Association between high-sensitivity troponin T levels below the ninety-ninth percentile and diabetic kidney disease: A cross-sectional study

Abstract

BACKGROUND

Identification of myocardial injury has traditionally relied on high-sensitivity troponin T (hs-TnT) levels exceeding the 99^th percentile threshold. However, patients with detectable hs-TnT levels below this threshold represent a heterogeneous group with an inadequately characterized risk profile.

AIM

To investigate the association between hs-TnT levels below the 99^th percentile and the presence of diabetic kidney disease (DKD) in patients with diabetes mellitus.

METHODS

This study analyzed data from the National Health and Nutrition Examination Survey obtained between 1999 and 2004, focusing on adults with type 2 diabetes mellitus. Serum hs-TnT concentrations were evaluated. DKD was defined as impaired glomerular filtration rate (< 60 mL/minute/1.73 m²), proteinuria (urinary albumin-to-creatinine ratio of ≥ 30 mg/g), or both conditions in patients with diabetes mellitus. Weighted multivariable logistic regression analysis and restricted cubic spline analyses were employed to examine the independent association between hs-TnT and DKD, with the likelihood ratio test being used to evaluate nonlinearity.

RESULTS

The study included 2505 patients with a mean age of 55.02 (standard error: 0.72) years, of whom 44.87% were females. Among the participants, 909 (32.34%) were diagnosed with DKD. Multivariable logistic regression analysis indicated that, compared to the lowest tertile of hs-TnT (< 5.93 ng/L), tertile 2 (5.94-9.79 ng/L) had an odds ratio of 1.25 (95% confidence interval: 0.77-2.02, P = 0.350), while tertile 3 (9.80-21.88 ng/L) had an odds ratio of 2.07 (95% confidence interval: 1.13-3.80, P = 0.022), with a significant trend (P for trend = 0.022). Smoothed curve fitting demonstrated a linear association between hs-TnT levels and DKD in the overall population (P = 0.061 for nonlinearity) and in male (P = 0.136 for nonlinearity) and female (P = 0.067 for nonlinearity) subgroups. Further stratification and sensitivity analyses yielded consistent conclusions.

CONCLUSION

Our study findings suggest that in individuals with type 2 diabetes, detectable hs-TnT levels below the 99^th percentile are associated with DKD.

Key Words: High-sensitivity troponin T; 99^th percentile; Diabetic kidney disease; Diabetic nephropathies; National Health and Nutrition Examination Survey

Core Tip: High-sensitivity troponin T levels below the 99^th percentile show a significant linear association with diabetic kidney disease in type 2 diabetes mellitus patients. This association, derived from National Health and Nutrition Examination Survey data analysis, suggests that even subclinical elevations in high-sensitivity troponin T could serve as an early indicator for diabetic kidney disease risk assessment, particularly in the highest tertile (9.80-21.88 ng/L) with an odds ratio of 2.07.

INTRODUCTION

Diabetes mellitus presents a global health crisis, affecting an estimated 463 million individuals worldwide in 2019, with projections reaching 700 million cases by 2045[1]. Type 2 diabetes mellitus (T2DM) accounts for most of these cases and continues to rise at an alarming rate. Among its complications, diabetic kidney disease (DKD) is a leading cause of morbidity and mortality, contributing significantly to the burden of end-stage renal disease[2]. Despite advancements in diabetes management, including sodium-glucose cotransporter 2 inhibitors and glucagon-like peptide-1 receptor agonists, the risk of developing DKD remains substantial in patients with T2DM[3]. This highlights an urgent need for novel biomarkers and mechanisms to understand better and manage the onset and progression of DKD.

