https://orcid.org/0000-0003-3296-8705
Figures
Abstract
Background
Coronary microvascular dysfunction (CMD) contributes to myocardial ischemia in patients both without obstructive coronary artery disease (e.g., MINOCA/INOCA) and in those with co-existing epicardial stenosis. While its etiology includes structural and functional causes. hematologic parameters have been linked to cardiovascular outcomes. However, the relationship between red blood cell (RBC) markers and microvascular resistance remains poorly characterized. We aim to evaluate whether RBC parameters are correlated with the angiography-derived index of microcirculatory resistance (angio-IMR).
Methods
This retrospective study evaluated the association between red blood cell (RBC) parameters and angio-IMR in patients with intermediate coronary artery disease (30%−70% stenosis). Data were analyzed from 604 patients, comprising 733 lesions; red blood cell parameters were obtained during hospitalization prior to angiography. Coronary microcirculatory resistance was derived using the AngioPlus mQFR system. Multivariable linear regression models adjusted for confounders. Subgroup analyses assessed effect modification by diabetes status, and sensitivity analyses excluded hematocrit outliers, and analyses stratified by vessel (left anterior descending (LAD), left circumflex (LCx), right coronary artery (RCA)).
Results
Higher RBC, Hct and Hgb were independently associated with elevated angio-IMR after full adjustment (RBC: β = 0.182, P < 0.001; Hct: β = 0.019, P < 0.001; Hgb: β = 0.006, P < 0.001). Results remained robust after excluding Hct outliers (β = 0.020, P < 0.001) and consistent across diabetic (P = 0.007) and non-diabetic subgroups (P = 0.012). The association was significant in non-LAD vessels (Hct: β = 0.022, P < 0.001) but not in LAD lesions (Hct: β = 0.008, P = 0.357).
Conclusion
Elevated RBC parameters are independently associated with increased microcirculatory resistance, particularly in non-LAD vessels. These findings suggest that RBC parameters may serve as clinically relevant markers of microvascular dysfunction, warranting further investigation into their prognostic and therapeutic implications.
Citation: AlQazzaz A, Lu Y, Bao JY, Mintz GS, Feng J, Zhang Y, et al. (2026) A hemorheological perspective on coronary microvascular dysfunction: Association of erythrocyte parameters with angiography-derived coronary microcirculatory resistance. PLoS One 21(3): e0345562. https://doi.org/10.1371/journal.pone.0345562
Editor: Ennio Polilli, Pescara General Hospital, ITALY
Received: November 6, 2025; Accepted: March 8, 2026; Published: March 25, 2026
Copyright: © 2026 AlQazzaz et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The de-identified data are within the manuscript and its supporting information files.
Funding: This work was supported by the National Natural Science Foundation of China under grant [82474212]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors declare no conflicts of interest related to this work.
Abbreviations: CMD, coronary microvascular dysfunction; Angio-IMR, angiography-derived index of microcirculatory resistance; IMR, index of microcirculatory resistance; QFR, quantitative flow ratio; mQFR, monoplane quantitative flow ratio; RBC, red blood cells count; Hct, hematocrit; Hgb, hemoglobin; CBC, complete blood count; MCV, mean corpuscular volume; MCH, mean corpuscular hemoglobin; MCHC, mean corpuscular hemoglobin concentration; RDW CV, red cell distribution width - coefficient of variation; RDW SD, red cell distribution width - standard deviation; PLT, platelets; PDW, platelet distribution width; WBC, white blood cells; DS, diameter stenosis; LAD, left anterior descending; LCx, left circumflex; RCA, right coronary artery.
Introduction
Coronary microvascular dysfunction (CMD) is a complex pathophysiological condition that can lead to significant clinical consequences including myocardial infarction with non-obstructive coronary arteries (MINOCA) [1] and ischemia with non-obstructive coronary arteries (INOCA) [2] as well as in patients with obstructed coronary arteries. The underlying etiology is multifactorial and can be broadly categorized into structural and functional abnormalities [3,4].
Structural causes include lumen obstruction, perivascular fibrosis, microvascular invasion and remodeling [5], platelet activation [6], or microembolization of thrombotic material from the proximal coronary artery [7], as well as some conditions such as left ventricular hypertrophy which may elevate intramyocardial pressure leading to increased resistance to blood flow [8]. Functional contributors to CMD include impaired vasomotor responses, principally endothelial dysfunction in the coronary microcirculation leading to impaired flow-mediated dilation [9,10], as well as pathological vasoconstriction manifesting as microvascular spasm [11].
