Risk factors in blood for attacks of angina in patients with coronavirus disease 2019 and stable angina : Chinese Medical Journal

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Risk factors in blood for attacks of angina in patients with coronavirus disease 2019 and stable angina

Geng, Song1; Zhou, Donghui1; Wang, Qi1; Wang, Guofeng1; Wei, Wei2; Yu, Tao3; Duan, Zhiying1; Liu, Jing1; Yu, Fei1; Jin, Yuanzhe1

Editor(s): Wei, Peifang; Pan, Xiangxiang

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Chinese Medical Journal ():10.1097/CM9.0000000000002334, May 03, 2023. | DOI: 10.1097/CM9.0000000000002334
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To the Editor: Patients with coronary heart disease (CHD) complicated by coronavirus disease 2019 (COVID-19) are at an increased risk of coronary events. Many studies have reported an association between cardiovascular disease and COVID-19. It is also known that patients with COVID-19 have worse outcomes and an increased mortality risk if they have cardiovascular disease.[1] According to a report by the World Health Organization, the estimated COVID-19 mortality rate is about 3.4% overall; however, in patients with cardiovascular disease, this figure increases to 10.5%, which is higher than the death rate in those with underlying diabetes (7.3%) or chronic respiratory diseases (6.3%).[2]

Several components in blood, including platelets and neutrophils, have an important role in ischemic heart disease, and particularly in acute myocardial infarction. White blood cells and their subtypes have been investigated as inflammatory biomarkers of adverse cardiovascular outcomes. COVID-19 infection has a considerable effect on the constituents of blood. In this retrospective observational study, we reviewed our patients with stable angina pectoris (AP) and COVID-19 treated between February 2020 and April 2020 with the aims of understanding better the relationship between these two conditions and providing guidance for clinical practice.

This study was approved by the Research Ethics Committee of the Fourth Affiliated Hospital of China Medical University (No. EC-2022-KS-024). The Ethics Committee of the Fourth Affiliated Hospital of China Medical University approved a waiver of informed consent.

Data were collected for 83 patients with stable AP and COVID-19 who were treated for COVID-19 at Wuhan Thunder God Mountain Hospital in February and March 2020 and for 49 patients with stable AP treated at Shenyang Fourth People's Hospital in March and April 2020. Information was collected including age, sex, clinical symptoms, complications, electrocardiographic findings, blood biochemistry, neutrophil count, lymphocyte count, platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), mean platelet volume (MPV), mean platelet volume-to-lymphocyte ratio (MPVLR), myocardial enzymes, and muscle calcium.

COVID-19 was diagnosed in all 83 cases at Wuhan Thunder God Mountain Hospital by a positive result of the reverse transcriptase polymerase chain reaction assay, and a computed tomography scan of the chest. All patients were classified as common type (83 cases, 100%) according to the Diagnosis and Treatment Protocol for Novel Coronavirus Pneumonia (Version 6).[3] Angina attack was identified by constricting discomfort in the chest or neck, shoulders, jaw or arms; precipitated by physical exertion; and relieved by rest or nitrates within about 5 to 10 min.[4]

A total of 83 patients in the COVID-19 + stable AP group were divided into a COVID-AP event (attacks of angina) group (n = 50) and a COVID-no AP event group (n = 33). Symptoms of attacks of angina in the COVID-AP event group consisted of chest pain (n = 25, 50.0%), chest tightness (n = 12, 24.0%), shortness of breath (n = 9, 18.0%) and toothache (n = 4, 8.0%). Thirty-one (62.0%) patients in this group had electrocardiographic changes. A total of 49 patients with stable AP alone served as a control group.

Blood components that were confirmed to be distributed in an approximately normal manner by the Kolmogorov-Smirnov test are expressed as the mean and standard deviation; those that were not are expressed as the median (interquartile range). Categorical variables, including sex, smoking status, comorbidities such as hypertension, diabetes mellitus, and ischemic stroke are shown as numbers and percentages. Differences in blood components and background characteristics were compared between groups using the Student's t-test, Fisher's exact test, chi-squared test, or Mann-Whithney U test as appropriate. Odds ratios (ORs) and 95% confidence intervals (CIs) for blood components and other risk factors for the attacks of angina in patients with stable AP complicated by COVID-19 were estimated using univariable and unconditional multivariable logistic regression analyses. All statistical analyses were performed using SPSS for Windows software (version 19.0; IBM Corp., Armonk, NY, USA). All tests were two-sided, and a P value of <0.05 was considered statistically significant.

