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Risk of stent thrombosis after sirolimus or paclitaxel eluting coronary stent implantation

2006· letter· en· W2106700211 on OpenAlexaboutno aff
Raúl Moreno, Cristina Fernández, Ángel Sánchez‐Recalde, Luís Calvo, Guillermo Galeote, Rosa Sánchez-Aquino, Jose‐Luis Lopez‐Sendon

Bibliographic record

VenueBritish Journal of Clinical Pharmacology · 2006
Typeletter
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsStentMedicineRestenosisThrombosisSirolimusInternal medicineDrug-eluting stentCardiologyPaclitaxelSurgeryRadiologyChemotherapy

Abstract

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Both sirolimus (SES) and paclitaxel eluting stents (PES) have been shown to reduce significantly both the incidence of binary angiographic restenosis and the need for new revascularization procedures [1]. We read with great interest the paper by Sidhu et al., in which the better angiographic behaviour of SES in comparison with PES was not translated into significant differences in terms of clinical events [2]. As paclitaxel is cytotoxic, whereas sirolimus is cytostatic, the risk of stent thrombosis between the two types of drug-eluting stents could be different. In fact, in a recent work, a trend to an increased risk of stent thrombosis after PES implantation was found, whereas the risk of stent thrombosis was similar with SES and bare-metal stents [3]. Stent thrombosis is an infrequent complication. Because of that, data from single trials are not sufficient to compare the incidence of stent thrombosis between two different types of stent. For the evaluation of such an infrequent entity, meta-analysis may increase increase power and precision and provides an overall estimate and range of effect. In order to help to clarify whether the risk of stent thrombosis is different between SES and PES, we have performed a meta-analysis from nine randomized trials that have compared SES and PES, including 5024 patients (2514 allocated to SES, 2510 allocated to PES). The trials included in the meta-analysis were: TAXI (n = 202), REALITY (n = 1353), SIRTAX (n = 1012), ISAR-DIABETES (n = 250), ISAR-DESIRE (n = 200), CORPAL (n = 652), ISAR-SMART-3 (n = 360), BASKET (n = 545) and ISAR-TEST (n = 450) [4–12]. Follow-up ranged from 6 to 12 months. In most trials, the Cypher stent (Cordis Corp., Miami Lakes, FL, USA) and the Taxus stent (Boston Sci., Natick, MA, USA), with polymeric-release of sirolimus and paclitaxel, respectively, were randomly compared in patients with native de novo lesions. In the ISAR-DESIRE study, only patients with in-stent restenosis after bare-metal stent implantation were included. In the ISAR-TEST, the Yukon stent, with nonpolymeric release of sirolimus, was compared with the Taxus stent. The risk ratio for stent thrombosis and its 95% confidence interval (CI) was calculated comparing SES with PES rates using raw data for each study and for the pooled population. The Q-test for heterogeneity and the fixed-effect model were used. There was no heterogeneity among the trials [Q-test for heterogeneity: χ2 = 5.41, d.f. = 6 (P = 0.49); I2 = 0%]. The overall risk of stent thrombosis in the overall population was 0.92% (n = 46 patients): 0.83% (21/2514) and 1.00% (25/2510) in patients allocated to SES and PES, respectively (risk ratio 1.17, 95% CI 0.67, 2.35; P = 0.57) (Figure 1). Comparison of the incidence of stent thrombosis in each of the nine randomized clinical studies included in the meta-analysis, as well as in the pooled population (fixed-effect model) Sirolimus and paclitaxel have different mechanisms of action (sirolimus is cytostatic, whereas paclitaxel is cytotoxic). Moreover, both stent platform and polymer are different in Taxus and Cypher stents, and whereas Taxus releases paclitaxel from a polymer, the Yukon stent has a nonpolymeric release of sirolimus. However, in view of our results, all these differences in stent design, type of polymer and type of drug do not seem to be translated into different risk of stent thrombosis. Given the high number of patients included in our meta-analysis (>5000), the possibility of existing but undetected differences in the risk of stent thrombosis between SES and PES is very low. In a previously published meta-analysis including trials that compared drug-eluting stents and bare-metal stents, we found a similar risk of stent thrombosis in PES and SES trials when the SCORE trial and the patients from the ASPECT study that did not receive thienopyridines were excluded (0.57% vs. 0.58%, P = 1.000) [13]. Drug-eluting stents have revolutionized cardiology worldwide, since they dramatically reduce the need for new revascularization procedures after percutaneous coronary interventions. Because of that, now that more diabetic patients are now being treated percutaneously,with longer lesions and smaller vessels, the absolute incidence of stent thrombosis in the era of drug-eluting stents will probably increase. However, we should bear in mind that the risk of stent thrombosis is related mainly to the appropriateness of antiplatelet therapy and the characteristics of the lesion, more than to the type of coronary stent.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.016
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.068
GPT teacher head0.414
Teacher spread0.346 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations5
Published2006
Admission routes1
Has abstractyes

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