Recurring staphylococcal scalded skin syndrome in a very low birth weight infant: A case report

Introduction. Staphylococcal scalded skin syndrome is an extensive desquamative erythematous condition caused by exfoliative toxins of Staphylococcus aureus. This disease usually affects neonates and generally responds rapidly to antibiotic therapy. Case presentation. We describe the case of a premature baby boy, weighing 1030 g, born after 26 6/7 weeks gestation, who developed two episodes of Staphylococcal scalded skin syndrome on days 19 and 48 of life. Cultures obtained during the first period did not reveal Staphylococcus aureus, but diagnosis was based on typical clinical grounds. Although the initial diagnosis was irritation by the fixation material of a nasal continuous positive airway pressure tube, the infant showed rapidly progressing skin blistering and exfoliation, characteristic of Staphylococcal scalded skin syndrome. After administration of antibiotic treatment, complete recovery was seen. In the second period, diagnosis of Staphylococcal scalded skin syndrome was made clinically and confirmed by results of microbiologic investigations. Staphylococcus aureus was cultured from the nose, skin lesions and the pharynx. The strain appeared to produce exfoliative toxin A. The clinical response to similar antibiotic treatment was identical to the first period of Staphylococcal scalded skin syndrome. Conclusion. This case report discusses an unusual presentation of recurring Staphylococcal scalded skin syndrome in a baby with a very low birth weight

16S rRNA Mutation-Mediated Tetracycline Resistance in Helicobacter pylori

Most Helicobacter pylori strains are susceptible to tetracycline, an antibiotic commonly used for the eradication of H. pylori. However, an increase in incidence of tetracycline resistance in H. pylori has recently been reported. Here the mechanism of tetracycline resistance of the first Dutch tetracycline-resistant (Tet(r)) H. pylori isolate (strain 181) is investigated. Twelve genes were selected from the genome sequences of H. pylori strains 26695 and J99 as potential candidate genes, based on their homology with tetracycline resistance genes in other bacteria. With the exception of the two 16S rRNA genes, none of the other putative tetracycline resistance genes was able to transfer tetracycline resistance. Genetic transformation of the Tet(s) strain 26695 with smaller overlapping PCR fragments of the 16S rRNA genes of strain 181, revealed that a 361-bp fragment that spanned nucleotides 711 to 1071 was sufficient to transfer resistance. Sequence analysis of the 16S rRNA genes of the Tet(r) strain 181, the Tet(s) strain 26695, and four Tet(r) 26695 transformants showed that a single triple-base-pair substitution, AGA(926-928)→TTC, was present within this 361-bp fragment. This triple-base-pair substitution, present in both copies of the 16S rRNA gene of all our Tet(r) H. pylori transformants, resulted in an increased MIC of tetracycline that was identical to that for the Tet(r) strain 181

Prediction of Late-Onset Sepsis in Preterm Infants Using Monitoring Signals and Machine Learning

Objectives: Prediction of late-onset sepsis (onset beyond day 3 of life) in preterm infants, based on multiple patient monitoring signals 24 hours before onset. Design: Continuous high-resolution electrocardiogram and respiration (chest impedance) data from the monitoring signals were extracted and used to create time-interval features representing heart rate variability, respiration, and body motion. For each infant with a blood culture-proven late-onset sepsis, a Cultures, Resuscitation, and Antibiotics Started Here moment was defined. The Cultures, Resuscitation, and Antibiotics Started Here moment served as an anchor point for the prediction analysis. In the group with controls (C), an "equivalent crash moment" was calculated as anchor point, based on comparable gestational and postnatal age. Three common machine learning approaches (logistic regressor, naive Bayes, and nearest mean classifier) were used to binary classify samples of late-onset sepsis from C. For training and evaluation of the three classifiers, a leave-k-subjects-out cross-validation was used. Setting: Level III neonatal ICU. Patients: The patient population consisted of 32 premature infants with sepsis and 32 age-matched control patients. Interventions: No interventions were performed. Measurements and Main Results: For the interval features representing heart rate variability, respiration, and body motion, differences between late-onset sepsis and C were visible up to 5 hours preceding the Cultures, Resuscitation, and Antibiotics Started Here moment. Using a combination of all features, classification of late-onset sepsis and C showed a mean accuracy of 0.79 ± 0.12 and mean precision rate of 0.82 ± 0.18 3 hours before the onset of sepsis. Conclusions: Information from routine patient monitoring can be used to predict sepsis. Specifically, this study shows that a combination of electrocardiogram-based, respiration-based, and motion-based features enables the prediction of late-onset sepsis hours before the clinical crash moment

Method for Phenotypic Detection of Extended-Spectrum Beta-Lactamases in Enterobacter Species in the Routine Clinical Setting ▿

In 271 Enterobacter blood culture isolates from 12 hospitals, extended-spectrum beta-lactamase (ESBL) prevalence varied between 0% and 30% per hospital. High prevalence was associated with dissemination, indicating the potential relevance of infection control measures. Screening with cefepime or Vitek 2, followed by a cefepime/cefepime-clavulanate Etest, was an accurate strategy for ESBL detection in Enterobacter isolates (positive predictive value, 100%; negative predictive value, 99%)