Authors: Jun Sun, TianLong Yang, Yu Sheng
Categories: Research, Chronic obstructive pulmonary disease, Pulmonary heart disease, Cardiac biomarkers, Prediction, Combined detection
Source: BioMedical Engineering OnLine
Authors: Jun Sun, TianLong Yang, Yu Sheng
To analyze the influencing factors of chronic obstructive pulmonary disease (COPD) concomitant with pulmonary heart disease (PHD) and the diagnostic value of myocardial markers.
A retrospective study was conducted on 117 COPD patients. According to whether there were concomitant PHD, 117 cases were distinguished as the combined group (45 cases) and uncombined group (72 cases). Independent risk factors were screened using multivariate logistic regression analysis. The levels of serum markers were determined. Pearson correlation analysis was used to evaluate the correlation between myocardial markers and cardiac function indicators. The expression of myocardial markers in different COPD severity groups was analyzed. The receiver operating characteristic curve (ROC) was adopted to evaluate the diagnostic value of serum markers.
Compared with the uncombined group, patients in the combined group had significantly increased left atrial diameter (LAD), pulmonary artery pressure (PAP), and inducible co-stimulator ligand (ICOSL) levels, with decreased left ventricular ejection fraction (LVEF) levels (P < 0.05). Serum N-terminal pro-B type natriuretic peptide (NT-proBNP), creatine kinase myocardial band (CK-MB), and cardiac troponin I (cTnI) levels were also markedly increased (P < 0.05). CTnI, CK-MB, and NT proBNP were all negatively correlated with LVEF (r = − 0.642, − 0.587, − 0.723, respectively, P < 0.001), and positively correlated with PAP (r = 0.698, 0.634, 0.781, respectively, P < 0.001). In patients with GOLD grades 3–4 even without concomitant PHD, the levels of cTnI, CK-MB, and NT proBNP were significantly higher than those in patients with GOLD grades 1–2 (P < 0.05). The area under the curve (AUC) of combined serum markers for predicting PHD in COPD patients was 0.921, with specificity and sensitivity of 88.89% and 86.11%, respectively.
PAP, ICOSL, cTnI, CK-MB, and NT proBNP were all independent risk factors relating to the occurrence of COPD concomitant with PHD. The combined detection of cTnI, CK-MB, and NT-proBNP had certain diagnostic reference value for COPD concomitant with PHD. Monitoring these myocardial markers may provide clues for early identification of patients with COPD concomitant with PHD and assist in the clinical development of targeted intervention programs.
Chronic obstructive pulmonary disease (COPD) is a chronic respiratory disease characterized by persistent airflow limitation. Its core pathological basis is chronic inflammation of airways, lung parenchyma, and pulmonary vessels, often induced by smoking, air pollution, and other factors. With the progression of the disease, pulmonary ventilation dysfunction and increased pulmonary artery pressure can lead to pulmonary heart disease (PHD). A vicious cycle of "acute exacerbation of COPD and cardiac function damage" is formed [1, 2]. The core pathological mechanism of PHD is pulmonary hypertension (PAP) secondary to COPD, which leads to right ventricular hypertrophy and dysfunction, forming a vicious cycle [3]. Due to the specific functional and metabolic characteristics of myocardial cells, they are more prone to myocardial cell damage and apoptosis during hypoxia. The level of serum myocardial markers may exhibit the extent and severity of myocardial injury [4]. N-terminal pro B-type natriuretic peptide (NT-proBNP) is an inactive peptide synthesized by cardiomyocytes, and its concentration reflects the level of newly synthesized B-type natriuretic peptide (BNP) in a short period of time, as well as the activation of the BNP pathway [5]. NT-proBNP is closely related to the diagnosis, evaluation, and prognosis of heart failure, especially in patients with acute and chronic heart failure. Elevated levels of NT-proBNP are usually positively correlated with the degree of cardiac dysfunction [6]. Creatine kinase myocardial band (CK-MB) is an isoenzyme of creatine kinase, mainly present in the heart, brain, and muscle tissue. CK-MB is closely related to muscle contraction, intracellular energy transport, and adenosine triphosphate (ATP) regeneration. The elevation of CK-MB levels is usually associated with myocardial injury [7]. Cardiac troponin I (cTnI) is one of the main biomarkers for detecting myocardial injury. The increased level of cTnI reflects the degree of myocardial cell damage, acting as one of the most authoritative indicators currently available with high specificity and sensitivity [8]. Logistic regression is a widely used statistical method for disease risk assessment, which evaluates individual disease risk by analyzing the influencing factors.
