Carbapenem-resistantEnterobacteriaceaeconferred by New Delhi metallo-b-lactamase (NDM-1) resistance mechanism are endemic in India and Southeast Asia. An understanding of risk factors for NDM-1 infections is necessary to guide prevention strategies. We performed a retrospective case-control study of patients admitted at Christian Medical College Hospital, Vellore, India between May 2010 and August 2014 withKlebsiella pneumoniaeblood stream infection (BSI). We compared patients with BSI caused by NDM-1 producing strains to two control groups: BSI with other multidrug resistant (MDR) strains and BSI with pan-susceptible strains. The study groups were assessed for risk factors for the outcomes: (1) infection with any MDR strain compared to pan-susceptible; and, (2) infection with NDM-1 strain as compared with other MDR and (3) Mortality. A total of 101 patients with BSI with NDM-1 producingKlebsiella pneumoniaewere matched to two groups of controls: 112 with non-NDM-1 MDR strains and 101 with pan-susceptible strains. Medical (OR 10.4) and neonatal (OR 0.7) ICU admission, central venous catheter placement (CVC, OR 7.4) predicted MDR BSI. Prior carbapenem use (OR 8.4) and CVC (OR 4.8) predicted acquisition of an NDM-1 strain. Significant predictors for mortality included ICU stay (OR 3.0), mechanical ventilation (OR 3.2), female gender (OR 2.2), diabetes (OR 0.4). CVC placement, prior carbapenem use and ICU admission were significantly associated with BSI with NDM-1 producing and other MDR strains.
Conclusion:The antibiotic susceptibility pattern of bacterial pathogen like P. aeruginosa in the hospital settings should be continuously monitored and the results readily made available to clinicians so as to maximize the possibility of administering an effective therapeutic agent whenever needed.http://dx.Background: Carbapenem resistance conferred by New Delhi metallo-lactamase 1 (NDM-1) is an increasing global public health problem and defining risk factors for acquisition of infections with NDM-1 containing organisms is urgently needed for its control. Methods & Materials:We investigated the patient and hospital related risk factors for acquisition of in patients at CMC Hospital infected with invasive Klebsiella pneumoniae with and without NDM-1. This was a retrospective case-control study of patients admitted at CMC Hospital, Vellore between Oct 2009 and Sept 2014, with blood culture + invasive Klebsiella pneumonia that were NDM-1 + (case), NDM-1 -ESBL + (ESBL + control), or NDM-1 -ESBL -(ESBLcontrol). Cases and controls were matched on date of admission ± 45 days.Results: There were 101 NDM-1 + cases, and 100 ESBL + and 101 ESBL -controls, with little difference in mean ages: 31.20±22.94, 29.78±23.30, and 41.55±21.11, respectively. NDM-1 + subjects were more likely to have received antibiotics in the last 180 days than either the ESBL + ]; P= .253) or ESBL - ; P = 0.124) controls, and were more likely to have acquired the infection nosocomially than the ESBL + ; P = 0.131) and ESBL -(OR= 3.390 [1.808-6.329]; P = <0.001). NDM-1 + patients were more likely than ESBL + (OR =2.114 [1.202-3.719]; P = 0.01) and ESBL -(OR =1.910 [1.088-3.352]; P = 0.024) to have been admitted to the ICU. The Case Fatality Ratio (CFR) was significantly higher in NDM-1 + patients than in ESBL + (2.26; P <0.001) and ESBL -(3.8 P <0.001). The mean length of hospital stay for NDM-1 + patients was 31.30±31.827, and was significantly higher in than in ESBL + (23.21±17.252; P = 0.001) and ESBL -(19.68±18.55; P =0.002).Conclusion: NDM-1 + K.pneumoniae invasive infections are as likely to be aquired in the community as nosocomially but in the latter circumstance are more likely to be aquired in the ICU.The CFR of 52% is twice that of ESBL + invasive Klebsiella.
