Prognostic significance of serum albumin stratified by total cholesterol in patients with coronary artery disease: based on a published research

doi:10.21203/rs.3.rs-1565517/v1

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Prognostic significance of serum albumin stratified by total cholesterol in patients with coronary artery disease: based on a published research

https://doi.org/10.21203/rs.3.rs-1565517/v1

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Background

Patients with coronary artery disease (CAD) usually show relatively poor long-term prognosis. Serum albumin level showed negative prediction of poor prognosis of CAD, while cholesterol level was also suggested poor prognosis, but most previous studies on albumin levels and prognosis in patients with CAD have not considered the effect of cholesterol levels on outcomes. Thus, we aim to investigate the prognostic impact of albumin levels under different cholesterol level groups.

Methods

We analyzed the data of 204 patients from October 2014 to October 2017 for newly diagnosed stable CAD. Albumin and cholesterol were measured at admission. The outcome was major adverse cardiac events (MACE). The median duration of follow-up was 783 days. COX models were performed to evaluate the prognostic significance of serum albumin on MACE.

Results

Higher serum albumin indicated lower risk of MACE (HR = 0.37, P = 0.0462). In participants whose total cholesterol level less than 200 mg/dL, the risk of MACE was related to lower serum albumin (HR = 0.19, P = 0.0072), but not significantly in the others (HR = 3.16, P = 0.3392).

Conclusion

In clinical practice, when using serum albumin to evaluate the prognosis of patients with cardiovascular disease, the influence of cholesterol on the evaluation results should be fully considered.

serum albumin

total cholesterol

major adverse cardiac events

coronary arterial disease

prognostic factors

Percutaneouscoronary intervention (PCI), as an important strategy for cardiac revascularization in acute/chronic coronary artery disease (CAD), has been widely used in clinical practice. Compared with people without CAD, the CAD patients usually show higher long-term cardiovascular events, long-term revascularization events, and rehospitalization rates^1,2. Therefore, the assessment of prognostic risk is very important for patients with CAD. Some biomarkers such as high sensitivity cardiac troponin (hs-cTn), C-reactive protein (CRP), etc. are considered to be related to the long-term poor prognosis of CAD^3,4. For patients with acute coronary syndrome (ACS) undergoing PCI, history of diabetes mellitus, uric acid level, blood urea nitrogen level, and activated partial thromboplastin time (APTT) were all considered predictors of poor prognosis⁵. Compared with these biomarkers, as a new CAD prognostic biomarker, serum albumin (sALB) has more and more been focused in recent years. In 2020, a study based on the CGPS (Copenhagen General Population Study) noted that lower sALB levels may be associated with an increased risk of long-term cardiovascular disease in healthy individuals⁶. In addition, some studies have suggested that low sALB levels may be associated with poor cardiovascular outcomes in patients with CAD^7,8. However, in clinical practice, as an easily available indicator, the predictive significance of albumin for the prognosis of coronary artery disease has not been widely focused⁹. Although current studies suggest the association of total cholesterol levels (TC) and low-density lipoprotein cholesterol levels (LDL-C) with poor prognosis in patients with CAD^10–12, most previous studies on albumin levels and prognosis in patients with CAD have not considered the effect of cholesterol levels on outcomes. We hope to re-analyze the prognostic impact of albumin levels under different cholesterol level groups based on data from existing studies.

Baseline characteristics of participants. The characteristics of the participants are shown in Table 1. Compared with the high sALB group (≥ 4g/dL), the low sALB group (< 4g/dL) had lower levels of BMI, Hb, T-chol, TG, LDL, EGFR, ALT, and higher CRP level. Given that the low sALB group were older, the lower levels of BMI, sALB, lipoprotein, EGFR and liver enzyme might be associated with age.

Relationship between the sALB and MACE. The unadjusted and adjusted models are shown in Table 2. Cox model was used to evaluate the association between sALB and the risk of MACE. In the crude model, the HR of MACE was 0.18 (95%CI: 0.10 ~ 0.34, P < 0.0001). In model I adjusted for demographic variables (Age, Sex, BMI), the HR of MACE was 0.24 (95%CI: 0.12 ~ 0.46, P < 0.0001). In model II fully adjusted for confounders, the risk of MACE decreased by 63% (95%CI: 0.14 ~ 0.98, P = 0.0462) for each 1g/dL sALB increased. Cox models were established by dividing the sALB of participants into the low sALB group (< 4g/dL) and the high sALB group (≥ 4g/dL) according to the median level. The results showed that, compared with the low sALB group, the HR of MACE in the high sALB group were 0.20 (95% CI: 0.08 ~ 0.49, P = 0.0004) and 0.30 (95% CI: 0.12 ~ 0.78, P = 0.0137) in the crude model and model I respectively. In model II, the HR of MACE in the high sALB group was 0.58 without statistical significant (95% CI: 0.19 ~ 1.78, P = 0.3378). Figure 1 showed a trend in the association between sALB and the risk of MACE (logHR), indicating that the risk of MACE decreased as the baseline sALB increased. When sALB level was in the range of 4.0g/dL to 4.5g/dL, it remained a protective factor although the risk of MACE increased. However, when sALB level was more than 4.5g/dL, the risk of MACE would increased with the increase of sALB. It is consistent with the clinical reference range of sALB.

