The Role of Diffusion-Weighted Imaging Based on Maximum-Intensity Projection in Young Patients with Marked Background Parenchymal Enhancement on Contrast-Enhanced Breast MRI.

Diffusion-weighted imaging (DWI) utilizing maximum-intensity projection (MIP) was suggested as a cost-effective alternative tool without the risk of gadolinium-based contrast agents. The purpose of this study was to investigate whether DWI MIPs played a supportive role in young (≤60) patients with marked background parenchymal enhancement (BPE) on contrast-enhanced MRI (CE-MRI). The research included 1303 patients with varying degrees of BPE, and correlations between BPE on CE-MRI, the background diffusion signal (BDS) on DWI, and clinical parameters were analyzed. Lesion detection scores were compared between CE-MRI and DWI, with DWI showing higher scores. Among the 186 lesions in 181 patients with marked BPE on CE-MRI, the main lesion on MIPs of CE-MRI was partially or completely seen in 88.7% of cases, while it was not seen in 11.3% of cases. On the other hand, the main lesion on MIPs of DWI was seen in 91.4% of cases, with only 8.6% of cases showing no visibility. DWI achieved higher scores for lesion detection compared to CE-MRI. The presence of a marked BDS was significantly associated with a lower likelihood of a higher DWI score (p < 0.001), and non-mass lesions were associated with a decreased likelihood of a higher DWI score compared with mass lesions (p = 0.196). In conclusion, the inclusion of MIPs of DWI in the preoperative evaluation of breast cancer patients, particularly young women with marked BPE, proved highly beneficial in improving the overall diagnostic process.

3D Breast Cancer Segmentation in DCE-MRI Using Deep Learning With Weak Annotation.

BACKGROUND: Deep learning models require large-scale training to perform confidently, but obtaining annotated datasets in medical imaging is challenging. Weak annotation has emerged as a way to save time and effort. PURPOSE: To develop a deep learning model for 3D breast cancer segmentation in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) using weak annotation with reliable performance. STUDY TYPE: Retrospective. POPULATION: Seven hundred and thirty-six women with breast cancer from a single institution, divided into the development (N = 544) and test dataset (N = 192). FIELD STRENGTH/SEQUENCE: 3.0-T, 3D fat-saturated gradient-echo axial T1-weighted flash 3D volumetric interpolated brain examination (VIBE) sequences. ASSESSMENT: Two radiologists performed a weak annotation of the ground truth using bounding boxes. Based on this, the ground truth annotation was completed through autonomic and manual correction. The deep learning model using 3D U-Net transformer (UNETR) was trained with this annotated dataset. The segmentation results of the test set were analyzed by quantitative and qualitative methods, and the regions were divided into whole breast and region of interest (ROI) within the bounding box. STATISTICAL TESTS: As a quantitative method, we used the Dice similarity coefficient to evaluate the segmentation result. The volume correlation with the ground truth was evaluated with the Spearman correlation coefficient. Qualitatively, three readers independently evaluated the visual score in four scales. A P-value <0.05 was considered statistically significant. RESULTS: The deep learning model we developed achieved a median Dice similarity score of 0.75 and 0.89 for the whole breast and ROI, respectively. The volume correlation coefficient with respect to the ground truth volume was 0.82 and 0.86 for the whole breast and ROI, respectively. The mean visual score, as evaluated by three readers, was 3.4. DATA CONCLUSION: The proposed deep learning model with weak annotation may show good performance for 3D segmentations of breast cancer using DCE-MRI. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

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In Korea, the number of institutions providing breast MRI, as well as the number of breast MRIs, has recently increased. However, MRI-guided procedures, including biopsy and needle localization, are rarely performed compared to ultrasound-guided or stereotactic biopsy. As breast MRI has high sensitivity but limited specificity, lesions detected only on MRI require pathologic confirmation through MRI-guided biopsy or surgical excision with MRI-guided needle localization. Thus, we aimed to review MRI-guided procedures, including their indications, techniques, procedural considerations, and limitations.

Diagnostic Usefulness of Diffusion-Weighted MRI for Axillary Lymph Node Evaluation in Patients with Breast Cancer.