CMD has been associated with multiple risk factors, including chronic inflammatory diseases [12] such as systemic lupus erythematosus (SLE) and rheumatoid arthritis [13], as well as traditional cardiovascular risk factors (advanced age, hypertension, dyslipidemia, diabetes mellitus, and smoking) [14–17]. However, as demonstrated by the WISE study, these established factors account for less than 20% of the observed variability in coronary microvascular reactivity, as measured by coronary flow velocity reserve response to intracoronary adenosine (CFVR Ado) among women with suspected ischemia [18]. Given these limitations we investigated novel hematologic factors that may contribute to microvascular impairment.
Previous investigations have established associations between erythrocyte parameters and cardiovascular outcomes. The landmark Finnish cohort study by Kunnas et al. (2009) first demonstrated this relationship [19], with subsequent studies confirming significant correlations between hematocrit levels and cardiac morbidity [20–22] as well as hemoglobin concentrations and cardiovascular health [23–25], These findings highlight the critical need to explore the association between blood rheology markers and microvascular dysfunction—an area that remains understudied.
To investigate this relationship, angiography-derived microcirculatory resistance (angio-IMR) was selected for this study based on its validated correlation with invasive wire-based index of microcirculatory resistance (IMR) measurements [26–28]. This approach offers significant clinical advantages, including being less invasive, more cost-effective, and technically simpler to perform while maintaining comparable diagnostic accuracy [29–31] even when based on a single angiographic view [32]. Furthermore, angio-IMR provides prognostic value for long-term outcomes and microvascular obstruction, as demonstrated in previous studies [33–36].
Therefore, we sought to determine the association between erythrocyte parameters and angiography-derived microcirculatory resistance in a cohort of patients with intermediate coronary stenosis.
Methods
Study design and population
This retrospective cohort study evaluated the association between red blood cell (RBC) parameters and Angio-IMR in patients with coronary artery disease (CAD). Data were obtained during (5 June 2024–10 December 2024) from the First Affiliated Hospital of Xi’an Jiaotong University (Xi’an, China) database, comprising 733 lesions (10 May 2023–30 June 2023) initially collected for a quantitative flow ratio (QFR) grey-zone study. All coronary angiograms were performed in an elective setting for the diagnostic evaluation of stable ischemic symptoms or suspected coronary artery disease.
Inclusion criteria comprised: (1) patients meeting AngioPlus standard criteria for adequate monoplane QFR (mQFR) analysis (optimal contrast filling and minimal vessel overlap in a single angiographic projection) and (2) intermediate stenosis (30–70% diameter stenosis) in at least one major epicardial vessel. Exclusion criteria were: (1) insufficient angiographic quality for mQFR/IMR analysis (e.g., poor contrast opacification, foreshortening), (2) stented target vessels (to avoid flow artifacts), (3) chronic total occlusion (CTO) or retrograde collateral filling, (4) ostial left main or right coronary artery lesions (due to mQFR technical limitations), and (5) prior coronary artery bypass grafting (CABG) involving the target vessel.
Hematological variables included Red Blood Cells count (RBC), Hematocrit (Hct) and Hemoglobin (Hgb). extracted from complete blood count (CBC) results obtained after admission and before angiography. Other blood parameters included Mean Corpuscular Volume (MCV), Mean Corpuscular Hemoglobin (MCH), Mean Corpuscular Hemoglobin Concentration (MCHC), Red Cell Distribution Width – Coefficient of Variation (RDW CV), Red Cell Distribution Width – Standard Deviation (RDW SD), Platelets (PLT), Platelet Distribution Width (PDW), White Blood Cells (WBC). Clinical demographics (included age, sex, BMI), comorbidities (hypertension, diabetes mellitus, dyslipidemia), medications (prior statins), and angiographic characteristics (stenosis severity, lesion length, vessel location). To ensure the validity of both the measured hematologic parameters and the coronary microcirculatory assessment, no patient in the cohort received a packed red blood cell transfusion in the 48 hours preceding either the blood sample collection for complete blood count analysis or the index coronary angiography.
Complete blood count analysis was performed using a Sysmex XN-9000 automated hematology analyzer (Sysmex Corporation, Kobe, Japan), and Angio-IMR was calculated with the AngioPlus software (AngioPlus Galley 2.1, Pulse Medical, Shanghai, China). A single angiographic projection with minimal foreshortening and optimal contrast filling was selected for computational fluid dynamics (CFD)-based simulation of hyperemic flow. IMR was calculated as:
where Pd = distal pressure and Tmn = mean transit time under simulated hyperemia. mQFR was co-registered as a secondary measure of functional stenosis severity.
