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31.
AimsOrgan preservation, an important goal in the treatment of head and neck squamous cell carcinoma (HNSCC), may include induction chemotherapy and cisplatin with radiation therapy (CRT). To our knowledge, no reports have directly compared the impact of induction chemotherapy with that of CRT on health-related quality of life (HRQOL).Materials and methodsIn a phase II trial, we assessed the HRQOL of patients treated with induction chemotherapy followed by CRT. Eligible patients had stage III–IV HNSCC. HRQOL questionnaires were administered at baseline, the end of induction (EOI), the end of CRT (EOCRT) and after CRT. Functional Assessment of Cancer Therapy (FACT version 4) assessed HRQOL. We carried out a comparison of changes in HRQOL from baseline to EOI and from EOI to EOCRT. This trial is registered with ClinicalTrials.gov (NCT01566435).ResultsThirty patients were enrolled in the study. Most HRQOL questionnaires were completed (88%). The mean total FACT scores did not differ from baseline to EOI (general: 83.8 versus 79.1, P = 0.08; head and neck: 109.7 versus 105.8, P = 0.33; Total Outcome Index: 69.7 versus 62.3, P = 0.03; respectively, using P ≤ 0.01 to adjust for multiple simultaneous tests of differences). However, total FACT scores significantly worsened from EOI to EOCRT (79.1 versus 62.3, P = 0.01; 105.8 versus 74.2, P < 0.01; 62.3 versus 34.2, P = 0.01; respectively). Within domains, the head and neck cancer subscale score did not differ from baseline to EOI (median 28.5 versus 27.0, P = 0.69), but significantly worsened from EOI to EOCRT (27.0 versus 9.5, P < 0.01). Swallowing, oral pain and voice quality improved from baseline to EOI, but worsened from EOI to EOCRT. Physical and functional scores worsened from baseline to EOI and from EOI to EOCRT. The emotional well-being score improved from baseline to EOI but worsened from EOI to EOCRT.ConclusionsOverall, HRQOL did not significantly change from baseline to EOI but dramatically worsened from EOI to EOCRT.  相似文献   
32.

Background and aims

Since accelerated atherosclerosis has been reported in systemic lupus erythematosus (SLE), predictive biomarkers of cardiovascular disease (CVD) are needed. Among non-traditional risk factors, bone mineral density (BMD) has been related to CVD. However, its role in SLE remains controversial. This study aims to analyze the associations of subclinical atherosclerosis with traditional and non-traditional CV risk factors.

Methods and results

In a cross-sectional study, atherosclerosis burden was compared between 112 female SLE patients and 31 controls. Plaque number and carotid intima-media wall thickness (cIMT) were assessed by ultrasonography. In a retrospective study, BMD determinations obtained 5-years before the ultrasonography assessment were analyzed in a subgroup of 62 patients. Plaque frequency was increased in SLE, even in patients without CV events or carotid wall thickening. cIMT was increased in patients with CVD, positively correlated with body mass index (BMI). Interestingly, a paradoxical effect of BMI on carotid parameters was observed. Whereas underweight patients (BMI < 20) showed increased prevalence of carotid plaques with low cIMT, those with BMI > 30 showed higher cIMT and plaque burden. Overweight patients (25 < BMI<30) exhibited both elevated cIMT and plaque number. BMI was an independent predictor of BMD. In our retrospective study, patients with either clinical or subclinical CVD exhibited lower BMD levels than their CV-free counterparts. A low lumbar spine BMD independently predicted CVD development after adjusting for confounders.