High-sensitivity troponin T (hs-TnT) has recently gained attention as a biomarker traditionally used to diagnose myocardial injury, with elevated levels above the 99^th percentile indicating myocardial injury[4]. However, patients with hs-TnT levels below this threshold represent a heterogeneous group with an inadequately defined risk profile and are often overlooked clinically. Emerging evidence suggests that even sub-threshold hs-TnT levels are associated with a higher burden of cardiovascular risk factors, greater cardiac pathology, and poorer prognosis[5,6]. This raises the possibility that low hs-TnT levels might indicate subclinical organ damage, including kidney damage in patients with diabetes. Evidence has demonstrated a potential relationship between hs-TnT levels and renal outcomes in diabetic populations[7]. Recent studies further highlight the predictive value of hs-TnT assays for peripheral microangiopathy in T2DM[8], and increased risks of renal and cardiovascular events in patients with DKD[9].

The pathophysiology of DKD is complex, involving a cascade of events triggered by chronic hyperglycaemia, including oxidative stress, inflammation, and endothelial dysfunction, which collectively contribute to progressive kidney function decline[10]. These mechanisms might plausibly lead to elevated hs-TnT levels, even below the myocardial injury threshold. This hypothesis is further supported by the shared pathways of vascular damage and inflammation between the heart and kidneys[11]. Despite this compelling rationale, comprehensive studies investigating the association between hs-TnT levels below the 99^th percentile and the presence and severity of DKD in patients with T2DM remain limited. This study used data from the National Health and Nutrition Examination Survey (NHANES) to examine the relationship between low hs-TnT levels and DKD in adults with T2DM.

MATERIALS AND METHODS

Study population

The NHANES program was designed to represent the United States population through a complex, stratified, multistage probability cluster sampling method, selecting participants from the noninstitutionalized civilian population. This study analyzed NHANES data obtained from 1999 to 2004, focusing on participants aged ≥ 20 years. The exclusion criteria included individuals with undiagnosed diabetes, baseline cancer, missing sample weights, or incomplete hs-TnT data. Additionally, participants with hs-TnT values exceeding the sex-specific 99^th percentile of the upper reference limit were excluded. A final cohort of 2505 participants was included, with the detailed inclusion and exclusion process shown in Figure 1. The NHANES protocol and the measurement of hs-TnT in stored samples were approved by the Ethics Review Board of the National Centre for Health Statistics. Written informed consent was obtained from all participants.

Figure 1  Study flowchart.

hs-TnT measurement

hs-TnT levels were measured using Elecsys reagents on the Roche Cobas e601 platform, which received Food and Drug Administration clearance on January 18, 2016. The lower limit of detection (LoD) for this fifth-generation assay is 3 ng/L. The sex-specific 99th percentile upper reference limits for hs-TnT, as defined by the International Federation of Clinical Chemistry and Laboratory Medicine[12], are 14 ng/L for females and 22 ng/L for males when using the Roche hs-TnT assay[12].

Outcome variable

Diabetes mellitus was defined based on one or more of the following criteria: (1) A prior diagnosis by healthcare professionals; (2) Fasting plasma glucose levels of ≥ 7.0 mmol/L; (3) Glycosylated haemoglobin (HbA1c) levels of ≥ 6.5%; and (4) The current use of diabetes medications. Albuminuria was evaluated using the urine albumin-to-creatinine ratio, while estimated glomerular filtration rate (eGFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration formula. DKD in patients with T2DM was diagnosed if albumin-to-creatinine ratio was ≥ 30 mg/g and/or eGFR was < 60 mL/minute/1.73 m²[13].