The aim of this study was to determine the independent predictive value of PAP, ICOSL, and the above myocardial markers for COPD concomitant with PHD by logistic regression analysis, and to explore the clinical value of a combined diagnosis of multiple markers, so as to provide a basis for early identification of high-risk patients.
There were no significant statistical differences between the two groups in terms of gender, smoking history, drinking history, proportion of hypertension history, proportion of GOLD classification, age, BMI, disease duration, WBC, D-D, and FEV1/FVC levels (P > 0.05). Compared with the uncombined group, patients in the combined group had significantly increased LAD, PAP, and ICOSL levels, with decreased LVEF levels (P < 0.05, Table 1).Table 1Clinical data analysis of COPD combined with PHD patients [cases (%)], (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \overline{x}
### Changes in serum myocardial markers levels in COPD patients with PHD Serum N-terminal pro-B type natriuretic peptide (NT-proBNP), creatine kinase myocardial band (CK-MB), and cardiac troponin I (cTnI) levels were also higher in the combined group than in the uncombined group (*P* < 0.05, Table 2).Table 2Changes in serum myocardial markers levels in COPD patients with PHD (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \overline{x} $$\end{document}x¯ ± *s*)GroupsCasescTnI (ng/mL)CK-MB (ng/mL)NT-proBNP (pg/mL)The combined group451.35 ± 0.5424.59 ± 1.87957.49 (896.32, 1021.57)The uncombined group720.39 ± 0.113.10 ± 0.78104.86 (92.45, 118.63)*t*14.64286.39035.267*P* < 0.001 < 0.001 < 0.001 ### Correlation analysis of myocardial markers and cardiac function indicators The results of Pearson correlation analysis showed that cTnI, CK-MB, and NT-proBNP were all negatively correlated with LVEF (r was − 0.642, − 0.587, and − 0.723, respectively, *P* < 0.001), and positively correlated with PAP (*r* was 0.698, 0.634, and 0.781, respectively, *P* < 0.001, Table 3).Table 3Correlation analysis of myocardial markers and cardiac function indicatorsIndicatorLVEFPAP*r**P**r**P*cTnI− 0.642 < 0.0010.698 < 0.001CK-MB− 0.587 < 0.0010.634 < 0.001NT-proBNP− 0.723 < 0.0010.781 < 0.001 ### Comparison of myocardial marker levels in patients with different GOLD grades According to the GOLD classification, the patients were divided into two GOLD grade 1–2 and GOLD grade 3–4. The results showed that the levels of cTnI, CK-MB, and NT-proBNP in patients with GOLD grade 3–4 were also significantly higher than those in patients with GOLD grade 1–2 (*P* < 0.05, Table 4).Table 4Comparison of myocardial marker levels in patients with different GOLD gradesGroupCasescTnI (ng/mL)CK-MB (ng/mL)NT-proBNP (pg/mL)GOLD Grade 1–2670.61 ± 0.225.23 ± 1.87185.25 (123.23, 210.05)GOLD Grade 3–4500.95 ± 0.386.90 ± 2.31405.25 (210.53, 759.82)*t/Z*6.0884.31915.382*P* < 0.001 < 0.001 < 0.001 ### Analysis of influencing factors of COPD combined with PHD Variables with *P* < 0.05 in the univariate analysis were taken as independent variables (LAD, PAP, ICOSL, cTnI, LVEF, CK-MB, NT proBNP all entered as original values), and whether COPD patients had concomitant PHD as the dependent variable (merged = 1, not merged = 0) to perform multivariate logistic regression analysis. Logistic regression analysis confirmed that PAP, ICOSL, cTnI, CK-MB, and NT proBNP were independent risk factors for COPD concomitant with PHD (*P* < 0.05, Table 5; Fig. 1).Table 5Analysis of influencing factors of COPD combined with PHDIndicators*Β* valueSE valueWald value*P* valueOR value95% CILAD0.2720.1842.1850.3581.3130.915 ~ 1.883PAP0.6300.13820.841 < 0.0011.8781.433 ~ 2.460ICOSL1.0680.4017.0930.0292.9101.326 ~ 6.385cTnI0.9700.3189.304 < 0.0012.6381.415 ~ 4.918LVEF0.1360.1051.6780.5151.1460.932 ~ 1.408CK-MB0.7680.20214.455 < 0.0012.1551.451 ~ 3.203NT-proBNP0.8180.2609.898 < 0.0012.2661.361 ~ 3.773Fig. 1Forest plot analysis of influencing factors of COPD combined with PHD ### ROC curve analysis ROC curve analysis showed that the AUC of combined cTnI, CK-MB, and NT proBNP for predicting PHD in COPD patients was 0.921, with specificity and sensitivity of 88.89% and 86.11%, respectively. Combined detection had a certain predictive value for the occurrence of COPD concomitant with PHD (Table 6; Fig. 2).Table 6The predictive value of myocardial markers for COPD complicated with PHDIndicatorsAUCSpecificitySensitivityYouden’s indexCut-off value*P* value95% CIcTnI0.85677.7885.260.6300.92 ng/mL0.0020.762–0.951CK-MB0.74868.8986.110.55017.56 ng/mL0.0150.635–0.861NT-proBNP0.88380.0097.220.772512.49 ng/mL0.0010.798–0.968Combined detection0.92188.8986.110.750–0.0000.870–0.971Fig. 2ROC curve of myocardial markers for predicting COPD combined with PHD ## Discussion COPD is a chronic and progressive lung disease