Chronic obstructive pulmonary disease (COPD) and coronary artery disease (CAD) are prevalent chronic disorders that contribute significantly to global mortality and impose a considerable socioeconomic burden [1, 2, 3]. Individuals with COPD exhibit a heightened susceptibility to cardiovascular disease (CVD) compared to non-COPD populations [4], with CVD accounting for nearly one-third of COPD-related fatalities [5]. The frequent co-occurrence of CAD and COPD [6] underscores a bidirectional relationship, wherein COPD is linked to an increased risk of adverse cardiovascular events [7]. Beyond common risk factors such as smoking and advanced age, heightened oxidative stress and systemic inflammation are key mechanisms connecting COPD and CAD [8]. Persistent systemic inflammation in COPD promotes endothelial dysfunction, atherosclerotic plaque progression, and thrombosis [9], processes that are directly implicated in vascular stenosis and poor cardiovascular outcomes. Consequently, biomarkers related to inflammation may offer valuable insights into the cardiovascular risk and prognosis of patients with concomitant COPD and CAD.

High-sensitivity C-reactive protein (hsCRP) is a well-established marker of systemic inflammation, whereas serum albumin reflects nutritional and metabolic health. Elevated hsCRP at the time of percutaneous coronary intervention (PCI) is associated with increased 10-year all-cause mortality and myocardial infarction (MI) risk [10]. Additionally, hsCRP serves as an independent prognostic indicator of CVD risk in COPD patients [11] and predicts long-term outcomes in those with COPD–CAD undergoing PCI [12]. Similarly, hypoalbuminemia has been identified as a predictor of all-cause mortality in acute coronary syndrome [13]. The high-sensitivity C-reactive protein to albumin ratio (hsCAR), an integration of these two parameters, has recently gained attention as a novel composite biomarker with prognostic relevance across a variety of cardiovascular and non-cardiovascular conditions. For example, a study involving 1210 COPD patients indicated that an elevated CRP-to-albumin ratio (CAR) significantly predicts 5-year mortality [14]. Moreover, hsCAR demonstrates superior predictive capability for CVD incidence compared to either hsCRP or albumin alone [15]. It has also been validated as an independent prognostic marker in PCI patients [16].

Although existing evidence supports the prognostic value of hsCAR in a diverse range of diseases, its role in predicting long-term cardiac outcomes specifically in COPD–CAD patients after PCI remains unexamined. Given the pivotal role of systemic inflammation in the initiation and progression of cardiac events, hsCAR represents a promising biomarker for risk stratification in such a high-risk group. Therefore, this study was designed to evaluate the long-term prognostic significance of hsCAR in COPD–CAD patients undergoing PCI, with the aim of informing individualized follow-up care.

In this cohort of 262 COPD–CAD patients treated with PCI, we found that hsCAR effectively predicts long-term adverse cardiovascular outcomes. During a 4-year follow-up, higher hsCAR at PCI was associated with significantly increased cumulative MACE incidence. After multivariate adjustment, the high-hsCAR group (Group C) maintained a significantly elevated risk compared to the low-hsCAR group (Group A). RCS analysis confirmed a monotonic relationship between increasing hsCAR and MACE risk, with a consistent risk rise beyond a hsCAR threshold of 0.0446. These results underscore the prognostic utility of hsCAR in this population, supporting its potential as a practical tool for post-PCI risk assessment.

Our findings align with previous studies in broader CAD populations. For instance, a multicenter prospective cohort study demonstrated that both elevated hsCRP and hypoalbuminemia independently predict long-term mortality, with the highest risk observed in patients exhibiting both abnormalities [21]. Other studies have confirmed the prognostic value of CAR in PCI settings. A study of 1630 CAD patients undergoing PCI found significant associations between CAR levels and both all-cause and cardiac mortality, identifying CAR as an independent predictor of these outcomes [22]. Additionally, hsCAR independently predicts MACE and MI in CAD patients receiving drug-eluting stents [16] and holds prognostic value in patients with ST-elevation MI undergoing primary PCI [23].