This study aimed to determine whether apparent diffusion coefficient (ADC) and morphological features on diffusion-weighted MRI (DW-MRI) can discriminate metastatic axillary lymph nodes (ALNs) from benign in patients with breast cancer. Two radiologists measured ADC, long and short diameters, long-to-short diameter ratio, and cortical thickness and assessed eccentric cortical thickening, loss of fatty hilum, irregular margin, asymmetry in shape or number, and rim sign of ALNs on DW-MRI and categorized them into benign or suspicious ALNs. Pathologic reports were used as a reference standard. Statistical analysis was performed using the Mann-Whitney U test and chi-square test. Overall sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy of DW-MRI were calculated. The ADC of metastatic ALNs was 0.905 × 10-3 mm2/s, and that of benign ALNs was 0.991 × 10-3 mm2/s (p = 0.243). All morphologic features showed significant difference between the two groups. The sensitivity, specificity, PPV, NPV, and diagnostic accuracy of the final categorization on DW-MRI were 77.1%, 93.3%, 79.4%, 92.5%, and 86.2%, respectively. Our results suggest that morphologic evaluation of ALNs on DWI can discriminate metastatic ALNs from benign. The ADC value of metastatic ALNs was lower than that of benign nodes, but the difference was not statistically significant.

The Frequency and Causes of Not-Detected Breast Malignancy in Dynamic Contrast-Enhanced MRI.

Breast MR is the most sensitive imaging modality, but there are cases of malignant tumors that are not detected in MR. This study evaluated the frequency and main causes of malignant breast lesions not detected in dynamic contrast-enhanced (DCE) MR. A total of 1707 cases of preoperative breast MR performed between 2020 and 2021 were included. Three radiologists individually reviewed the DCE MRs and found not-detected malignancy cases in the MRs. The final cases were decided through consensus. For the selected cases, images other than DCE MRIs, such as mammography, ultrasounds, diffusion-weighted MRs, and, if possible, contrast-enhanced chest CTs, were analyzed. In the final sample, 12 cases were not detected in DCE MR, and the frequency was 0.7% (12/1707). Six cases were not detected due to known non-enhancing histologic features. In four cases, tumors were located in the breast periphery and showed no enhancement in MR. In the remaining two cases, malignant lesions were not identified due to underlying marked levels of BPE. The frequency of not-detected malignancy in DCE MR is rare. Knowing the causes of each case and correlating it with other imaging modalities could be helpful in the diagnosis of breast malignancy in DCE MR.

Radiomics Nomogram: Prediction of 2-Year Disease-Free Survival in Young Age Breast Cancer.

This study aimed to predict early breast cancer recurrence in women under 40 years of age using radiomics signature and clinicopathological information. We retrospectively investigated 155 patients under 40 years of age with invasive breast cancer who underwent MRI and surgery. Through stratified random sampling, 111 patients were assigned as the training set, and 44 were assigned as the validation set. Recurrence-associated factors were investigated based on recurrence within 5 years during the total follow-up period. A Rad-score was generated through texture analysis (3D slicer, ver. 4.8.0) of breast MRI using the least absolute shrinkage and selection operator Cox regression model. The Rad-score showed a significant association with disease-free survival (DFS) in the training set (p = 0.003) and validation set (p = 0.020) in the Kaplan-Meier analysis. The nomogram was generated through Cox proportional hazards models, and its predictive ability was validated. The nomogram included the Rad-score and estrogen receptor negativity as predictive factors and showed fair DFS predictive ability in both the training and validation sets (C-index 0.63, 95% CI 0.45-0.79). In conclusion, the Rad-score can predict the disease recurrence of invasive breast cancer in women under 40 years of age, and the Rad-score-based nomogram showed reasonably high DFS predictive ability, especially within 2 years of surgery.

The Usefulness of Magnetic Resonance Imaging (MRI) for the Detection of Local Recurrence after Mastectomy with Reconstructive Surgery in Breast Cancer Patients.

