Purpose Investigation of the current practice of diagnostics and treatment in pediatric cancer patients with febrile neutropenia. Methods On behalf of the German Society for Pediatric Oncology and Hematology and the German Society for Pediatric Infectious Diseases, an Internet-based survey was conducted in 2016 concerning the management of febrile neutropenia in pediatric oncology centers (POC). This survey accompanied the release of the corresponding German guideline to document current practice before its implementation in clinical practice. Results In total, 51 POCs participated (response rate 73%; 43 from Germany, and 4 each from Austria and Switzerland). Identified targets for antimicrobial stewardship concerned blood culture diagnostics, documentation of the time to antibiotics, the use of empirical combination therapy, drug monitoring of aminoglycosides, the time to escalation in patients with persisting fever, minimal duration of IV treatment, sequential oral treatment in patients with persisting neutropenia, indication for and choice of empirical antifungal treatment, and the local availability of a pediatric infectious diseases consultation service. Conclusion This survey provides useful information for local antibiotic stewardship teams to improve the current practice referring to the corresponding national and international guidelines. Electronic supplementary material The online version of this article (10.1007/s15010-020-01462-z) contains supplementary material, which is available to authorized users.
Background The role of primary immunodeficiencies (PID) in susceptibility to sepsis remains unknown. It is unclear whether children with sepsis benefit from genetic investigations. We hypothesized that sepsis may represent the first manifestation of underlying PID. We applied whole-exome sequencing (WES) to a national cohort of children with sepsis to identify rare, predicted pathogenic variants in PID genes. Methods We conducted a multicenter, population-based, prospective study including previously healthy children aged ≥28 days and <17 years admitted with blood culture-proven sepsis. Using a stringent variant filtering procedure, analysis of WES data was restricted to rare, predicted pathogenic variants in 240 PID genes for which increased susceptibility to bacterial infection has been reported. Results There were 176 children presenting with 185 sepsis episodes who underwent WES (median age, 52 months; interquartile range, 15.4–126.4). There were 41 unique predicted pathogenic PID variants (1 homozygous, 5 hemizygous, and 35 heterozygous) found in 35/176 (20%) patients, including 3/176 (2%) patients carrying variants that were previously reported to lead to PID. The variants occurred in PID genes across all 8 PID categories, as defined by the International Union of Immunological Societies. We did not observe a significant correlation between clinical or laboratory characteristics of patients and the presence or absence of PID variants. Conclusions Applying WES to a population-based cohort of previously healthy children with bacterial sepsis detected variants of uncertain significance in PID genes in 1 out of 5 children. Future studies need to investigate the functional relevance of these variants to determine whether variants in PID genes contribute to pediatric sepsis susceptibility.
Motivation Sepsis is a leading cause of death and disability in children globally, accounting for ∼3 million childhood deaths per year. In pediatric sepsis patients, the multiple organ dysfunction syndrome (MODS) is considered a significant risk factor for adverse clinical outcomes characterized by high mortality and morbidity in the pediatric intensive care unit. The recent rapidly growing availability of electronic health records (EHRs) has allowed researchers to vastly develop data-driven approaches like machine learning in healthcare and achieved great successes. However, effective machine learning models which could make the accurate early prediction of the recovery in pediatric sepsis patients from MODS to a mild state and thus assist the clinicians in the decision-making process is still lacking. Results This study develops a machine learning-based approach to predict the recovery from MODS to zero or single organ dysfunction by 1 week in advance in the Swiss Pediatric Sepsis Study cohort of children with blood-culture confirmed bacteremia. Our model achieves internal validation performance on the SPSS cohort with an area under the receiver operating characteristic (AUROC) of 79.1% and area under the precision-recall curve (AUPRC) of 73.6%, and it was also externally validated on another pediatric sepsis patients cohort collected in the USA, yielding an AUROC of 76.4% and AUPRC of 72.4%. These results indicate that our model has the potential to be included into the EHRs system and contribute to patient assessment and triage in pediatric sepsis patient care. Availability and implementation Code available at https://github.com/BorgwardtLab/MODS-recovery. The data underlying this article is not publicly available for the privacy of individuals that participated in the study. Supplementary information Supplementary data are available at Bioinformatics online.
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