Association of Systemic Immune Inflammation Index and System Inflammation Response Index with Cardiovascular Disease among prediabetes and diabetes

doi:10.21203/rs.3.rs-4891715/v1

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Association of Systemic Immune Inflammation Index and System Inflammation Response Index with Cardiovascular Disease among prediabetes and diabetes

https://doi.org/10.21203/rs.3.rs-4891715/v1

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We aimed to explore the association of the systemic immune inflammation (SII) index and system inflammation response index (SIRI) with CVD among prediabetes and diabetes. The cross-sectional study included 4534 participants with prediabetes and diabetes from the National Health and Nutrition Examination Survey (NHANES) 2015–2018. Multivariate logistic regression analysis was used to assess the association of SII and SIRI with CVD. Restricted cubic spline (RCS) model was used to examine the dose-response relationships between SII, SIRI, and CVD. Among 4,534 individuals with prediabetes and diabetes, the prevalence of CVD was 16.6%, with 19.4% in males and 14.0% in females. SII (OR: 1.27, 95%CI: 1.04–1.56) and SIRI (OR: 1.38, 95%CI: 1.09–1.76) were positively associated with CVD among prediabetes and diabetes. Among prediabetes, SIRI was positively associated with CVD (OR: 1.32, 95%CI: 1.03–1.70). Among diabetes, there was a similar finding that SIRI was positively associated with CVD (OR: 1.43, 95%CI: 1.04–1.96). The dose-responses relationship of SIRI with CVD was significantly nonlinear (P for nonlinear < 0.001). SIRI index may be an important biomarker in people with diabetes and prediabetes. Therefore, we recommended long-term monitoring of the SII index and SIRI in these vulnerable individuals.

Biological sciences/Immunology

Health sciences/Biomarkers

Health sciences/Cardiology

Health sciences/Diseases

Health sciences/Endocrinology

Systemic Immune Inflammation Index

System Inflammation Response Index

Cardiovascular Disease

Diabetes

Diabetes is a growing threat to the global health burden. The data from the International Diabetes Federation (IDF) showed that 537 million people were living with diabetes in the world in 2021 [1]. Prediabetes, the concentration levels of blood glucose are usually higher than normal level but lower than diabetic threshold, is rapidly increasing worldwide and is related to the risk of diabetes and diabetic complications [2]. In 2021, 298 million people had prediabetes in the world, and this is expected to increase to 414 million by 2045, with prediabetes prevalence highest in developed countries [3]. It is noted that people with diabetes and prediabetes are associated with a series of complications, among which the risk of cardiovascular disease (CVD) is higher and more prevalent [4]. Compared with general population, diabetic and prediabetic patients had two and four-fold higher risk of CVD [5, 6]. Therefore, revealing risk factors in people with diabetes and prediabetes, and identifying modifiable risk factors are critical for the prevention of CVD.

The pathogenesis of CVD is complex and influenced by many risk factors, but it is undeniable that inflammation plays a central role in these complex etiologies [7, 8]. Indeed, those with chronic inflammation are more susceptible to CVD than the general population [9], which suggesting the importance of developing markers that can detect chronic inflammatory states to help predict CVD risk in people with diabetes and prediabetes. Recently, two new indicators are mainly calculated using three cell counts (including monocytes, neutrophils, and platelet counts), including the systemic inflammatory response index (SIRI) and the systemic immune inflammation index (SII) [10, 11], which comprehensively reflect the balance between inflammation and immune status. Studies have shown that compared with previous inflammatory biomarkers and immune indicators, SII and SIRI are better predictors of CVD [1]. Associations of increased the SII levels and SIRI levels with increased risk of CVD have been found in middle-aged and older adults and in the general population [12–14]. Other studies have found that the correlation between SII and CVD mortality [15, 16], which one finding a U-shaped relationship [16]. However, these studies have overlooked people with diabetes and prediabetes, who are not only at high risk for CVD, but also often accompanied by chronic inflammation. At the same time, the predictive value of the SII index and SIRI for CVD in people with diabetes and prediabetes is unclear.

Therefore, to fill the gaps in current research and to provide some epidemiological reference and value for the management of diabetes and prediabetes, our study used the data from the National Health and Nutrition Examination Survey (NHANES) to explore the association of SII and SIRI index with CVD among prediabetes and diabetes.

