Background Pulse oximeters are not routinely available in outpatient clinics in low- and middle-income countries. We derived clinical scores to identify hypoxemic child pneumonia.

Methods This was a retrospective pooled analysis of two outpatient datasets of 3-35 month olds with World Health Organization (WHO)-defined pneumonia in Bangladesh and Malawi. We constructed, internally validated, and compared fit & discrimination of four models predicting SpO2<93% and <90%: (1) Integrated Management of Childhood Illness guidelines, (2) WHO-composite guidelines, (3) Independent variable least absolute shrinkage and selection operator (LASSO); (4) Composite variable LASSO. Results: 12,712 observations were included. The independent and composite LASSO models discriminated moderately (both C-statistic 0.77) between children with a SpO2<93% and ≥94%; model predictive capacities remained moderate after adjusting for potential overfitting (C-statistic 0.74 and 0.75). The IMCI and WHO-composite models had poorer discrimination (C-statistic 0.56 and 0.68) and identified 20.6% and 56.8% of SpO2<93% cases. The highest score stratum of the independent and composite LASSO models identified 46.7% and 49.0% of SpO2<93% cases. Both LASSO models had similar performance for a SpO2<90%.

Conclusions In the absence of pulse oximeters, both LASSO models better identified outpatient hypoxemic pneumonia cases than the WHO guidelines. Score external validation and implementation are needed.

The authors have declared no competing interest.

The study was funded by GlaxoSmithKline, Bill & Melinda Gates Foundation, and the National Institute of Health.

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Ethical approval was provided by National Health Sciences Research Committee of Malawi, the Ethics Committee of University College London, and The Bangladesh Medical Research Counsel, International Centre for Diarrhoeal Diseases Research, Johns Hopkins Bloomberg School of Public Health and School of Medicine Institutional Review Boards.

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