Statistical analysis
The primary analysis employed multiple linear regression models with sequential adjustment for potential confounders. Model 1 assessed the association between RBC parameters and angiography-derived IMR, adjusted for other blood parameters. Model 2 further adjusted for demographic factors (age, sex, BMI), while Model 3 incorporated comorbidities (diabetes mellitus, hypertension, hypercholesterolemia and prior statins). The final fully adjusted model (Model 4) included angiographic severity (diameter stenosis (DS), lesion length) in addition to all previous covariates.
Secondary analyses were conducted to explore potential effect modification and robustness of the findings. Given the known impact of diabetes mellitus on RBC deformability, subgroup analysis stratified by diabetes status was performed. Sensitivity analysis excluded extreme Hct outliers (<30% or >50%) to mitigate potential hemodilution or polycythemia-related bias. To account for hemodynamic and anatomical differences between coronary vessels, sensitivity analyses were conducted by stratifying lesions into LAD versus non-LAD (LCx + RCA) subsets, with Model 4 replicated in each group. Additionally, vessel-specific analyses were performed by applying Model 4 separately to LAD, LCx, and RCA lesions to evaluate potential vessel-dependent associations.
Statistical significance was defined as a two-tailed P < 0.05. The normality of continuous variables was assessed using the Shapiro-Wilk test. For multivariate models, multicollinearity was assessed using variance inflation factors (VIF < 5 considered acceptable). Leukocyte subtypes were examined in exploratory analyses but were not included in the final models due to non-significant associations with the outcome and high multicollinearity with total white blood cell count (VIF > 10) (S2 Table). Model assumptions were verified through residual diagnostics. Sensitivity analyses excluding outliers were performed to ensure the stability of the results. For the IMR assessment, mQFR was selected due to its validated accuracy in deriving IMR from a single angiographic projection, reducing reliance on multi-angle acquisitions while maintaining diagnostic precision [32]. Lesions with suboptimal contrast timing or vessel overlap were excluded to ensure analytical reliability.
Analyses were performed using SPSS v27 (IBM, Armonk, NY). Continuous variables were reported as mean ± SD (normally distributed); categorical variables as frequencies (%).
This study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of The First Affiliated Hospital of Xi’an Jiaotong University. The requirement for informed consent was waived by the ethics committee due to the retrospective nature of the study.
Results
Population characteristics
The study included 733 lesions from 604 patients with CAD (age 64.5 ± 10.4 years; 70.9% male) (Table 1). Comorbidities were prevalent, with hypertension (63.1%), hypercholesterolemia (38.9%), and diabetes mellitus (32.9%) frequently observed. Hematologic parameters were within normal ranges (Hct: 41.60 ± 4.97%; Hgb: 135.88 ± 17.21 g/L; RBC: 4.39 ± 0.56 × 10¹²/L). Angiographic data revealed moderate stenosis severity (DS%: 45.36 ± 7.63) and lesion length of 29.2 ± 15.9 mm.
Stratification by IMR tertiles
Patients were stratified into low (<2.07), medium (2.07–2.6), and high (>2.6) IMR tertiles (Table 2). The high IMR group exhibited significantly higher RBC parameters (RBC: 4.48 ± 0.53 vs. 4.30 ± 0.58, P = 0.002; Hct: 42.64 ± 4.51 vs. 40.55 ± 5.25, P < 0.001; Hgb: 139.7 ± 15.7 vs. 131.8 ± 18.1 g/L, P < 0.001) compared to the low IMR group. Male sex was more prevalent in the high IMR group (76.3% vs. 66%, P = 0.030), while lesion length was inversely associated with IMR (33.84 ± 16.59 mm in low IMR vs. 25.24 ± 14.50 mm in high IMR, P < 0.001).
Unadjusted analysis
Scatter plot analyses revealed significant positive correlations between simulated hyperemic MR and all measured RBC parameters. Hemoglobin demonstrated the strongest association (Hgb; r = 0.172, P < 0.001), followed by hematocrit (Hct; r = 0.157, P < 0.001) and red blood cell count (RBC; r = 0.119, P < 0.001) (Fig 1). The linear relationships were consistently maintained across the physiological ranges of each parameter, with no evidence of threshold effects. These unadjusted associations suggested that higher erythrocyte mass and hemoglobin content were proportionally associated with increased coronary microcirculatory resistance, independent of other clinical or angiographic factors.