There was no significant difference in patient sex (51.1% vs. 51.8%, P = 0.931) or mean age (65.57 ± 7.48 years vs. 64.87 ± 7.13 years, P = 0.585) between the control group and the COVID-19 + stable AP group; moreover, there was no significant between-group difference in the rate of smoking, hypertension, diabetes, or ischemic stroke (all P > 0.05, Table 1). Similarly, there was no statistically significant difference in sex or age distribution or in smoking history, hypertension, diabetes, or ischemic stroke between the COVID-AP event group and the COVID-no AP event group (all P > 0.05, Table 1).

Table 1 - Demographic and clinical data of patients with COVID-19 and stable angina (with or without attacks of angina) and a control group with stable angina alone.
Characteristics Stable AP (control) group (n = 49) COVID-19 + stable AP group (n = 83) P-value COVID-19 + stable AP with attacks of angina (n = 50) COVID-19 + stable AP without attacks of angina (n = 33) P-value
Age (years) 65.57 ± 7.48 64.87 ± 7.13 0.585 66.86 ± 6.66 61.67 ± 6.82 0.471
Sex 0.931 0.396
 Female 24 (48.9) 40 (48.2) 26 (52.0) 14 (42.4)
 Male 25 (51.1) 43 (51.8) 24 (48.0) 19 (57.6)
Smoking history 0.434 0.961
 No 30 (61.2) 45 (54.2) 27 (54.0) 18 (54.5)
 Yes 19 (38.8) 38 (45.8) 23 (46.0) 15 (45.5)
Hypertension 0.675 0.563
 No 29 (59.2) 50 (60.2) 33 (66.0) 17 (51.5)
 Yes 20 (40.8) 33 (39.8) 17 (34.0) 16 (48.5)
Diabetes mellitus 0.790 0.894
 No 38 (77.5) 66 (79.5) 40 (80.0) 26 (78.8)
 Yes 11 (22.5) 17 (20.5) 10 (20.0) 7 (21.2)
Ischemic stroke 0.733 0.862
 No 44 (89.8) 76 (91.6) 46 (92.0) 30 (90.9)
 Yes 5 (10.2) 7 (8.4) 4 (8.0) 3 (9.1)
Neutrophil count (×109/L) 3.91 ± 1.02 5.80 ± 1.58 0.041 6.47 ± 1.41 4.58 ± 1.52 0.002
Platelet count (×109/L) 196.34 ± 42.37 192.30 ± 31.96 0.412 201.16 ± 28.74 175.55 ± 31.47 0.006
MPV (fL) 8.12 ± 1.65 11.50 ± 2.12 0.034 11.88 ± 1.64 8.77 ± 0.79 0.003
Lymphocyte count (×109/L) 1.91 ± 0.46 1.14 ± 0.39 0.047 1.05 ± 0.40 0.054
NLR 8.83 (5.79, 14.90) 10.14 (6.08, 14.51) 0.473 11.85 (7.50, 15.54) 7.42 (5.45, 10.33) 0.013
PLR 169.35 (104.25, 196.9) 182.03 (116.88, 266.77) 0.021 220.00 (147.01, 283.33) 127.42 (97.87, 187.73) 0.001
MPVLR 6.48 (4.63, 13.96) 9.84 (5.79, 14.09) 0.772 11.69 (7.42, 15.57) 6.59 (4.97, 10.11) 0.003
Continuous data are presented as mean and standard deviation or median (Q1, Q3) and categorical data as the number (percentage). AP: Angina pectoris; COVID-19: Coronavirus disease 2019; MPV: Mean platelet volume; MPVLR: Mean platelet volume-to-lymphocyte ratio; NLR: Neutrophil-to-lymphocyte ratio; PLR: Platelet-to-lymphocyte ratio.

Compared with the control group, the COVID-19 + stable AP group had a significantly higher neutrophil count (P= 0.041), MPV (P= 0.034), lymphocyte count (P = 0.047) and PLR (P= 0.021). However, there was no statistically significant between-group difference in the platelet count, lymphocyte count, NLR, or MPVLR (all P > 0.05, Table 1).

The platelet count, neutrophil count, MPV, NLR, PLR, and MPVLR were significantly higher in the COVID-AP event group than in the COVID-no AP event group (P = 0.006, 0.002, 0.003, 0.013, 0.001, and 0.003, respectively, Table 1). The lymphocyte count was comparable between the COVID-AP event and COVID-19 no AP event group (P = 0.054).