2.1 Study population

The NHANES measures the overall health and nutritional status of non-institutionalized individuals in the USA. It is a cross-section study with a complex, multistage, stratified sampling design. Our study used the public data from population recruited in tow cycles (2015–2018) with SII and SIRI index measured in these cycles. Initially, 19225 participants were covered over the tow cycles. We included participants 20 years of age with diabetes or prediabetes. Pregnant women, participants for whom SII and SIRI index were not measured and those for whom CVD were not available were excluded. Finally, there were 4534 participants including in the analysis (Fig. 1). The NHANES was approved by the NCHS Ethics Review Board, and all the participants with informed consent forms.

2.2 Diabetes and Prediabetes

According to the 2013 American Diabetes Association guidelines[17], diabetes was defined by self-reported diagnosis or HbA1c level ≥ 6.5%, or the use of insulin or oral hypoglycemic medication. Moreover, prediabetes was identified by self-reported prediabetes status or having an HbA1c level between 5.7% and 6.4%.

2.3 Exposure: SII and SIRI

The SII index and SIRI were calculated by the results of the complete blood count test, which is a standard laboratory methodology detailed on the NHANES website. Specifically, SII was derived as the product of peripheral platelet count and the neutrophil-to-lymphocyte ratio, while SIRI was calculated by the neutrophil-to-lymphocyte-to-monocyte ratio[18, 19]. Participants were then equally classified into four groups according to the distribution of SII or SIRI values: lower (≤ 311.78 or ≤ 0.72), low middle (> 311.78–441.46 or > 0.72–1.10), middle (> 441.46–625.39 or > 1.10–1.63), and high (> 625.39 or > 1.63).

2.4 Outcome: CVD

The diagnosis of CVD was determined through self-reports of participants from physician diagnoses, obtained on a standardized questionnaire of medical condition interviews. Participants were asked whether a doctor or health expert had ever informed them of having conditions such as congestive heart failure, myocardial infarction (MI), coronary heart disease (CHD), stroke, or angina pectoris. Those who answered affirmatively to any of these types of CVD were considered to have CVD.

2.5 Covariates

Sociodemographic information, such as gender (male or female), age (≤ 60 years or > 60 years), race (Mexican American, other Hispanic, non-Hispanic white, non-Hispanic black or other), marital status (married or other), education level (≤ high school diploma or > high school diploma), family poverty income ratio (PIR) (≤ 1.30, 1.31–3.50, or > 3.50), drinking status (yes or no), and smoking status (yes or no) were collected using a standard questionnaire in NHANES. Body mass index (BMI) was classified into overweight (≥ 25 kg/m²) and normal (< 25 kg/m²)[20]. Moderate or vigorous physical activity based on self-reported activity intensity dividing into two groups (yes or no).

2.6 Statistical analysis

We incorporated the NHANES sample weights strata, and clustering variables into all analysis using standard methods. Categorical variables were presented using frequencies (percentages). Continuous variables were described using means (standard deviations). SII and SIRI were expressed as continuous or categorical variables. The association of SII, SIRI, with CVD in all populations among diabetes and prediabetes by using multivariate logistic regression analysis, respectively. In addition, we explored associations of SII, SIRI, with CVD, respectively, among patients with diabetes or prediabetes. Model 1 was non-adjusted; Model 2 adjusted for gender (male or female) and age (≤ 60 or > 60); Model 3 was further adjusted for race (Mexican American; Other Hispanic; Non-Hispanic White; Non-Hispanic Black; Other), educational level, (≤ High school diploma; >High school diploma) marital status (Married; Other), PIR (≤ 1.30; 1.31–3.50; >3.5), smoking status (Never; Former; Current), drinking status (Yes; No), BMI (< 25 kg/m²; ≥225 kg/m²), moderate or vigorous physical activity (Yes; No). To quantify dose-response relationships, we used restricted cubic spline (RCS) models to examine the association of SII, SIRI, with CVD. To comprehend whether the potential association between SII, SIRI, and CVD could be modified by covariates, potential interactions were assessed. All data were conducted with IBM SPSS Statistics 21.0 (IBM, ASiaAnalytics Shanghai) and R software (R 4.1.2). If the P value < 0.05 on two sides, the statistics were considered significant.