Statistical interaction between sALB and total cholesterol on MACE. Figure 2 presents the association between sALB level and the risk of MACE (logHR), stratified by total cholesterol level. The solid line, which represents those whose total cholesterol level less than 200 mg/dL, shows a decline in MACE risk with increasing sALB level after adjusting for confounders. Contrarily, there is no such association in those whose total cholesterol level more than 200 mg/dL. This association was further demonstrated by Cox models as presented in Table 3. Correspondingly, we found that the risk of varied by sALB level and total cholesterol level. Specifically, there was an negative association between sALB level and the risk of MACE in participants whose total cholesterol level less than 200 mg/dL in the fully adjusted model (HR, 0.19;95%CI, 0.06 ~ 0.64; P = 0.0072). However, no such association was found in those whose total cholesterol level more than 200 mg/dL (HR, 3.16; 95% CI, 0.30 ~ 33.51; P = 0.3392). A test for interaction between sALB level and total cholesterol level on the risk of MACE was statistically significant (P = 0.0176). And the similar association and statistically significant interaction test were observed in other model (Table 3).

Table 1

Baseline Characteristics of the Study Participants*
Variable	sALBumin (g/dL)		P-value
Variable	< 4 (n = 89)	≥ 4 (n = 115)	P-value
Age (years)	75.96 ± 10.87	69.98 ± 9.15	< 0.001
Male sex, n (%)	59 (66.29%)	83 (72.17%)	0.365
BMI (kg/m²)	22.49 ± 4.17	24.51 ± 3.49	< 0.001
Systolic blood pressure (mmHg)	134.20 ± 23.40	137.90 ± 17.76	0.201
Diastolic blood pressure (mmHg)	76.07 ± 15.21	78.48 ± 11.38	0.197
Hypertension, n (%)	58 (65.17%)	93 (80.87%)	0.011
Dyslipidemia, n (%)	32 (35.96%)	72 (62.61%)	< 0.001
Diabetes mellitus, n (%)	33 (37.08%)	40 (34.78%)	0.734
Atrial fibrillation, n (%)	14 (15.73%)	12 (10.43%)	0.261
Old cerebral infarction, n (%)	19 (21.35%)	16 (13.91%)	0.162
PAD, n (%)	27 (30.34%)	26 (22.61%)	0.212
Past smoker, n (%)	34 (38.20%)	67 (58.26%)	0.004
Hb (g/dL)	12.41 ± 2.02	14.48 ± 1.46	< 0.001
T-chol (mg/dL)	174.62 ± 34.60	197.24 ± 34.54	< 0.001
TG (mg/dL)	111.57 ± 87.82	150.66 ± 105.01	0.005
HDL-C (mg/dL)	49.09 ± 14.03	52.60 ± 13.81	0.075
LDL-C (mg/dL)	99.44 ± 27.76	117.56 ± 27.07	< 0.001
eGFR(mL/min/1.73m2)	51.99 ± 28.46	68.54 ± 18.25	< 0.001
AST(U/L)	24.48 ± 12.59	24.83 ± 9.54	0.195
ALT(U/L)	18.51 ± 12.58	22.82 ± 11.62	< 0.001
HbA1C (%)	8.79 ± 21.33	6.31 ± 0.85	0.501
CRP (mg/dL)	0.82 ± 1.50	0.16 ± 0.27	< 0.001
LVEF (%)	61.06 ± 10.62	64.94 ± 8.72	0.005
Aspirin, n (%)	87 (97.75%)	115 (100.00%)	0.189
Thienopiridines, n (%)	87 (97.75%)	113 (98.26%)	1.000
Warfarin, n (%)	2 (2.25%)	3 (2.61%)	1.000
DOAC, n (%)	11 (12.36%)	10 (8.70%)	0.393
Ezetimibe, n (%)	1 (1.12%)	2 (1.74%)	1.000
PPI, n (%)	57 (64.04%)	77 (66.96%)	0.664
ACE-I, n (%)	9 (10.11%)	10 (8.70%)	0.730
ARB, n (%)	40 (44.94%)	48 (41.74%)	0.647
β-blocker, n (%)	25 (28.09%)	30 (26.09%)	0.749
MRA, n (%)	6 (6.74%)	5 (4.35%)	0.453
MACE: major adverse cardiac events (Defined as all-cause death, non-fatal myocardial infarction, non-fatal stroke); BM: body mass index; PAD: Peripheral artery disease; Hb: hemoglobin; T-chol: total cholesterol; TG: Triglycerides; HDL-C: high-density lipoprotein cholesterol; LDL Chol: low density lipoprotein cholesterol; eGFR = estimated glomerular filtration rate; HbA1c: hemoglobin A1c; CRP: C-reactive protein; LVEF: left ventricular ejection fraction; DOAC: direct oral anticoagulants; PPI: proton pump inhibitor; ACE-I: angiotensin converting enzyme inhibitor; ARB: angiotensin-receptor blocker; MRA: mineralocorticoid receptor antagonist; .
*For continuous variables, values are presented as mean ± SD; For Categorical variable, values are presented as N(%).

