Restenosis after PCI. Part 1: pathophysiology and risk factors

Jukema, J. Wouter; Verschuren, Jeffrey J. W.; Ahmed, Tarek; Quax, Paul H.A.

doi:10.1038/nrcardio.2011.132

Cited by 258 publications

(242 citation statements)

References 117 publications

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“…Cellular response to mechanical vascular damage initiated immediately after PCI includes an early phase, consisting of platelet activation and inflammation, followed by an intermediate phase of granulation tissue corresponding to vascular smooth muscle cell migration and proliferation, and a late phase of neointima formation and finally progression to ISR (21). Although the exact etiopathogenesis remains to be fully elucidated, various pre-, peri-, and postprocedural risk factors represent possible actors in the development of ISR (14). The clinical parameter that most consistently increases the risk of ISR is diabetes mellitus (22).…”

Section: Discussionmentioning

confidence: 99%

“…However, ISR represents a major nightmare for interventionalists and efforts are ongoing to circumvent this serious problem (15,20). Along with technical issues, several cellular and molecular pathways play a role in coronary wall injury after PCI (14,21). Cellular response to mechanical vascular damage initiated immediately after PCI includes an early phase, consisting of platelet activation and inflammation, followed by an intermediate phase of granulation tissue corresponding to vascular smooth muscle cell migration and proliferation, and a late phase of neointima formation and finally progression to ISR (21).…”

Section: Discussionmentioning

confidence: 99%

“…In-stent restenosis (ISR) continues to be a major pitfall for interventional cardiologists, and numerous efforts have been made to predict or resolve this important problem (14,15). Various reactions following percutaneous coronary intervention (PCI) mediated vascular damage occur in sequence including inflammation, granulation, extracellular matrix remodeling, and vascular smooth muscle cell proliferation and migration, which result in neointimal hyperplasia and restenosis (16,17).…”

Section: Introductionmentioning

confidence: 99%

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Impact of free thyroxine levels and other clinical factors on bare metal stent restenosis

Canpolat

Turak

Özcan

et al. 2017

Arch. Endocrinol. Metab.

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Objective: Thyroid hormones have both direct and indirect effects on thermogenesis such as modulating vascular smooth muscle cell proliferation. However, the influence of more subtle changes in thyroid hormones on coronary atherosclerosis remains a matter of speculation. Smooth muscle cells play a crucial role in the pathogenesis of in-stent restenosis (ISR). However, the relationship between free thyroxine (fT4) and ISR has not been studied. In the present study, we aimed to assess the role of preprocedural serum fT4 level on the development of ISR in patients undergoing coronary bare metal stent (BMS) implantation. Materials and methods: We enrolled and analyzed clinical, biochemical, and angiographic data from 705 consecutive patients without a history of primary thyroid disease [mean age 60.3 ± 9.3 years, 505 (72%) male]; all patients had undergone BMS implantation and further control coronary angiography owing to stable or unstable angina pectoris. Patients were divided into 3 tertiles based on preprocedural serum fT4 levels. Results: ISR was observed in 53 (23%) patients in the lowest tertile, 82 (35%) patients in the second tertile, and 107 (46%) patients in the highest fT4 tertile (p < 0.001). Using multiple logistic regression analysis, five characteristics emerged as independent predictors of ISR: diabetes mellitus, smoking, HDL-cholesterol, stent length, and preprocedural serum fT4 level. In receiver operating characteristics curve analysis, fT4 level > 1.23 mg/dL had 70% sensitivity and 73% specificity (AUC: 0.75, p < 0.001) in predicting ISR. Conclusion: Higher preprocedural serum fT4 is a powerful and independent predictor of BMS restenosis in patients with stable and unstable angina pectoris. Arch Endocrinol Metab. 2017;61(2):130-6.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Impact of free thyroxine levels and other clinical factors on bare metal stent restenosis

Canpolat

Turak

Özcan

et al. 2017

Arch. Endocrinol. Metab.

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“…Restenosis is a complication of percutaneous coronary intervention. 46, 47 An ABM was developed for modeling of the biological and physical influences induced by per cutaneous transluminal intervention, and subsequent inflammation and healing will lead to improved mechanistic insights and therapy (unpublished observations). The ABM simulated the dynamic formation of a neointima after balloon overstretch injury in the absence of stents or drugs.…”

