Stroke is the most common cause of disability and death and is a global health concern (1). Despite the significant reduction in stroke-related mortality, the prognosis for patients with acute ischemic stroke (AIS) remains unsatisfactory (2). There is increasing focus on identifying new prognostic markers to better classify patients at higher risk of poor prognosis. Studies have shown that atherosclerosis (AS) is the most common cause of AIS, and dyslipidemia is the most important risk factor of AS (3, 4). Many blood lipid parameters have been used to evaluate the risk of stroke outcomes, such as total cholesterol (TC), triglyceride (TG), low-density lipoprotein (LDL-C), high-density lipoprotein (HDL-C), non-HDL-C, and other parameters (5–8), but the predictive values of these indicators are still limited.

The atherogenic index of plasma (AIP) is calculated as log (TG/HDL) and reflects the levels of TG and HDL-C cholesterol. AIP, as a robust biomarker of dyslipidemia and AS, has been used to quantify comprehensive lipid levels (9). It is also considered a biomarker of coronary syndrome and metabolic syndrome (10, 11). Previous studies have demonstrated that it is positively correlated with cardiovascular disease risk (12). Notably, some studies demonstrate that AIP may be more closely associated with cardiovascular and cerebrovascular disease risk than other individual lipoprotein cholesterol concentrations alone (13). However, few studies have examined the relationship between AIP and functional outcomes in AIS. Therefore, larger sample size studies and prospective cohort studies are needed to evaluate the relationship.

In the study, we aimed to explore the relationship between AIP and functional outcomes in patients with AIS at 3 months.

Patients enrolled in the study were from the database of the Henan Province Stroke Registry (14–16) at the First Affiliated Hospital of Zhengzhou University from January 2015 to December 2018. AIS was diagnosed according to criteria defined by the World Health Organization (17) based on neuroimaging results, patient history, and clinical data. All patients signed written informed consent, and this study was approved by the Ethics Committee of the First Affiliated Hospital of Zhengzhou University (14).

The exclusion criteria include the following aspects: (1) the time from onset to admission is more than 24 h; (2) age <18 years; (3) a history of cancer, hematologic disease, or immunosuppressant use; (4) patients without complete clinical data; (5) severe hepatic or renal diseases; (6) infectious or systematic inflammatory disease; and (7) major trauma, surgery, or loss to follow-up.

In the present study, our results showed that high AIP value was associated with risk of poor prognosis within 3 months of AIS. Furthermore, the AIP represented a clinically available prognostic predictor and had a better predictive value than other lipid levels in the current analysis. Compared with other types of stroke, high AIP level in patients with LAA was closely associated with poor outcomes.

As shown in various pathologic conditions, studies have shown that AS was the most common cause of AIS, and dyslipidemia was the most important risk factor of AS (3, 4). Many blood lipid parameters have been used to evaluate the risk of stroke outcomes, such as TG, TC, LDL-C, HDL-C, non-HDL-C, and other parameters (5–7). However, most studies have shown that the traditional single index of blood lipid as the evaluation of AS and cerebrovascular diseases was still debated and not of high predictive value (19). Recently, the AIP, which was calculated by the log10 of TG to HDL-C ratio had emerged as a novel marker of dyslipidemia and was more stable than other lipid counts alone (13). Furthermore, compared with the unconverted variables, the logarithmic conversion value of TG/HDL-C to calculate AIP, which was used to describe the clinical prediction effect, could better satisfy the statistical model assumed as ecological distribution (20). Several studies have identified AIP as a prognostic biomarker of cardiovascular disease. Wu et al. conducted a case–control study involving 696 individuals (348 patients and 348 controls). Results showed that AIP was identified as an independent risk factor for cardiovascular disease after adjusting for traditional risk factors (21). A study by Garg et al. enrolled 267 patients who were referred to carotid artery stenosis; the findings demonstrated that the AIP was the only lipid parameter independently associated with symptomatic carotid artery stenosis (22). Another study of 1,131 Chinese patients who underwent selective coronary angiography found that AIP as a new marker appeared to be an independent predictor of CVD severity (23). Won et al. included 1,488 patients who underwent serial coronary computed tomography angiography with a median inter-scan period of 3.4 years and revealed that AIP was an independent predictor of rapid plaque progression outperformed traditional risk factors (24). However, few studies have examined the relationship between AIP and functional outcomes in AIS. Therefore, larger sample size studies and prospective cohort studies are needed to explore this relationship.

