Mobiluncus curtisii Bacteremia: Case Study and Literature Review

Background: There are few reports of bacteremia caused by Mobiluncus curtisii in the literature. We present a review of the literature in addition to a case study. Method: We describe the case of an 82-year-old patient who underwent gastrointestinal surgery and subsequently presented with dehydration, nausea, and hyperkalemia secondary to diarrhea. Further clinical work included blood cultures, and the patient was started empirically on piperacillin/tazobactam. Results: After five days, the blood culture bottle showed growth of a gram-variable, curved rod-shaped organism. After culture under anaerobic conditions on sheep blood agar, the organism was identified as Mobiluncus curtisii by MALDI-TOF mass spectrometry and enzymatic technology. A review of the literature reveals five additional cases of Mobiluncus curtisii bacteremia. Conclusions: This is the sixth case in the literature describing Mobiluncus species bacteremia. This organism is rarely identified in blood culture and is most often thought of in the context of bacterial vaginosis. However, the reported cases of bacteremia show gastrointestinal symptoms and presumed gastrointestinal source of infection. The pathogenesis of infection of this organism requires further investigation.

C-Reactive Protein Monitoring and Clinical Presentation of Fever as Predictive Factors of Prolonged Febrile Neutropenia and Blood Culture Positivity after Autologous Hematopoietic Stem Cell Transplantation—Single-Center Real-Life Experience

Background: Febrile neutropenia (FN) is a medical emergency that requires urgent evaluation, timely administration of empiric broad-spectrum antibiotics and careful monitoring in order to optimize the patient’s outcome, especially in the setting of both allogeneic and autologous hematopoietic stem cell transplant (ASCT). Methods: In this real-life retrospective study, a total of 49 consecutive episodes of FN were evaluated in 40 adult patients affected by either multiple myeloma (thirty-eight) or lymphoma (eleven), following ASCT, with nine patients having fever in both of the tandem transplantations. Results: Febrile neutropenia occurred a median of 7 days from ASCT. Median duration of FN was 2 days, with 25% of population that had fever for at least four days. Ten patients had at least one fever spike superior to 39 °C, while the median number of daily fever spikes was two. Twenty patients had positive blood cultures with XDR germs, namely Pseudomonas aeruginosa and Klebsiella pneumoniae, present in seven cases. ROC analysis of peak C-reactive protein (CRP) values was conducted based on blood culture positivity and a value of 12 mg/dL resulted significant. Onset of prolonged fever with a duration greater than 3 days was associated with the presence of both a peak number of three or more daily fever spikes (p = 0.02) and a body temperature greater than 39 °C (p = 0.04) based on odds ratio (OR). Blood culture positivity and peak CRP values greater than 12 mg/dL were also associated with prolonged fever duration, p = 0.04, and p = 0.03, respectively. The probability of blood culture positivity was also greater in association with fever greater than 39 °C (p = 0.04). Furthermore, peak CRP values below the cut-off showed less probability of positive blood culture (p = 0.02). Conclusions: In our study, clinical characteristics of fever along with peak CRP levels were associated with a higher probability of both prolonged fever duration and positive blood culture, needing extended antibiotic therapy.

Prediction of Bacteremia Based on 12-Year Medical Data Using a Machine Learning Approach: Effect of Medical Data by Extraction Time

Early detection of bacteremia is important to prevent antibiotic abuse. Therefore, we aimed to develop a clinically applicable bacteremia prediction model using machine learning technology. Data from two tertiary medical centers’ electronic medical records during a 12-year-period were extracted. Multi-layer perceptron (MLP), random forest, and gradient boosting algorithms were applied for machine learning analysis. Clinical data within 12 and 24 hours of blood culture were analyzed and compared. Out of 622,771 blood cultures, 38,752 episodes of bacteremia were identified. In MLP with 128 hidden layer nodes, the area under the receiver operating characteristic curve (AUROC) of the prediction performance in 12- and 24-h data models was 0.762 (95% confidence interval (CI); 0.7617–0.7623) and 0.753 (95% CI; 0.7520–0.7529), respectively. AUROC of causative-pathogen subgroup analysis predictive value for Acinetobacter baumannii bacteremia was the highest at 0.839 (95% CI; 0.8388–0.8394). Compared to primary bacteremia, AUROC of sepsis caused by pneumonia was highest. Predictive performance of bacteremia was superior in younger age groups. Bacteremia prediction using machine learning technology appeared possible for acute infectious diseases. This model was more suitable especially to pneumonia caused by Acinetobacter baumannii. From the 24-h blood culture data, bacteremia was predictable by substituting only the continuously variable values.