Assessment of covariates

Covariates included age (years), sex (male or female), race/ethnicity (Mexican American, non-Hispanic white, non-Hispanic black, other Hispanic, or other races including multi-racial), educational level (< 9 years, 9-13 years, or ≥ 13 years), household poverty income ratio (PIR), body mass index (BMI), smoking status (never smoker, current smoker, or former smoker), alcohol intake (never, moderate, or heavy), use of diabetes medications (none, other medications, insulin, or oral medications), and diabetes duration (< 10 years or ≥ 10 years). Hypertension was defined as systolic blood pressure of ≥ 140 mmHg or diastolic blood pressure of ≥ 90 mmHg, self-reported hypertension, physician-diagnosed hypertension, or the use of antihypertensive medication. Self-reported cardiovascular disease (CVD) included congestive heart failure, angina, myocardial infarction, or coronary heart disease. Hyperlipidaemia was defined as triglyceride levels of ≥ 150 mg/dL (1.7 mmol/L), total cholesterol levels of ≥ 200 mg/dL (5.18 mmol/L), low-density lipoprotein cholesterol levels of ≥ 130 mg/dL (3.37 mmol/L), or high-density lipoprotein cholesterol levels of < 40 mg/dL (1.04 mmol/L) for men, and < 50 mg/dL (1.30 mmol/L) for women. Healthy Eating Index (HEI) scores were computed based on the HEI-2015 guidelines. Physical activity was defined as engaging in moderate- or vigorous-intensity sports, fitness programs, or recreational activities for more than 10 minutes per week. Participants were classified as inactive if they engaged in such activities for ≤ 10 minutes per week.

Statistical analysis

To account for the complex sampling design of NHANES, our analyses incorporated sample weights, clustering, and stratification to ensure valid and representative results. Weighted means were calculated for continuous variables, while weighted percentages were used for categorical variables. Statistical comparisons were conducted using analysis of variance or the Kruskal-Wallis test for continuous variables and the χ² test for categorical variables. The hs-TnT levels were categorized into tertiles: Tertile 1 (< 5.93 ng/L), tertile 2 (5.94-9.79 ng/L), and tertile 3 (9.80-21.88 ng/L). Weighted multivariable logistic regression analyses were used to assess the correlation between hs-TnT levels and DKD across three models: Model I: Adjusted for age and sex; Model II: Included additional adjustments for race/ethnicity, education level, PIR, BMI, smoking status, eGFR, and comorbidities, including hypertension, CVD, and hyperlipidaemia, as well as physical activity and alcohol intake; Model III: Further as adjusted for HbA1c, HEI, diabetes duration, and diabetes medication use. To investigate the potential nonlinear relationship between hs-TnT and DKD, a restricted cubic spline analysis with three knots was performed. Multiple imputation was used to address missing values in covariates.

Stratified analyses were performed based on age (< 60 years or ≥ 60 years), sex (female or male), race (White or non-White), PIR (< 1.0, 1.0-3.0, or ≥ 3.0), BMI (< 30 kg/m² or ≥ 30.0 kg/m²), education level (< 9 years, 9-13 years, ≥ 13 years), smoking status (never smoker, former smoker, or current smoker), physical activity (inactive or active), alcohol intake (none, moderate, or heavy), diabetes duration (< 10 years or ≥ 10 years), use of diabetes medications (none, other, or insulin/oral medications), HbA1c (< 7.0% or ≥ 7.0%), and the presence of comorbid conditions including hypertension (yes or no), CVD (yes or no), and hyperlipidaemia (yes or no). Interaction terms between hs-TnT and these stratified variables were evaluated, and their significance was assessed using P values. The results of these analyses were visually presented in a forest plot. To assess the robustness of the findings, sensitivity analyses were conducted. First, comparisons of covariates were made using interpolated data across the complete dataset. Second, given the potential unreliability of hs-TnT measurements below LoD (< 3 ng/L), these data points were excluded and repeated weighted regression analyses were performed.

RESULTS

Study participants and baseline characteristics

Among the final cohort of 2505 individuals with diabetes, the mean age was 55.02 (standard error: 0.72) years , and 44.87% of the participants were females. Baseline characteristics of the study population, stratified by hs-TnT tertiles, are detailed in Table 1. Participants with higher hs-TnT levels were more likely to be older, male, non-Hispanic white, and former smokers. They also exhibited higher rates of hypertension, CVD, and DKD. Additionally, these individuals tended to have a longer duration of diabetes, were more likely to use insulin, had more severe proteinuria, and demonstrated lower eGFRs.

Table 1 Baseline characteristics of the study participants, n (%).

