The clinical features and therapy of community-acquired gram negative bacteremia in children less than three years old

Combination of Hemoglobin-for-Age Z-Score and Plasma Hepcidin Identified as a Novel Predictor for Kawasaki Disease

Kawasaki disease (KD) is a febrile coronary vasculitis that affects younger children and includes complications such as coronary artery aneurysm. KD diagnoses are diagnosed based on clinical presentations, a process that still poses a challenge for front-line physicians. In the current study, we developed a novel predictor using the hemoglobin-for-age z-score (HbZ) and plasma hepcidin to differentiate Kawasaki disease (KD) from febrile children (FC). There were 104 FC and 115 KD subjects (89 typical KD; 26 incomplete KD) for this study, and data were collected on the biological parameters of hemoglobin and plasma hepcidin levels. A receiver operating characteristic curve (auROC), multiple logistics regression, and support vector machine analysis were all adopted to develop our prediction condition. We obtained both predictors, HbZ and plasma hepcidin, for distinguishing KD and FC. The auROC of the multivariate logistic regression of both parameters for FC and KD was 0.959 (95% confidence interval = 0.937–0.981), and the sensitivity and specificity were 85.2% and 95.9%, respectively. Furthermore, the auROC for FC and incomplete KD was 0.981, and the sensitivity and specificity were 92.3% and 95.2%, respectively. We further developed a model of support vector machine (SVM) classification with 83.3% sensitivity and 88.0% specificity in the training set, and the blind cohort performed well (78.4% sensitivity and 100% specificity). All data showed that sensitivity and specificity were 81.7% and 91.3%, respectively, by SVM. Overall, our findings demonstrate a novel predictor using a combination of HbZ and plasma hepcidin with a better discriminatory ability for differentiating from WBC and CRP between children with KD and other FC. Using this predictor can assist front-line physicians to recognize and then provide early treatment for KD.

Clinical characteristics and predictors of community-acquired pseudomonas aeruginosa sepsis and nontyphoidal salmonella sepsis in infants: A matched Case-Control study

BACKGROUND

Pseudomonas aeruginosa and nontyphoidal Salmonella (NTS) species may cause enteric illness with sepsis in infancy. The clinical predictors distinguishing the two pathogens have not been comprehensively evaluated in this population in Taiwan.

METHODS

A retrospective matched case-control study was conducted in a teaching hospital in southern Taiwan from January 1, 2003 to January 30, 2019. The patients with community-acquired P. aeruginosa sepsis were matched at a ratio of 1:2 by age and gender with controls (who developed NTS sepsis).

RESULTS

A total of 21 infants with community-acquired P. aeruginosa sepsis were identified; of these, 12 (57.1%) were male, and the mean ± standard deviation of age was 6.95 ± 2.47 months. Two independent predictors indicative of P. aeruginosa sepsis, as identified by multivariate analysis using conditional logistic regression, were hemoglobin level (Hb) (matched odds ratio [mOR], 0.155; 95% confidence interval [CI], 0.027-0.900; p = 0.038) and platelet count (mOR, 0.988, 95% CI, 0.976-1.000; p = 0.049). The areas under the receiver operating characteristic (ROC) curves of Hb and platelet count for P. aeruginosa sepsis prediction were 0.855 and 0.803, respectively. With cut-off values for Hb of 10.7 g/dL and platelet count of 173,000/μL, the predictors had maximal diagnostic accuracy.

CONCLUSION

Most patients with P. aeruginosa sepsis are less than one year old. A lower hemoglobin level and a lower platelet count are significant predictors of P. aeruginosa sepsis. These findings should help to reshape the policy of empirical antibiotics in infants with sepsis.

Antimicrobial activity of biosynthesised silver nanoparticles against multidrug-resistant microbes isolated from cancer patients with bacteraemia and candidaemia

Background

In the past years, saprophytic bacteria and candida have been emerging as potential human pathogens causing life-threatening infections in patients with cancer. This study was designed to determine the bacteria and candida species, causing bloodstream infections in cancer patients and the assessment of their susceptibility to antibiotics and biosynthesised silver nanoparticles.

Materials and Methods

Ninety-seven microbial pathogens recovered from blood samples of cancer patients were included in the present study. The microbial isolates were collected in a duration period extending from December 2016 to July 2018 at National Cancer Institute, Cairo, Egypt. The clinical samples were collected using microbiological methods and were cultivated on MacConkey agar, blood agar media and Sabouraud dextrose agar media. The microbial isolates were identified using both standard microbiological methods and VITEK 2 compact automated system. The antibiotic resistance pattern was determined by the VITEK 2 compact automatic system and disk diffusion method, according to the Clinical and Laboratory Standards Institute. The characterisation of nanoparticles was carried out using ultraviolet spectroscopy and electron microscope. The antimicrobial activity of bio (AgNPs) was evaluated.

Results

A total of 97 microbial isolates recovered from collected blood samples from cancer patients were included in the study. Pathogenic bacteria and Candida were represented by 74 isolates (76.22%) and 23 isolates (23.69), respectively. Among the 74 bacterial isolates, Escherichia coli constituted (27.81%), Klebsiella pneumoniae (24.72%), Acinetobacter baummannii (11.33%), Pseudomonas aeruginosa (4.12%), Enterobacter spp. (3.09%) and) Staphylococcus aureus (2.06%). Cedecea davisae (1.03%), Burkholderia cepacia (1.03%) and Pantoea agglomerans (1.03%). Among the 23 Candida isolates, Candida tropicalis constituted (9.27%), Candida albicans (5.15%), Candida glabrata (5.15%) and Candida krusei (4.12%) from the total microbial isolates. The antibiotic susceptibility results revealed that amikacin and gentamycin were the most effective antibiotics against Gram-negative bacteria, while vancomycin and linezolid were most effective against S. aureus. Caspofungin was the most effective against candida species. The obtained stable biosynthesised silver nanoparticles ranged in size from 10 nm to 100 nm and were mostly spherical in shape. These biosilver nanoparticles showed the highest antimicrobial activity against most of the microbial isolates (bacteria and Candida). The in vitro cytotoxicity of biosynthesised AgNPs on HeLa cell lines revealed a dose-dependent potential. The IC50 value of AgNPs was found 6 and 5.6 μg/ml, respectively.

Conclusion

The present study revealed a significant distribution of multidrug-resistant microbes, which may increase the burden of healthcare to prevent infections in cancer patients. Biosilver nanoparticles exhibit antimicrobial activity against multidrug-resistant microbes and could be considered as effective agents against these strains.