Table 1 showed that the characteristics of study participants. We included 4,534 individuals with prediabetes and diabetes, the prevalence of CVD was 16.6%, with 19.4% in males and 14.0% in females. Among participants aged < 60 years, the prevalence of CVD was 8.1%, but it is 26.1% in participants aged ≥ 60 years. In terms of race, educational level, marital status, PIR, smoking statis, drinking status, BMI and MVPA, the participants with and without CVD differed. In addition, both SII and SIRI have higher levels in individuals with CVD than in individuals without CVD.

Table 1

Characteristics of the study participants with and without CVD in prediabetes and diabetes
Characteristic	CVD
Characteristic	No	Yes
N (%)	3736 (83.4)	798 (16.6)
Age, years, N (%)
< 60	1977 (91.9%)	155 (8.1%)
≥ 60	1759 (73.9%)	643 (26.1%)
Gender
Male	1817 (80.6%)	457 (19.4%)
Female	1919 (86.0%)	341 (14.0%)
Race, N (%)
Mexican American	690 (93.2%)	78 (6.8%)
Other Hispanic	441 (85.1%)	85 (14.9)
Non-Hispanic White	945 (80.9%)	355 (19.1%)
Non-Hispanic Black	995 (84.0%)	196 (16.0%)
Other	665 (84.7%)	84 (15.3%)
Educational level, N (%)
≤High school diploma	1815 (83.1%)	422 (16.9%)
>High school diploma	1913 (83.6%)	374 (16.4%)
Marital status, N (%)
Married	2081 (84.1%)	386 (15.9%)
Other	1651 (82.4%)	412 (17.6%)
PIR, N (%)
≤ 1.30	1003 (81.8%)	269 (18.2%)
1.31–3.50	1359 (81.4%)	303 (18.6%)
> 3.50	912 (87.7%)	141 (12.3%)
Smoking status, N (%)
Yes	1556 (79.1%)	478 (20.9%)
No	2176 (87.3%)	319 (12.7%)
Drinking status, N (%)
Yes	1805 (84.5%)	373 (15.5%)
No	1454 (82.0%)	337 (18.0%)
BMI, kg/m², N (%)
< 25	634 (85.6%)	122 (14.4%)
≥ 25	3058 (83.3%)	651 (16.7%)
Moderate or vigorous physical activity, N (%)
Yes	2211 (82.2%)	499 (17.8%)
No	1517 (84.5%)	298 (15.5%)
SII (1,000 cells/µl), mean (SD)	512.9 (7.8)	595.7 (28.1)
SIRI (1,000 cells/µl), mean (SD)	1.3 (0.02)	1.8 (0.1)
Abbreviation: CVD: Cardiovascular disease; PIR: family poverty income ratio; BMI: body mass index; SD, Standard deviation; SII: systemic immune-inflammation index; SIRI: systemic inflammation response index Percent values were weighted to account for the complex survey design.

In Table 2, SII (OR: 1.27, 95%CI: 1.04–1.56) and SIRI (OR: 1.38, 95%CI: 1.09–1.76) as continuous variables were positively associated with CVD. SII as a categorical variable showed a trend for association with CVD (P for trend: 0.002) after adjusting for all covariates. As a categorical variable, the highest level of SIRI was positively associated with CVD (OR: 1.97, 95%CI: 1.06–3.67, P for trend: 0.007). The dose-responses relationship of SIRI with CVD was significantly nonlinear (P for nonlinear < 0.001) in Fig. 2.