Studies focusing on PCI patients with different comorbidities have reported similar findings. In a prospective observational cohort study of 2755 patients with type 2 diabetes mellitus treated with PCI and dual antiplatelet therapy, higher CAR levels were associated with worse 5-year outcomes [24]. In patients with chronic total occlusion undergoing PCI, incorporating hsCAR into conventional risk prediction models significantly improved their prognostic accuracy [25]. Collectively, these consistent findings confirm that hsCAR is a robust predictor of post-PCI outcomes in patients with different types of CAD and different comorbidities. Our study extends these findings to patients with COPD–CAD, a subgroup that has not received attention in previous research, further demonstrating the broad prognostic utility of hsCAR in diverse types of patients with CAD.

In our RCS analysis, the inflection point is at hsCAR $>$0.0446, above which the risk of MACE increased almost linearly. Notably, this threshold is highly consistent with previously reported hsCAR cut-offs in different cardiovascular cohorts. Yang et al. [16] examined hsCAR in patients undergoing PCI and reported optimal cut-off values ranging from 0.027 to 0.134 for predicting adverse cardiovascular outcomes. Similarly, Yang et al. [15] identified hsCAR cut-offs of 0.0267 and 0.0622 for stratifying CVD risk in a large Chinese community population. Although the exact numerical values differ, likely due to variations in study populations, baseline risk profiles, and sample sizes, these studies consistently suggest that hsCAR values in the approximate range of 0.03–0.06 are associated with increased cardiovascular risk. Our spline-derived threshold (hsCAR $\approx$ 0.045) falls within this range, thereby supporting the external plausibility and clinical relevance of hsCAR as a prognostic biomarker in COPD–CAD patients after PCI.

In COPD, chronic oxidative stress driven by excessive reactive oxygen species production contributes to endothelial dysfunction, lipid oxidation, and plaque instability, thereby accelerating atherosclerosis progression. Reactive oxygen species-mediated activation of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-$\kappa$B) and cytokine cascades (e.g., Interleukin (IL)-6, tumor necrosis factor-alpha (TNF-$\alpha$)) sustains a low-grade systemic inflammation that may be reflected indirectly by elevated hsCRP and reduced albumin levels [5]. Although hsCAR integrates inflammatory and nutritional information through hsCRP and albumin, we did not include additional biomarkers such as interleukin-6, tumor necrosis factor-$\alpha$, or prealbumin, which could have provided more direct evidence linking systemic inflammation and malnutrition to adverse outcomes. Future studies could integrate multi-marker panels, including oxidative stress biomarkers (e.g., malondialdehyde, superoxide dismutase), pro-inflammatory cytokines, and nutritional indices, to elucidate the mechanistic pathways linking hsCAR, COPD-related inflammation, and adverse cardiovascular outcomes.

The prognostic value of hsCAR may be attributed to its ability to simultaneously capture both inflammatory and nutritional status. While hsCRP alone is easily affected by infection and acute stress, albumin levels change more slowly and lack sensitivity. By integrating these two parameters, hsCAR amplifies their opposite biological responses and reduces the confounding effects associated with fluctuations in a single biomarker. Consequently, hsCAR provides a more stable and reliable indicator for risk prediction. Consistent with previous findings, several studies have reported that hsCAR exhibits greater prognostic accuracy for cardiovascular events compared with hsCRP or albumin alone [15, 24, 26].

Notably, although the HR of Group C versus Group A was $>$1.00 in all subgroups analyzed, including age, sex, smoking status, hypertension, and dyslipidemia, the difference was statistically significant only in males, non-smokers, former smokers, and patients with hypertension. This may be attributed to the influence of smoking status, sex, and related factors on systemic inflammation and nutritional reserves, which in turn affected these subgroup-specific outcomes [27, 28, 29]. It should be noted that the small sample size within each subgroup may have limited the accuracy and stability of the subgroup analyses. Nevertheless, these intergroup differences highlight the importance of considering patient characteristics, lifestyle factors, and comorbidities in future research and clinical application of hsCAR, as such variables may modify the inflammatory burden and potentially influence its predictive value in different subpopulations.

Moreover, several potential confounders were not fully adjusted for, which may have influenced our findings. For instance, although diabetes and HbA1c were included as variables in the analysis, the collinearity test did not reveal high interaction with hsCAR. This may be attributed to the limited sample size. Previous studies have demonstrated that HbA1c levels are independently associated with cardiovascular events and all-cause mortality [30, 31]. Second, long-term medication for cardioprotective or anti-inflammatory agents such as statins, $\beta$-blockers, or ACEI/ARBs could markedly change when long-term follow-up is conducted, but affect the inflammation status a lot [32]. Finally, although current/former smoking status was recorded, quantitative tobacco exposure (e.g., pack-years) was not assessed, potentially resulting in residual confounding. Future studies are encouraged to incorporate HbA1c levels, standardized medication adherence metrics, and quantitative smoking indicators to enhance the robustness of the findings.