The purpose of this study is to investigate the usefulness of magnetic resonance imaging (MRI) for the detection of local recurrence after nipple-sparing mastectomy (NSM) or skin-sparing mastectomy (SSM) with immediate reconstructive surgery for breast cancer. Two hundred and eighty-six NSM or SSM procedures and immediate reconstruction cases between August 2015 and February 2020 were reviewed. The detectability rates of for local recurrence using MRI and ultrasound were assessed, and the characteristics of recurrent and primary cancers were evaluated. The patients with multifocal or multicentric primary cancer and a dense parenchymal pattern showed a higher recurrence rate (p < 0.001). A total of 22 cases showed recurrence, and due to multifocal recurrence, a total of 27 recurrent lesions were identified in the reconstructed breast, of which 12 were symptomatic and 15 were asymptomatic (p < 0.001). With the exception of skin recurrence (n = 6), MRI showed a significantly higher detectability rate (95.2%, 20 of 21) than ultrasound (38.1%, 8 of 21) for the recurrence of cancer in the reconstructed breast (p < 0.001), especially for small-sized (<1 cm) asymptomatic lesions. In addition, the mean recurrence interval of MRI-detected asymptomatic lesions was 21.7 months (SD ± 17.7), which was significantly longer than that of symptomatic recurrence. In conclusion, postoperative MRI can be useful for identifying small-sized (<1 cm) asymptomatic recurrence lesions in reconstructed breast tissue after NSM or SSM, which can be implemented within two years of surgery.

Ipsilateral Recurrence of DCIS in Relation to Radiomics Features on Contrast Enhanced Breast MRI.

The purpose of this retrospective study was to investigate the association between ipsilateral recurrence of ductal carcinoma in situ (DCIS) and radiomics features from DCIS and contralateral normal breast on contrast enhanced breast MR imaging. A total of 163 patients with DCIS who underwent preoperative MR imaging between January 2010 and December 2014 were included (training cohort; n = 117, validation cohort; n = 46). Radiomics features were extracted from whole tumor volume of DCIS on early dynamic T1-subtraction images and from the contralateral normal breast on precontrast T1 and early dynamic T1-subtraction images. After feature selection, a Rad-score was established by LASSO Cox regression model. Performance of Rad-score was evaluated by the receiver operating characteristic (ROC) curve and Kaplan Meier curve with log rank test. The Rad-score was significantly associated with ipsilateral recurrence free survival (RFS). The low-risk group with a low Rad-score showed higher ipsilateral RFS than the high-risk group with a high Rad-score in both training and validation cohorts (p < 0.01). The Rad-score based on radiomics features from DCIS and contralateral normal breast on breast MR imaging showed the potential for prediction of ipsilateral RFS of DCIS.

Evaluation of Computer-Aided Detection (CAD) in Screening Automated Breast Ultrasound Based on Characteristics of CAD Marks and False-Positive Marks.

The present study evaluated the effectiveness of computer-aided detection (CAD) system in screening automated breast ultrasound (ABUS) and analyzed the characteristics of CAD marks and the causes of false-positive marks. A total of 846 women who underwent ABUS for screening from January 2017 to December 2017 were included. Commercial CAD was used in all ABUS examinations, and its diagnostic performance and efficacy in shortening the reading time (RT) were evaluated. In addition, we analyzed the characteristics of CAD marks and the causes of false-positive marks. A total of 1032 CAD marks were displayed based on the patient and 534 CAD marks on the lesion. Five cases of breast cancer were diagnosed. The sensitivity, specificity, PPV, and NPV of CAD were 60.0%, 59.0%, 0.9%, and 99.6% for 846 patients. In the case of a negative study, it was less time-consuming and easier to make a decision. Among 530 false-positive marks, 459 were identified clearly for pseudo-lesions; the most common cause was marginal shadowing, followed by Cooper's ligament shadowing, peri-areolar shadowing, rib, and skin lesions. Even though CAD does not improve the performance of ABUS and a large number of false-positive marks were detected, the addition of CAD reduces RT, especially in the case of negative screening ultrasound.

Retrospective Review of Missed Cancer Detection and Its Mammography Findings with Artificial-Intelligence-Based, Computer-Aided Diagnosis.