Variables	Total (n = 2505)	High-sensitivity troponin T (ng/L)			P value
		< 5.93	5.94-9.79	9.80-21.88
		Tertile 1 (n = 839)	Tertile 2 (n = 831)	Tertile 3 (n = 835)
Age, years	55.02 (0.72)	47.64 (1.00)	56.69 (1.09)	62.99 (0.93)	< 0.001
Sex					< 0.001
Female	1132 (44.87)	569 (63.57)	359 (38.07)	204 (27.68)	-
Male	1373 (55.13)	270 (36.43)	472 (61.93)	631 (72.32)	-
Race-ethnicity					0.010
Mexican American	798 (8.10)	313 (11.07)	277 (6.98)	208 (5.43)	-
Non-Hispanic black	537 (14.49)	178 (16.02)	159 (12.53)	200 (14.71)	-
Non-Hispanic white	897 (60.58)	234 (52.97)	286 (60.22)	377 (71.23)	-
Other Hispanic	158 (8.53)	67 (9.92)	64 (9.97)	27 (4.95)	-
Other race	115 (8.31)	47 (10.02)	45 (10.30)	23 (3.68)	-
Poverty income ratio	2.62 (0.08)	2.63 (0.15)	2.72 (0.12)	2.48 (0.11)	0.220
BMI, kg/m2	32.62 (0.50)	33.05 (0.61)	32.69 (0.90)	31.96 (0.52)	0.306
Education level					0.108
Low (< 9 years)	683 (11.73)	216 (11.02)	232 (10.82)	235 (13.74)	-
Medium (9-13 years)	1074 (47.90)	362 (46.04)	334 (44.80)	378 (54.02)	-
High (≥ 13 years)	748 (40.37)	261 (42.94)	265 (44.38)	222 (32.25)	-
Smoking status					0.030
Never smoker	1144 (45.76)	446 (51.51)	360 (41.46)	338 (43.06)	-
Former smoker	877 (32.26)	214 (25.21)	306 (34.64)	357 (38.95)	-
Current smoker	484 (21.98)	179 (23.28)	165 (23.90)	140 (17.99)	-
Comorbidity
Hyperlipidemia					0.948
No	307 (10.33)	92 (10.00)	97 (10.78)	118 (10.24)	-
Yes	2198 (89.67)	747 (90.00)	734 (89.22)	717 (89.76)	-
Hypertension					0.001
No	864 (39.05)	375 (48.26)	286 (40.55)	203 (24.92)	-
Yes	1641 (60.95)	464 (51.74)	545 (59.45)	632 (75.08)	-
CVD					< 0.001
No	2064 (83.38)	767 (90.46)	702 (87.41)	595 (69.16)	-
Yes	441 (16.62)	72 (9.54)	129 (12.59)	240 (30.84)	-
Alcohol intake					0.510
None	2094 (79.83)	703 (79.11)	683 (77.18)	708 (83.89)	-
Moderate	188 (10.27)	56 (9.83)	75 (12.65)	57 (8.10)	-
Heavy	223 (9.90)	80 (11.07)	73 (10.17)	70 (8.00)	-
Physical activity					0.060
Inactive	869 (28.65)	285 (26.14)	285 (25.77)	299 (35.41)	-
Active	1636 (71.35)	554 (73.86)	546 (74.23)	536 (64.59)	-
Diabetes duration					< 0.001
< 10 years	1657 (69.37)	653 (80.08)	548 (70.91)	456 (53.18)	-
≥ 10 years	848 (30.63)	186 (19.92)	283 (29.09)	379 (46.82)	-
Use of diabetes medications					0.001
No	442 (18.47)	200 (24.69)	154 (18.38)	88 (10.23)	-
Other1	627 (26.07)	196 (26.25)	224 (27.90)	207 (23.69)	-
Insulin	227 (9.70)	62 (7.64)	71 (7.50)	94 (15.03)	-
Oral medications	1209 (45.76)	381 (41.42)	382 (46.21)	446 (51.05)	-
ACR category					0.004
A1 (< 30 mg/g)	1758 (73.89)	617 (77.88)	616 (75.15)	525 (67.04)	-
A2 (30-300 mg/g)	600 (21.64)	209 (20.30)	174 (21.96)	217 (23.07)	-
A3 (≥ 300 mg/g)	147 (4.47)	13 (1.82)	41 (2.89)	93 (9.89)	-
Diabetic kidney disease					< 0.001
No	1596 (67.66)	612 (77.51)	556 (68.63)	428 (53.28)	-
Yes	909 (32.34)	227 (22.49)	275 (31.37)	407 (46.72)	-
HbA1c (%)	7.56 (0.09)	7.55 (0.18)	7.55 (0.11)	7.59 (0.14)	0.977
Healthy eating index	51.34 (0.71)	50.36 (1.20)	52.11 (1.07)	51.77 (0.93)	0.409
eGFR (mL/minute/1.73 m2)	89.94 (0.79)	100.45 (1.33)	88.53 (1.48)	77.47 (1.38)	< 0.001