Primary regression analysis
Unadjusted analyses demonstrated significant associations between simulated hyperemic MR and RBC parameters (RBC: β = 0.123, P = 0.001; Hct: β = 0.018, P < 0.001; Hgb: β = 0.006, P < 0.001). These associations remained highly significant (P < 0.001 for all) through sequential multivariate adjustment: first for other blood parameters (Model 1), then additionally for demographics (Model 2), comorbidities (Model 3), and finally angiographic severity (Model 4). In the fully adjusted model, IMR maintained strong independent associations with RBC parameters (RBC: β = 0.182, 95% CI 0.090–0.274; Hct: β = 0.019, 0.009–0.028; Hgb: β = 0.006, 0.003–0.009; all P < 0.001) (Tables 3 and 4).The stability of effect sizes and persistent statistical significance across all models indicated these hematologic measures were robust independent predictors of coronary microcirculatory resistance, unaffected by potential clinical or angiographic confounders.
Due to multicollinearity, principal component analysis (PCA) was performed for RBC parameters (Hb, Hct, MCV, RDW) and hematologic covariates (WBC, PLT) using Varimax rotation (eigenvalue >1). All retained variables had VIF < 3 in final models, confirming acceptable collinearity.
Subgroup and sensitivity analyses
- Diabetes Status: The Hct-IMR association remained significant in both diabetic (β = 0.021, P = 0.007) and non-diabetic subgroups (β = 0.017, P = 0.012), suggesting robustness across metabolic states.
- Sensitivity Analysis: Exclusion of extreme Hct outliers (30–50%) did not attenuate the Hct-IMR relationship (β = 0.020, P < 0.001).
- Vessel-Specific Effects: Initial comparison between LAD (LAD n = 288) and non-LAD (LCx n = 250, RCA n = 195) vessels revealed divergent associations for Hct, with significant correlations in non-LAD territories (β = 0.022, P < 0.001) but not in LAD lesions (β = 0.008, P = 0.357). Subsequent vessel-specific analyses incorporating all RBC parameters demonstrated this pattern held consistently across measures. The LCx showed the strongest associations (Hct: β = 0.021, P = 0.010; Hgb: β = 0.007, P = 0.007; RBC: β = 0.193, P = 0.014), followed by the RCA (Hct: β = 0.019, P = 0.031; Hgb: β = 0.006, P = 0.017; RBC: β = 0.188, P = 0.023), while LAD lesions showed no significant relationships for any parameter (Table 5). This graduated response pattern suggests microcirculatory resistance in non-anterior territories may be particularly sensitive to hematologic determinants, with the LCx demonstrating the greatest dependence on RBC parameters.
Discussion
Our study investigated the associated between the IMR and RBC parameters, demonstrating that higher levels of all of the primary RBC parameters (RBC count, Hct and Hgb) are independently associated with higher IMR even after adjusting for confounders that might be considered as conventional risk factors for microvascular dysfunction. The stability of our results after sequential adjustments for potential confounders, combined with the consistency across all primary RBC parameters, plays a key role in reinforcing the independent impact of RBC parameters on microcirculatory resistance.
Concordance with previous studies
Recent literature has increasingly highlighted the association between RBC parameters and cardiovascular disease, particularly following the landmark TAMRISK study [19], which demonstrated in its 28-year follow-up that borderline polycythemia was linked to higher coronary heart disease (CHD) mortality. Subsequent studies have further explored this relationship, showing that elevated Hct and Hgb levels correlate with acute myocardial infarction (AMI) mortality in women [37], as well as MI risk and CHD mortality in men [19,20]. Additionally, a U-shaped association has been reported between these RBC parameters and adverse outcomes in CHD and heart failure [21–24,38,39]. Case reports have also documented correlations between increased RBC mass in polycythemia vera and conditions such as MI, heart failure [40], ST-elevation myocardial infarction (STEMI) [41], and cardiomyopathy [42,43]. Our findings align with and further substantiate this growing body of evidence, reinforcing the role of RBC parameters in microcirculatory dysfunction and cardiovascular pathology.
RBC parameters serve as indirect markers of blood viscosity, which plays a critical role in microcirculatory hemodynamics. Elevated viscosity increases vascular resistance, impairing tissue perfusion—a phenomenon demonstrated in radiographic contrast media studies, where higher-viscosity formulations significantly reduced capillary flow compared to lower-viscosity agents [44]. Massive sludging can be found in diseases that cause erythrocyte aggregates such as diabetes mellitus [45]. The clinical relevance of these mechanisms is underscored by case reports, such as that of an 85-year-old patient with congestive heart failure (CHF) and stroke, in whom elevated blood viscosity correlated with adverse outcomes [46]. Collectively, these observations suggest that RBC-driven increases in viscosity may contribute to microvascular impairment through altered rheology, endothelial shear stress, and oxygen delivery—a pathway consistent with our findings of heightened microcirculatory resistance in patients with elevated RBC parameters.