To investigate whether artificial-intelligence-based, computer-aided diagnosis (AI-CAD) could facilitate the detection of missed cancer on digital mammography, a total of 204 women diagnosed with breast cancer with diagnostic (present) and prior mammograms between 2018 and 2020 were included in this study. Two breast radiologists reviewed the mammographic features and classified them into true negative, minimal sign or missed cancer. They analyzed the AI-CAD results with an abnormality score and assessed whether the AI-CAD correctly localized the known cancer sites. Of the 204 cases, 137 were classified as true negative, 33 as minimal signs, and 34 as missed cancer. The sensitivity, specificity and diagnostic accuracy of AI-CAD were 84.7%, 91.5% and 86.3% on diagnostic mammogram and 67.2%, 91.2% and 83.38% on prior mammogram, respectively. The AI-CAD correctly localized 27 cases from 34 missed cancers on prior mammograms. The findings in the preceding mammography of AI-CAD-detected missed cancer were common in the order of calcifications, focal asymmetry and asymmetry. Asymmetry was the most common finding among the seven cases, which could not be detected by AI-CAD in the missed cases (5/7). The assistance of AI-CAD can be helpful in the early detection of breast cancer in mammography screenings.

Risk Stratification of Ductal Carcinoma In Situ and Texture Analysis of Contrast-Enhanced Breast Magnetic Resonance Imaging.

OBJECTIVE: The aim of this study was to investigate whether texture analysis of contrast-enhanced T1 weighted images could predict risk of ductal carcinoma in situ (DCIS). METHODS: The study included 185 DCIS lesions that were classified as either low risk or non-low risk using surgical pathology records. All magnetic resonance imaging texture analyses were performed using postprocessing software, and texture-derived parameters were extracted. RESULTS: The sphericity, compactness, and spherical disproportion were significantly different in the low-risk and non-low risk groups using the Van Nuys Prognostic Index (mean ± SD, 0.479 ± 0.189 vs 0.414 ± 0.176, 0.161 ± 0.159 vs 0.112 ± 0.134, and 2.569 ± 1.434 vs 2.934 ± 1.374, respectively; P < 0.05). In the univariate analyses, sphericity (odds ratio, 7.091; 95% confidence interval, 1.236-40.666; P = 0.028) and compactness (odds ratio, 9.267; 95% confidence interval, 1.125-76.360; P = 0.039) were significantly associated with a high probability of being low risk according to the Van Nuys Prognostic Index. CONCLUSIONS: Whole-lesion texture analysis may be helpful in identifying patients classified as having low-risk DCIS before surgery.

Correlation between antibiotic consumption and the incidence of healthcare facility-onset Clostridioides difficile infection: a retrospective chart review and analysis.

BACKGROUND: Healthcare facility-onset Clostridioides difficile infection is the leading cause of antibiotic-associated diarrhea, and is associated with morbidity and mortality. The use of antibiotics is an important risk factor for healthcare facility-onset C. difficile infection. We evaluated the correlation between the incidence of healthcare facility-onset C. difficile infection and antibiotic consumption, according to antibiotic class. METHODS: Patients with healthcare facility-onset C. difficile infection from January 2017 to December 2018 at Konkuk University Medical Center (a tertiary medical center) were included. We evaluated changes in the incidence of healthcare facility-onset C. difficile infection and antibiotic consumption. The correlation between the incidence of healthcare facility-onset C. difficile infection and antibiotic consumption was evaluated two ways: without a time interval and with 1-month interval matching. RESULTS: A total of 446 episodes of healthcare facility-onset C. difficile infection occurred during the study period. The incidence of healthcare facility-onset C. difficile infection was 9.3 episodes per 10,000 patient-days, and increased significantly. We observed an increase in the consumption of ß-lactam/ß-lactamase inhibitors, and a decrease in the consumption of other classes of antibiotics, with a significant decrease in the consumption of fluoroquinolones, glycopeptides, and clindamycin (P = 0.01, P < 0.001, and P = 0.001, respectively). The consumption of ß-lactam/ß-lactamase inhibitors was independently correlated with the incidence of healthcare facility-onset C. difficile infection in the analysis without a time interval. When the analysis was conducted with 1-month interval matching, glycopeptide consumption was independently associated with the incidence of healthcare facility-onset C. difficile infection. CONCLUSIONS: Despite the reduction in fluoroquinolone and clindamycin consumption, the incidence of healthcare facility-onset C. difficile infection increased during the study period, and was correlated with increased consumption of ß-lactam/ß-lactamase inhibitors. Reduced consumption of specific antibiotics may be insufficient to reduce the incidence of healthcare facility-onset C. difficile infection.