¹Indicated drugs except diabetes medications.

Data are represented as the weighted proportion (%) or mean ± SE. BMI: Body mass index; CVD: Cardiovascular disease; ACR: Albumin-to-creatinine ratio; HbA1c: Glycated hemoglobin A1c; eGFR: Estimated glomerular filtration rate.

Association of hs-TnT with DKD

In Model III of the weighted multivariate logistic regression analysis, a linear relationship between hs-TnT levels and DKD was observed. Compared to tertile 1 (< 5.93 ng/L), the odds ratios for tertile 2 (5.94-9.79 ng/L) and tertile 3 (9.80-21.88 ng/L) were 1.25 [95% confidence interval (CI): 0.77-2.02] and 2.07 (95%CI: 1.13-3.80), respectively, with a significant trend (P for trend = 0.022). When hs-TnT was analyzed as a continuous variable, the odds ratio was 1.07 (95%CI: 1.01-1.13). Smoothed curve fitting further supported a linear association between hs-TnT and DKD across the total population (P for nonlinearity = 0.061), as well as among males (P for nonlinearity = 0.136) and females (P for nonlinearity = 0.067) (Figure 2 and Table 2).

Figure 2 Multivariable-adjusted odds ratio for diabetic kidney disease by high-sensitivity troponin T. Age, sex, race, education, body mass index, poverty income ratio, smoking status, hypertension, cardiovascular disease, hyperlipidemia, physical activity, alcohol intake, estimated glomerular filtration rate, diabetes duration, use of diabetes medications, healthy eating index, and glycated hemoglobin A1c were adjusted. Solid lines and shading represent estimates and their corresponding 95% confidence intervals, respectively. A: All population; B: Females; C: Males. hs-TnT: High-sensitivity troponin T.

Table 2 Association between high-sensitivity troponin T and diabetic kidney disease in patients with type 2 diabetes mellitus.

Variable	DKD/total	Non-adjusted model	P value	Model I	P value	Model II	P value	Model III	P value
	n	HR (95%CI)		HR (95%CI)		HR (95%CI)		HR (95%CI)
Continuous variable
hs-troponin T (ng/L)	909/2505	1.11 (1.06-1.16)	< 0.001	1.11 (1.05-1.16)	< 0.001	1.08 (1.02-1.15)	0.017	1.07 (1.01-1.13)	0.030
Binary variable
Tertile 1 (< 5.93)	227/839	Reference	-	Reference	-	Reference	-	Refrence	-
Tertile 2 (5.94-9.79)	275/831	1.58 (1.00-2.48)	0.048	1.51 (0.91-2.50)	0.110	1.32 (0.82-2.13)	0.239	1.25 (0.77-2.02)	0.350
Tertile 3 (9.80-21.88)	407/835	3.02 (1.87-4.88)	< 0.001	2.80 (1.62-4.83)	< 0.001	2.30 (1.20-4.41)	0.015	2.07 (1.13-3.80)	0.022
P for trend	-	-	< 0.001	-	< 0.001	-	0.015	-	0.022