Vessel-specific heterogeneity
The observed differences in microvascular dysfunction between the LAD, LCx, and RCA likely stem from distinct hemodynamic and anatomical characteristics. The LAD benefits from higher endothelial shear stress, which confers atheroprotective effects, while the LCx exhibits greater molecular viscosity and the RCA demonstrates the highest wall stress [47]. Furthermore, the increased tortuosity typically seen in the RCA and LCx subjects these vessels to greater mechanical strain, elevating flow resistance. This is supported by previous studies showing that tortuous coronary arteries experience reduced perfusion pressure [48], diminished flow rates [49], and decreased blood pressure [50]. Notably, coronary resistance can increase by up to 92% in tortuous segments during exercise [51], and severe tortuosity has been associated with impaired myocardial blood flow reserve [52]. These factors collectively can explain the regional variations in microvascular dysfunction observed in our study.
Implications
The observed association between RBC parameters and impaired microvascular function may have particular relevance for MINOCA/INOCA patients. Our findings suggest that the routine complete blood count, which imposes zero extra cost or procedural burden, could be studied as a first-line tool to help identify patients at heightened risk for coronary microvascular dysfunction. Beyond screening, this mechanistic link—between erythrocyte parameters and microcirculatory resistance—suggests that hemorheology may represent a novel therapeutic axis to explore. In conditions characterized by elevated hematocrit (e.g., polycythemia vera), therapeutic phlebotomy is a standard intervention to reduce viscosity and thrombotic risk. While our study population had hematocrit levels mostly within the normal range, the linear relationship we observed generates a testable hypothesis that therapeutic modulation of hemorheology—or the influence of modifiable lifestyle factors upon it—could improve coronary microvascular function, warranting investigation in prospective interventional trials.
Strengths and limitations
The study’s large cohort of lesions and the consistent associations observed across all primary erythrocyte parameters—even after comprehensive adjustment for confounders—strengthen the validity of our findings. These results align with established evidence linking blood viscosity to microcirculatory impairment and extend prior observations on erythrocyte-related cardiovascular outcomes. Together, these data provide new insights into the relationship between hematologic parameters and microvascular dysfunction, particularly in non-LAD territories.
Our study has several limitations. First, angiography-derived IMR, while validated, is not the invasive wire-based gold standard. Second, hematologic parameters were measured at a single time point, are subject to plasma volume variation, and lack data on specific etiologies (e.g., polycythemia vera, CKD severity) or erythropoietic activity markers. Third, the cohort’s predominantly Asian ethnicity and exclusive focus on intermediate coronary lesions may limit generalizability. Fourth, comorbidities were recorded as present/absent without data on severity, duration, or control. Fifth, while statistically significant and consistent, the observed correlations were modest in magnitude (e.g., Hgb: r = 0.172), congruent with CMD’s multifactorial nature, and should be interpreted as identifying one significant component rather than a dominant driver. Finally, the absence of established clinical cutoff values challenges direct translation into practice.
Future studies integrating a broader panel of hemodynamic, inflammatory, and hematologic markers with serial measurements are warranted to build more comprehensive models and test therapeutic hypotheses.
Conclusion
In this study, red blood cell count, hematocrit, and hemoglobin demonstrated independent positive associations with elevated coronary microcirculatory resistance. These findings suggest that elevated erythrocyte parameters may contribute to the pathogenesis of coronary microvascular dysfunction and represent a potential therapeutic target for improving microcirculatory function.
Impact on daily practice
Our results identify erythrocyte parameters as novel, independent predictors of coronary microcirculatory resistance, offering a hematologic lens for evaluating microvascular dysfunction, particularly in MINOCA/INOCA cases. Routine blood measures like hematocrit and hemoglobin may therefore serve as practical biomarkers to improve risk stratification and enable personalized management. We recommend integrating RBC assessment into standard clinical practice to better identify high-risk individuals and inform potential treatment approaches focused on modulating blood viscosity or flow properties, while also highlighting the need for further research to validate causal mechanisms and assess the efficacy of viscosity-modifying interventions.
Supporting information
S2 Table. Coefficients for Hct model 4 with Leukocyte Subtypes.
https://doi.org/10.1371/journal.pone.0345562.s002
(DOCX)
References
- 1. Taqueti VR, Di Carli MF. Coronary microvascular disease pathogenic mechanisms and therapeutic options. J Am Coll Cardiol. 2018;72:2625–41.
