The Impact of Abnormal Distribution of Abdominal Adiposity and Skeletal Muscle on the Prognosis of Ischemic Stroke.

doi:10.21203/rs.3.rs-3802955/v1

Background and Purpose

The study aimed at investigating the role of novel indicators related to obesity in predicting long-term functional outcome and risk of stroke recurrence in patients with first-ever acute ischemic stroke (AIS).

Methods

The area and density of visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and skeletal muscle (SM) at the third lumbar level, as well as VAT area (VATA) to SM area (SMA) ratio (VSR) and ratio of SAT area to SMA (SSR) were assessed using whole-abdominal CT upon admission. The primary endpoint was the presence of recurrent stroke. Second outcomes were all causes mortality and death specifically due to cardiovascular and cerebrovascular diseases (CCVD). Cox's proportional hazards regression model was used to examine the association between the new indicators of obesity and clinical outcomes.

Results

A total of 1007 patients were enrolled with an average follow-up time of 49.8 months. Patients in the high VSR group had a higher recurrence rate of stroke (OR, 0.67 [95% CI, 0.48–0.93]; p = 0.018). In adjusted analysis, VSR was significantly associated with the increased risk of all-cause mortality (HR, 2.16 [95% CI, 1.51–3.80]; p < 0.001) and CCVD (HR, 2.44 [95% CI, 1.61–3.69]; p < 0.001). Among AIS with severe neurologic deficit (the National Institutes of Health Stroke Scale score 16–42), the mortality in the obese group tended to be lower, although without statistically significance.

Conclusions

Higher VSR levels were associated with a higher risk of mortality and stroke recurrence in patients with first-ever AIS.

Health sciences/Diseases/Cardiovascular diseases

Health sciences/Health care/Therapeutics/Nutrition therapy

adipose tissue

obesity

sarcopenic

body mass index

stroke

recurrence

The prevalence of overweight, defined as a body mass index (BMI) ≥ 25 Kg/m², is projected to affect over 4 billion individuals globally by the year 2035. (1) Previous studies long proven that obesity is closely associated with an increased risk of developing multiple diseases, such as acute ischemic stroke (AIS), cardiovascular disease. However, the impact of obesity on stroke outcomes remains controversial. (2, 3, 4, 5) Some studies indicated that obesity, as defined by BMI, is correlated with the decreased mortality rates, the incidence of recurrent strokes, and readmission rates following the index stroke, a phenomenon known as “obesity paradox”.(6, 7, 8)Additionally, the risk of all-cause death was significantly lower in AIS patients with abdominal obesity or overweight compared to patients with normal BMI or waist circumference (WC).(9) The emergency of the obesity paradox may due to the limitations of BMI which can not provide information on body composition distribution and distinguish abdominal obesity from other types of obesity. Therefore, it is necessary to verify the existence of the obesity paradox in patients with AIS using more delicate indicators.

CT imaging is a precise method for quantifying the regional distribution of abdominal fat and skeletal muscle tissue parameters, and also considered the gold standard for assessing body composition.(10) The current approach utilized whole-abdominal CT imaging to accurately assess the distribution of different abdominal tissues, such as visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and skeletal muscle (SM). Previous studies have demonstrated the closely association between VAT, SAT and SM and with cerebrovascular diseases. The accumulation of VAT and the ratio of VAT to SAT were independently linked to the presence of cerebral small vessel disease such as leukoencephalopathy and asymptomatic lacunar infarction, regardless of age, cardiovascular risk factors.(11, 12) A lower VAT rate was reported to related with better outcomes after intravenous thrombolysis after 90 days.(11) Meanwhile, it has been demonstrated that the cross-sectional area of a single slice of abdominal fat and skeletal muscle at the third lumbar spine (L3) level is highly correlated with total body muscle and adipose tissue volume.(10, 13, 14) Furthermore, the skeletal muscle mass deficit was associated with poor functional prognosis in AIS patients. (15)Currently, there have been few studies that investigate VAT and SM in relation to prognosis after AIS.