Model I: Adjusted for age (continuous) and sex (male or female); Model II: Adjusted for Model I plus race (Mexican American, non-Hispanic white, non-Hispanic black, Other Hispanic, other races including multi-racial), education level (< 9, 9-13, ≥ 13); body mass index (continuous), poverty income ratio (continuous), smoking status (never smoker, former smoker, current smoker), hypertension (no, yes), cardiovascular disease (no, yes), hyperlipidemia (no, yes), physical activity (inactive, active), alcohol intake (none, moderate, heavy), and estimated glomerular filtration rate(continuous); Model III: Adjusted for Model II plus diabetes duration (< 10 years, ≥ 10 years), use of diabetes medications (no, other, insulin, oral medications), healthy eating index (continuous), and glycated hemoglobin A1c (continuous); DKD: Diabetic kidney disease; HR: Hazard ratio; CI: Confidence interval; hs-troponin T: High-sensitivity troponin T.

Stratified and sensitivity analyses

Stratified analysis across various demographic and clinical factors, including age, sex, race, PIR, BMI, education level, smoking status, physical activity, alcohol intake, diabetes duration, use of diabetes medications, HbA1c, hypertension, CVD, and hyperlipidaemia, did not reveal significant modifications to the linear relationship between hs-TnT levels and DKD (Figure 3). However, within the subgroup of individuals with a diabetes duration of ≥ 10 years, a higher risk of DKD was associated with increasing hs-TnT levels. No significant interactions were observed within the other stratified variables (Figure 3). Comparisons between the complete dataset and the dataset with imputed covariates showed consistent findings (Supplementary Table 1). Similarly, excluding data points where hs-TnT was < LoD yielded comparable outcomes (Supplementary Table 2).

Figure 3 Associations of high-sensitivity troponin T with diabetic kidney disease in various subgroups among patients with diabetes. Each stratification was adjusted for age, sex, race, education, body mass index, poverty income ratio, smoking status, hypertension, cardiovascular disease, hyperlipidemia, physical activity, alcohol intake, estimated glomerular filtration rate, diabetes duration, use of diabetes medications, healthy eating index, and glycated hemoglobin A1c. The stratified variable was not included when stratifying by itself. OR: Odds ratio; CI: Confidence interval; BMI: Body mass index; CVD: Cardiovascular disease; HbA1c: Glycated hemoglobin A1c.

DISCUSSION

In this large, cross-sectional study using nationally representative NHANES data, a linear association was observed between hs-TnT levels below the 99^th percentile and an increased risk of DKD among United States adults with T2DM. This relationship persisted in the overall population and was consistent when analyzed separately in males and females. Additionally, the findings were robust across multiple stratified and sensitivity analyses. Our results build on previous research investigating the association between troponin levels and kidney outcomes in individuals with diabetes. For example, a secondary analysis of the ADVANCE trial demonstrated that elevated troponin levels were associated with an increased risk of new or worsening kidney disease in individuals with diabetes and CVD[8]. Similarly, Bidadkosh et al[9] reported a significant association between elevated hs-TnT levels and renal events in patients with type 2 diabetes and nephropathy. Findings from the Edinburgh type 2 diabetes study further supported this association, linking hs-TnT levels to incident kidney disease[14]. Moreover, Anderson et al[15] identified worse kidney function associated with hs-TnT even among individuals without diabetes. Our study contributes to this growing body of evidence by highlighting a linear association between hs-TnT levels below the 99^th percentile and DKD in a large, nationally representative sample of United States adults with diabetes. These results suggest that even slight elevations in hs-TnT, potentially indicative of subclinical myocardial injury, are associated with renal dysfunction in this high-risk population.