Table 2

Relationship between sALB and major adverse cardiac events in different models*
sALB, g/dL	Crude Model (n = 204)	Model I (n = 204)	Model II (n = 196)
As linear trend	0.18 (0.10, 0.34) < 0.0001	0.24 (0.12, 0.46) < 0.0001	0.37 (0.14, 0.98) 0.0462
As median cutoff point
Lower(< 4)	Reference	Reference	Reference
Higher(≥ 4)	0.20 (0.08, 0.49) 0.0004	0.30 (0.12, 0.78) 0.0137	0.58 (0.19, 1.78) 0.3378
Model I adjusted for: Age, MALE (sex), BMI
Model II adjusted for: Age; MALE (sex) ; BMI; Hb; T-chol; eGFR; CRP; PAD; Warfarin
*Models are presented as HR (95% CI) P-value.

The graph displays the adjusted association between sALB and the risk of MACE. The model adjusted for Age; MALE (sex) ; BMI; Hb; T-chol; eGFR; CRP; PAD; Warfarin.

The graph displays the adjusted association between sALB and the risk of MACE stratified by total cholesterol. The model adjusted for Age, MALE (sex), BMI, Hb, eGFR, CRP, PAD, Warfarin.

Table 3

The prognostic significance of sALB on major adverse cardiac events stratified by total cholesterol in different models*
Model	T-chol < 200 mg/dL (n = 132)	T-chol ≥ 200 mg/dL (n = 72)	P interaction
Crude Model	0.07 (0.03, 0.17) < 0.0001	1.15 (0.27, 4.99) 0.8475	0.0003
Model I	0.09 (0.03, 0.22) < 0.0001	1.32 (0.30, 5.85) 0.7116	0.0005
Model II	0.15 (0.05, 0.47) 0.0012	2.95 (0.43, 20.08) 0.2679	0.0010
Model II#	0.19 (0.06, 0.64) 0.0072	3.16 (0.30, 33.51) 0.3392	0.0176
Model I adjusted for: Age, MALE (sex), BMI
Model II adjusted for: Age, MALE (sex), BMI, Hb, eGFR, CRP, PAD, Warfarin
Model II# adjusted for: Age, MALE (sex), BMI, Hb, eGFR, CRP, PAD, Warfarin and the interaction terms for following variables: Age, BMI, Hb, eGFR
*Models are presented as HR (95% CI) P-value.

