascular mortality in the MHD (A) and MPD (B) subgroups. MHD, maintenance hemodialysis; MPD, maintenance peritoneal dialysis
Restricted cubic splines were also used to visualize the relationship between CMI and adverse outcomes in the different subgroups. In the MHD subgroup, the risk of all-cause mortality significantly increased when the CMI was ≥ 2.3 (Fig. 4A). When the CMI ≥ 2.14, the risk of cardiovascular mortality significantly increased (Fig. 4B). In the MPD subgroup, the risk of all-cause mortality was significantly increased when the CMI was ≥ 2.51 (Fig. 4C). When the CMI ≥ 1.25, the risk of cardiovascular mortality significantly increased (Fig. 4D).
Fig. 4.
RCS curves showing the association between CMI and the risk of all-cause mortality (A) and cardiovascular mortality (B) in the MHD subgroup, and the association between CMI and the risk of all-cause mortality (C) and cardiovascular mortality (D) in the MPD subgroup. RCS, restricted cubic spline; CI, confidence interval; MHD, maintenance hemodialysis; MPD, maintenance peritoneal dialysis; CMI, cardiometabolic index
Analysis of CMI values and mortality risk in patients undergoing MHD and MPD
To present the outcomes of patients undergoing dialysis with varying CMI values, we constructed Kaplan–Meier survival curves. These curves illustrate all-cause and cardiovascular mortality based on low, medium, and high CMI levels. Among all patients undergoing dialysis (MHD and MPD), significant differences in all-cause and cardiovascular mortality were observed between the three groups, with log-rank values of 44.601 (p < 0.001) and 34.305 (p < 0.001), respectively (Fig. 5A and B). In both the MHD and MPD subgroups, significant differences in all-cause and cardiovascular mortality were observed between the three groups. The log-rank values were 18.719 (p < 0.001) and 9.127 (p = 0.010) for MHD (Fig. 5C and D), and 24.448 (p < 0.001) and 13.060 (p = 0.001) for MPD (Fig. 5E and F), respectively.
Fig. 5.
Kaplan–Meier curves of patients undergoing dialysis with different CMI levels showing all-cause mortality (A) and cardiovascular mortality (B) for all patients undergoing dialysis, all-cause mortality (C) and cardiovascular mortality (D) in MHD groups, and all-cause mortality (E) and cardiovascular mortality (F) in MPD groups across different CMI levels. CMI, cardiometabolic index; MHD, maintenance hemodialysis; MPD, maintenance peritoneal dialysis
Simultaneous group comparisons revealed statistically significant differences in all-cause and cardiovascular mortality among all patients undergoing dialysis across the three groups. The log-rank values for all-cause mortality were 8.504 (p = 0.004), 13.469 (p < 0.001), and 42.573 (p < 0.001), and those for cardiovascular death were 3.896 (p = 0.048), 12.984 (p < 0.001), and 31.097 (p < 0.001), respectively, as shown in Fig. 5A and B.
In the MHD subgroup, statistically significant differences in all-cause mortality were observed among the three groups, with log-rank values of 4.392 (p = 0.036), 5.210 (p = 0.022), and 17.766 (p < 0.001), respectively. No statistically significant differences were observed between the low- and medium-CMI groups (log-rank = 0.427, p = 0.513). Significant differences were observed in cardiovascular mortality between the remaining two groups, with log-rank values of 4.519 (p = 0.034) and 7.307 (p = 0.007), respectively, as shown in Fig. 5C and D.
In the MPD subgroup, we analyzed all-cause mortality among the three groups. There were no significant differences between the low- and middle-CMI groups (log-rank = 2.551, p = 0.110). However, statistically significant differences were observed between the other two groups, with log-rank values of 8.716 (p = 0.003) and 22.634 (p < 0.001). Regarding cardiovascular mortality between the three groups, no significant difference was found between the low- and middle-CMI groups (log-rank = 1.899, p = 0.168). However, significant differences were observed between the low- and high-CMI groups (log-rank = 4.147, p = 0.042) and between the middle- and high-CMI groups (log-rank = 12.293, p < 0.001), as shown in Fig. 5E and F.