Table 2

Association of SII and SIRI with CVD among participants with prediabetes and diabetes
	Model 1	Model 2	Model 3
	OR (95%CI)	OR (95%CI)	OR (95%CI)
SII
Continuous per 1 SD	1.31 (1.13, 1.53)	1.32 (1.12, 1.55)	1.27 (1.04, 1.56)
Quartile 1	1.00	1.00	1.00
Quartile 2	1.50 (0.95, 2.36)	1.60 (0.99, 2.59)	1.56 (0.88, 2.77)
Quartile 3	1.68 (1.10, 2.58)	1.67 (1.07, 2.60)	1.52 (0.87, 2.65)
Quartile 4	2.11 (1.36, 3.29)	2.22 (1.39, 3.55)	1.78 (0.96, 3.30)
P for trend	0.005	0.004	0.002
SIRI
Continuous per 1 SD	1.68 (1.32, 2.15)	1.50 (1.20, 1.87)	1.38 (1.09, 1.76)
Quartile 1	1.00	1.00	1.00
Quartile 2	0.83 (0.52, 1.32)	0.79 (0.47, 1.31)	0.60 (0.36, 1.01)
Quartile 3	1.96 (1.17, 3.28)	1.85 (1.09, 3.13)	1.61 (0.85, 3.04))
Quartile 4	3.51 (2.04, 6.03)	2.60 (1.53, 4.40)	1.97 (1.06, 3.67)
P for trend	< 0.001	< 0.001	0.007
Abbreviation: OR: Odds ratio; CI: Confidence interval; SII: systemic immune-inflammation index; SIRI: systemic inflammation response index; CVD: Cardiovascular disease
Model 1: Adjusted for none.
Model 2: Adjusted for gender (male; female), age (≤ 60 years; >60 years)
Model 3: Adjusted for gender (male; female), age (≤ 60 years; >60 years), race (Mexican American; Other Hispanic; Non-Hispanic White; Non-Hispanic Black; Other), educational level, (≤ High school diploma; >High school diploma) marital status (Married; Other), PIR (≤ 1.30; 1.31–3.50; >3.5), smoking status (Never; Former; Current), drinking status (Yes; No), BMI (< 25 kg/m²; ≥25 kg/m²), moderate or vigorous physical activity (Yes; No).

Subsequently, a subgroup analysis was performed to evaluate the relationship between the SII and SIRI and CVD among prediabetes or diabetes in Table 3. Among prediabetes, SIRI was positively associated with CVD when SIRI was a continuous variable (OR: 1.32, 95%CI: 1.03–1.70), and SIRI as a categorical variable still showed a trend for association with CVD (P for trend: 0.041). Among diabetes, there was a similar finding that SIRI was positively associated with CVD when it was a continuous variable (OR: 1.43, 95%CI: 1.04–1.96), and SIRI as a categorical variable still showed a trend for association with CVD (P for trend: 0.041).

Table 3

Association of SII and SIRI with CVD among participants with prediabetes and diabetes
	Model 1	Model 2	Model 3
	OR (95%CI)	OR (95%CI)	OR (95%CI)
Prediabetes
SII
Continuous per 1 SD	1.28 (1.05, 1.57)	1.31 (1.06, 1.62)	1.23 (0.997, 1.53)
Quartile 1	1.00	1.00	1.00
Quartile 2	1.26 (0.74, 2.16)	1.39 (0.77, 2.51)	1.64 (0.83, 3.25)
Quartile 3	1.43 (0.78, 2.62)	1.43 (0.72, 2.84)	1.55 (0.70, 3.43)
Quartile 4	1.67 (0.99, 2.84)	1.90 (1.09, 3.33)	1.59 (0.74, 3.39)
P for trend	0.060	0.029	0.345
SIRI
Continuous per 1 SD	1.59 (1.21, 2.08)	1.42 (1.11, 1.82)	1.32 (1.03, 1.70)
Quartile 1	1.00	1.00	1.00
Quartile 2	0.76 (0.39, 1.49)	0.69 (0.33, 1.47)	0.54 (0.23, 1.27)
Quartile 3	1.73 (0.91, 3.28)	1.65 (0.83, 3.31)	1.41 (0.52, 3.81)
Quartile 4	3.18 (1.71, 5.95)	2.42 (1.33, 4.41)	1.85 (0.76, 4.50)
P for trend	< 0.001	0.002	0.041
Diabetes
SII
Continuous per 1 SD	1.24 (1.003, 1.53)	1.25 (0.998, 1.55)	1.28 (0.97, 1.68)
Quartile 1	1.00	1.00	1.00
Quartile 2	1.63 (0.68, 3.86)	1.66 (0.74, 3.74)	1.41 (0.60, 3.32)
Quartile 3	1.63 (0.67, 3.96)	1.60 (0.67, 3.85)	1.16 (0.41, 3.27)
Quartile 4	2.10 (0.94, 4.67)	2.09 (0.94, 468)	1.74 (0.78, 3.85)
P for trend	0.101	0.118	0.184
SIRI
Continuous per 1 SD	1.62 (1.21, 2.17)	1.47 (1.13, 1.91)	1.43 (1.04, 1.96)
Quartile 1	1.00	1.00	1.00
Quartile 2	0.87 (0.48, 1.56)	0.86 (0.45, 1.67)	0.69 (0.30, 1.58)
Quartile 3	1.85 (0.83, 4.14)	1.77 (0.78, 4.01)	1.53 (0.62, 3.75)
Quartile 4	3.01 (1.44, 6.33)	2.35 (1.11, 4.99)	2.06 (0.82, 5.16)
P for trend	0.001	0.009	0.041
Abbreviation: OR: Odds ratio; CI: Confidence interval; SII: systemic immune-inflammation index; SIRI: systemic inflammation response index; CVD: Cardiovascular disease
Model 1: Adjusted for none.
Model 2: Adjusted for gender (male; female), age (≤ 60 years; >60 years)
Model 3: Adjusted for gender (male; female), age (≤ 60 years; >60 years), race (Mexican American; Other Hispanic; Non-Hispanic White; Non-Hispanic Black; Other), educational level, (≤ High school diploma; >High school diploma) marital status (Married; Other), PIR (≤ 1.30; 1.31–3.50; >3.5), smoking status (Never; Former; Current), drinking status (Yes; No), BMI (< 25kg/m²; ≥25 kg/m²), moderate or vigorous physical activity (Yes; No).