There are some other limitations to consider. First, as a single-center cohort in China, the generalizability of findings to other populations may be limited. Future multicenter studies with larger and more diverse populations are warranted to externally validate our findings. Second, as an observational study, despite adjustment for known confounders, the possibility of residual confounding cannot be excluded. Moreover, previous studies have shown that the inflammatory state is associated with the severity of COPD and the complexity of CVD [33, 34]. Although our study reported the GOLD level and the presence of multivessel disease in the baseline characteristics, we did not perform stratified analyses based on COPD severity or CAD complexity. Future research should incorporate refined COPD severity classification and more comprehensive coronary complexity indices (e.g., SYNTAX score) to enhance generalizability. The study did not high AUC value, and the AUC curve below 0.7 should be carefully interpreted. Considering the primary focus of our study is to provide a proof-of-concept, demonstrating the feasibility of constructing such a prediction model using real-world data, the model utilizes routinely available clinical laboratory indicators, making it suitable for rapid screening. It holds profound value in terms of feasibility and predictive capability. But more studies remain to be conducted. Finally, hsCRP and albumin were measured only once at baseline, and we did not perform a longitudinal assessment of changes in hsCAR over time during the follow-up period. Both parameters may fluctuate over time due to post-PCI inflammation, secondary infections, comorbidities, or nutritional alterations, potentially affecting the temporal stability of hsCAR and its prognostic interpretation.

Despite these limitations, our study offers clinically relevant evidence that hsCAR is an independent predictor of long-term cardiovascular events in COPD–CAD patients after PCI. The routine availability and low cost of hsCRP and albumin measurements make hsCAR a practical tool for widespread clinical use. Patients with elevated hsCAR may benefit from intensified management. Future large-scale multicenter studies are needed to validate these findings, refine the subgroup analyses, and explore whether interventions targeting hsCAR modulation—such as anti-inflammatory agents or nutritional optimization—can improve outcomes in this high-risk population. Future interventional trials investigating hsCAR-guided strategies may help clarify its causal and therapeutic implications.

This study demonstrated that hsCAR is a reliable predictor of long-term adverse cardiovascular outcomes in patients with COPD–CAD undergoing PCI. Elevated hsCAR levels were independently associated with an increased risk of long-term adverse cardiovascular outcomes, particularly MACE and TVR. There was a positive linear relationship between hsCAR and MACE risk, with a marked risk increase in patients with a hsCAR value above 0.0446. HsCAR may provide a practical, cost-effective tool for post-PCI risk stratification in patients with COPD–CAD. Future multicenter studies with larger cohorts are warranted to validate our findings and to explore whether targeted anti-inflammatory or nutritional interventions can improve cardiovascular prognosis by modulating hsCAR.

All supporting data and materials are available from the corresponding author upon reasonable request.

YZ and YDT designed the research study, YCT and ZW performed the research. YQ, JG, and WW participated in data collection and revised the manuscript. YC and YZ analyzed the data. YC, YCT, and ZW drafted the manuscript. YZ and YDT supervised and edited the manuscript. All authors read and approved the final manuscript. All authors have participated sufficiently in the work and agreed to be accountable for all aspects of the work.

This study was approved by Peking University Third Hospital Research Ethics Committee (approval number: M2021523). All procedures adhered to the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants after a detailed explanation of the study procedures.

We thank the support of statistical expert Prof. Dongsheng Di.

This study was supported by Beijing Natural Science Foundation (7254448), National Natural Science Foundation (82500346) and (No. Z241100009024048) from Beijing Municipal Science & Technology Commission, Noncommunicable Chronic Diseases-National Science and Technology Major Project (2023ZD0514600); and the Research Unit of Medical Science Research Management/Basic and Clinical Research of Metabolic Cardiovascular Diseases, Chinese Academy of Medical Sciences (2021RU003); and CAMS Special Project for Clinical and Translational Medicine Research (Grant No. 2022-I2M-C&T-B-119).

The authors declare no conflict of interest.

Supplementary material associated with this article can be found, in the online version, at https://doi.org/10.31083/RCM46633.