CMI was associated with all-cause mortality and cardiovascular mortality
To identify the independent predictors of adverse outcomes in patients with all-cause and cardiovascular mortality, we performed univariate and multivariate Cox proportional hazards regression analyses for primary, secondary, and composite outcomes. Univariate Cox regression analysis revealed that CMI, age, history of diabetes mellitus, history of hypertension, history of CVD, hemoglobin level, CRP level, and serum inorganic phosphate level were associated with adverse outcomes. After adjusting for various potential confounders, CMI remained an independent risk factor for all-cause mortality (HR = 1.137, 95% confidence interval [CI] = 1.010–1.279, p = 0.034) and cardiovascular mortality (HR = 1.163, 95% CI = 1.012–1.337, p = 0.033) (Table 3).
Table 3.
Association of CMI with all-cause mortality and cardiovascular mortality
| Model 1 | Model 2 | Model 3 | ||||
|---|---|---|---|---|---|---|
| HR (95%CI) | p value | HR (95%CI) | p value | HR (95%CI) | p value | |
| All-cause mortality |
1.288 (1.155–1.435) |
< 0.001 |
1.142 (1.017–1.282) |
0.025 |
1.137 (1.010–1.279) |
0.034 |
| Cardiovascular mortality |
1.220 (1.076–1.383) |
0.002 |
1.189 (1.036–1.365) |
0.014 |
1.163 (1.012–1.337) |
0.033 |
Model 1: adjusted for age, history of diabetes mellitus
Model 2: adjusted for age, history of diabetes mellitus, history of hypertension, history of CVD
Model 3: adjusted for age, history of diabetes mellitus, history of hypertension, history of CVD, hemoglobin, C-reactive protein, Serum phosphate
HR hazard ratio, CI confidence interval, CMI cardiometabolic index, CVD cardiovascular disease, p value < 0.05 was considered statistically significant
Discussion
Despite numerous efforts over the past few decades to improve clinical outcomes, CVD remains the leading cause of death and illness in the general population in China [15–17]. This study aimed to investigate the relationship between CMI and the risk of CVD events in patients undergoing dialysis. To the best of our knowledge, this is the first study to explore CMI and mortality in patients undergoing dialysis, including those undergoing hemodialysis and peritoneal dialysis.
This study was based on a 3.5-year retrospective investigation of a dialysis population from a single center in a southern Chinese city. Cardiovascular causes were the most prevalent causes of death among patients undergoing dialysis. According to the tertiles of the CMI, higher CMI levels were associated with significantly increased cardiovascular and all-cause mortality. Even after adjusting for potential confounders, CMI remained associated with cardiovascular and all-cause mortality in patients undergoing dialysis.Subgroup analyses of hemodialysis and peritoneal dialysis showed that CMI was associated with outcome events.
The CMI is a newly developed indicator of visceral adipose tissue (VAT) distribution and dysfunction and has proven useful for evaluating the risk of obesity-related metabolic diseases, such as diabetes [18, 19] and cardiovascular diseases [20–22]. CMI includes anthropometric and biochemical measures, such as the WHtR and the TG/HDL-C ratio [18], both of which can be readily obtained during health examinations. The WHtR is recognized as a valuable measure that reflects the functions of both subcutaneous adipose tissue and VAT compartments [23]. The TG/HDL-C ratio is a well-established simple marker that closely reflects diabetic dyslipidemia and insulin resistance (IR) [24] and is strongly associated with cardiovascular mortality. Additionally, we aimed to explore the factors contributing to all-cause mortality in patients with high CMI values undergoing dialysis.
Patients with ESRD who are undergoing dialysis have an elevated risk of mortality. This risk is primarily due to CVDs, which are the leading causes of death in this patient population. Given the complexity of their condition, which is often complicated by comorbidities such as diabetes and hypertension, the identification of reliable prognostic indicators is crucial. Previous studies have suggested that CMI may be associated with mortality risk in patients undergoing dialysis [25, 26].
Our research uncovered a notable trend: elevated CMI values were significantly associated with higher mortality rates, emphasizing the importance of incorporating CMI monitoring into routine clinical assessments to improve prognostic accuracy and guide treatment in patients undergoing dialysis [27].
Our study results have several significant clinical implications. These findings may improve patient management strategies aimed at reducing cardiovascular complications, which are the leading causes of death in patients on dialysis. Moreover, the development of nomograms based on the CMI can offer clinicians an invaluable instrument for predicting mortality risk and optimizing decision-making processes in clinical scenarios [28].