A COVID-19 Exposure at a Dental Clinic Where Healthcare Workers Routinely Use Particulate Filtering Respirators.

Asymptomatic/mildly symptomatic coronavirus disease 2019 (COVID-19) patients produce a considerable amount of virus and transmit severe acute respiratory syndrome virus 2 (SARS-CoV-2) through close contact. Preventing in-hospital transmission of SARS-CoV-2 is challenging, since symptom-based screening protocols may miss asymptomatic/mildly symptomatic patients. In particular, dental healthcare workers (HCWs) are at high risk of exposure, as face-to-face contact and exposure to oral secretions is unavoidable. We report exposure of HCWs during dental procedures on a mild symptomatic COVID-19 patient. A 32-year-old male visited a dental clinic at a tertiary care hospital. He experienced mild cough, which started three days before the dental visit, but did not report his symptom during the entrance screening. He underwent several dental procedures and imaging for orthognathic surgery without wearing a mask. Seven HCWs were closely exposed to the patient during dental procedures that could have generated droplets and aerosols. One HCW had close contact with the patient during radiologic exams, and seven HCWs had casual contact. All HCWs wore particulate filtering respirators with 94% filter capacity and gloves, but none wore eye protection or gowns. The next day, the patient experienced dysgeusia and was diagnosed with COVID-19 with high viral load. All HCWs who had close contact with the patient were quarantined for 14 days, and polymerase chain reaction and antibody tests for SARS-CoV-2 were negative. This exposure event suggests the protective effect of particulate filtering respirators in dental clinics. The recommendations of different levels of personal protective equipment (PPE) for dental HCWs according to the procedure types should be established according to the planned procedure, the risk of COVID-19 infection of the patient, and the outbreak situation of the community.

Impact of antiviral treatment on long-term prognosis in non-immunocompromised patients with CMV reactivation.

BACKGROUND: Reactivation of human cytomegalovirus (CMV) occurs in non-immunocompromised patients with or without specific organ involvement, but it is still unknown whether it has a clinical implication on long-term prognosis or not. METHODS: A retrospective cohort study evaluating non-immunocompromised adult patients with CMV reactivation was conducted during the period between January 2010 and February 2018. Patients were divided into ganciclovir-treated and non-treated groups. Patients who died within 30 days from CMV reactivation were excluded as they died from complex causes of conditions. Survivors were followed for 30-months to evaluate long-term prognosis. RESULTS: A total of 136 patients with CMV reactivation was included, consisting of 66 ganciclovir-treated (48.5%) and 70 non-treated (51.5%) patients. Overall, patients were old-aged (median 70 years old) and most were treated with pneumonia of any cause (91.2%). More patients in ganciclovir-treated group were treated at intensive care unit (43.9% vs 24.3%, respectively) and had higher viral load over 5000 copies/ml (48.5% vs 22.9%) than non-treated group (all P < 0.05). Primary and secondary endpoints including 30-months survival (28.0 vs 38.9%, respectively) and 12-months survival (40.3% vs 49.2%) were not statistically different between the ganciclovir-treated and non-treated groups. In the multivariate analyses, ganciclovir treatment was not associated with 30-months survival (HR 1.307, 95% CI 0.759-2.251) and 12-months survival (HR 1.533, 95% CI 0.895-2.624). CONCLUSION: In a retrospective cohort study evaluating non-immunocompromised patients with CMV reactivation, ganciclovir treatment was not associated with long-term prognosis. Antiviral treatment in this condition would not be necessary unless organ involvement is suspected.