Section: Incorporating Tissue Realism and Clinically Measureable Physmentioning

confidence: 99%

Computational Modeling of Inflammation and Wound Healing

Ziraldo

et al. 2013

Advances in Wound Care

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Objective: Inflammation is both central to proper wound healing and a key driver of chronic tissue injury via a positive-feedback loop incited by incidental cell damage. We seek to derive actionable insights into the role of inflammation in wound healing in order to improve outcomes for individual patients. Approach: To date, dynamic computational models have been used to study the time evolution of inflammation in wound healing. Emerging clinical data on histo-pathological and macroscopic images of evolving wounds, as well as noninvasive measures of blood flow, suggested the need for tissue-realistic, agent-based, and hybrid mechanistic computational simulations of inflammation and wound healing. Innovation: We developed a computational modeling system, Simple Platform for Agent-based Representation of Knowledge, to facilitate the construction of tissue-realistic models. Results: A hybrid equation-agent-based model (ABM) of pressure ulcer formation in both spinal cord-injured and -uninjured patients was used to identify control points that reduce stress caused by tissue ischemia/reperfusion. An ABM of arterial restenosis revealed new dynamics of cell migration during neointimal hyperplasia that match histological features, but contradict the currently prevailing mechanistic hypothesis. ABMs of vocal fold inflammation were used to predict inflammatory trajectories in individuals, possibly allowing for personalized treatment. Conclusions: The intertwined inflammatory and wound healing responses can be modeled computationally to make predictions in individuals, simulate therapies, and gain mechanistic insights. INTRODUCTIONWound healing is a complex process that is initiated and driven by inflammation.1,2 The first phase of the wound healing response involves the degranulation of platelets and infiltration of inflammatory cells, followed by proliferation of fibroblasts and epithelial cells that deposit collagen and cause contraction of wounds. Inflammatory mediators such as tumor necrosis factor alpha (TNF-a), 3 interferon-c, 4 interleukin (IL)-6, 5 IL-10, 6 transforming growth factor beta-1 (TGF-b1), 7 and nitric oxide 8,9 modulate the wound-healing response. Wound healing is well studied in animal systems. 10,11 However, even though some experimental methodologies are emerging that may allow for the study of time courses of wound healing in humans, 11 it is difficult to collect time courses of primary samples from humans suffering from chronic wound-healing diseases without disturbing the very process which is being measured. An alternative method for studying such a complex, clinically realistic system is to use a mechanistic computational model based on literature knowledge, which could be validated experimentally or clinically, which, in turn, may have applications in diagnosing/predicting wound healing trajectories of individuals or possibly in the design of novel therapeutic modalities for wound healing. Extensive work has gone into computational studies of wound healing, spanning many stages of this proces...

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“…Excessive accumulation of extracellular matrix is mediated by several growth factors (5,9,11). Morphologically, these stenotic lesions closely resemble restenotic lesions after percutaneous coronary intervention (12,13). Additional specific pathophysiologic stimuli for intimal hyperplasia in vascular access stenosis include the abnormal calcium/phosphate metabolism in patients with CKD that result in arterial as well as venous calcification of the tunica media (14).…”

Section: Introductionmentioning

confidence: 99%

Candidate Gene Analysis of Arteriovenous Fistula Failure in Hemodialysis Patients

Verschuren

Ocak²,

Dekker³

et al. 2013

Clinical Journal of the American Society of Nephrology

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SummaryBackground and objectives Arteriovenous fistula (AVF) failure remains an important cause of morbidity in hemodialysis patients. The exact underlying mechanisms responsible for AVF failure are unknown but processes like proliferation, inflammation, vascular remodeling, and thrombosis are thought to be involved. The current objective was to investigate the association between AVF failure and single nucleotide polymorphisms (SNPs) in genes related to these pathophysiologic processes in a large population of incident hemodialysis patients.Design, setting, participants, & measurements A total of 479 incident hemodialysis patients were included between January 1997 and April 2004. Follow-up lasted 2 years or until AVF failure, defined as surgery, percutaneous endovascular intervention, or abandonment of the vascular access. Forty-three SNPs in 26 genes, related to proliferation, inflammation, endothelial function, vascular remodeling, coagulation, and calcium/ phosphate metabolism, were genotyped. Relations were analyzed using Cox regression analysis.Results In total, 207 (43.2%) patients developed AVF failure. After adjustment, two SNPs were significantly associated with an increased risk of AVF failure. The hazard ratio (95% confidence interval) of LRP1 rs1466535 was 1.75 (1.15 to 2.66) and patients with factor V Leiden had a hazard ratio of 2.54 (1.41 to 4.56) to develop AVF failure. The other SNPs were not associated with AVF failure. ConclusionsIn this large cohort of hemodialysis patients, only 2 of the 43 candidate SNPs were associated with an increased risk of AVF failure. Whether other factors, like local hemodynamic circumstances, are more important or other SNPs play a role in AVF failure remains to be elucidated.

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Restenosis after PCI. Part 1: pathophysiology and risk factors

Cited by 258 publications

References 117 publications

Impact of free thyroxine levels and other clinical factors on bare metal stent restenosis

Impact of free thyroxine levels and other clinical factors on bare metal stent restenosis

Computational Modeling of Inflammation and Wound Healing

Candidate Gene Analysis of Arteriovenous Fistula Failure in Hemodialysis Patients

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