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Br Heart J. Dec 1995; 74(6): 592–597.
PMCID: PMC484111
Can early closure and restenosis after endoluminal stenting be predicted from clinical, procedural, and angiographic variables at the time of intervention?
E. Eeckhout, G. van Melle, J. C. Stauffer, P. Vogt, L. Kappenberger, and J. J. Goy
Cardiology Division, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland.
OBJECTIVES--To develop a statistical model to assess the risk of early closure and restenosis on the basis of the information available at the time of stent implantation. DESIGN--An exploratory forward, stepwise multivariate logistic regression for each adverse event and multivariate polychotomous analysis for both events. SETTING--Tertiary referral centre for interventional treatment of coronary artery disease. PATIENTS--243 consecutive, successful stenting procedures between 1986 and 1993 with the Wallstent, the Palmaz-Schatz and Wiktor stents with analysis of clinical, procedural, and angiographic variables. MEAN OUTCOME MEASURES--Early closure was defined as angiographically documented stent thrombosis within the first 3 weeks after implantation and restenosis according to the 50% reference diameter reduction criterion. RESULTS--Overall early closure and restenosis rates were 14.4% (35/243) and 19.2% (40/208, for a 97% repeat angiography rate). The statistical model predicted a worse outcome for male patients, with less restenosis in female patients. The only risk factor in female patients was the presence of collaterals to the target lesion. For male patients the following risk factors for closure and restenosis were retained: multiple stent implantation during the same session, the presence of collaterals to the target lesion, stenting of the left anterior descending artery or of the left circumflex artery, and bailout stenting. Only bailout stenting implied a decreased restenosis risk. CONCLUSIONS--Clinical, procedural and angiographic variables increase the risk for early closure and restenosis after endoluminal stenting. The prediction models described above need to be validated prospectively.
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