Survivors of neonatal infections are at risk of neurodevelopmental impairment (NDI), a burden not previously systematically quantified and yet important for program priority setting. Systematic reviews and meta-analyses were undertaken and applied in a three-step compartmental model to estimate NDI cases after severe neonatal bacterial infection in South Asia, sub-Saharan Africa, and Latin America in neonates of >32 wk gestation (or >1,500 g). We estimated cases of sepsis, meningitis, pneumonia, or no severe bacterial infection from among estimated cases of possible severe bacterial infection ((pSBI) step 1). We applied respective case fatality risks ((CFRs) step 2) and the NDI risk among survivors (step 3). For neonatal tetanus, incidence estimates were based on the estimated deaths, CFRs, and risk of subsequent NDI. For 2010, we estimated 1.7 million (uncertainty range: 1.1-2.4 million) cases of neonatal sepsis, 200,000 (21,000-350,000) cases of meningitis, 510,000 cases (150,000-930,000) of pneumonia, and 79,000 cases (70,000-930,000) of tetanus in neonates >32 wk gestation (or >1,500 g). Among the survivors, we estimated moderate to severe NDI after neonatal meningitis in 23% (95% confidence interval: 19-26%) of survivors, 18,000 (2,700-35,000) cases, and after neonatal tetanus in 16% (6-27%), 4,700 cases (1,700-8,900). Data are lacking for impairment after neonatal sepsis and pneumonia, especially among those of >32 wk gestation. Improved recognition and treatment of pSBI will reduce neonatal mortality. Lack of follow-up data for survivors of severe bacterial infections, particularly sepsis, was striking. Given the high incidence of sepsis, even minor NDI would be of major public health importance. Prevention of neonatal infection, improved case management, and support for children with NDI are all important strategies, currently receiving limited policy attention.

Each year almost one million newborns die from infections, mostly in low-income countries. Timely case management would save many lives but the relative mortality effect of varying strategies is unknown. We have estimated the effect of providing oral, or injectable antibiotics at home or in first-level facilities, and of in-patient hospital care on neonatal mortality from pneumonia and sepsis for use in the Lives Saved Tool (LiST). We conducted systematic searches of multiple databases to identify relevant studies with mortality data. Standardized abstraction tables were used and study quality assessed by adapted GRADE criteria. Meta-analyses were undertaken where appropriate. For interventions with biological plausibility but low quality evidence, a Delphi process was undertaken to estimate effectiveness. Searches of 2876 titles identified 7 studies. Among these, 4 evaluated oral antibiotics for neonatal pneumonia in non-randomised, concurrently controlled designs. Meta-analysis suggested reductions in all-cause neonatal mortality (RR 0.75 95% CI 0.64- 0.89; 4 studies) and neonatal pneumonia-specific mortality (RR 0.58 95% CI 0.41- 0.82; 3 studies). Two studies (1 RCT, 1 observational study), evaluated community-based neonatal care packages including injectable antibiotics and reported mortality reductions of 44% (RR= 0.56, 95% CI 0.41-0.77) and 34% (RR =0.66, 95% CI 0.47-0.93), but the interpretation of these results is complicated by co-interventions. A third, clinic-based, study reported a case-fatality ratio of 3.3% among neonates treated with injectable antibiotics as outpatients. No studies were identified evaluating injectable antibiotics alone for neonatal pneumonia. Delphi consensus (median from 20 respondents) effects on sepsis-specific mortality were 30% reduction for oral antibiotics, 65% for injectable antibiotics and 75% for injectable antibiotics on pneumonia-specific mortality. No trials were identified assessing effect of hospital management for neonatal infections and Delphi consensus suggested 80%, and 90% reductions for sepsis and pneumonia-specific mortality respectively. Oral antibiotics administered in the community are effective for neonatal pneumonia mortality reduction based on a meta-analysis, but expert opinion suggests much higher impact from injectable antibiotics in the community or primary care level and even higher for facility-based care. Despite feasibility and low cost, these interventions are not widely available in many low income countries. This work was supported by the Bill & Melinda Gates Foundation through a grant to the US Fund for UNICEF, and to Saving Newborn Lives Save the Children, through Save the Children US.

Image classification is central to the big data revolution in medicine. Improved information processing methods for diagnosis and classification of digital medical images have shown to be successful via deep learning approaches. As this field is explored, there are limitations to the performance of traditional supervised classifiers. This paper outlines an approach that is different from the current medical image classification tasks that view the issue as multi-class classification. We performed a hierarchical classification using our Hierarchical Medical Image classification (HMIC) approach. HMIC uses stacks of deep learning models to give particular comprehension at each level of the clinical picture hierarchy. For testing our performance, we use biopsy of the small bowel images that contain three categories in the parent level (Celiac Disease, Environmental Enteropathy, and histologically normal controls). For the child level, Celiac Disease Severity is classified into 4 classes (I, IIIa, IIIb, and IIIC).