Therefore, we aim to investigate the association between various measures of body composition (e.g.VAT, SAT, SM) and long-term outcomes in patients with AIS.

Study population

We retrospectively enrolled patients from Jinling Hospital, the first affiliated hospital of University of Science and Technology of China Technology of China and the affiliated hospital of Xuzhou Medical University between April 2015 and August 2022. The inclusion criteria were as follows: (1) age ≥ 18 years; (2) diagnosed with first-ever AIS; (2) time from stroke onset to admission within 14 days; (3) total abdominal CT was performed within 72 hours after admission. Patients were excluded if they (1) received intravenous thrombolysis or endovascular therapy; (2) had underlying diseases out of control, such as those diagnosed with aneurysms and arteriovenous malformations, tumors, serious infections and liver diseases; (3) had incomplete key baseline data (such as poor imaging quality or missing critical time points for treatment). All clinical investigations were conducted in accordance with the principles outlined in the Declaration of Helsinki. The study has received approval from the Ethics Committee of Xuzhou Medical University Affiliated Hospital (XYFY2023-KL425).

Imaging parameters and radiological assessment

The abdomen CT scans were obtained using three multi-slice spiral CT scanners (Siemens, Munich, Germany; Philips Brilliance, Netherlands; General Electric LightSpeed VCT, GE Healthcare, Milwaukee, WI, USA). All subjects were placed in a supine position and told to hold their breath to reduce respiratory and motion artifacts in abdominal tissue during the scan (as assessed by assessing tissue area [cm²] and tissue density [Hounsfield unit, HU] on axial CT images at the umbilical cord level). Adipose tissue area and density measurements were made using previously standardized and validated methods. (16) In a nutshell, the method involves setting the display contrast window to -195HU~ -45HU at the L3 plane, and then manually drawing the area of interest that surrounds the fat layer under the skin of the abdomen. VAT area (VATA) is defined as the area with attenuation values between − 150 HU and − 50 HU, excluding intestinal contents. The subcutaneous adipose tissue area (SATA) is defined as the area whose attenuation value is -190HU~-30HU. SM area (SMA) was identified on CT images according to the HU threshold of -29 HU to + 150 HU. SM at L3 level included the psoas major, the erector spinus, the quadrate psoas, the left and right external oblique muscles of the abdomen and the internal oblique muscles of the abdomen, and the transverse muscles of the abdomen. (Figure S1 and Table S1) (17)Then manual contour refinement was performed using a previously standardized and validated method.(16, 18) After demarcating the area, SliceOmatic V5.0 software (Rev-8, Tomovision, Montreal, Quebec, Canada) will automatically calculate the contrast window width of the corresponding area, that is, the tissue density. Both the image analyst and the radiologist, who were blind to clinical information, examined all selected CT sections and segmentation areas. Twenty patients were randomly selected from the entire image dataset. Two neurologists utilized SliceOmatic V5.0 software to accurately identify and label VAT, SAT, and SM. The inter-rater reliability of neurologists measuring indicators mentioned above were evaluated. Additionally, one of the doctors re-evaluated and re-labeled the same randomly chosen data three months later, thereby assessing the intra-rater consistency of their measurements. L3-Skeletal muscle Area Index (SMI) is calculated by dividing L3 skeletal muscle area by the square of height (cm²/m²). Sarcopenic/obesity (SO) was defined according to previous studies (male: SMI < 44.77cm²/m² and VATA > 100cm² or BMI > 25 Kg/m²; female: SMI < 32.50cm²/m² and VATA > 100cm² or BMI > 25 Kg/m²) [34520115]. Overall, the cohort was divided into four groups based on SMI and VATA or BMI: nonmyopenic/nonobesity (NN), nonsarcopenic/obesity (NO), sarcopenic/nonobesity (SN), and sarcopenic/obesity (SO).

Data collection and follow-up

Demographics, medical history, stroke etiology, the National Institutes of Health Stroke Scale (NIHSS) score at admission, BMI (weight in kilograms divided by height in meters squared, Kg/m²), waist circumference, clinical features and laboratory data were collected within 24 h after admission.

