19 research outputs found
Changes in vascular distensibility during angiotensin-converting enzyme inhibition involve bradykinin type 2 receptors
Interventional Cardiologists of the T. The risk of stent thrombosis in patients with acute coronary syndromes treated with bare-metal and drug-eluting stents
ObjectivesWe aimed to evaluate the risk of definite stent thrombosis with bare-metal stents (BMS) and drug-eluting stents (DES) in patients treated for acute coronary syndromes.BackgroundAcute coronary syndromes (ACS) have been reported as increasing the risk for stent thrombosis.MethodsBetween January 2000 and December 2005, 5,816 consecutive patients underwent percutaneous coronary intervention for de novo lesions with a single stent type. These patients consisted of 3 sequential groups of BMS (n = 2,248), sirolimus-eluting stents (n = 822) and paclitaxel-eluting stents (n = 2,746). In total, 3,485 patients presented with an ACS.ResultsAfter a median follow-up of 1,394 days, patients with ACS had a definite stent thrombosis rate of 2.5% versus 1.0% in patients with stable angina (propensity score-adjusted hazard ratio [HR]: 2.80, 95% confidence interval [CI]: 1.72 to 4.56). ACS patients had a higher risk of early and late stent thrombosis, although the increased risk of very late stent thrombosis was only present in ACS patients treated with DES. In stable patients, any stent thrombosis resulted in a significant increase in mortality (adjusted HR: 4.0, 95% CI: 1.7 to 9.3), although this was particularly evident for late or very late stent thrombosis; in contrast only early stent thrombosis significantly increased mortality in patients with acute coronary syndrome patients (adjusted HR: 2.0, 95% CI: 1.0 to 4.1).ConclusionsPatients with acute coronary syndromes are at higher risk of early and late stent thrombosis with either BMS or DES, although very late stent thrombosis seems to be uniquely associated with DES. The clinical sequelae of late and very late stent thrombosis are more pronounced in stable patients
First direct in vivo comparison of two commercially available three-dimensional quantitative coronary angiography systems
How accurate is ultrasound pattern recognition at predicting the histological diagnosis of an ovarian mass?
Objectives: To assess the accuracy of pattern recognition for the
histological diagnosis of an adnexal mass, when the examinations
are performed by ultrasound experts of similar experience.
Methods: Static B-mode preoperative ultrasound images, containing
gray-scale and color Doppler information on the adnexal masses
of 166 patients were examined independently by three expert
sonologists. They all had access to relevant clinical information,
but none of the experts performed the original real-time scans.
The expert sonologists were asked to classify tumors into one
of 11 histological groups. They were also asked to indicate the
degree of confidence with which they made the diagnosis. In cases
of disagreement between the experts reviewing the images, the
histological diagnosis made by two of the three examiners was taken
as the representative of the particular case. The gold standard was
the final histology.
Results: As a group the experts reached an accuracy of 83.13%
in classifying the adnexal mass as benign or malignant. In six
patients all three examiners gave a different histological diagnosis
and these cases were excluded from further analysis. The sensitivity
and specificity for the different histologies were: 91.43% (32/35)
and 97.60% (122/125) for dermoid cysts; 66.67% (22/33) and
90.55% (115/127) for cystadenoma (fibroma); 93.33% (14/15) and
99.31% (144/145) for endometrioma; 68.75% (22/32) and 90.63%
(116/128) for borderline ovarian tumors (BOT); 42.86% (6/14) and
95.89% (140/146) for gastrointestinal BOTs; 88.89% (16/18) and
95.77% (136/142) for serous BOTs; 88.00% (22/25) and 99.26%
(134/135) for invasive epithelial cancer; and 90.00% (9/10) and
98.00% (147/150) for rare malignant tumors.
Conclusions: Using pattern recognition ultrasound experts are able
to make a correct histological diagnosis in nearly 80% of cases.
The diagnostic accuracy was highest in cases of dermoid cysts,
endometriomas, serous BOTs, invasive epithelial cancer and rare
malignant tumors