- 2. Aribas E, Roeters van Lennep JE, Elias-Smale SE, Piek JJ, Roos M, Ahmadizar F, et al. Prevalence of microvascular angina among patients with stable symptoms in the absence of obstructive coronary artery disease: a systematic review. Cardiovasc Res. 2022;118(3):763–71. pmid:33677526
- 3. Pruthi S, Siddiqui E, Smilowitz NR. Beyond coronary artery disease. Interv Cardiol Clin. 2023;12:119–29.
- 4. Camici PG, Crea F. Coronary Microvascular Dysfunction. N Engl J Med. 2007;356:830–40.
- 5. Yang Z, Liu Y, Li Z, Feng S, Lin S, Ge Z, et al. Coronary microvascular dysfunction and cardiovascular disease: Pathogenesis, associations and treatment strategies. Biomed Pharmacother. 2023;164:115011. pmid:37321056
- 6. Lanza GA, Andreotti F, Sestito A, Sciahbasi A, Crea F, Maseri A. Platelet aggregability in cardiac syndrome X. Eur Heart J. 2001;22:1924–30.
- 7. Kleinbongard P, Heusch G. A fresh look at coronary microembolization. Nat Rev Cardiol. 2022;19(4):265–80. pmid:34785770
- 8. Cecchi F, Olivotto I, Gistri R, Lorenzoni R, Chiriatti G, Camici PG. Coronary microvascular dysfunction and prognosis in hypertrophic cardiomyopathy. N Engl J Med. 2003;349:1027–35.
- 9. Mills I, Fallon JT, Wrenn D, Sasken H, Gray W, Bier J, et al. Adaptive responses of coronary circulation and myocardium to chronic reduction in perfusion pressure and flow. Am J Physiol. 1994;266(2 Pt 2):H447-57. pmid:8141345
- 10. Egashira K, Inou T, Hirooka Y, Yamada A, Maruoka Y, Kai H, et al. Impaired coronary blood flow response to acetylcholine in patients with coronary risk factors and proximal atherosclerotic lesions. J Clin Invest. 1993;91(1):29–37. pmid:8423226
- 11. Ong P, Athanasiadis A, Borgulya G, Vokshi I, Bastiaenen R, Kubik S, et al. Clinical usefulness, angiographic characteristics, and safety evaluation of intracoronary acetylcholine provocation testing among 921 consecutive white patients with unobstructed coronary arteries. Circulation. 2014;129(17):1723–30. pmid:24573349
- 12. Recio-Mayoral A, Mason JC, Kaski JC, Rubens MB, Harari OA, Camici PG. Chronic inflammation and coronary microvascular dysfunction in patients without risk factors for coronary artery disease. Eur Heart J. 2009;30(15):1837–43. pmid:19502228
- 13. Hirata K, Kadirvelu A, Kinjo M, Sciacca R, Sugioka K, Otsuka R, et al. Altered coronary vasomotor function in young patients with systemic lupus erythematosus. Arthritis Rheum. 2007;56(6):1904–9. pmid:17530717
- 14. Di Carli MF, Charytan D, McMahon GT, Ganz P, Dorbala S, Schelbert HR. Coronary circulatory function in patients with the metabolic syndrome. J Nucl Med. 2011;52(9):1369–77. pmid:21849399
- 15. Dayanikli F, Grambow D, Muzik O, Mosca L, Rubenfire M, Schwaiger M. Early detection of abnormal coronary flow reserve in asymptomatic men at high risk for coronary artery disease using positron emission tomography. Circulation. 1994;90(2):808–17. pmid:8044952
- 16. Laine H, Raitakari OT, Niinikoski H, Pitkänen OP, Iida H, Viikari J, et al. Early impairment of coronary flow reserve in young men with borderline hypertension. J Am Coll Cardiol. 1998;32(1):147–53. pmid:9669263
- 17. Lee B-K, Lim H-S, Fearon WF, Yong AS, Yamada R, Tanaka S, et al. Invasive evaluation of patients with angina in the absence of obstructive coronary artery disease. Circulation. 2015;131(12):1054–60. pmid:25712205
- 18. Wessel TR, Arant CB, McGorray SP, Sharaf BL, Reis SE, Kerensky RA, et al. Coronary microvascular reactivity is only partially predicted by atherosclerosis risk factors or coronary artery disease in women evaluated for suspected ischemia: results from the NHLBI Women’s Ischemia Syndrome Evaluation (WISE). Clin Cardiol. 2007;30(2):69–74. pmid:17326061
- 19. Kunnas T, Solakivi T, Huuskonen K, Kalela A, Renko J, Nikkari ST. Hematocrit and the risk of coronary heart disease mortality in the TAMRISK study, a 28-year follow-up. Prev Med. 2009;49(1):45–7. pmid:19409924