According to NIHSS at admission, the patients were classified into two categories (19, 20): mild/moderate (0–15) and severe stroke (16–42). Patients were followed by phone or outpatient visits at 1, 3, 6 months and every 6 months thereafter until the endpoint or the most recent follow-up until August 2022. If there were any changes in the patient's condition following discharge, immediate medical attention should be sought. Recurrent ischemic stroke is defined as the reappearance of new neurological deficits based on improvement or disappearance of initial symptoms and signs, along with confirmation of new infarcts through imaging (21) Cardio-cerebrovascular death was defined according to the ICD code (Table S2) for the patient’s causes of death. The primary endpoint was the presence of recurrent stroke. Second outcome were all causes mortality and death specifically due to cardiovascular and cerebrovascular diseases (CCVD).

Statistical analysis

Subjects were grouped according to survival outcomes. Normality distributions of parameters were examined using hypothesis test. Independent sample T test or Mann-Whitney U test was used for continuous variables, and χ2 or Fisher exact test was used for categorical variables. Variables with p < 0.05 were included as covariates in the cox survival regression analysis to examine the association between radiographic measurements and outcomes. The mortality rates of NN, NO, SN and SO groups were compared among patients with mild/moderate (NIHSS 0–15) and severe (NIHSS 16–42) stroke. The intraclass correlation coefficient (ICC) was employed to assess the inter - observer consistency of the area and density of VAT, SAT and SM.

Statistical testing was conducted at the 2-tailed α-level of 0.05. All statistical analyses were performed with Statistical Package for Social Sciences version 26.0 (IBM, Chicago, Illinois) Exceptionally, the effects of VSR and SSR on all-cause death and cardiovascular and cerebrovascular mortality were analyzed by “survival” and “survminer” packages in R software version 4.2.1 (R Development Core Team, Vienna, Austria).

The study included a total of 1063 patients, and after excluding 56 patients, 1007 patients was finally included in the statistical analysis. The flow chart is illustrated in Fig. 1.

Patient characteristics

A total of 1007 patients with AIS (mean age 68, 649 [64.4%] male) were retrospectively enrolled. There were 182 all-cause mortality during follow-up. Of the patients, 131 had cardiovascular and cerebrovascular origin death (CCVD), and 144 developed recurrent stroke.The baseline characteristics and related indicators of quantified obesity were compared between different groups according to the occurrence of all-cause death or CCVD respectively. Compared to the survival group, the patients in all-cause mortality group were older (p < 0.001), had a higher proportion of smoking history (p = 0.039), coronary heart disease (p < 0.001), and atrial fibrillation (p < 0.001). Additionally, the proportion of patients using anticoagulants (p < 0.001) and Beta-blocker-blockers (p < 0.001) was also higher in the all-cause mortality group. Compared to the CCVD group, patients in the corresponding survival group exhibited a younger age profile, lower prevalence of coronary heart disease and atrial fibrillation, as well as reduced usage of anticoagulants and beta-blockers. VATA, SATA, SMA, VATA to SMA ratio (VSR) and ratio of SATA to SMA (SSR) in survival group were significantly higher than those in all-cause death group, while VATD and SATD showed no significant difference between the two groups. VATA and VSR in CCVD group were significantly higher than those in the survival group. There was no significant difference between the survival group and the death group including the all-cause death group and the CCVD group in the traditional assessment of obesity, namely BMI and waist circumference.

The measured inter-observer consistencies demonstrate high levels of agreement, ranging from good to excellent, as presented in the supplementary table 4.

