- Design
- Population-based surveillance cohort, time-dependent Cox models
- Population
- 6,044 children hospitalised with laboratory-confirmed influenza in 13 US states
- Primary outcome
- Time from symptom onset to ICU admission
- Effect
- aHR 0.69 (95% CI 0.60 to 0.80) for ICU admission; discharge aHR 1.13 (1.06 to 1.21)
US national surveillance captured children hospitalised with laboratory-confirmed influenza over eight seasons from 2014 to 2023. The ICU analysis included 6,044 children, median age 3, half with a comorbidity, most often asthma; 70% received oseltamivir.
Treating oseltamivir as a time-dependent exposure, to avoid crediting it with outcomes before it was given, treatment was associated with a lower hazard of ICU admission (aHR 0.69, 95% CI 0.60 to 0.80) and faster discharge (aHR 1.13, 1.06 to 1.21).
Antiviral use for hospitalised children has been falling despite recommendations. This is observational, but the design addresses several biases that weakened earlier studies, and the result supports treating early rather than waiting for test results.
In India, oseltamivir is widely available and inexpensive, and influenza admissions in young children with asthma are common in season.
- Start oseltamivir promptly in any child admitted with suspected or confirmed influenza
- Do not wait for test results or limit treatment to the first 48 hours of illness in admitted children
- Pay particular attention to children with asthma or other chronic conditions
- Dose by weight and adjust for renal impairment
- Offer annual influenza vaccination to children with chronic conditions
Why it matters
It gives fresh support to a recommendation that hospitals have been following less often.
Don't overread it
This is observational surveillance data, not a randomised trial.
The statistics, in plain English
An adjusted hazard ratio of 0.69 means about a 31% lower rate of ICU admission among treated children. Because this was not randomised, sicker or less sick children may have been treated differently, though the time-dependent analysis reduces that bias.
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