Clinical and Health System Impact of Biofire Filmarray Meningitis/Encephalitis Routine Testing of CSF in a Pediatric Hospital: An Observational Study.

BACKGROUND

Rapid cartridge-based molecular test panels targeting multiple pathogens are increasingly available, improve pathogen detection and reduce turn-around-time but are more expensive than standard testing. Confirmation that these test panels contribute to improved patient or health service outcomes is required.

METHODS

In March 2021, our pediatric hospital laboratory implemented the BioFire Filmarray™ meningitis/encephalitis (M/E) panel as an additional routine test for all cerebrospinal fluid (CSF) samples collected from infants <90 days or from any patient in the emergency department. A retrospective chart review was done to ascertain changes in clinical outcomes, antimicrobial prescribing practices, and hospital length of stay, comparing two discrete 6-month periods: preimplementation (March-August 2019) and postimplementation (March-August 2021).

RESULTS

Both pre- and postimplementation groups were similar at baseline, except the preimplementation group had a higher proportion of infants with enterovirus and parechovirus meningitis. There was no significant difference between the groups in terms of median length of stay (2.94 vs 3.47 days, p = 0.41), duration of antibiotic treatment (2.0 vs 2.3 days, p = 0.25), need for central venous access (12.9% vs 17%, p = 0.38) or hospital-in-the-home admission (9.4% vs 9%, p = 0.92). A similar proportion of infants received aciclovir (33% vs 31%), however, a reduction in duration was observed (1.36 vs 0.90 days, p = 0.03) in the postimplementation period.

CONCLUSIONS

Introduction of the Biofire Filmarray™ M/E panel for routine testing of CSF samples reduced the duration of antiviral prescribing but had only a minor impact on antibiotic prescribing practices or health service outcomes in our pediatric hospital. The introduction of new laboratory testing needs to be supported by a comprehensive stewardship program to see optimal outcomes from new testing platforms.