Ipsilateral avid axillary lymph node uptake at FDG PET/CT persists in 29% (49 of 169) of patients between 7 to 10 weeks after the second dose of the mRNA-based BNT162b2 COVID-19 vaccination.
Bloodstream infections (BSI) represent a serious bacterial infection with substantial morbidity and mortality. Population-based studies demonstrate an increased incidence, especially among elderly ...patients. Controversy exists regarding whether presentation of BSI are different in older patients compared to younger patients; our narrative review of the literature suggests that BSI in elderly patients would probably include one or more of the traditional symptoms/signs of fever, severe sepsis or septic shock, acute kidney injury, and/or leukocytosis. Sources of BSI in older adults are most commonly the urinary tract (more so than in younger adults) and the respiratory tract. Gram-negative bacteria are the most common isolates in the old (~ 40–60% of BSI); isolates from the elderly patient population show higher antibiotic resistance rates, with long-term care facilities serving as reservoirs for multidrug-resistant bacteria. BSI entail significantly higher rates of mortality in older age, both short and long term. Some of the risk factors for mortality are modifiable, such as the appropriateness of empirical antibiotic therapy and nosocomial acquisition of infection. Health-related quality of life issues regarding the elderly patient with BSI are not well addressed in the literature. Utilization of comprehensive geriatric assessment and comprehensive geriatric discharge planning need to be investigated further in this setting and might serve as key for improved results in this population. In this review, we address all these aspects of BSI in old patients with emphasis on future goals for management and research.
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EMUNI, FZAB, GEOZS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
This study's aim is to describe the imaging findings in pregnant patients undergoing emergent MRI for suspected acute appendicitis, and the various alternative diagnoses seen on those MRI scans. This ...is a single center retrospective analysis in which we assessed the imaging, clinical and pathological data for all consecutive pregnant patients who underwent emergent MRI for suspected acute appendicitis between April 2013 and June 2021. Out of 167 patients, 35 patients (20.9%) were diagnosed with acute appendicitis on MRI. Thirty patients (18%) were diagnosed with an alternative diagnosis on MRI: 17/30 (56.7%) patients had a gynecological source of abdominal pain (e.g. ectopic pregnancy, red degeneration of a leiomyoma); 8 patients (26.7%) had urological findings such as pyelonephritis; and 6 patients (20%) had gastrointestinal diagnoses (e.g. abdominal wall hernia or inflammatory bowel disease). Our conclusions are that MRI is a good diagnostic tool in the pregnant patient, not only in diagnosing acute appendicitis, but also in providing information on alternative diagnoses to acute abdominal pain. Our findings show the various differential diagnoses on emergent MRI in pregnant patients with suspected acute appendicitis, which may assist clinicians and radiologists is patient assessment and imaging utilization.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Although regulatory changes towards correcting the underrepresentation of women in randomized controlled trials (RCTs) occurred (National Institutes of Health 1994), concerns exist about whether an ...improvement is taking place. In this systematic review and meta-analysis, we aimed to assess the inclusion rates of women in recent RCTs and to explore the potential barriers for the enrollment of women.
RCTs published in 2017 examining any type of intervention in adults were searched in PubMed and Cochrane Library. The following predefined medical fields were included: cardiovascular diseases, neoplasms, endocrine system diseases, respiratory tract diseases, bacterial and fungal infections, viral diseases, digestive system diseases, and immune system diseases. Studies were screened independently by two reviewers, and an equal number of studies was randomly selected per calendric month. The primary outcome was the enrollment rate of women, calculated as the number of randomized women patients divided by the total number of randomized patients. Rates were weighted by their inverse variance; statistical significance was tested using general linear models (GLM).
Out of 398 RCTs assessed for eligibility, 300 RCTs were included. The enrollment rate of women in all the examined fields was lower than 50%, except for immune system diseases median enrollment rate of 68% (IQR 46 to 81). The overall median enrollment rate of women was 41% (IQR 27 to 54). The median enrollment rate of women decreased with older age of the trials' participants mean age of trials' participants ≤ 45 years: 47% (IQR 30-64), 46-55 years: 46% (IQR 33-58), 56-62 years: 38% (IQR 27-50), ≥ 63 years: 33% (IQR 20-46), p < 0.001. Methodological quality characteristics showed no significant association with the enrollment rates of women. Out of the 300 included RCTs, eleven did not report on the number of included women. There was no significant difference between these studies and the studies included in the analysis.
Women are being inadequately represented, in the selected medical fields analyzed in our study, in recent RCTs. Older age is a potential barrier for the enrollment of women in clinical trials. Low inclusion rates of elderly women might create a lack of crucial knowledge in the adverse effects and the benefit/risk profile of any given treatment. Factors that might hinder the participation of women should be sought and addressed in the design of the study.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Vaccines have changed modern medicine, and are a mainstay in reducing morbidity and mortality from infections. Our research group recently published a study in which we found that vaccines approved ...by the US Food and Drugs Administration were safe with few clinically important post-approval adverse effects. The current COVID-19 pandemic presents regulators with the unprecedented challenge of balancing a public demand for the rapid development and approval of a safe and effective SARS-CoV-2 vaccine without compromising the strict pre-marketing requirements used for previous vaccines. Here, we review the approval process and safety profiles of FDA approved vaccines and discuss some of the challenges currently facing the FDA regarding the SARS-CoV-2 vaccine approval.
Objectives
To evaluate if radiomics with machine learning can differentiate between F-18-fluorodeoxyglucose (FDG)-avid breast cancer metastatic lymphadenopathy and FDG-avid COVID-19 mRNA ...vaccine–related axillary lymphadenopathy.