The mechanisms underlying the observed association between hs-TnT and DKD are complex and multifactorial, likely involving direct and indirect pathways that link cardiac injury to renal dysfunction. One potential explanation is the concept of heart-kidney crosstalk, supported by animal studies demonstrating that myocardial damage in mild renal impairment could exacerbate glomerular sclerosis and proteinuria[16]. These findings suggest that cardiac injury might directly contribute to kidney damage through haemodynamic alterations, neurohumoral activation, or other mediators. Alternatively, elevated hs-TnT levels might reflect systemic processes driving the progression of cardiac and renal diseases. Neurohormonal activation, chronic inflammation, and oxidative stress, which are prevalent pathogenic mechanisms in diabetes, are known to contribute to cardiac damage[17,18]. In this context, hs-TnT might serve as a marker of these underlying disturbances rather than acting as a direct mediator of kidney injury. The association between hs-TnT and proteinuria offers additional insight into potential mechanisms. Proteinuria, a well-established marker of diffuse endothelial dysfunction and a strong risk factor for cardiovascular and renal complications, might represent a shared pathophysiological link between elevated hs-TnT and DKD[19]. The co-occurrence of these conditions suggests a common basis, potentially involving generalized microvascular dysfunction. Supporting this hypothesis, cross-sectional studies in individuals with diabetes have identified correlations between cardiac biomarkers and microvascular complications in other vascular beds[20]. Furthermore, findings from the Prevention of Renal and Vascular End-stage Disease cohort demonstrated that elevated hs-TnT predicts the onset of microalbuminuria in patients with hypertensive, reinforcing the relationship between subclinical cardiac injury and early kidney damage[21]. Integrating these lines of evidence, it is plausible that diabetes-related functional microvascular abnormalities result in subclinical ischaemia affecting the heart and kidneys[22]. This ischaemia could manifest as elevated hs-TnT, structural cardiac changes, and progressive renal damage, even in the absence of overt clinical events. Over time, these interrelated processes might act synergistically to drive the development and progression of DKD.

Although the precise mechanisms remain to be fully elucidated, our findings underscore a complex interplay between subclinical cardiac injury and kidney dysfunction in individuals with diabetes. Further research integrating mechanistic studies, longitudinal designs, and multimodal evaluations of cardiovascular and renal health is crucial to unravel these pathophysiological connections. Such efforts might facilitate the development of novel therapeutic strategies addressing cardiac and renal risks in this high-risk population. Our findings highlight the prognostic value of hs-TnT in individuals with diabetes, even at levels below the 99^th percentile typically used for diagnosing acute myocardial infarction. This indicates its potential as a marker of subclinical CVD and its associated renal risks. Incorporating hs-TnT into risk stratification models could help identify patients with diabetes who might benefit from more intensive cardiorenal protective interventions. From a public health standpoint, our results highlight the substantial burden of subclinical cardiovascular injury and DKD among adults with diabetes in the United States. Given the high prevalence of diabetes and its associated morbidity, mortality, and healthcare costs, there is an urgent need for early detection and intervention strategies to address these interconnected complications. Population-level strategies focusing on improving glycaemic control, optimising cardiac health, and preventing or delaying DKD onset are crucial.

The strengths of our study include its large, nationally representative sample, comprehensive assessment of potential confounders, and the robustness of findings across numerous sensitivity analyses. However, several limitations should be acknowledged. The cross-sectional design limits the ability to infer temporality and causality. Additionally, our analysis was based on a single hs-TnT measurement, which might not reflect long-term or dynamic changes in subclinical cardiac injury. Although extensive adjustments were made, the possibility of residual confounding cannot be excluded. Future research should focus on the longitudinal trajectories of hs-TnT and kidney function among individuals with diabetes, as well as the underlying mechanisms linking these variables. Furthermore, studies should assess whether hs-TnT could enhance clinical prediction models to improve DKD risk stratification and inform therapeutic strategies. Ultimately, randomized controlled trials will be necessary to determine whether interventions targeting hs-TnT levels could lead to improved renal outcomes in at-risk diabetic populations.

CONCLUSION

In conclusion, our cross-sectional analysis of adults with diabetes in the United States demonstrates a robust linear association between hs-TnT levels below the 99^th percentile and DKD. These findings suggest that subclinical myocardial injury might contribute to DKD pathogenesis, highlighting the close relationship between cardiac and kidney health in individuals with diabetes. Assessing hs-TnT as a novel cardiorenal risk marker and exploring its potential as a therapeutic target represent promising directions for future research.