Implementation of Delayed Cord Clamping in public health facilities: a case study from India.

BACKGROUND: Global and country specific recommendations on Delayed umbilical cord clamping (DCC) are available, though guidance on their implementation in program settings is lacking. In India, DCC (clamping not earlier than 1 min after birth) is a component in the package of services delivered as part of the India Newborn Action Plan (INAP) supported by Nutrition International (NI) in two states. The objective of this case study was to document the learnings from implementation of DCC in these two states and to understand the health system factors that affected its operationalization. METHODS: Mixed methods were followed. Using the World Health Organization (WHO) Health Systems building blocks as a framework, 20 Key-Informant Interviews were conducted to explore facilitators and barriers to routine implementation of DCC in public health settings. Existing quantitative program data and secondary data from labour-room registers from eight NI- supported districts were analysed to assess the prevalence of DCC implementation in public health systems settings. RESULTS: A demonstrated commitment from the government to implement DCC at all delivery points in NI supported districts was observed. Funds were sufficient, trainings were optimal, knowledge of the health workforce was adequate and a recording mechanism was in place. According to record reviews, DCC was more likely to happen in facilities that provide Basic Emergency Obstetric services and among normal deliveries. It was less likely to be followed in babies delivered by Caesarean section (OR 0.03; 95%CI 0.02,0.05), birthweight < 2000 g (OR 0.22; 95%CI 0.12,0.47), multiple pregnancies (OR 0.17, 95%CI 0.05,0.63), birth asphyxia requiring resuscitation (0.37; 95%CI 0.26,0.52), and those delivered during day shift (OR 0.59, 95%CI 0.40, 0.83). CONCLUSIONS: Wide coverage of DCC in public health settings in the two states was observed. Good governance, adequate funding, commitment of health workforce has likely contributed to its success in these contexts. These are critical elements to guide DCC implementation in India and for consideration in other settings.

Prediction of protein-protein interaction network using a multi-objective optimization approach.

Protein-Protein Interactions (PPIs) are very important as they coordinate almost all cellular processes. This paper attempts to formulate PPI prediction problem in a multi-objective optimization framework. The scoring functions for the trial solution deal with simultaneous maximization of functional similarity, strength of the domain interaction profiles, and the number of common neighbors of the proteins predicted to be interacting. The above optimization problem is solved using the proposed Firefly Algorithm with Nondominated Sorting. Experiments undertaken reveal that the proposed PPI prediction technique outperforms existing methods, including gene ontology-based Relative Specific Similarity, multi-domain-based Domain Cohesion Coupling method, domain-based Random Decision Forest method, Bagging with REP Tree, and evolutionary/swarm algorithm-based approaches, with respect to sensitivity, specificity, and F1 score.