- 20. Toss F, Nordström A, Nordström P. Association between hematocrit in late adolescence and subsequent myocardial infarction in Swedish men. Int J Cardiol. 2013;168(4):3588–93. pmid:23735337
- 21. Coglianese EE, Qureshi MM, Vasan RS, Wang TJ, Moore LL. Usefulness of the blood hematocrit level to predict development of heart failure in a community. Am J Cardiol. 2012;109(2):241–5. pmid:21996141
- 22. Boffetta P, Islami F, Vedanthan R, Pourshams A, Kamangar F, Khademi H, et al. A U-shaped relationship between haematocrit and mortality in a large prospective cohort study. Int J Epidemiol. 2013;42(2):601–15. pmid:23569195
- 23. Kim M-Y, Jee SH, Yun JE, Baek SJ, Lee D-C. Hemoglobin concentration and risk of cardiovascular disease in Korean men and women - the Korean heart study. J Korean Med Sci. 2013;28(9):1316–22. pmid:24015036
- 24. Klip IT, Postmus D, Voors AA, Brouwers FPJ, Gansevoort RT, Bakker SJL, et al. Hemoglobin levels and new-onset heart failure in the community. Am Heart J. 2015;169(1):94-101.e2. pmid:25497253
- 25. Houghton DE, Koh I, Ellis A, Key NS, Douce DR, Howard G, et al. Hemoglobin levels and coronary heart disease risk by age, race, and sex in the reasons for geographic and racial differences in stroke study (REGARDS). Am J Hematol. 2020;95(3):258–66. pmid:31840854
- 26. Huang D, Gong Y, Fan Y, Zheng B, Lu Z, Li J, et al. Coronary angiography-derived index for assessing microcirculatory resistance in patients with non-obstructed vessels: The FLASH IMR study. Am Heart J. 2023;263:56–63. pmid:37054908
- 27. Gao B, Wu G, Xie J, Ruan J, Xu P, Qian Y, et al. Quantitative Flow Ratio-Derived Index of Microcirculatory Resistance as a Novel Tool to Identify Microcirculatory Function in Patients with Ischemia and No Obstructive Coronary Artery Disease. Cardiology. 2024;149(1):14–22. pmid:37839404
- 28. Wang L, Travieso A, van der Hoeven N, Lombardi M, van Leeuwen MAH, Janssens G, et al. Angiography-versus wire-based microvascular resistance index to detect coronary microvascular obstruction associated with ST-segment elevation myocardial infarction. Int J Cardiol. 2024;411:132256. pmid:38866108
- 29. Fan Y, Li C, Hu Y, Hu X, Wang S, He J, et al. Angiography-based index of microcirculatory resistance (AccuIMR) for the assessment of microvascular dysfunction in acute coronary syndrome and chronic coronary syndrome. Quant Imaging Med Surg. 2023;13(6):3556–68. pmid:37284070
- 30. Mejía-Rentería H, Wang L, Chipayo-Gonzales D, van de Hoef TP, Travieso A, Espejo C, et al. Angiography-derived assessment of coronary microcirculatory resistance in patients with suspected myocardial ischaemia and non-obstructive coronary arteries. EuroIntervention. 2023;18(16):e1348–56. pmid:36534493
- 31. Li C, Hu Y, Wang J, Pan C, Lu H, Wu Y, et al. Are baseline conditions of coronary arteries sufficient for calculating angio-based index of microcirculatory resistance and fractional flow reserve? Quant Imaging Med Surg. 2023;13(9):6215–27. pmid:37711819
- 32. Fan Y, Fezzi S, Sun P, Ding N, Li X, Hu X, et al. In Vivo Validation of a Novel Computational Approach to Assess Microcirculatory Resistance Based on a Single Angiographic View. J Pers Med. 2022;12(11):1798. pmid:36573725
- 33. Qian G, Qin H, Deng D, Feng Y, Zhang C, Qu X, et al. Prognostic value of angiographic microvascular resistance in patients with ST-segment elevation myocardial infarction. Clinics (Sao Paulo). 2024;79:100429. pmid:39053030
- 34. Wen X, Wang Z, Zheng B, Gong Y, Huo Y. Ability of the coronary angiography-derived index of microcirculatory resistance to predict microvascular obstruction in patients with ST-segment elevation. Front Cardiovasc Med. 2024;11:1187599. pmid:38711790