Our analysis suggested an interaction between TC and sALB levels after adjusting for confounders. Similar to previous studies, we observed an inverse association between baseline albumin levels and the risk of poor prognosis in participants with TC < 200 mg/dL, but in participants with TC > 200 mg/dL, this relationship is unobvious, which suggests that total cholesterol levels influence the predictive role of baseline serum albumin levels in predicting long-term cardiovascular outcomes in patients with coronary artery disease undergoing percutaneous coronary intervention. The study by Suzuki et al suggested that the baseline sALB was a negative predictor of long-term major adverse cardiovascular events (MACE) in patients undergoing PCI¹³. Shih-Chieh Chien et al pointed out that sALB is a reliable predictor of CVD prognosis¹⁴. Oduncu et al retrospectively analyzed 1706 patients with ST-segment elevation myocardial infarction (STEMI) who underwent PCI and suggested that lower sALB was independent predictors of long-term mortality¹⁵. The molecular mechanism of albumin's effect on the prognosis of CVD may be multifactorial, which may include maintaining vascular endothelial integrity, regulating vasodilation, binding toxins, anticoagulation, and antioxidation, etc⁷. Burl R Don et al pointed out that the poor nutritional status reflected by low sALB may also be one of the factors of poor prognosis¹⁶. Studies have pointed out that albumin plays an important role in the transport of serum and cellular cholesterol and the maintenance of cholesterol homeostasis^9,14,17,18. Albumin can shuttle free cholesterol among various receptors, which will increase the movement of free cholesterol under concentration gradients between the numerous cholesterol pools present in plasma and tissues, thereby promoting and maintaining cholesterol metabolism to restore steady-state levels¹⁸. The improving of cholesterol efflux may improve the prognosis of CAD¹⁹. These study results may suggest that the influence of albumin level on prognosis may be closely related to cholesterol level. In conclusion, based on our analysis, we believe that serum albumin has a variable predictive effect on prognosis among CAD patients treated by percutaneous coronary intervention stratified by total cholesterol levels after adjusting for multiple confounders. In patients with higher cholesterol levels, serum albumin has a weaker prognostic value. In clinical practice, when using serum albumin to evaluate the prognosis of patients with cardiovascular disease, the influence of cholesterol on the evaluation results should be fully considered.

However, our study also has some limitations. The data of our study came from a single-center sample, mainly elderly patients with CAD who underwent PCI. Therefore, for the extension of the research conclusions, further research is still needed.

Research design and population. This was a secondary scientific analysis of a retrospective, single-center cohort study where the dataset was collected by Sho et al. and is now available on Dryad (via: https://doi.org/10.5061/dryad.fn6730j) ¹³. The cohort included hospitalized patients newly diagnosed with stable coronary heart disease and treated with PCI at shinonoi general hospital from October 2014 to October 2017 in Shinonoi General Hospital. Patients with old myocardial infarction or malignancy were excluded. The collected data included medical history, laboratory, echocardiography data, discharge medications and follow-up results. The baseline sALB was measured at admission by bromocrosol pure assay and the LABOSPECT 008 analyzer (Hitachi Ltd, Tokyo, Japan), with a measurement range of 1.0 ~ 8.0 g/dl and a coefficient of variation of 5%. The minimum detection limit was 0.1g/dl. All participants were enrolled after the approval of Shinonoi General Hospital Ethics Committee and written informed consent. The research was consistent with the principles outlined in Helsinki Declaration. The outcome was major adverse cardiac events (MACE; defined as all cause mortality, non fatal myocardial infarction, and non fatal stroke). Events were validated by chart review and the median duration of follow-up was 783 days.

Statistical analysis. The baseline characteristics of the participants were analyzed and divided into two groups according to the median baseline sALB level. The continuous variables were presented as Mean ± SD (comparison between groups by ANOVA) and the categorical variables were presented as N(%) (comparison between groups by χ² test) .

The primary outcome was to determine the association between MACE and baseline sALB level stratified by total cholesterol. Therefore, the results of unadjusted and adjusted confounders model analysis were presented based on STROBE recommendations. When the confounder was included or excluded from the model, the hazard ratio of the match was changed by at least 10%, and this confounders needed to be adjusted²⁰. In the association analysis, baseline sALB level was first analyzed as a continuous variable and then divided into two groups according to the median level for clinical interpretation. The models were divided into unadjusted model, model I and Model II according to the adjusted confounders and presented as HR (95% CI) P-value.

P values less than 0.05 (two-tailed) were considered statistically significant. EmpowerStats ver.3.0 (http://www.empowerstats.net/analysis/, X&Y Solutions,Inc., Boston, MA) and the R software ver.3.3.1 (http://www.R-project.org/, The R Foundation), were used for all statistical analyses.

Acknowledgement

This research was supported by Shenzhen Science and Technology R & D Fund Project (JCYJ20150330102720161) and Clinical Research Project of Shenzhen Second People's Hospital in 2019 (No.20193357009).

Author contributions

Yufeng Yao contributed to the conception, data analyses and manuscript preparation of the study;

Zhenyu Chen contributed to the conception, data analyses and wrote the manuscript;

Haibo Chen and Tianyi Luo helped perform the analysis with constructive discussions.

All authors reviewed the manuscript.

Competing interests

The authors declare no competing interests.

Data availability

The dataset was collected by Sho et al. and is now available on Dryad (via: https://doi.org/10.5061/dryad.fn6730j). The datasets generated or analysed during the current study are available from the corresponding author on reasonable request.

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Prognostic significance of serum albumin stratified by total cholesterol in patients with coronary artery disease: based on a published research

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