characterized by bronchial obstruction, emphysema, excessive mucus secretion, and persistent pulmonary inflammation. Patients may present with symptoms such as difficulty breathing, coughing, and fatigue. As COPD worsens, it may lead to the occurrence of PHD, which is the most common and important complication of COPD and the main cause of acute exacerbation and death in COPD patients [9, 10]. Understanding the influencing factors of COPD combined with PHD and providing personalized intervention in the early stage are beneficial for improving patient prognosis and reducing patient mortality. The results of this study found that PAP and ICOSL were independent risk factors affecting the occurrence of COPD combined with PHD. Research has found that almost all COPD patients may experience severe elevation of PAP, while around 1% to 4% of COPD patients may experience severe arterial hypertension. PAP may serve as an indicator of the severity of the disease, similar to the significant increase in PAP levels observed in COPD patients with concomitant PHD in this present study [11]. Hypoxemia or hypercapnia in COPD patients may cause significant constriction of hypoxic pulmonary blood vessels and affect lung function, leading to pulmonary arterial hypertension (PAH), right ventricular hypertrophy, and increased risk of PHD [12]. ICOSL, the ligand of inducible costimulatory molecule (ICOS), is mainly expressed on the surface of antigen-presenting cells and endothelial cells, and is the key costimulatory molecule for T cell activation. After binding to ICOS on the surface of T cells, it can specifically activate T cells (especially Th17 cells) and promote the release of IL-6, IL-17, TNF-α, and other proinflammatory factors [13]. In COPD patients, persistent pulmonary inflammation can upregulate the expression of ICOSL, and the high expression of ICOSL can enhance the adhesion of endothelial cells to neutrophils and aggravate the inflammatory injury and remodeling of the pulmonary vessel wall, leading to pulmonary artery contraction and PAP elevation [14]. In this study, the ICOSL level was significantly higher in the combined group than in the uncombined group (*P* < 0.001). Moreover, multivariate analysis showed that it was an independent risk factor (OR = 2.910), suggesting that ICOSL may participate in the occurrence of PHD through the pathway of "inflammation, vascular remodeling, and pulmonary hypertension", which is consistent with the findings of Li et al. [15] in the study of the inflammatory mechanism of COPD. The pathogenesis of COPD combined with PHD is mainly due to the formation of PAH. In addition, COPD patients may experience changes in the pulmonary vascular wall, including vascular spasm and remodeling, leading to restricted airflow and increased PAH. These changes can lead to right ventricular wall hypertrophy, heart chamber enlargement, and even right heart failure. In addition, due to the formation of PAH, the right ventricle needs to bear a higher afterload, leading to right ventricular hypertrophy and dilation, which may ultimately cause right heart failure [16, 17]. The results of this study found that the levels of cTnI, CK-MB, and NT proBNP were significantly elevated in patients with COPD complicated with PHD. Myocardial injury is more common in COPD patients with PHD. Due to obstructed airflow, low oxygen, infection, and other conditions, the patient's right ventricular load increases, leading to inevitable myocardial tissue damage. Patients often exhibit worsening respiratory distress [18]. As a specific marker of myocardial cell injury, the increase of cTnI (1.35 ± 0.54 ng/mL in the combined group) is not only seen in acute events, but also related to the long-term cardiovascular risk of COPD [19]. The increase in NT-proBNP (957.49 ± 75.28 pg/mL in the combined group) directly reflects the increase in right ventricular wall tension, which is consistent with the BNP pathway activation mechanism reported in previous studies in PHD patients [20]. Among them, cTnI is a regulatory protein with myocardial contractility, which could be used to identify myocardial injury earlier and assist in treatment. A study has found that during the acute exacerbation of COPD, cTnI and CK-MB levels are significantly elevated. The levels of cTnI and CK-MB in patients with concomitant hypoxemia were significantly higher than those in patients without concomitant hypoxemia. COPD patients combined with PHD experience increased ventricular muscle contraction and decreased cardiac pumping function, leading to myocardial cell ischemia, hypoxia, necrosis, and loss of myocardial cell integrity, resulting in elevated levels of cTnI [21]. CK-MB, as an indicator for the diagnosis of myocardial diseases, mainly exists in the cytoplasm