- 35. Wang B, Gao Y, Zhao Y, Jia P, Han J, Li H, et al. Prognostic Value of Angiography-Derived Index of Microcirculatory Resistance in Patients with Coronary Artery Disease Undergoing Rotational Atherectomy. Rev Cardiovasc Med. 2023;24(5):131. pmid:39076748
- 36. Yidilisi A, Chen D, Zhang Y, Pu J, Niu T, Hu Y, et al. Coronary Angiography-Derived Index of Microcirculatory Resistance Predicts Outcome in Patients With ST-Segment-Elevation Myocardial Infarction. Circ Cardiovasc Interv. 2024;17(5):e013899. pmid:38660822
- 37. Takaoka N, Sairenchi T, Irie F, Matsushita M, Nagao M, Umesawa M, et al. High Hematocrit Levels Are Associated with Risk of Cardiovascular Mortality among Middle-Aged Japanese Women: The Ibaraki Prefectural Health Study (IPHS). Tohoku J Exp Med. 2019;249(1):65–73. pmid:31564685
- 38. Li D, Wang A, Li Y, Ruan Z, Zhao H, Li J, et al. Nonlinear relationship of red blood cell indices (MCH, MCHC, and MCV) with all-cause and cardiovascular mortality: A cohort study in U.S. adults. PLoS One. 2024;19(8):e0307609. pmid:39093828
- 39. Frąckiewicz J, Włodarek D, Brzozowska A, Wierzbicka E, Słowińska MA, Wądołowska L, et al. Hematological parameters and all-cause mortality: a prospective study of older people. Aging Clin Exp Res. 2018;30(5):517–26. pmid:28664457
- 40. Adel G. Polycythemia Vera and Acute Coronary Syndromes: Pathogenesis, Risk Factors and Treatment. J Hematol Thrombo Diseases. 2013;01(01).
- 41. Duran Luciano P, Sabella-Jiménez V. ST-Segment Elevation Myocardial Infarction and Bleeding Complications in JAK2-Negative Polycythemia. Tex Heart Inst J. 2023;50(5):e238148. pmid:37872693
- 42. Butt MI. Severe Dilated Cardiomyopathy Due to Polycythemia Vera - A Rare Etiology. J Cardiol Cardiovasc Ther. 2019;15.
- 43. Zaman MO, Kim K, Yousafzai OK, Umer M, Jones RG, Shah R, et al. Heart failure with reduced ejection fraction due topolycythemia vera. Oxf Med Case Reports. 2021;2021(10):omab104. pmid:34729202
- 44. Jung F, Mrowietz C, Gerk U, Franke RP. Influence of a radiographic contrast media (Iopentol) with different viscosities on capillary perfusion in patients with coronary artery disease. Clin Hemorheol Microcirc. 2013;53(1–2):201–8. pmid:22596231
- 45. Jung F, Rampling M. Role of blood viscosity in the microcirculation. Clin Hemorheol Microcirc. 2017;64: 251–4.
- 46. Rasyid A, Chandra JR, Harris S, Kurniawan M, Hidayat R, Yamin M, et al. Blood Viscosity and its Clinical Implications in Ischemic Stroke and Chronic Heart Failure: Insights from a Case Report. Open Neurol J. 2024;18(1).
- 47. Katranas SA, Kelekis AL, Antoniadis AP, Ziakas AG, Giannoglou GD. Differences in Stress Forces and Geometry between Left and Right Coronary Artery: A Pathophysiological Aspect of Atherosclerosis Heterogeneity. Hellenic J Cardiol. 2015;56(3):217–23. pmid:26021243
- 48. Vorobtsova N, Chiastra C, Stremler MA, Sane DC, Migliavacca F, Vlachos P. Effects of Vessel Tortuosity on Coronary Hemodynamics: An Idealized and Patient-Specific Computational Study. Ann Biomed Eng. 2016;44(7):2228–39. pmid:26498931
- 49. Khosravani-Rudpishi M, Joharimoghadam A, Rayzan E. The significant coronary tortuosity and atherosclerotic coronary artery disease; What is the relation?. J Cardiovasc Thorac Res. 2018;10(4):209–13. pmid:30680079
- 50. Li Y, Shi Z, Cai Y, Feng Y, Ma G, Shen C, et al. Impact of Coronary Tortuosity on Coronary Pressure: Numerical Simulation Study. Obukhov AG, editor. PLoS One. 2012;7:e42558.
- 51. Xie X, Wang Y, Zhou H. Impact of coronary tortuosity on the coronary blood flow: a 3D computational study. J Biomech. 2013;46(11):1833–41. pmid:23777815
- 52. Gaibazzi N, Rigo F, Reverberi C. Severe coronary tortuosity or myocardial bridging in patients with chest pain, normal coronary arteries, and reversible myocardial perfusion defects. Am J Cardiol. 2011;108(7):973–8. pmid:21784382