Association of VSR/SSR/BMI with mortality and recurrence of stroke

VSR was significantly associated with increased risk of all-cause mortality [(hazard ratios, HR), 2.159 (95% CI, 1.51–3.80); p < 0.001)] as well as CCVD (HR, 2.437 [95% CI 1.61–3.69]; p < 0.001; Table II). The results of Fig. 2 further showed that VSR was an independent factor for all-cause death and CCVD in AIS patients. The 940 survivors were followed up for a mean period of 49.8 months, and 144 (15.3%) had a recurrent ischemic stroke. High level of VSR was found to have a significant association with stroke recurrence, whereas no significant association was observed for SSR (Fig. 3). Also, the association between BMI and all-cause mortality, CCVD, and stroke recurrence was not observed. The impact of obesity-related binary imaging measures on overall mortality, cardiovascular and cerebrovascular disease (CCVD) and recurrence of stroke were shown in Supplement Table 5.

Mortality on obese patients defined by BMI or VATA level in patients with mild/moderate and severe deficit

In the mild/moderate (NIHSS 0–15) AIS group, the mortality rate of obese patients defined by VATA level was significantly higher than non-obese patients, while the difference of mortality according to BMI group was not statistically significant. Nonetheless, in the severe AIS (NIHSS 16–42) group, obese individuals classified based on either VATA or BMI exhibited a lower mortality rate compared to non-obese individuals; but did not reach statistical significance. (the cohort was divided into four groups based on SMI [calculated by dividing L3 skeletal muscle area by the square of height] and VATA or BMI: nonmyopenic/nonobesity (NN), nonsarcopenic/obesity (NO), sarcopenic/nonobesity (SN), and sarcopenic/obesity (SO)

The present study revealed a significant association between VSR and poor prognosis of AIS. In the mild AIS groups, obese patients categorized by VATA exhibited significantly higher mortality rates, while no significant difference in mortality was observed between obese and non-obese patients classified by BMI.

The association between obesity and ischemic stroke has been established in numerous studies. Obesity accounted for 35.5% of all strokes patients,(22) probably exacerbating ischemic brain injury and leading to further neurological function deterioration.(23) Whereas, the findings of a recent meta-analysis, with an average follow-up duration of 13.7 years, indicate that the risk of all-cause mortality is at its lowest when BMI falls within the range of 20 Kg/m² to 25 Kg/m².(24) The cerebrovascular domain also has a similar phenomenon, that is obesity distinctly influences functional outcomes after AIS. A linear association exists between higher BMI and increased survival, known as the obesity paradox. However, BMI demonstrates a U-shaped/J-shaped relationship with disability after stroke. These distinct patterns suggest different pathophysiological mechanisms, indicating that metabolic reserve plays a more crucial role in the nutritional challenge of survival than in achieving favorable functional outcomes.(5, 25, 26, 27) Nevertheless, studies related to the obesity paradox for AIS patients have reached inconsistent conclusions. More comprehensive approaches for assessing obesity and the association of stroke outcomes are deserving further research.(28) The findings of several prior studies have exhibited incongruent outcomes. One such explanation is the possibility of bias resulting from misclassification when using BMI as a measure of obesity as ignored the distribution of body composition including adipose tissue and muscle. The present study utilized VAT, SAT, SM, and VSR which reflected the distribution of body composition to investigate their association with AIS prognosis and compared with BMI on the predictive role of mortality after AIS. In this study, there was no significant correlation observed between BMI and all-cause mortality, CCVD, as well as stroke recurrence. Additionally, no significant difference in mortality rates was found between the obese and non-obese groups defined by BMI in mild/moderate stroke subgroup. However, it is worth noting that the non-obese patients exhibited increased mortality in severe stroke subgroup. These findings align with previous research outcomes. (5) Furthermore, our results demonstrated a significant association between VATA and VSR with all-cause mortality, CCVD, and stroke recurrence, which is consistent with prior studies.(29) Obesity-related imaging indicators, such as VATA, provide valuable insights into the distribution of body components, particularly adipose tissue and muscular tissue, which has been recognized linked to AIS prognosis. However, BMI fails to capture the difference in body composition distribution and quantity, thus presenting certain limitations.

