Risk factors associated with intra‑stent restenosis after percutaneous coronary intervention

Alexandrescu, Dan-Mihai; Mitu, Ovidiu; Costache, Irina Iuliana; Macovei, Liviu; Mitu, Ivona; Alexandrescu, Anca; Georgescu, Cătălina Arsenescu

doi:10.3892/etm.2021.10575

Cited by 17 publications

(13 citation statements)

References 25 publications

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“…These results were comparable to the previous studies. [11,12] We found that 40 (48.2%) patients were smokers. Mean LDL cholesterol of the patients was 68.6±1.97 mg/dl and mean uric acid was 6.2±2.35 mg/dl.…”

Section: Discussionmentioning

confidence: 74%

“…Our results showed that the stents longer than 30mm were associated with a higher incidence of In-Stent Restenosis (p=0.03). [11,12] Active pharmacologic medication, stent plat shape, and drug carrier are the three main components of a drug eluting stent that contribute to its efficacy. Within the first 30 days after artery injury, newer DES designs allow for the controlled release of medicines that are anti-inflammatory, immunological modulatory, and/or antiproliferative at the site of injury.…”

Section: Discussionmentioning

confidence: 99%

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Frequency of in-Stent Restenosis in patients having DES, with Stent Length Greater than 30mm Presenting to Tertiary Care Center

Butt¹,

Khan²,

Afridi³

et al. 2023

PJMHS

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Objective: The purpose of this study was to calculate the incidence of in-stent restenosis in patients with DES and stent lengths higher than 30mm who presented to a tertiary care hospital. Study Design: A Cross-sectional study Place and Duration: This cross-sectional study was conducted at Department of Cardiology, Rashid Latif Medical College, Lahore in the duration from February, 2022 to July, 2022. Methods: There were 83 patients of coronary artery disease (CAD)were included. After obtaining written consent from participants, researchers collected information about their participants' ages, sexes, body mass indexes, and co-morbidities. Atherosclerosis risk variables were collected with baseline investigations and an echocardiography for ejection fraction determination. Imaging studies were reviewed by board-certified interventional cardiologists, who found evidence of ISR. Past angioplasty information and stent details were recorded. Results: In our study mean age of the presented cases was 54.13±7.44 years and mean BMI 25.2±13.87 kg/m2. Most common comorbidity was diabetes found in 25 (30.1%) followed by hypertension in 23 (27.7%) and dyslipidemia in 20 (24.1%) cases. We found that 40 (48.2%) patients were smokers. Mean LDL cholesterol of the patients was 68.6±1.97 mg/dl and mean uric acid was 6.2±2.35 mg/dl. Majority of the cases 45 (54.2%) had poor socio-economic status. We found that frequency of ISR was higher among cases of biomatrix stent 24 (28.9%), followed by Xience stent in 22 (26.5%) cases, Ultimaster stent in 19 (22.9%) and Xlimus stent in 18 (21.7%) cases after coronary angiograpghy. Our results showed that the stents longer than 30mm were associated with a higher incidence of In-Stent Restenosis (p=0.03). Conclusion: Based on the findings of this study, we came to the conclusion that a previous diagnosis of diabetes mellitus and a longer stent length are both significant risk factors for developing in-stent restenosis. In our research, we found that instances with biomatrix stents had a greater incidence of ISR. Keywords: CAD, Drug eluting stents (DES), Coronary angiography, In-Stent Restenosis

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Section: Discussionmentioning

confidence: 74%

Section: Discussionmentioning

confidence: 99%

Frequency of in-Stent Restenosis in patients having DES, with Stent Length Greater than 30mm Presenting to Tertiary Care Center

Butt¹,

Khan²,

Afridi³

et al. 2023

PJMHS

View full text Add to dashboard Cite

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“…In some studies, classic cardiovascular risk factors are deemed to increase the likelihood of ISR ( 9 , 10 ), but in some others this relationship is not very clearly validated ( 11 ). Many studies investigated the role of various cardiovascular risk factors in the development of restenosis; diabetes mellitus was incriminated in many researches as an independent risk factor for ISR, along with arterial hypertension, active smoking and low-density lipoprotein cholesterol (LDL-C) ( 12 – 14 ). Erkan Yıldırım et al ( 15 ) showed in multivariate logistic regression that ISR was independently associated with Gensini score, stent diameter and length, left ventricle ejection fraction, and LDL-C.…”

Section: Introductionmentioning

confidence: 99%

In-stent restenosis in acute coronary syndrome—a classic and a machine learning approach

Scafa-Udriște,

Itu,

Puiu

et al. 2023

Front. Cardiovasc. Med.