Univariable logistic regression analysis showed that the risk factors for attacks of angina in patients with COVID-19 and stable AP were neutrophil count (OR 3.248, 95% CI: 1.859–5.678, P < 0.001), lymphocyte count (OR 0.241, 95% CI: 0.073–0.798, P = 0.020), platelet count (OR: 1.013, 95% CI: 1.000–1.026, P = 0.042), PLR (OR 1.014, 95% CI: 1.005–1.022, P = 0.026), MPVLR (OR 1.212, 95% CI: 1.078–1.362, P = 0.001), NLR (OR 1.196, 95% CI: 1.063–1.346, P = 0.003), and MPV (OR 2.547, 95% CI: 1.516–4.282, P = 0.033), but not smoking (OR 0.892, 95% CI: 0.370–2.150, P = 0.800), diabetes mellitus (OR 1.011, 95% CI: 0.342–2.987, P = 0.984), hypertension (OR 1.185, 95 CI: 0.492–2.856, P = 0.705), or lymphocyte count, OR 0.241, 95% CI: 0.073–0.798, P = 0.020. Multivariable logistic regression analysis identified risk factors for the attacks of angina in patients with COVID-19 and stable to AP neutrophil count (OR 2.501, 95% CI: 1.322–4.733, P = 0.008), and MPV (OR 3.077, 95% CI: 1.094–8.658, P = 0.033), but not smoking (OR 0.222, 95% CI: 0.020–2.443, P = 0.219), hypertension (OR 3.886, 95% CI: 0.361–41.860, P = 0.263), diabetes mellitus (OR 1.138, 95% CI: 0.288–4.491, P = 0.854), or any other blood parameter (lymphocyte count, OR 0.262, 95% CI: 0.018–3.899, P = 0.331; platelet count, OR 0.991, 95% CI: 0.961–1.022, P = 0.564; NLR, OR 0.489, 95% CI: 0.158–1.511, P = 0.214; PLR, OR 1.004, 95% CI: 0.975–1.034, P = 0.792; MPVLR, OR 1.704, 95% CI: 0.722–4.017, P = 0.224).

Our statistical analysis revealed significant differences in the neutrophil count and MPV between the control group and the COVID + stable AP group and between the COVID-AP event group and COVID-no AP event group. Therefore, for patients with COVID-19 and stable AP, components of blood should be investigated to identify risk factors for attacks of angina.

Patients with COVID-19 and stable AP have a high mortality risk, and there may be a pathogenic relationship between COVID-19 and CHD, which could involve hematological abnormalities. COVID-19 infection alters inflammatory marker levels in the blood, which can cause an excessive immune inflammatory response, leading to many hematological abnormalities, including lymphopenia, neutrophilia, and an increased platelet count. These changes can be used to evaluate the severity of infectious diseases.[5] At present, an increasing number of studies found that components of blood, including neutrophils, MPV, and the NLR, are related to CHD.[6] In this study, the neutrophil count and MPV were higher in patients with COVID-19 than in those without COVID-19 and also higher in patients with COVID-19 who had attacks of angina than in their counterparts who did not have. Therefore, the immune response and inflammation caused by COVID-19 may be related to the occurrence of coronary ischemia.

Logistic regression analysis showed that the relative risk of neutrophil count and MPV for attacks of angina was >1, which suggests that these two parameters were risk factors for acute ischemia in patients with COVID-19 and stable AP. An association of the neutrophil count and MPV with AP has been reported and may be due to the significant increase in neutrophil elastase and vascular endothelial injury caused by neutrophil extracellular traps, thrombosis, increased platelet adhesion, and a decreased coronary collateral circulation.[7,8] Moreover, the coronary collateral circulation is negatively correlated with MPV, indicating that the increase in MPV may contribute to coronary ischemia attack.[9] It has been reported in the literature that systemic inflammation or the cytokine storm caused by COVID-19 can induce coronary vasospasm and coronary microthrombosis, which are followed by AP.[1] It seems probable that COVID-19 and stable AP are linked via abnormalities in the components of blood. However, this is only one possibility, and there are still many unknown reasons to be identified.

The findings of this study suggest that a high neutrophil count and a high MPV increase the risk of attacks of angina in patients with stable AP who develop COVID-19.


We thank Liwen Bianji (Edanz) (www.liwenbianji.cn) for editing the English text of a draft of this manuscript.


This study was partially supported by a grant from the COVID-19 Foundation of China Medical University (No. 1210120011).

Conflicts of interest



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