Besides, the advancement of imaging technology has sparked a revolution in investigating the correlation between body adiposity and incidence and prognosis of disease. By taking into account the distinct characteristics of adipose tissue and muscle, it becomes feasible to accurately evaluate body composition and phenotypes related to adipose tissue and muscle distribution. (30, 31, 32) Therefore, it is imperative to embrace novel obesity-related biomarkers such as VAT, measured through adipose tissue imaging, avoiding the inherent deficiencies of BMI. A recent study utilizing adipose tissue imaging demonstrated that VAT volume was associated with several cerebrovascular risk factors, while SAT did not show such association. (33) Furthermore, VAT served as a crucial predictor of brain-healthy.(34, 35, 36) The AIS patients received intravenous thrombolysis and had the lowest VAT rates were more likely to experience a favorable or excellent prognosis.(29) On the other hand, Jennifer et al. revealed that individuals with low SM have a higher prevalence of type 2 diabetes mellitus and coronary heart disease. (37) The protective effect of SM against cardiometabolic diseases stems from its role as the primary tissue for insulin-mediated postprandial glucose uptake. Sarcopenia is a well-established risk factor for poor functional outcomes in patients with vascular disease or metabolic syndrome. (38) Additionally, patients with sarcopenia are more likely to experience poor functional outcomes at 90 days after AIS.(39) A cross-sectional study of rehabilitation patients suggests that improving sarcopenia may be associated with better global functional status.(40) Previous studies have demonstrated a correlation between VSR and an increased risk of cardiometabolic disease.(41) While previous research has separately focused on the prognostic of increased VAT and reduction of SM in AIS patients, few studies have simultaneously investigated the impact of VAT and SM on functional outcomes. Our study revealed that VSR was significantly correlated with all-cause mortality, CCVD and stroke recurrence among patients with AIS.

The aforementioned clinical phenomena can be ascribed to the pathophysiology of VAT and SM. Firstly, VAT has been demonstrated to exert multiple detrimental effects. Specifically, excessive VAT can promote macrophage infiltration and trigger chronic mild systemic inflammation by releasing inflammatory cytokines, such as monocyte chemoattractant protein-1, interleukin-6, and tumor necrosis factor-α, (42) as well as exacerbating oxidative stress. (43) Moreover, VAT has been linked to the occurrence of white matter lesions, (44) alterations in brain volume and cortical thickness, leading to the impairments in cognitive domains including verbal memory and attentional processes.(45, 46) Simultaneously, animal studies have demonstrated that VAT can also impact brain damage following acute ischemic injury by augmenting inflammatory mediators and increasing blood-brain barrier permeability. (47, 48) Besides, a study has indicated the activation of β-adrenergic receptors in the sympathetic nervous system by proinflammatory cytokines in VAT exacerbates inflammatory responses and subsequently intensifies ischemic brain injury. (49, 50) Thirdly, SM is an endocrine organ, can produce and secrete irisin, muscle nexin and other muscle factors. Irisin and musculin are important muscle factors that have been shown to promote adipose tissue browning, promote thermogenesis, and increase nonesterified fatty acid uptake and oxidation in liver and adipose tissue. (51, 52) Thus, impaired secretion of muscle factors due to SM loss may play a role in the development of insulin resistance and cardiometabolic disease.(53) In addition, the accumulation of VAT has a significant detrimental impact on musculoskeletal integrity. It has been observed that VAT is inversely associated with inferior trabecular and cortical bone mineral density as well as sarcopenia, even after adjusting for BMI and age.(54) Among patients with severe AIS, obese defined by BMI or VATA were found to have a relatively reduced mortality rate possibly due to that the reduction in SM mass had a greater influence on AIS prognosis compared to the accumulation of VAT .

Some limitations of this study persist. First, due to the observational and non-random nature of this study, which may weaken the causal relationship between obesity and stroke outcomes as defined in the study, we exercise caution in interpreting results that may entail a high risk of confounding bias. Second, patients undergoing abdominal CT are likely to be evaluated for other systemic conditions, potentially indicating underlying comorbidities. Consequently, patients included in this study might exhibit elevated NIHSS scores, raising uncertainty regarding the generalizability of these findings to the broader cohort of AIS patients due to inherent selection biases. Third, the obesity-related indicators of the subjects were not continuously monitored post-discharge, and there was a lack of in-depth investigation into the causal relationship between body composition and stroke. Last, the subjects included in this study were from only three hospitals, which had a limited representation of patients.