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BackgroundIn acute coronary syndrome (ACS), a number of previous studies tried to identify the risk factors that are most likely to influence the rate of in-stent restenosis (ISR), but the contribution of these factors to ISR is not clearly defined. Thus, the need for a better way of identifying the independent predictors of ISR, which comes in the form of Machine Learning (ML).ObjectivesThe aim of this study is to evaluate the relationship between ISR and risk factors associated with ACS and to develop and validate a nomogram to predict the probability of ISR through the use of ML in patients undergoing percutaneous coronary intervention (PCI).MethodsConsecutive patients presenting with ACS who were successfully treated with PCI and who had an angiographic follow-up after at least 3 months were included in the study. ISR risk factors considered into the study were demographic, clinical and peri-procedural angiographic lesion risk factors. We explored four ML techniques (Random Forest (RF), support vector machines (SVM), simple linear logistic regression (LLR) and deep neural network (DNN)) to predict the risk of ISR. Overall, 21 features were selected as input variables for the ML algorithms, including continuous, categorical and binary variables.ResultsThe total cohort of subjects included 340 subjects, in which the incidence of ISR observed was 17.68% (n = 87). The most performant model in terms of ISR prediction out of the four explored was RF, with an area under the receiver operating characteristic (ROC) curve of 0.726. Across the predictors herein considered, only three predictors were statistically significant, precisely, the number of affected arteries (≥2), stent generation and diameter.ConclusionML models applied in patients after PCI can contribute to a better differentiation of the future risk of ISR.

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“…It is a minimally invasive surgical procedure, i.e., using a catheter to place a stent to open up the narrowed blood vessel [ 4 , 5 ]. However, post-treatment with PCI is frequently followed by vascular wall injury leading to inflammation, thrombosis, and finally restenosis (re-narrowing of the treated blood vessel) [ 6 , 7 ]. Thus, restenosis after PCI is the main problem that limits the long-term success of the PCI.…”

Section: Introductionmentioning

confidence: 99%

“…This allows the stable arrest of platelets, platelet activation, and irreversible platelet aggregation leading to thrombus growth [ 9 ]. Growth factors released from activated platelets promote vascular smooth muscle cell (SMC) proliferation and migration from the media to the intima, causing a thickening of the intimal vessel wall layer, called intimal hyperplasia, which restricts the luminal blood flow causing instent restenosis [ 6 , 7 , 10 , 11 , 12 , 13 ]. Thus, binding the platelet GPIb-V-IX complex to vWF is crucial for early platelet adherence to the damaged vessel wall.…”

Section: Introductionmentioning

confidence: 99%

Targeted Nanoparticles for the Binding of Injured Vascular Endothelium after Percutaneous Coronary Intervention

et al. 2022

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Percutaneous coronary intervention (PCI) is a common procedure for the management of coronary artery obstruction. However, it usually causes vascular wall injury leading to restenosis that limits the long-term success of the PCI endeavor. The ultimate objective of this study was to develop the targeting nanoparticles (NPs) that were destined for the injured subendothelium and attract endothelial progenitor cells (EPCs) to the damaged location for endothelium regeneration. Biodegradable poly(lactic-co-glycolic acid) (PLGA) NPs were conjugated with double targeting moieties, which are glycoprotein Ib alpha chain (GPIbα) and human single-chain antibody variable fragment (HuscFv) specific to the cluster of differentiation 34 (CD34). GPIb is a platelet receptor that interacts with the von Willebrand factor (vWF), highly deposited on the damaged subendothelial surface, while CD34 is a surface marker of EPCs. A candidate anti-CD34 HuscFv was successfully constructed using a phage display biopanning technique. The HuscFv could be purified and showed binding affinity to the CD34-positive cells. The GPIb-conjugated NPs (GPIb-NPs) could target vWF and prevent platelet adherence to vWF in vitro. Furthermore, the HuscFv-conjugated NPs (HuscFv-NPs) could capture CD34-positive cells. The bispecific NPs have high potential to locate at the damaged subendothelial surface and capture EPCs for accelerating the vessel repair.

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Risk factors associated with intra‑stent restenosis after percutaneous coronary intervention

Cited by 17 publications

References 25 publications

Frequency of in-Stent Restenosis in patients having DES, with Stent Length Greater than 30mm Presenting to Tertiary Care Center

Frequency of in-Stent Restenosis in patients having DES, with Stent Length Greater than 30mm Presenting to Tertiary Care Center

In-stent restenosis in acute coronary syndrome—a classic and a machine learning approach

Targeted Nanoparticles for the Binding of Injured Vascular Endothelium after Percutaneous Coronary Intervention

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