Patients undergoing dialysis encounter multiple complications such as renal failure, accumulation of uremic toxins and wastes, dyslipidemia, and premature cellular aging. Additionally, these patients are exposed to dialysis-related factors such as dialysis membranes, central venous catheters, dialysis fluid contamination, and peritoneal dialysis-related peritonitis [29]. This may explain why the difference in mortality rates between low CMI and middle CMI in the MHD subgroup was smaller than that in the MPD subgroup. Patients undergoing MHD often have more uniform health management strategies that may mitigate the impact of CMI levels on mortality. In contrast, the MPD subgroup may exhibit greater variability in health outcomes owing to differing treatment responses and disease progression, leading to a larger disparity in mortality rates between the CMI categories.
Previous research has established a strong correlation between the atherogenic index of plasma (AIP), triglyceride (TyG) index, homeostasis model assessment of insulin resistance (HOMA-IR), and the inflammation biomarker high-sensitivity CRP [30]. The AIP, stress hyperglycemia ratio, TyG index, and HOMA-IR are crucial cardiometabolic indices reflecting various aspects of metabolic health [31–33], all of which are cardiometabolic indices. Based on our study, the observed CMI values in patients undergoing dialysis were associated with cardiovascular and all-cause mortality and can serve as a key cardiometabolic index.
This study has certain limitations. First, its retrospective design intrinsically restricted the capacity to ascertain a causal relationship between CMI and mortality outcomes. Moreover, the single-center design may have introduced selection bias, limiting the universality of the findings to larger and more diverse dialysis populations. Notably, our use of Cox regression analysis may potentially overestimate mortality rates, which represents a limitation of our study design. Future research should consider multicenter designs with larger and more heterogeneous cohorts to validate the predictive capacity of the CMI across diverse populations and settings. Although various confounding factors were adjusted for, residual confounding cannot be entirely ruled out and may have affected the observed associations. The dependence on historical data for CMI measurements may introduce variability, owing to temporal changes in clinical practice. Finally, the study duration, ending in June 2025, may not have captured long-term outcomes beyond this period, which may limit the long-term applicability of the results. Longitudinal studies evaluating the temporal association between changes in the CMI and mortality outcomes are warranted to provide deeper insights into the utility of the CMI as a dynamic clinical marker [34].
Conclusion
This study revealed a notable correlation between elevated CMI and heightened risks of cardiovascular and all-cause mortality among patients undergoing dialysis. Higher CMI was associated with increased mortality risk. Considering the independent predictive value of CMI in both the MHD and MPD subgroups, additional prospective investigations are necessary to validate these findings and explore potential interventions for reducing mortality risks associated with elevated CMI in patients undergoing dialysis.
Acknowledgements
Not applicable.
Abbreviations
- AIP
Atherogenic index of plasma
- BUN
Blood urea nitrogen
- Ca
Calcium
- CKD
Chronic kidney disease
- CMI
Cardiometabolic index
- CVD
Cardiovascular disease
- ESRD
End-stage renal disease
- HDL-C
High-density lipoprotein cholesterol
- HOMA-IR
Homeostasis model assessment of insulin resistance
- IR
Insulin resistance
- K
Potassium
- MHD
Maintenance hemodialysis
- MPD
Maintenance peritoneal dialysis
- P
Phosphorus
- PTH
Parathyroid hormone
- Scr
Serum creatinine
- SHR
Stress hyperglycemia ratio
- TG
Triglyceride
- TyG
Triglyceride-glucose index
- VAT
Visceral adipose tissue
- WHtR
Waist-to-height ratio
- SAT
Subcutaneous adipose tissue
Author contributions
Z.H. Li and J.X. Wan conceived and designed the study. H.J. Chen and M.M. Cai were responsible for data collection and curation. Z.H. Li and H.J. Chen carried out the data analysis, executed the data visualization, and prepared the initial draft of the manuscript. B.L. Hong oversaw the research and played a role in securing the funding. All authors participated in the revision of the manuscript and gave their approval for the final version of the manuscript.
Funding
J.X.W. has received research grants from the Fujian Provincial Science and Technology Plan Project (No. 2021Y2005). B.L.H. has received research grants from Quanzhou City Science and Technology Project (No. 2024NY118).
Data availability
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Declarations
Ethics approval and consent to participate
This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Shishi Municipal Hospital (202539). The written informed consent was exempted by the Ethics Committee of Shishi Municipal Hospital for the retrospective nature of the current study.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Zhenhui Li and Hanjie Chen contributed equally to this work.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.