In our study, AIP was used as a continuous variable and a categorical variable, respectively. Spline regression showed a dose–response relationship between AIP levels with risk of poor outcomes. After controlling for other confounding factors, we used restricted cubic splines with five knots at the 5th, 35th, 50th, 65th, and 95th centiles to flexibly model the association of AIP with poor outcomes. The results showed a J-shaped curve. Furthermore, as categorical variable, previous studies have shown that dividing patients into four groups may better reflect the efficacy of AIP in different groups (25). Our study showed that a high AIP value was associated with risk of poor prognosis within 3 months of AIS and had a higher predictive value than other lipid factors. Several speculations may explain this phenomenon. In the process of stroke occurrence, studies have shown that different sizes of lipid particles have different effects on stroke, especially small dense low-density lipoprotein (sdLDL), which was the most closely related to AIS and was an independent risk factor (26). A large number of sdLDL could easily pass through the vascular endothelium and combined with the glycoprotein on the arterial wall to form lipid deposition (27). Furthermore, apoB100 of sdLDL was difficult to combine with plasma LDL receptors, which greatly reduces the clearance rate (28). On the other hand, sdLDL was easily oxidized to oxidized LDL-C, which caused the aggregation of adhesion molecules and chemokines and induced the transformation of monocytes to macrophages (29). Macrophage phagocytes oxidized LDL-C to produce foam cells. Foam cells could fuse and burst, releasing large amounts of cholesterol that form the core of atherosclerotic plaque. This process could also aggravate AS and affect the outcomes of stroke (30–32). Dobiasova et al. found that the AIP value was inversely proportional to the diameter of oxidized LDL particles and indirectly showed sdLDL particle size, which could be used as an indirect method to reflect LDL particle size instead (33). We speculated that the calculation of the AIP value could more accurately evaluate the tendency of blood lipid-induced stroke.

Our results also showed that compared with other conventional lipid markers, AIP demonstrated a higher predictive value. However, this predictive value is not superior to traditional NIHSS. With further research, we found that combining AIP and NIHSS scores into one variable can significantly improve the predictive value of the model. In order to predict the prognosis of stroke better, more composite indicators may be needed in the future.

In the study, subgroup analysis showed that high levels of AIP were associated with stroke subtypes, especially in the LAA stroke subtype. Some studies have verified that AS plays a important role in LAA stroke (34). AIP may reflect subtle metabolic interactions throughout the lipoprotein complex (11). The etiological mechanism of different stroke subtypes is different, which is of great significance for treatment and prognosis evaluation (35). Up to now, few studies havec investigated the relationship between AIP and the outcomes of different stroke subtypes. We hypothesize that AIP may not have the equal contribution on the prognosis of patients with LAA and other stroke subtypes. We also found that the association of 3-month outcomes of AIS with AIP seemed to be more obvious among patients with diabetes. It was plausible to suppose that these traditional cardiovascular risk factors may amplify the detrimental effect of high level of AIP on poor prognosis of stroke. Previous studies showed that LAA is the most common stroke subtype in patients with AIS with type 2 diabetes (36, 37). We supposed that there may be the following reasons. The high glucose level in diabetics accelerates the formation of protein glycosylation end products, causing them to accumulate in tissues, causing proliferation of smooth muscle cells and thickening of blood vessel walls. Lipid deposits in the intima of blood vessels form fat stripes and cause intima thickening. Then, there was local aggregation of complex sugars and lipids, fibrous tissue hyperplasia, and finally plaque formation leading to lumen stenosis or even occlusion.

Several limitations remained in this study. First, the study was a single center and cannot avoid some selection bias. Second, only baseline AIP was available in our study. Dynamic changes of AIP during the follow-up were not available. However, the Framingham Offspring cohort showed that serum lipid parameter concentrations were usually stable over the 30-year life course (38). Third, follow-up was only by telephone in this study, and end-point assessment could not be validated by hospital records in all individuals. Finally, some imaging data were not provided for readers to evaluate the degree of AS among this cohort. Further large-scaled cohort studies in other populations are needed to verify the generalizability of our findings.

In summary, our findings suggested that high AIP value was associated with death and poor outcomes in patients with AIS, especially the stroke subtype of LAA. In medical practice, the AIP level may be easily applied to distinguish poor outcomes and provided a novel target for neuroprotection in AIS patients.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.

YX and BS: research design. YG and HL: writing. SL, LZ, and HF: data analysis and arrangement. LP and KL: English editing help. KZ, CZ, and JZ: data collection. SS and JW: tables and figures. All authors contributed to the article and approved the submitted version.

This research has been supported by the China National Key R&D Program during the 13th Five-year Plan Period (Grant No. 2018YFC1311303) and Major Science and Technology Projects of Henan Province in 2020 (Grant No. 201300310300).

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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