Conclusion

SLE was associated with a higher subclinical atherosclerosis burden, a bimodal effect being observed for BMI. Decreased BMD can be a CV risk biomarker in SLE.  相似文献   
33.
BackgroundThe efficacy of ticagrelor in the long-term post–ST-segment elevation myocardial infarction (STEMI) treated with fibrinolytic therapy remains uncertain.ObjectivesThe purpose of this study was to evaluate the efficacy of ticagrelor when compared with clopidogrel in STEMI patients treated with fibrinolytic therapy.MethodsThis international, multicenter, randomized, open-label with blinded endpoint adjudication trial enrolled 3,799 patients (age <75 years) with STEMI receiving fibrinolytic therapy. Patients were randomized to ticagrelor (180-mg loading dose, 90 mg twice daily thereafter) or clopidogrel (300- to 600-mg loading dose, 75 mg daily thereafter). The key outcomes were cardiovascular mortality, myocardial infarction, or stroke, and the same composite outcome with the addition of severe recurrent ischemia, transient ischemic attack, or other arterial thrombotic events at 12 months.ResultsThe combined outcome of cardiovascular mortality, myocardial infarction, or stroke occurred in 129 of 1,913 patients (6.7%) receiving ticagrelor and in 137 of 1,886 patients (7.3%) receiving clopidogrel (hazard ratio: 0.93; 95% confidence interval: 0.73 to 1.18; p = 0.53). The composite of cardiovascular mortality, myocardial infarction, stroke, severe recurrent ischemia, transient ischemic attack, or other arterial thrombotic events occurred in 153 of 1,913 patients (8.0%) treated with ticagrelor and in 171 of 1,886 patients (9.1%) receiving clopidogrel (hazard ratio: 0.88; 95% confidence interval: 0.71 to 1.09; p = 0.25). The rates of major, fatal, and intracranial bleeding were similar between the ticagrelor and clopidogrel groups.ConclusionAmong patients age <75 years with STEMI, administration of ticagrelor after fibrinolytic therapy did not significantly reduce the frequency of cardiovascular events when compared with clopidogrel. (Ticagrelor in Patients With ST Elevation Myocardial Infarction Treated With Pharmacological Thrombolysis [TREAT]; NCT02298088)  相似文献   
34.

Purpose

To qualitatively and quantitatively compare unenhanced ultra-low-dose chest computed tomography (ULD-CT) acquired at 80 kVp and 135 kVp.

Materials and methods

Fifty-one patients referred for unenhanced chest CT were prospectively included. There were 29 men and 22 women, with a mean age of 64.7 ± 11.6 (SD) years (range: 35–91 years) and a mean body mass index of 26.2 ± 6.3 (SD) (range: 17–54.9). All patients underwent two different ULD-CT protocols (80 kVp-40 mA and 135 kVp-10 mA). Image quality of both ULD-CT examinations using a 5-level scale as well as assessability of 6 predetermined lung parenchyma lesions were blindly evaluated by three radiologists and compared using a logistic regression model. Image noise of the two protocols was compared with Wilcoxon signed-rank test.

Results

The mean dose-length product at 80 kVp and at 135 kVp were 14.7 ± 1.8 (SD) mGy.cm and 15.6 ± 1.9 (SD) mGy.cm, respectively (P < 0.001). Image noise was significantly lower at 135 kVp (58.9 ± 12.4) than at 80 kVp (74.7 ± 14.5) (P < 0.001). For all readers and for all examinations, the 135 kVp protocol yielded better image quality than 80 kVp protocol, with a mean qualitative score of 4.5 ± 0.7 versus 3.9 ± 0.8 (P < 0.001). The 135 kVp protocol was significantly more often of diagnostic quality than the 80 kvp protocol (92.3% versus 77.8%, respectively) (P < 0.001) and was less prone to image quality deterioration in obese patients. Parenchymal lesions were never better depicted on the 80 kVp protocol than with the 135 kVp protocol.

Conclusion

Unenhanced chest ULD-CT should be acquired at a high kilovoltage and low current, such as 135 kVp-10 mA, over a low kilovoltage and high current protocol.  相似文献   
35.

Purpose

The purpose of this study was to assess the potential of a deep learning model to discriminate between benign and malignant breast lesions using magnetic resonance imaging (MRI) and characterize different histological subtypes of breast lesions.

Materials and methods

We developed a deep learning model that simultaneously learns to detect lesions and characterize them. We created a lesion-characterization model based on a single two-dimensional T1-weighted fat suppressed MR image obtained after intravenous administration of a gadolinium chelate selected by radiologists. The data included 335 MR images from 335 patients, representing 17 different histological subtypes of breast lesions grouped into four categories (mammary gland, benign lesions, invasive ductal carcinoma and other malignant lesions). Algorithm performance was evaluated on an independent test set of 168 MR images using weighted sums of the area under the curve (AUC) scores.

Results

We obtained a cross-validation score of 0.817 weighted average receiver operating characteristic (ROC)-AUC on the training set computed as the mean of three-shuffle three-fold cross-validation. Our model reached a weighted mean AUC of 0.816 on the independent challenge test set.

Conclusion

This study shows good performance of a supervised-attention model with deep learning for breast MRI. This method should be validated on a larger and independent cohort.  相似文献   
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