Clinical Impact of Revised Ciprofloxacin Breakpoint in Patients with Urinary Tract Infections by Enterobacteriaceae.

In 2018, the Clinical and Laboratory Standards Institute (CLSI) revised ciprofloxacin (CIP)-susceptible breakpoint for Enterobacteriaceae from ≤1 µg/mL to ≤0.25 µg/mL, based on pharmacokinetic-pharmacodynamic (PK-PD) analysis. However, clinical data supporting the lowered CIP breakpoint are insufficient. This retrospective cohort study evaluated the clinical outcomes of patients with bacteremic urinary tract infections (UTIs) caused by Enterobacteriaceae, which were previously CIP-susceptible and changed to non-susceptible. Bacteremic UTIs caused by Enterobacteriaceae with CIP minimal inhibitory concentration (MIC) ≤ 1 µg/mL were screened, and then patients treated with CIP as a definitive treatment were finally included. Patients in CIP-non-susceptible group (MIC = 0.5 or 1 µg/mL) were compared with patients in CIP-susceptible group (MIC ≤ 0.25 µg/mL). Primary endpoints were recurrence of UTIs within 4 weeks and 90 days. A total of 334 patients were evaluated, including 282 of CIP-susceptible and 52 of CIP-non-susceptible. There were no significant differences in clinical outcomes between two groups. In multivariate analysis, CIP non-susceptibility was not associated with recurrence of UTIs. CIP non-susceptibility based on a revised CIP breakpoint, which was formerly susceptible, was not associated with poor clinical outcomes in bacteremic UTI patients were treated with CIP, similar to those of the susceptible group. Further evaluation is needed to guide the selection of definitive antibiotics for UTIs.

Fully Automatic Assessment of Background Parenchymal Enhancement on Breast MRI Using Machine-Learning Models.

BACKGROUND: Automated measurement and classification models with objectivity and reproducibility are required for accurate evaluation of the breast cancer risk of fibroglandular tissue (FGT) and background parenchymal enhancement (BPE). PURPOSE: To develop and evaluate a machine-learning algorithm for breast FGT segmentation and BPE classification. STUDY TYPE: Retrospective. POPULATION: A total of 794 patients with breast cancer, 594 patients assigned to the development set, and 200 patients to the test set. FIELD STRENGTH/SEQUENCE: 3T and 1.5T; T2 -weighted, fat-saturated T1 -weighted (T1 W) with dynamic contrast enhancement (DCE). ASSESSMENT: Manual segmentation was performed for the whole breast and FGT regions in the contralateral breast. The BPE region was determined by thresholding using the subtraction of the pre- and postcontrast T1 W images and the segmented FGT mask. Two radiologists independently assessed the categories of FGT and BPE. A deep-learning-based algorithm was designed to segment and measure the volume of whole breast and FGT and classify the grade of BPE. STATISTICAL TESTS: Dice similarity coefficients (DSC) and Spearman correlation analysis were used to compare the volumes from the manual and deep-learning-based segmentations. Kappa statistics were used for agreement analysis. Comparison of area under the receiver operating characteristic (ROC) curves (AUC) and F1 scores were calculated to evaluate the performance of BPE classification. RESULTS: The mean (±SD) DSC for manual and deep-learning segmentations was 0.85 ± 0.11. The correlation coefficient for FGT volume from manual- and deep-learning-based segmentations was 0.93. Overall accuracy of manual segmentation and deep-learning segmentation in BPE classification task was 66% and 67%, respectively. For binary categorization of BPE grade (minimal/mild vs. moderate/marked), overall accuracy increased to 91.5% in manual segmentation and 90.5% in deep-learning segmentation; the AUC was 0.93 in both methods. DATA CONCLUSION: This deep-learning-based algorithm can provide reliable segmentation and classification results for BPE. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2.

Clinical Benefits of Piperacillin/Tazobactam versus a Combination of Ceftriaxone and Clindamycin in the Treatment of Early, Non-Ventilator, Hospital-Acquired Pneumonia in a Community-Based Hospital.