The Oncotype DX (ODX) is a 21 panel gene-expression based assay for identifying which Estrogen Receptor-positive (ER+) breast cancer (BCa) patients are candidates for adjuvant chemotherapy. The objective of this research was to identify whether computerized texture features on a staging DCE-MRI can distinguish ER+ BCa with low and high ODX recurrence scores (RS) (i.e. to distinguish which ER+ BCa patients are more likely to benefit from adjuvant hormonal therapy from those who require chemotherapy). This would provide a non-invasive, imaging based, pre-therapeutic assessment tool for predicting the appropriate treatment regimen. This work, to the best of our knowledge, is the first attempt to quantitatively correlate low versus high risk stratification via computer derived MRI measurements to corresponding risk stratification via the ODX assay. 52 ER+ BCa patient studies with high (>30, N = 28) and low (<18, N = 24) ODX RS were available for this study from two sites; 16 breast MRIs from the Boston Medical Center using a Phillips 1.5T magnet with a 7-channel breast coil, and 36 MRIs from the Case Medical Center using a Siemens 1.5T magnet with a 8-channel breast coil. All datasets included T1w images obtained prior to, during, and after administration of 0.1 mmol/kg of Gd-DTPA and corresponding ODX RS. For each study a radiologist picked a representative slice showing the tumor and then manually segmented the region of interest (ROI) containing the lesion. Computerized image analysis tools developed in-house via the MATLAB© programming platform were applied to the manually segmented lesion ROI for each of the 52 MRI studies to quantitatively characterize the lesion via a set of (a) 6 shape, (b) 3 pharmacokinetic (Ktrans, ve, kep) based on Tofts model (PK), (c) 12 enhancement kinetic (EK), (d) 12 intensity kinetic (IK), (e) 312 textural kinetic (TK), (f) 6 dynamic local binary pattern (DLBP), and (g) 5 dynamic histogram of oriented gradient (DHoG) features. The computer extracted features were evaluated via a linear discriminant analysis (LDA) classifier in terms of their ability to distinguish ER+ BCa as having a low or high ODX RS via a 2-fold randomized cross validation scheme. At each iteration, half of the studies were randomly selected from the 52 cases and used for training the LDA classifier and the remaining 26 studies were used for independent testing. This process was repeated 200 times. Classification performance was evaluated by area under the ROC curve (AUC). Higher AUC values suggest a stronger relationship between risk stratification via MRI attributes and ODX. Table 1Feature classAccuracy (μ±Δ)AUC (μ±Δ)DHoG87.07%±5.66%0.89±0.04DLBP85.86%±7.82%0.83±0.07EK82.36%±8.46%0.80±0.06PK81.14%±7.55%0.78±0.07TK75.93%±6.65%0.76±0.08IK76.43%±7.23%0.75±0.12Shape71.04%±6.81%0.70±0.06 Table 1 illustrates the mean and standard deviation in accuracy and AUC values over 200 runs of randomized cross validation. DHoG, DBLP and EK features yielded the highest classification accuracy and AUC. Although lesion shape has been shown to be important for discriminating benign and malignant lesions on MRI, shape appears to be less useful in distinguishing between ER+ BCa lesions with low and high ODX RS. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P2-02-12.
Oncotype DX (ODX) is a 21 panel gene-expression based assay for predicting whether patients with estrogen receptor-positive (ER+) breast cancer (BCa) are candidates for adjuvant chemotherapy. However, the time and expense associated with genomic assays suggests the need for a non-invasive, imaging-based, pre-therapeutic tool for assessment of disease risk and selection of an appropriate treatment regimen. The objective of this research was to determine whether (a) computer extracted image features on T2-weighted (T2w) MRI and H&E stained histopathology are independently able to distinguish ER+ BCa with low and high ODX recurrence scores (RS) and (b) to determine whether there is a correlation between MRI and histologic features identified as being predictive of low and high ODX risk categories. A total of 11 ER+ BCa patients were considered in this study, based on availability of in vivo 1.5 Tesla T2w MRI. For each study, the corresponding formalin-fixed paraffin-embedded H&E stained tissue specimens were digitized at 20x (0.5 μm/pixel) using a whole-slide scanner. Of the 11 patients, 8 were identified in the low ODX (RS < 18) and 3 in the high ODX (RS > 30) risk categories. Each dataset was accompanied by expert annotations of (a) the lesion ROI on MRI and (b) boundaries of epithelial nuclei from a representative field-of-view on the digitized histology slide. For each MRI study, a multi-scale, multi-orientation Gabor filter bank was convolved with the annotated lesion area providing a set of 192 texture features (FMRI). For each corresponding histology image, 471 features (FHIST) were extracted describing both nuclear morphology (NM) and Laws texture (LT) within the nuclear regions. Independent 2-sample t-tests were used to identify salient features in FMRI and FHIST that are able to distinguish low and high ODX risk categories. We found that, for the MRI dataset, Gabor texture features at several scales and orientations yielded salient features (p < 0.05) while on histopathology, nuclear texture and convexity (shape) features were identified as the top discriminative features (p < 0.01). Relationships between significant features were evaluated via Spearman's rank correlation test (see table), where high correlations were observed between lesion texture on T2w MRI and nuclear texture and shape on histology. Correlation of histologic and MRI features able to distinguish low and high ODX RSHistologic feature correlated with ODXMRI feature correlated with ODXCorrelation coefficient (ρ)p-valueLT: 70 Mean HSVGF: Scale 2: Orientation 3: min/max-0.85450.0008NM: ConvexityGF: Scale 5: Orientation 6: mean-0.85450.0008LT: 70 Mean HSVGF: Scale 2: Orientation 3: min/max-0.83640.0013LT: 70 Mean HSVGF: Scale 3: Orientation 8: mean-0.83640.0013LT: 70 Mean HSVGF: Scale 3: Orientation 2: mean-0.81820.0021 Our results suggest that quantitative features extracted on both T2w MRI and histopathology can independently distinguish between low and high risk ODX classes. Moreover, some of these MRI and histologic features appear to be significantly correlated, suggesting that information regarding tumor biology is reflected in both MRI and histologic image features. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P2-03-01.
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