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Backgrounds:

The sepsis-3 definitions were developed from databases of adult patients and were neither designed nor validated in children. We sought to validate the performance of age-adapted PMODS, qSOFA, PELOD-2 and SIRS in predicting outcomes for children consecutively admitted to a Paediatric Intensive Care Unit (PICU).

Design:

Prospective, observational study.

Setting:

A single-centre regional PICU in the United Kingdom.

Patients:

656 consecutively admitted children under the age of 16 years were enrolled.

Methods

All children were categorised based on the Sepsis-3 definitions: sepsis, septic shock and no infection. Biochemical and physical parameters were measured within the first 24 hours of PICU admission. The primary outcomes were a composite outcome of 28-day mortality and PICU LOS>3 days, and development of multi-organ dysfunction syndrome (MODS). We derived scores for age-adapted PMODS, qSOFA, PELOD-2 and SIRS in predicting the primary outcomes. The performance of the scores were evaluated using area under the curve (AUC).

Results:

Median age was 1.02 years (IQR 0.29 – 5.02). 367 were post-operative cardiac surgical patients (56%), 105 other surgical (16%), and 184 non-surgical (28%). 351 infectious episodes were described.

In all patients, SIRS was positive in 39.8% of episodes (n=261). 10.5% of children developed DIC (n=69). 123 developed MODS, and D28 mortality was 1.8%. PMODS gave the best discrimination for predicting mortality or LOS, and MODS, in the sepsis and septic shock subgroups. Mortality or LOS>3; sepsis: 0.50 (0.38 – 0.62) and septic shock: 0.67 (0.39 – 0.95) MODS; sepsis: 0.62 (0.49 – 0.75) and septic shock: 0.75 (0.45 – 1.00).

Conclusions/Learning Points:

When using Sepsis-3 criteria, PMODS provides excellent prediction of both in-hospital mortality or PICU length of stay over 3 days, and development of MODS in children with septic shock.

Backgrounds:

Febrile children below three months have a higher risk of serious bacterial infections, which often leads to extensive diagnostics and treatment. However, there is practice variation in management due to differences in guidelines and the usage and adherence. We aimed to assess whether management in febrile children below three months attending European Emergency Departments (EDs) was according to the available guidelines for fever.

Methods

This study is part of the MOFICHE study, which is an observational multicenter study including routine data of febrile children (0-18 years) attending twelve European EDs. In febrile children <3 months (excluding bronchiolitis), we analyzed actual management compared to the available guidelines for fever. Ten EDs applied the (adapted) NICE guideline and two EDs applied local guidelines. Management included diagnostic tests, antibiotic treatment and admission. Subgroup analyses in children <1 month and 1-3 months were performed. Data on follow-up was not collected.

Results:

We included 913 children (median age 1.7 months) with the majority triaged as intermediate/high urgent (53%), 40% having a respiratory tract infection and 56% having a viral illness. Management per ED varied: diagnostic tests 14-83%, antibiotic treatment 23-54%, admission 34-86%. Adherence to the guidelines varied: blood cultures were obtained in 43% (374/868), lumbar punctures in 30% (144/488), antibiotics were prescribed in 55% (270/492) and 67% (573/859) were admitted. Full adherence to all these four components occurred in 15% (132/868, range 0-38%), 31% (71/223) in children <1 month and 10% (61/645) in children 1-3 months respectively.

Conclusions/Learning Points:

There is large practice variation in management and guideline adherence was limited, but highest for admission which implies good safety netting. Future studies should focus on guideline revision with new biomarkers in order to optimize management in young febrile children.

Backgrounds:

Many host transcript signatures for paediatric inflammatory and infectious diseases are in development, but require validation in independent cohorts; their translation to clinically useful test platforms lags behind discovery. We used NanoString technology to efficiently validate multiple signatures in parallel and explore the potential for more sophisticated multi-class classification models.

Methods

We validated five transcriptomic diagnostic signatures using prospectively recruited patients from multiple paediatric cohorts. Final phenotypes were assigned using pre-agreed definitions after review of clinical and laboratory data. We quantified 69 transcripts on a custom NanoString nCounter cartridge, normalising expression values using reference genes. Signature performance was assessed using Area Under ROC Curve (AUC) statistics. We explored two approaches to multiclassification diagnostics to develop proof-of-concept methods: a mixed test combining four independent one-vs-all models, and a multinomial model.

Results:

Our cohort of 92 paediatric patients included 23 definite bacterial and 20 definite viral infections, 15 Kawasaki disease, 18 with tuberculosis and 16 healthy controls. The signatures achieved AUCs above 0.82 (Table 1), with confidence intervals overlapping those of the respective discovery studies. However, performance declined in all signatures when tasked with differentiating additional groups. For example, the single-transcript BATF2 had AUC of 0.910 differentiating TB from healthy individuals, reducing to 0.745 when differentiating TB from other febrile diseases. In comparison, the multinomial approach identified a 24-transcript model that correctly classified all 76 non-control patients (0% in-sample error), outperforming the mixed-model (19 transcripts, 19.8% in-sample error).

Conclusions/Learning Points:

The cross-platform, out-of-sample findings validated 5 signatures, but discriminatory power was reduced in patients drawn from outside their remit. An exploratory 24-transcript model had improved accuracy across all diagnostic groups, demonstrating in principle the utility for one-step multi-class diagnosis in patients with broad diagnostic uncertainty.

Backgrounds:

Invasive bacterial disease is a major cause of morbidity and mortality in African children. Here we leverage cases of bacterial sepsis among children diagnosed with severe malaria to augment study power in a genome-wide association study (GWAS) of invasive bacterial disease in Kenyan children.

Methods

We performed a GWAS of invasive bacterial infection in Kenyan children (n=5,482: 1,445 bacteraemia cases, 1,143 severe malaria cases, 2,894 controls). To account for the varying probabilty of invasive bacterial disease among malaria cases, we used probabilistic models to identify children with a high probability of culture-negative bacterial sepsis, applying these probabilities as weights for malaria cases in our analysis. We replicated our findings in a second sample collection (n=1,692: 434 bacteraemia cases, 1,258 controls).

Results:

In children with a clinical diagnosis of severe malaria, 31.1% have a low (P(SM|Data)<0.5) probability of their disease being ‘true’ severe malaria. These children are critically unwell (case fatality=14.5%) and are enriched for bacteraemia (OR=3.06, p=1.07 x10^-4). We thus hypothesised that a substantial proportion of these children have bacterial sepsis. By including these children in a weighted logistic regression GWAS, we identify and validate rs183868412 as a risk locus for invasive bacterial infection in Kenyan children: OR_disc=2.14, P_disc=4.02x10^-9; OR_rep=2.77, P_rep=1.29x10^-3; OR_meta=2.22, P_meta=1.66 x10^-11. This locus is a determinant of BIRC6 splicing in stimulated monocytes (PP_coloc=0.94).

Conclusions/Learning Points:

Here we identify children with a high likelihood of invasive bacterial disease among critically unwell Kenyan children with malaria. By including these children in a GWAS of invasive bacterial infection we identify and validate a novel risk locus for invasive bacterial disease. The trait-associated variation modifies splicing of BIRC6 in stimulated monocytes, implicating the regulation of apoptosis and autophagy in the pathogenesis of sepsis in African children.