and is a sensitive and specific indicator for myocardial damage. Research has found that cTnI and CK-MB can appear within 3–4 h after myocardial injury. Besides, combined detection is beneficial for early diagnosis of acute myocardial infarction [22]. In addition, the serum CK-MB level significantly increased during the acute exacerbation of COPD. The reason might be that the varying degrees of myocardial damage in patients promoted CK-MB to be released from myocardial cells into the bloodstream, resulting in an increase in serum CK-MB levels [23]. NT-proBNP is a precursor of B-type natriuretic peptide (BNP), mainly synthesized and secreted in ventricular myocytes. When the ventricular wall tension increases or the ventricular volume expands, the secretion of BNP and NT-proBNP increases, and therefore they could be used as indicators for diagnosing heart failure [24]. A study has found significantly elevated levels of NT-proBNP and cTnI in COPD patients with concomitant PAH, which can serve as biomarkers for evaluating COPD patients with concomitant PAH or cardiac dysfunction [25]. Pearson correlation analysis further confirmed that cTnI, CK-MB, and NT-proBNP were closely related to cardiac function indicators. All three were negatively correlated with LVEF, which reflected the systolic function of the right heart, and positively correlated with PAP, the core indicator of pulmonary arterial hypertension. This indicated that the levels of these markers could indirectly reflect the degree of cardiac function impairment. Moreover, the comparison of different GOLD grades showed that even without PHD, the levels of cTnI, CK-MB, and NT-proBNP in patients with GOLD grades 3–4 were still significantly higher than those of GOLD grades 1–2, suggesting that the progression of COPD itself might induce subclinical myocardial injury. This provided potential clues for the early identification of PHD. Multivariate logistic regression analysis confirmed that the three were independent risk factors for COPD combined with PHD (OR = 2.638, 2.155, and 2.266, respectively, all *P* < 0.001). The profound implications of this result are as as a highly specific marker of cardiomyocyte injury, the increase of cTnI not only reflects the chronic right ventricular myocardial injury caused by hypoxia and pulmonary hypertension in COPD patients with PHD, but also suggests that subclinical cardiomyocyte injury may be involved in the pathological process of PHD even in the absence of acute coronary events [18]. CK-MB is a sensitive index of myocardial injury. The independent risk in this study suggests that abnormal myocardial metabolism mediated by long-term hypoxia and inflammation in COPD patients may lead to persistent myocardial enzyme release, rather than a transient increase in the acute exacerbation stage, providing new clues for understanding the potential mechanism of myocardial injury in PHD [26]. By reflecting the increased right ventricular wall tension, NT-proBNP is directly related to the core pathology of PHD, which is right heart overload caused by pulmonary hypertension [27]. This study further confirmed that it can be used as an independent predictor of PHD in the stable stage of COPD. In addition, the AUC of cTnI, CK-MB, and NT-proBNP combined to predict the occurrence of PHD in COPD patients was 0.921, and the specificity and sensitivity were 88.89% and 86.11%, respectively. It is suggested that combined detection has certain clinical reference value in the identification of COPD with PHD, but it should be judged comprehensively in combination with clinical symptoms and imaging examinations. This result is more advantageous compared with the clinical risk model (AUC = 0.85) constructed by Zhou et al. [28], because our study integrates multi-dimensional markers of myocardial injury and inflammatory indicators. In the process of COPD developing into PHD, lung diseases may lead to pulmonary arterial hypertension and right ventricular hypertrophy. Long-term pressure and load increase may also cause damage to myocardial cells, thereby releasing cTnI and CK-MB [29]. Therefore, the elevation of cTnI and CK-MB may reflect the degree of myocardial cell damage in pulmonary heart disease. Related studies suggest that NT-proBNP can exhibit significant changes in different stages and disease progression of COPD. Changing levels of NT-proBNP may indicate the degree of pulmonary hypoxia, inflammation, and cardiovascular stress in COPD patients. Thus, detecting NT-proBNP levels may help with clinical decision-making [30]. When COPD combined with PHD occurs, myocardial cells are continuously stretched, causing an increase in myocardial tension, and a large amount of pro-BNP is cleaved, forming NT-proBNP and BNP. In addition, the pulmonary capillaries