The findings of this study suggested a robust association between VSR and the risk of mortality and stroke recurrence in AIS patients. It is recommended to shift the focus from BMI to VAT, SAT, and SM when investigating the correlation between obesity and stroke prognosis.

Study funding

This study was supported by National Science Foundation of China (U22A20341, 82171331, 82101245, 82001452).

Competing interests:

None declared.

Author Contributions

Chengcheng Cui was responsible for studying concept and design, analysis of data and drafting the manuscript for intellectual content. Zhiwen Geng was responsible for studying concept and design and revising the manuscript. Haotao Li contributed to studying concept and design. Rui Li conducted the analysis of data and drafting figures of the manuscript. Mengxia Lu contributed to drafting figures of the manuscript. Yuqiao Wang contributed to studying design and acquisition data. Lulu Xiao contributed to studying concept and design, drafting and revision of manuscript. Xinfeng Liu contributed to studying concept and design.

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Table 1： Baseline characteristics of all patients.

	Total(N=1007)	Mortality(N=182)	Survival(N=825)	P value
Age, median (IQR), years	68.0(58.0-76.0)	74.0(66.0-80.8)	66.0(57.0-75.0)	< 0.001
Male, n（%）	649(64.4)	128(70.3)	521(63.2)	0.067
Smoking, n（%）	260(25.8)	58(31.9)	202(24.5)	0.039
Alcohol use, n（%）	170(16.9)	36(19.8)	134(16.2)	0.249
Comorbidities, n（%）
Hypertension	744(73.9)	130(71.4)	614(74.4)	0.405
Coronary artery disease	131(13.0)	41(22.5)	90(10.9)	< 0.001
Hyperlipidaemia	67(6.7)	15(8.2)	52(6.3)	0.342
Atrial fibrillation	282(28.0)	77(42.3)	205(24.8)	< 0.001
Diabetes mellitus	411(40.8)	85(46.7)	326(39.5)	0.074
Baseline NIHSS, median (IQR)	9(7-12)	11(8-16)	9(7-11)	< 0.001
Stroke etiology, n（%）				0.002
Large-artery atherosclerosis	521(51.7)	104(57.1)	417(50.5)
Cardiac	276(27.4)	59(32.4)	217(26.3)
Lacunar	60(6.0)	5(2.7)	55(6.7)
Others	150(14.9)	14(7.7)	136(16.5)
Medication use, n （%）
Statins	890(88.4)	160(87.9)	730(88.5)	0.827
Hypoglycemic agent	382(37.9)	74(40.7)	308(37.3)	0.403
Antiplatelet drug	947(94.0)	167(91.8)	780(94.5)	0.150
Anticoagulant	88(8.7)	31(17.0)	57(7.0)	< 0.001
Beta-blocker	127(12.6)	39(21.4)	88(10.7)	< 0.001
Laboratory data, mmol/L median (IQR)
Total cholesterol	4.3(3.5-5.1)	4.3(3.5-5.0)	4.3(3.5-5.1)	0.795
Triglyceride	1.4(1.1-2.0)	1.5(1.1-2.1)	1.4(1.1-2.0)	0.199
LDL	2.4(1.8-3.1)	2.3(1.7-3.1)	2.5(1.8-3.1)	0.237
HDL	1.0(0.9-1.2)	1.0(0.8-1.2)	1.0(0.9-1.2)	0.134
Obesity related index, median (IQR)
BMI(Kg/m²)	25.5(23.3-27.4)	25.7(23.5-27.6)	25.4(23.2-27.3)	0.660
Waist circumference(cm)	88.0(80.0-95.0)	87.0(80.0-95.0)	88.0(80.0-95.0)	0.335
VATD(HU)	-95.1(-99.8- -91.0)	-95.6(-100.0- -91.8)	-95.0(-99.7- -90.8)	0.167
SATD(HU)	-101.9(-106.0- -97.3)	-102.4(-106.3- -97.4)	-101.8(-105.9- -97.2)	0.386
SMD(HU)	36.9(29.5-41.9)	37.1(27.8-42.4)	36.8(29.9-41.8)	0.722
VATA(cm²)	106.6(78.4-148.1)	132.4(95.3-151.3)	103.7(77.2-145.6)	0.001
SATA(cm²)	126.6(105.3-152.2)	137.5(110.4-158.7)	124.7(105.1-150.6)	0.023
VATA/SATA	0.9(0.6-1.2)	1.0(0.6-1.2)	0.8(0.6-1.2)	0.079
SMA(cm²)	131.6(97.0-160.1)	122.2(90.9-150.1)	135.6(97.5-161.4)	0.002
VATA/SMA	0.9(0.7-1.1)	1.0(0.8-1.3)	0.9(0.7-1.1)	< 0.001
SATA/SMA	1.0(0.7-1.4)	1.0(0.8-1.5)	1.0(0.7-1.4)	0.006

