Management of chronic diseases requiring immunosuppression, such as inflammatory bowel disease (IBD), during this time period has led to difficult and exceptional decision making by both healthcare ...providers and patients. Rapid mobilisation of efforts globally has led to expert recommendations by various medical societies to help guide clinicians.1 2 Furthermore, through commendable efforts made by the IBD community through international registries and regular updates there is now some relative clarity.3 IBD affects over 700 000 people in the UK and forms one of the largest groups of chronic diseases that require immunosuppressive therapies.4 5 It is estimated that around 50% of patients experience at least one flare annually. There is preliminary data to support the potential usage of low-dose corticosteroids in the treatment of respiratory coronavirus infections, including COVID-19, severe acute respiratory syndrome and the Middle East respiratory syndrome, through a modulation of the immune response, but this is specific to cases of severe acute respiratory coronavirus and acute lung injury or adult respiratory distress syndrome.9–12 In the earlier stages of COVID-19 infection, however, it is likely that higher dose steroids, as typically used in management of flare of IBD, are detrimental.13 14 It is therefore essential that before starting steroids if indicated for the treatment of a flare, clinicians can rule out COVID-19 infection.
The fecal microbiota and metabolome are hypothesized to be altered before late-onset neonatal meningitis (LOM), in analogy to late-onset sepsis (LOS). The present study aimed to identify fecal ...microbiota composition and volatile metabolomics preceding LOM.
Cases and gestational age-matched controls were selected from a prospective, longitudinal preterm cohort study (born <30 weeks' gestation) at nine neonatal intensive care units. The microbial composition (16S rRNA sequencing) and volatile metabolome (gas chromatography-ion mobility spectrometry (GC-IMS) and GC-time-of-flight-mass spectrometry (GC-TOF-MS)), were analyzed in fecal samples 1-10 days pre-LOM.
Of 1397 included infants, 21 were diagnosed with LOM (1.5%), and 19 with concomitant LOS (90%). Random Forest classification and MaAsLin2 analysis found similar microbiota features contribute to the discrimination of fecal pre-LOM samples versus controls. A Random Forest model based on six microbiota features accurately predicts LOM 1-3 days before diagnosis with an area under the curve (AUC) of 0.88 (n=147). Pattern recognition analysis by GC-IMS revealed an AUC of 0.70-0.76 (P<0.05) in the three days pre-LOM (n=92). No single discriminative metabolites were identified by GC-TOF-MS (n=66).
Infants with LOM could be accurately discriminated from controls based on preclinical microbiota composition, while alterations in the volatile metabolome were moderately associated with preclinical LOM.
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