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Objectives
This study reported a hospital outbreak due to an extensively drug-resistant (XDR) OXA-72-producing strain of Acinetobacter baumannii (A. baumannii).Methods and Results
The isolates were found to be genotypically indistinguishable by whole-genome multiple locus sequence typing, and to belong to the international clonal complex CC2. One of these isolates sequentially developed a high resistance to colistin and rifampicin under treatment, as a result of mutations in genes pmrB and rpoB, respectively. The blaOXA-72 gene was localised on a 10-kb transferable plasmid, named pAB-STR-1, whose sequence is nearly identical to that of another plasmid previously found in Lithuanian strains, pAB120.Conclusion
This report highlighted the need to carefully monitor the emergence of colistin and rifampicin resistance in patients treated for infections with multidrug-resistant A. baumannii. 相似文献Methods: Attributes were defined from a literature search, clinician and patient interviews: shape, dose insertion, dose preparation, dose release, dose confirmation, dose counter and reusability. An online DCE was conducted in respondents with self-reported COPD stage 2–4 recruited through a panel. The study questionnaire included twelve choice scenarios per respondent and questions on patient characteristics, treatment and disease severity. Statistical analyses used a mixed logit regression model with random effects. Utility scores were estimated for four types of inhalers: Inhaler A – soft mist inhaler; Inhaler B – reusable soft mist inhaler; Inhaler C – multi-dose dry powder inhaler; and Inhaler D – single dose dry powder inhaler.
Results: The study was completed by 153 patients (50 females); respondents were 50.4?years old on average; 13 different inhaler devices were reported. The most preferred inhaler is L-shaped, has dose preparation with capsule insertion and a dose counter, and is reusable. Inhaler profiles A and B had the highest utilities (mean of 1.2533 and 0.9578 respectively) compared to inhaler C (0.6315) and D (0.2200).
Conclusions: This study showed statistically significant results that the strongest drivers of preference in French users of inhalation devices for COPD are shape, dose counter and reusability. Convenience-related characteristics are important to patients and should be taken into account by clinicians prescribing these devices. 相似文献
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- Download : Download high-res image (184KB)
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