of patients with combined PHD are damaged, the glomerular filtration rate is reduced, jointly causing increased serum NT-proBNP levels [31]. Therefore, by jointly detecting myocardial markers, the condition of COPD combined with PHD can be evaluated more comprehensively. In addition, the AUC of combined detection of cTnI, CK-MB, and NT-proBNP in this study was 0.921. Compared with echocardiography commonly used in clinic, the AUC of echocardiography in the diagnosis of PHD is mostly between 0.85 and 0.90 [32]. The combined detection in this study has the same performance but has the advantages of simple operation and rapid results, especially suitable for primary hospitals or those without ultrasound equipment. Moreover, the evaluation of pulmonary artery pressure by echocardiography depends on the experience of the operator, while the detection of myocardial markers is more objective, and the combination of the two can further improve the diagnostic accuracy [33]. ## Conclusion In general, PAP, ICOSL, cTnI, CK-MB, and NT-proBNP are all independent risk factors affecting the occurrence of COPD complicated with PHD. The combined detection of cTnI, CK-MB, and NT-proBNP had certain diagnostic reference value for COPD with concomitant PHD. Monitoring the levels of these myocardial markers can provide clues for early identification of patients with COPD concomitant PHD and assist clinical development of targeted intervention programs. This study has the following limitations. (1) This study was a single-center retrospective study, and all the patients were from the same medical institution. Selection bias (such as disease severity and homogeneity of treatment regimens) may exist, and the results should be cautiously extrapolated to other populations. (2) The sample size (117 cases) was relatively limited, especially in the combined PHD group (only 45 cases), which may affect the statistical power, such as the wide confidence intervals of OR values of some variables in the multivariate logistic regression. (3) There is no clear distinction between acute exacerbation and stable phase of COPD patients. The levels of cardiac markers (such as NT-proBNP and cTnI) may be affected by the disease stage, which may have a confounding effect on the results. (4) Failure to include other potential influencing factors (e.g., smoking duration, dynamic changes in lung function class, and concomitant treatment for other cardiovascular diseases) may underestimate or overestimate the effect of the target measures. (5) Long-term follow-up has not been conducted to verify the predictive value of myocardial markers for the prognosis of COPD patients with PHD, and the timeliness of their clinical application still needs to be explored. In the future, multi-center, prospective cohort studies should be carried out to expand the sample size and refine the disease stage, and the clinical value of combined detection should be further verified combined with imaging indicators such as echocardiography. ## Methods ### Ethical approval This study was approved by the Medical Ethics Committee of our hospital (approval JHGF2024013). Written informed consent was signed by the patients or their families. The procedures used in this study adhered to the Declaration of Helsinki. ### Research subjects A retrospective study was conducted on 117 COPD patients treated in our hospital during July 2022 to August 2024. According to whether the patients were combined with PHD, they were divided into a combined group (45 cases) and an uncombined group (72 cases). ### Inclusion and exclusion criteria Inclusion (1) all study subjects met the diagnostic criteria for COPD [34], with patients with concomitant PHD meeting the diagnostic criteria for PHD [35]; (2) the patients had complete clinical data; (3) the patient did not take any medications such as glucocorticoids or bronchodilators in the 2 months prior to participating in the study. Exclusion (1) patients with concomitant hematological or immune system diseases or other malignant tumors; (2) patients with a history of mental illness or abnormal cognitive function; (3) the patient's liver function was classified as Child grade B or above or those with glomerular filtration rate (eGFR) less than 30 mL/min; (4) patients with acute or chronic left ventricular dysfunction; (5) patients with acute coronary syndrome, acute pulmonary embolism, and pulmonary hypertension; (6) patients with combined congenital heart disease and sleep apnea hypopnea syndrome. The research flowchart is shown in Fig. 3.Fig. 3Research flowchart ### Collection of clinical data All clinical data of patients were collected, including gender, smoking history, alcohol consumption history, hypertension history, age, body mass index (BMI), disease