NIHSS: National Institutes of Health Stroke Scale; HDL: High density lipoprotein; LDL: Low density lipoprotein; BMI: Body mass index; VATA: Visceral adipose tissue area; VATD: Visceral adipose tissue density; SATA: Subcutaneous adipose tissue area; SATD: Subcutaneous adipose tissue density; SMA: Skeletal muscle area; SMD: Skeletal muscle density.

Table 2 Multivariate analysis of all-cause death and cardio-cerebrovascular origin death (CCVD) with cox regression model

	All-cause death		CCVD
	Adjusted OR* 95% CI	p Value	Adjusted OR* 95% CI	p Value
Age	1.04(1.03-1.05)	< 0.001	1.04(1.02-1.05)	< 0.001
Stroke etiology
Large-artery atherosclerosis	Reference		Reference
Cardiac	0.72(0.48-1.07)	0.108	0.76(0.49-1.19)	0.226
Lacunar	0.50(0.20-1.24)	0.134	0.31(0.08-1.29)	0.108
Others	0.53(0.30-0.92)	0.025	0.31(0.13-0.71)	0.006
Baseline NIHSS	1.09(1.06-1.13)	< 0.001	1.12(1.08-1.16)	< 0.001
VATA(cm²)	1.01(1.00-1.01)	0.002	1.01(1.01-1.02)	< 0.001
SMA(cm²)	0.99(0.99-1.00)	0.002	0.99(0.99-1.00)	0.019
VSR	2.17(1.52-3.11)	< 0.001	2.49(1.64-3.79)	< 0.001
SSR	1.24(0.95-1.61)	0.117	1.10(0.80-1.51)	0.550

Abbreviations: CCVD= cardio-cerebrovascular origin death; NIHSS= National Institutes of Health Stroke Scale; VATA= visceral adipose tissue area; SATA= subcutaneous adipose tissue area; SMA= skeletal muscle area; VSR=VATA/SMA；SSR= SATA/SMA.

Regression analyses were adjusted for the following variables: age, atrial fibrillation, stroke etiology, anticoagulant and beta-blocker, baseline NIHSS,VATA, SATA, SMA,VSR.

There is NO conflict of interest to disclose

Supplement.docx

The Impact of Abnormal Distribution of Abdominal Adiposity and Skeletal Muscle on the Prognosis of Ischemic Stroke.

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Abstract

Background and Purpose

Methods

Results

Conclusions

Figures

Introduction

Materials and methods

Study population

Imaging parameters and radiological assessment

Data collection and follow-up

Statistical analysis

Results

Patient characteristics

Association of VSR/SSR/BMI with mortality and recurrence of stroke

Discussion

Conclusion

Declarations

Study funding

Competing interests:

Author Contributions

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1