A recommendation to refer after MUAC screening did not, by itself, change outcomes near the cut-off

Design

Prospective regression discontinuity analysis nested in a cluster-randomised trial, Burkina Faso

Population

65,554 children aged 6 to 59 months; 226 (0.34%) below the MUAC cut-off of 11.5 cm at least once

Primary outcome

MUAC at the next census and all-cause mortality before it

Effect

MUAC difference 0.21 cm (95% CI -0.22 to 0.65); mortality OR 0.95 (95% CI 0.03 to 31.37)

In Nouna District, Burkina Faso, this regression discontinuity analysis was nested within a cluster-randomised azithromycin trial. Children aged 6 to 59 months were screened at twice-yearly censuses, and a MUAC below 11.5 cm triggered a recommendation to refer for nutritional treatment. Among 65,554 children, 226 (0.34%) were below the cut-off at least once.

The analysis compared children just below and just above the cut-off. Eligibility for referral made no clear difference to MUAC at the next census (0.21 cm, 95% CI -0.22 to 0.65) or to death before it (odds ratio 0.95, 95% CI 0.03 to 31.37). The mortality estimate is so wide that it cannot exclude a large benefit or harm. Treatment uptake was not measured, so the analysis estimates the effect of being eligible for referral, not of treatment.

The authors conclude that stronger mechanisms may be needed to complete referral and link children to treatment. For a clinician, the point is practical: identifying a child with severe acute malnutrition is the start of the pathway, and what matters is whether the child reaches and completes care.

• Do not stop screening with MUAC; this study did not test whether screening or treatment works.
• Confirm that a referred child actually attends and completes nutritional treatment.
• Record who is responsible for follow-up when you refer.
• Consider barriers to attendance such as distance, cost and caregiver time.

Why it matters

It highlights the gap between identifying severe malnutrition and delivering treatment.

Don't overread it

The analysis does not evaluate treatment itself, uptake was not measured, and the mortality estimate was highly imprecise.

The statistics, in plain English

A confidence interval for mortality of 0.03 to 31.37 is so wide that the result tells you almost nothing about mortality. The finding is the absence of evidence of an effect, not evidence of no effect.

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