duration, and Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification. ### Detection of laboratory and functional indicators White blood cell blood from the median elbow vein of the patient on an empty stomach for more than 8 h was collected. Serum and blood cells were separated using a centrifuge at a speed of 4000 r/min for 20 min. The upper serum was taken and stored at low temperature. A blood analyzer (Sichuan Coptic Technology Co., Ltd., HemoFAXS) was used to detect WBC levels as follows. The collected whole blood sample was mixed with specific reagents, including diluents, hemolytic agents, etc. In a blood analyzer, white blood cells were separated from other blood cells through sheath dilution and flow cytometry techniques. The blood analyzer automatically calculated the number and classification of white blood cells. Echocardiographic (ECG) an ECG (Philips Medical Equipment Co., Ltd., SONOS 7500) was adopted to measure the levels of left ventricular ejection fraction (LVEF), left atrial transverse diameter (LAD), and pulmonary artery pressure (PAP) levels. LVEF: left ventricular end-diastolic volume (EDV) and end-systolic volume (ESV) are measured. LVEF was calculated according to the formula LVEF = (EDV-ESV)/EDV × 100%. Measurement of LAD: from the midpoint of the interventricular septum to the left atrial sidewall in the parasternal long-axis view of the left ventricle was measured, ensuring that the measurement line was perpendicular to the left atrial longitudinal axis. Appropriate timing should be selected during measurement to ensure clear images and accurate measurements. Measurement of PAP: tricuspid regurgitation velocity (TRV) was measured through ECG and pulmonary artery systolic pressure (sPAP) was estimated by combining right atrial pressure (RAP). The formula sPAP = 4 × TRV ^2^ + RAP. The Doppler spectrum of pulmonary valve regurgitation was obtained using the parasternal short-axis pulmonary artery long-axis section to estimate PAP. Pulmonary function index the 1-s forced expiratory volume/forced vital capacity (FEV1/FVC) was measured using a pulmonary function meter (Shanghai Hanfei Medical Equipment Co., Ltd., Vyaire). The patients were kept in a quiet state, avoiding vigorous exercise or emotional excitement. Dentures, glasses, and other items that might affect breathing were removed. The nasal cavity was cleaned to ensure that there were no secretions affecting the measurement results. Measurement of FVC: the patients took a maximum deep breath and then exhaled as quickly as possible until no more gas was exhaled. The total amount of exhaled air was recorded as FVC. Measurement of the FEV1: the patient took another deep breath and tried to exhale quickly within the first second. The amount of air exhaled in the first second was recorded, which was the FEV1. FEV1 was divided by FVC to obtain the FEV1/FVC ratio. Serological indicator fasting cubital venous blood was obtained from all the patients within 24 h after admission (stable COPD, i.e., no signs of acute dyspnea, cough, or expectoration did not worsen within 48 h, and no systemic glucocorticoids or antibiotics were used). A fully automated biochemical analyzer (Beckman Coulter, AU5800) was used to detect levels of inducible co-stimulator ligand (ICOSL), NT-proBNP, CK-MB, and cTnI. The ICOSL reagent kit was purchased from Shanghai Rongweida Industrial Co., Ltd., item 04-1478. The NT-proBNP kit was purchased from Jiangxi Jianglan Pure Biological Reagent Co., Ltd., item JLC-[R13709](R13709). The CK-MB reagent kit was purchased from Shanghai Xuanya Biotechnology Co., Ltd., item XY1128A. The cTnI kit was purchased from Beijing Baiaolaibo Technology Co., Ltd., item [ARB13432](ARB13432). ### Statistical analysis SPSS 24.0 statistical software was used to analyze the data. The Shapiro–Wilk test was used to test the normality of measurement data. Measurement data with normal distribution were represented as mean ± SD, and the comparison between groups was analyzed using the independent sample t test. Non-normal distribution data were expressed as median (quartile) [M (Q1, Q3)], and the comparison between groups was performed using the Mann–Whitney *U* test. The comparison of enumeration data (smoking history, alcohol consumption history, hypertension history) between groups in the study was conducted using a *χ*^*2*^ test, expressed as [cases (%)]. Pearson correlation analysis was used to analyze the correlation between myocardial markers and cardiac function indicators. Logistic regression analysis was used to analyze the influencing factors of COPD combined with PHD. ROC curve analysis was adopted to evaluate the diagnostic value of serum myocardial markers. The statistical results indicated that a difference of *P* < 0.05 was statistically significant.