Evidence map›Paper›PMID 38674195›Full record

ReviewMedicina (Kaunas, Lithuania)2024

In-Stent Restenosis Overview: From Intravascular Imaging to Optimal Percutaneous Coronary Intervention Management.

Neda Shafiabadi Hassani, Lucas Carlini Ogliari, Pedro Rafael Vieira de Oliveira Salerno, Gabriel Tensol Rodrigues Pereira, Marcelo Harada Ribeiro, Luis Augusto Palma Dallan

Abstract readReview
In one paragraph

Review in Medicina (Kaunas, Lithuania), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Neda Shafiabadi HassaniHarrington Heart and Vascular Institute, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA.ORCID 0000-0001-8492-2683
Lucas Carlini OgliariSOS Cardio Hospital and Imperial Hospital de Caridade, Florianópolis 88020-210, SC, Brazil.
Pedro Rafael Vieira de Oliveira SalernoHarrington Heart and Vascular Institute, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA.ORCID 0000-0002-5116-5062
Gabriel Tensol Rodrigues PereiraHarrington Heart and Vascular Institute, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA.ORCID 0000-0001-8484-1816
Marcelo Harada RibeiroSOS Cardio Hospital and Imperial Hospital de Caridade, Florianópolis 88020-210, SC, Brazil.ORCID 0000-0003-4458-6835
Luis Augusto Palma DallanHarrington Heart and Vascular Institute, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA.ORCID 0000-0002-8122-6647

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite ongoing progress in stent technology and deployment techniques, in-stent restenosis (ISR) still remains a major issue following percutaneous coronary intervention (PCI) and accounts for 10.6% of all interventions in the United States. With the continuous rise in ISR risk factors such as obesity and diabetes, along with an increase in the treatment of complex lesions with high-risk percutaneous coronary intervention (CHIP), a substantial growth in ISR burden is expected. This review aims to provide insight into the mechanisms, classification, and management of ISR, with a focus on exploring innovative approaches to tackle this complication comprehensively, along with a special section addressing the approach to complex calcified lesions.

Indexed as

Coronary RestenosisPercutaneous Coronary InterventionStentsHumansRisk FactorsUltrasonography, Interventionalin-stent restenosisintravascular imagingpercutaneous coronary intervention management

Identifiers

PMID38674195
PMCPMC11051745

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.