PURPOSE: There is an increasing prevalence of multidrug-resistant (MDR) organisms worldwide. Therefore, broad-spectrum antibiotics are recommended in the treatment of hospital-acquired pneumonia (HAP). However, it remains controversial whether patients with early onset, non-ventilator HAP (NV-HAP) should also be empirically treated with broad-spectrum antibiotics. We compared the clinical benefit of ceftriaxone plus clindamycin vs piperacillin/tazobactam as the initial empirical treatment of adults with early NV-HAP. PATIENTS AND METHODS: Retrospective cohort study was conducted in adult patients who were diagnosed with early, NV-HAP between January 2013 and June 2017 at a community-based tertiary care hospital. Patients were eligible for inclusion if they had received empiric treatment with either ceftriaxone and clindamycin or piperacillin/tazobactam for at least 3 days. Patients with increased risk of MDR pathogens were excluded. RESULTS: A total of 89 patients were treated with ceftriaxone and clindamycin, while 124 received piperacillin/tazobactam. There were no significant differences between the two antibiotic groups with regard to median age, sex, or risk of pneumonia. The 30-day all-cause mortality did not differ significantly between the ceftriaxone plus clindamycin and piperacillin/tazobactam groups (4.5% vs 1.6%, P=0.202, respectively). However, in multivariate analysis, clinical failure was more frequent in the ceftriaxone plus clindamycin group than in the piperacillin/tazobactam group (HR 3.316; 95% CI, 1.589-6918, P=0.001). CONCLUSION: Treatment with piperacillin/tazobactam was more effective than that with ceftriaxone plus clindamycin in patients with early NV-HAP. This study supports the recent treatment recommendations that patients with early NV-HAP should be treated empirically with broad-spectrum antibiotics.

Clinical factors influencing the performance of bacterial multiplex polymerase chain reaction in patients with community-onset pneumonia.

The etiologic diagnostic yield of community-onset pneumonia (COP) using conventional methods is low. Bacterial multiplex polymerase chain reaction (mPCR) has been shown to be more sensitive than conventional methods. This study assessed the clinical factors influencing bacterial mPCR results in patients with COP. Patients with COP admitted to a tertiary care hospital between November 2015 and April 2016 were retrospectively assessed. Conventional methods included culture-based methods and serology for Mycoplasma pneumoniae. Bacterial mPCR that could identify Streptococcus pneumoniae, Haemophilus influenzae, Mycoplasma pneumoniae, and Legionella pneumophilia was performed. Bacterial mPCR was performed in a total of 342 patients with COP in the study. Bacterial mPCR alone provided etiology in 99 patients. The total etiologic diagnosis rates improved from 22.2 to 51.1% when bacterial mPCR was added to conventional methods. Additional diagnostic benefits of bacterial mPCR were more prominent in the prior antibiotic non-exposure group (77.8% vs 63.5%, P = 0.015) and in the low-risk group with low CURB 65 score (62.6% vs 44.9%, P = 0.005). Patients who required ICU care, those with healthcare-associated pneumonia (HCAP), and patients with any underlying diseases were not associated with the additional pathogen detection rates using bacterial mPCR. By supplementing conventional diagnostic methods with bacterial mPCR-based methods, the overall pathogen detection rates improved in patients with COP. Moreover, the additional diagnostic usefulness of bacterial mPCR was significantly higher in patients without prior antibiotic exposure and in the mild-to-moderate-risk group with lower CURB 65 score.

Infectious Complications in Patients Who Received High-Volume Plasma Exchange Prior to Liver Transplant: A Case Report.

Acute liver failure is a rare but life-threatening medical emergency. Despite advancements in medical management, mortality rates of acute liver failure remain high. Currently, liver transplant is the only definitive therapeutic option available. High-volume plasma exchange has been shown to increase transplant-free survival in patients with acute liver failure before liver transplant. However, the occurrence of infectious complications in patients who receive this treatment has not been well studied. We report 2 cases of severe opportunistic infections occurring within 30 days of transplant in patients who underwent high-volume plasma exchange before liver transplant.