Nhiễm trùng huyết cấy máu dương tính ở bệnh nhân mắc Covid-19

TÓM TẮT Đặt vấn đề: Nhiễm Covid-19 đồng thời nhiễm trùng huyết là một bệnh nặng, nguy cơ tử vong cao. Nghiên cứu này nhằm mô tả đặc điểm bệnh nhân Covid-19 nhiễm trùng huyết cấy máu dương tính; đặc điểm vi khuẩn gây nhiễm trùng huyết và mức độ đáp ứng kháng sinh của vi khuẩn trên kháng sinh đồ. Phương pháp nghiên cứu: Mô tả cắt ngang, 26 bệnh nhân Covid-19 cấy máu dương tính từ 8/2021 - 10/2021. Kết quả: 26 bệnh nhân có độ tuổi trung bình 57,89 (nhỏ nhất 32; lớn nhất 78) tuổi, 57,7% bệnh nhân lớn hơn 60 tuổi, nữ nhiều hơn nam, 69,23% bệnh nhân có bệnh nền, thời gian nằm viện trung bình là 16,35 ngày, 84,62% bệnh nhân cấy máu dương tính sau 48 giờ nằm viện, 23,08% bệnh nhân hồi phục sau điều trị. 96,15% bệnh nhân tăng CRP, 100% bệnh nhân tăng Procalcitonin, 86,46% bệnh nhân tăng bạch cầu chung và bạch cầu trung tính. Vi khuẩn gây nhiễm trùng huyết nhiều nhất là Acinetobacter baumannii, Escherichia coli, Burkholderia cepacia với tỷ lệ 19,23% mỗi loại. Vi khuẩn Gram âm nhạy cảm nhiều nhất với nhóm kháng sinh Carbapenem, Aminoglycosid, vi khuẩn Gram dương nhạy cảm nhiều với kháng sinh Linezolid, Vancomycin. Kết luận: Nhiễm trùng huyết trên bệnh nhân Covid làm tăng tỷ lệ tử vong, xác định chủng vi khuẩn và điều trị kháng sinh tích cực phù hợp với từng chủng vi khuẩn là cần thiết. ABSTRACT POSITIVE BLOOD CULTURE SEPSIS IN COVID-19 PATIENTS Background: Infection with Covid 19 and sepsis is a severedisease that leads to a high risk of death. This study aims to describe the characteristics of Covid-19 patients with positive blood culture, elements of bacteria causing sepsis, and the level of antibiotic response of bacteria on the antibiotic chart. Methods: A cross - sectional descriptive study was conducted on 26 Covid-19 patients with positive blood culture 8/2021-10/2021. Result: Twenty - six Covid-19 patients had an average age of 57.89 years (range: 32 - 78). Of these, 57.7% of patients were older than 60 years; women were more than men. 69.23% of patients had a medical history of the disease. The average treatment time was 16.35 days; 84.62% of patients had positive blood cultures after 48 hours of treatment. 23.08% of patients were recovered after treatment. 96.15% of patients increased CRP, 100% of patientsincreased Procalcitonin, and 86.46% increased leukocytosis and neutrophils. The bacteria that caused the most sepsis are Acinetobacter baumannii, Escherichia coli, Burkholderia cepacia with 19.23%. Gram - negative bacteria were most sensitive to Carbapenem, Aminoglycoside antibiotics. Gram - positive bacteria were more susceptible to Linezolid and Vancomycin antibiotics. Conclusion: Sepsis with positive blood culture in covid patients increases the mortality rate. Identifying bacterial strains and appropriate aggressive antibiotic treatment for each bacterial is necessary. Keywords: Sepsis, bacteria, sensitive, Covid-19.

Clinical prediction rule for bacteremia with pyelonephritis and hospitalization judgment: chi-square automatic interaction detector (CHAID) decision tree analysis model

Objective This study was performed to identify predictive factors for bacteremia among patients with pyelonephritis using a chi-square automatic interaction detector (CHAID) decision tree analysis model. Methods This retrospective cross-sectional survey was performed at Juntendo University Nerima Hospital, Tokyo, Japan and included all patients with pyelonephritis from whom blood cultures were taken. At the time of blood culture sample collection, clinical information was extracted from the patients’ medical charts, including vital signs, symptoms, laboratory data, and culture results. Factors potentially predictive of bacteremia among patients with pyelonephritis were analyzed using Student’s t-test or the chi-square test and the CHAID decision tree analysis model. Results In total, 198 patients (60 (30.3%) men, 138 (69.7%) women; mean age, 74.69 ± 15.27 years) were included in this study, of whom 92 (46.4%) had positive blood culture results. The CHAID decision tree analysis revealed that patients with a white blood cell count of >21,000/μL had a very high risk (89.5%) of developing bacteremia. Patients with a white blood cell count of ≤21,000/μL plus chills plus an aspartate aminotransferase concentration of >19 IU/L constituted the high-risk group (69.0%). Conclusion The present results are extremely useful for predicting the results of bacteremia among patients with pyelonephritis.