Our study suggests that dyslipidaemia (TG, TC) rather than obesity (BMI, BFP) acts as a significant factor contributing to the unfavourable prognosis of IS patients. The data from our derivation cohort, which incorporated a comprehensive range of adiposity measures such as BMI, BFP, HDL, TG, and TC, revealed that TG and TC consistently emerged as predictors of negative clinical outcomes. Contravening conventional understanding, failed to detect a protective effect linked to augmented BMI figures. The conclusions were further reinforced by utilizing robust techniques such as multivariate analysis, PSM and RDD. Besides, the result of a rigorous national prospective cohort study underscored that the prognostic impact of dyslipidemia distinctly presents within the initial year following IS onset and weakens considerably beyond this period. This indicates that TG and TC, as markers of dyslipidaemia, continue to represent risk factors for IS. Notably, wasting was identified as a risk factor for IS, while obesity did not emerge as a significant protective factor.
Interestingly, our results contradict the 'obesity paradox'13, 37, which argues for a survival edge among overweight members of critically ill cohorts16, 19, 24, 38 - our sample population of East Asian individuals experiencing their first-ever IS episode didn’t exhibit this phenomenon. This discrepancy contradicts some previous studies that hint at a protective impact attributed to high BMI in the case of stroke patients16, 27. The variation possibly stems from the complex BMI-stroke outcome relationship8, exacerbated by ethnic and racial differences, implying that generic metrics like BMI are inadequate to illustrate nuanced risk profiles spanning different demographic groups20, 39. To further probe this complexity, we leveraged BFP, an advanced measure that amalgamates BMI, age, and gender, into our research. We confirmed that neither BFP nor BMI held any significant correlation with poorer outcomes in IS cases, casting doubt on obesity's alleged protective effect, particularly within the context of our study's demographic, where regional differences in the definition of obesity may affect conventional interpretations. For instance, individuals of East Asian descent generally have smaller body frames. In Western countries, obesity is typically defined as a BMI of 30 kg/m2 or higher, whereas in China, the obesity standard is a BMI of 28 kg/m2or higher40.
Highlighting a notable aspect of our study, we identified significantly elevated TG and TC levels as key risk factors for the prognosis of IS patients. This discovery builds upon the growing evidence that emphasizes the crucial importance of lipid management in IS patient care8, 10–12. This conclusion aligns with existing research, such as Chung et al.10 and Tanne et al., stressing the correlation between dyslipidaemia and the heightened risk of IS relapse. While the link between dyslipidaemia and cardiovascular disease is well-established, our study provides further evidence of the detrimental impact of elevated TG and TC levels specifically on the prognosis of IS patients. These results have important implications for clinical practice, highlighting the need for targeted interventions to manage lipid levels in IS patients to mitigate the risk of adverse outcomes. Additionally, our findings suggest that monitoring TG and TC levels in the acute and subacute phases of ischemic stroke may be particularly important, as the highest risk of adverse outcomes was observed within the first year of disease onset. The temporal effect partially accounts for the evolving impact of obesity on the prognosis of critically ill patients over time41, 42. Thus, our results carry significant implications for clinical practice, underlining the necessity of diligent lipid monitoring and management in the aftermath of an IS, particularly within the initial year, where the risk of adverse outcomes is most acute.
Another strength of our study is employing a comprehensive and rigorous methodological framework, including retrospective and prospective cohort analyses bolstered by advanced statistical methods (such as PSM and RDD), enhanced the robustness of our study and potentially its applicability to a broader patient population. Additionally, the nationwide multicentre nature of our study allowed for a large and diverse patient population to be included, increasing the generalizability of our findings. By utilizing both retrospective and prospective data, our study provides a comprehensive and reliable assessment of the relationship between fat-related indicators and adverse outcomes in IS patients. In a novel approach, we integrated a machine learning predictive model, utilizing SHAPE values to decode the influential contributions of different adiposity measures upon IS outcomes, affirming that metrics of dyslipidemia are chief predictors for adverse clinical events. Our analysis revealed that body fat percentage, TG, and TC score emerged as the top three contributors to adverse clinical outcomes. These findings provide further evidence supporting the notion that fat-related indicators serve as significant risk factors for adverse outcomes in stroke patients. These methodological strengths contribute to the significance and reliability of our findings, providing valuable insights for clinical practice and future research in this area.
Despite these strengths, we acknowledge the inherent limitations of our study, such as potential selection bias and confounding variables characteristic of observational studies. Furthermore, while we have established associations between fat-related indices and IS outcomes, this study has not probed into the underlying biological mechanisms that may explain these observations. Future research should seek to unveil the biological pathways through which lipid levels and other fat-related factors impact IS patient prognosis, thereby gaining a deeper comprehension of the underpinning pathophysiology and potential intervention targets.