Materials and methods
We retrospectively analyzed FDG-positive, pathology-proven, metastatic axillary lymph nodes in 53 breast cancer patients who had PET/CT for follow-up or staging, and FDG-positive axillary lymph nodes in 46 patients who were vaccinated with the COVID-19 mRNA vaccine. Radiomics features (110 features classified into 7 groups) were extracted from all segmented lymph nodes. Analysis was performed on PET, CT, and combined PET/CT inputs. Lymph nodes were randomly assigned to a training (
n
= 132) and validation cohort (
n
= 33) by 5-fold cross-validation. K-nearest neighbors (KNN) and random forest (RF) machine learning models were used. Performance was evaluated using an area under the receiver-operator characteristic curve (AUC-ROC) score.
Results
Axillary lymph nodes from breast cancer patients (
n
= 85) and COVID-19-vaccinated individuals (
n
= 80) were analyzed. Analysis of first-order features showed statistically significant differences (
p
< 0.05) in all combined PET/CT features, most PET features, and half of the CT features. The KNN model showed the best performance score for combined PET/CT and PET input with 0.98 (± 0.03) and 0.88 (± 0.07) validation AUC, and 96% (± 4%) and 85% (± 9%) validation accuracy, respectively. The RF model showed the best result for CT input with 0.96 (± 0.04) validation AUC and 90% (± 6%) validation accuracy.
Conclusion
Radiomics features can differentiate between FDG-avid breast cancer metastatic and FDG-avid COVID-19 vaccine–related axillary lymphadenopathy. Such a model may have a role in differentiating benign nodes from malignant ones.
Key Points
• Patients who were vaccinated with the COVID-19 mRNA vaccine have shown FDG-avid reactive axillary lymph nodes in PET-CT scans.
• We evaluated if radiomics and machine learning can distinguish between FDG-avid metastatic axillary lymphadenopathy in breast cancer patients and FDG-avid reactive axillary lymph nodes.
• Combined PET and CT radiomics data showed good test AUC (0.98) for distinguishing between metastatic axillary lymphadenopathy and post-COVID-19 vaccine–associated axillary lymphadenopathy. Therefore, the use of radiomics may have a role in differentiating between benign from malignant FDG-avid nodes.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, VSZLJ, ZAGLJ
To evaluate the significance of sonographic perinephric fluid collection on the emergent management of patients with acute urinary stone obstruction.
We conducted a prospective study with ...retrospective analysis. Since January 2016 through July 2017, patients admitted to our tertiary hospital's emergency department (ED) with suspected symptomatic urinary stones underwent ultrasound evaluation. Images were prospectively interpreted by experienced radiologist who analyzed each case for the following imaging features: hydronephrosis, perinephric fluid and urethral stone identification. The presence and measurements of perinephric fluid were re-evaluated by second radiologist who was blinded for the first reader's measurements. Retrospective analysis was conducted to evaluate for an association between perinephric fluid collection and the following outcome variables: need for analgesics, the number of doses of analgesics and the amount of morphine (mg) in the ED, elevation of creatinine levels, hospitalization and need for urological interventions.
The need for analgesics, the number of doses of analgesics and the amount of morphine were significantly associated with the presence of perinephric fluid (p < 0.05). The odds ratio for the need for analgesics was 3.8 in the presence of any perinephric fluid, and 8.9 in the presence of moderate/severe perinephric fluid. No other patient outcome variables were found to be significantly associated with the presence of perinephric fluid (p > 0.05).
This study shows a correlation between sonographic evidence of perinephric fluid and more severe pain. Therefore, an emergency physician can consider the evidence of perinephric fluid, in acute urethral stone obstruction, a predictor for more severe pain.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
18 F-FDG, the most commonly used PET radiopharmaceutical in clinical practice, can also accumulate in inflammatory and infectious conditions. This may account for false-positive PET findings when ...staging or restaging a patient with malignancy. As clinical use of FDG-PET-CT is increasing, nuclear medicine physicians are encountering a myriad of cutaneous and subcutaneous lesions, many of which are incidental and benign. The most common cause for the FDG avidity of these lesions is inflammation. Although a specific diagnosis may not always be possible, background clinical history and morphologic features of the lesion on CT may help narrow the differential diagnosis. This article aims to familiarize nuclear medicine physicians and radiologists with various benign cutaneous and subcutaneous conditions encountered in routine clinical practice.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Purpose
Natural language processing (NLP) can be used for automatic flagging of radiology reports. We assessed deep learning models for classifying non-English head CT reports.
Methods
We ...retrospectively collected head CT reports (2011–2018). Reports were signed in Hebrew. Emergency department (ED) reports of adult patients from January to February for each year (2013–2018) were manually labeled. All other reports were used to pre-train an embedding layer. We explored two use cases: (1) general labeling use case, in which reports were labeled as normal vs. pathological; (2) specific labeling use case, in which reports were labeled as with and without intra-cranial hemorrhage. We tested long short-term memory (LSTM) and LSTM-attention (LSTM-ATN) networks for classifying reports. We also evaluated the improvement of adding Word2Vec word embedding. Deep learning models were compared with a bag-of-words (BOW) model.
Results
We retrieved 176,988 head CT reports for pre-training. We manually labeled 7784 reports as normal (46.3%) or pathological (53.7%), and 7.1% with intra-cranial hemorrhage. For the general labeling, LSTM-ATN-Word2Vec showed the best results (AUC = 0.967 ± 0.006, accuracy 90.8% ± 0.01). For the specific labeling, all methods showed similar accuracies between 95.0 and 95.9%. Both LSTM-ATN-Word2Vec and BOW had the highest AUC (0.970).
Conclusion
For a general use case, word embedding using a large cohort of non-English head CT reports and ATN improves NLP performance. For a more specific task, BOW and deep learning showed similar results. Models should be explored and tailored to the NLP task.
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