The stratified analyses presented in Table S1-2 provide valuable insights into the intricate associations of systemic inflammation indices (SII and SIRI) with CVD across diverse populations. Notably, the findings suggest that age and systemic inflammation indices (SII [P-interaction = 0.001] and SIRI [P-interaction < 0.001]) exhibit significant interactions in their effects on CVD among individuals with prediabetes and diabetes. Specifically, SIRI was found to be associated with an increased CVD risk only in aged above 60 years (OR: 2.24, 95% CI: 1.16–4.35). Furthermore, the data indicate that SII interacts with race and smoking status in influencing CVD risk (P-interaction < 0.05), while SIRI demonstrates interactions with education level, PIR, smoking status, drinking status, and BMI (P-interaction < 0.05).

In a nationally representative sample of population from the USA, we explored the association of two new inflammatory indices (SII and SIRI) with CVD in prediabetes and diabetes. We found that there was a positive association both SII and SIRI with CVD among prediabetes and diabetes. In addition, a nonlinear association between SIRI and CVD in diabetic and prediabetic populations was observed. Furthermore, in the prediabetes, there was a positive association between SIRI and CVD. Similarly, SIRI was positively associated with CVD in diabetes.

Our study found that two inflammatory indices were associated with CVD in prediabetes and diabetes. In fact, some studies have confirmed that SII index and SIRI were effective biological predictors of CVD [12, 21, 22], elevated SII was also associated with an increased CVD risk from a recent systematic review and meta-analysis [23]. For example, Xu et all focused on middle-aged and elderly in China and found that SII played an important effect on the development of stroke and CHD [12]. Another decade-long cohort study in general people also confirmed that stroke risk increased with the increase of SII and SIRI [22]. The above studies show that the two inflammatory indices assess the impact of inflammation on disease. However, these studies ignored people with diabetes and prediabetes who are at high risk of CVD. Our study highlights the importance of monitoring SII index and SIRI to those diabetes and prediabetes, to understand the interaction between inflammation and disease outcomes and the possible impact on CVD.

Our study further explored the association between doses of both inflammatory indices and CVD, a nonlinear relationship between SIRI and CVD was observed. In the previous study, a nonlinear association of the SIRI with CVD and all-cause mortality was demonstrated in hypertensive populations [24]. Our research shows that in the nonlinear relationship between SIRI and CVD, the risk of developing CVD decreases when the turning points of SIRI about exceeding 2. Consistently, several studies have demonstrated a non-linear association between white blood cell count and CVD outcomes [25–27]. On the contrary, a positive relationship between SIRI and severe CVD outcomes was found in the cohort study by Han et all [28]. Although there is some controversy in the current study on the specific relationship, our study and previous studies agree that when the lower of cell index may weak the poor physical healthy. Similarly, for per 1 SD increase in SII, the risk of CVD increased by 27%, and a linear trend was observed, but a non-linear association was not found in our study. However, a U shape curve was found between SII and CVD, cancer and all-cause mortality among hypertensive or CVD individuals [16, 29]. Our study did not find a non-linear association between SII index and CVD in people with diabetes and prediabetes. It is possible that SII index and SIRI two inflammatory indexes have different effects on CVD.

For each one SD increase in the SIRI, the risk of CVD increased in both diabetic and prediabetic individuals, while SII index not. In fact, several studies also found that inconsistencies in the effects of the SII index and the SIRI index on disease [22, 30]. For example, a study shown that higher SIRI, but not SII index was corelated with myocardial infarction among general population, elevated two indicators significantly increased the risk of stroke conversely [22]. Similarly, SIRI was corelated with coronary artery disease, while the SII index not [30]. Our research also confirmed the predictive value of SIRI for disease, which may be higher than the SII index. Different definitions of the SII index and the SIRI may contribute significantly to the different effects on CVD. Neutrophil and lymphocyte counts are included in both two inflammation index definitions, but the SIRI index considers monocyte counts, while the SII index focuses on platelet counts. Atherosclerosis is a kind of chronic inflammation, and Inflammation is involved in the development of CVD. During the occurrence of inflammation, the immune system cells of the body will sense and produce systemic changes, thus activating monocytes in blood circulation and participating in the formation of foam cells and the secretion of cytokines and chemokines. Therefore, the increase of monocyte count plays an important role in the pathogenesis of cardiovascular diseases [31–33]. Relevant studies have also shown that monocyte count was positively related to the risk of CVD [34]. Moreover, for people with diabetes, studies have shown that monocytes are more likely to accumulate in the diabetic environment (such as insulin deficiency or resistance, abnormal glucose tolerance and repeated fluctuations in blood sugar and possibly long-term hyperglycemia) and reduced efferocytosis, thereby accelerating atherosclerosis [35]. In contrast, studies discovered that platelet count was not directly related to the development of CVD, and that activated platelets may contribute to the development of CVD [36, 37]. Therefore, it is necessary to monitor monocyte count and prevent platelet activation in diabetic and prediabetic populations to delay the development of CVD.

There are some strengths and limitations in our study. We focused on a relatively new population, including diabetes and prediabetes. In addition, we explored two inflammatory indices, SII index and SIRI, and compared the relationship between indices and CVD in detail to explore the dose-response relationship between them. However, it is a cross-sectional study in an observational study, and causation cannot be well explained. We also preliminarily explored the correlation between the inflammation indices and CVD, which is convenient for further development of subsequent cohort studies. Finally, although we adjusted for relevant confounding factors during the study, there may still be some residual confounding.

In this large study of people with diabetes and prediabetes in the United States, we found a positive relationship between two inflammatory indices, including SII index and SIRI, and CVD. A nonlinear dose-response relationship was observed between SIRI and CVD among prediabetes and diabetes. In participants with prediabetes or diabetes, the SIRI index is strongly associated with CVD. The SIRI index may be an important biomarker in people with diabetes and prediabetes. Therefore, long-term monitoring of the SII index and SIRI of these susceptible people, while further controlling the inflammatory state, and timely proposing appropriate interventions to promote health.

BMI, body mass index; CVD, cardiovascular disease; CHD, coronary heart disease; MI, myocardial infarction; NHANES, National Health and Nutrition Examination Survey; IDF, International Diabetes Federation; RCS, restricted cubic spline; SII, systemic immune inflammation index; SIRI, system inflammation response index.

Author Contributions:

Jiayu Sun: Conceptualization, Software, Formal analysis, Writing - review & editing. Min Liu, Andong Zhang and Yutong Dong: Review & editing. Mengmeng Shi: Conceptualization, Review & editing, Supervision, Resources.

Sources of Funding: None

Funding/Support: None

Declaration of competing interest:

The authors declare that they have no known competing financial interests or personal relationships.

Data availability

The data utilized and examined in this study are available upon reasonable request from the corresponding author.

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No competing interests reported.

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Association of Systemic Immune Inflammation Index and System Inflammation Response Index with Cardiovascular Disease among prediabetes and diabetes

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Abstract

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1. Introduction

2. Methods

2.1 Study population

2.2 Diabetes and Prediabetes

2.3 Exposure: SII and SIRI

2.4 Outcome: CVD

2.5 Covariates

2.6 Statistical analysis

3. Results

4. Discussion

5. Conclusion

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1