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Objectives To estimate the costs and health consequences of three different screening strategies for neonatal alloimmune thrombocytopenia (NAIT).Design Cost-utility analysis on the basis of a decision tree that incorporates the relevant strategies and outcomes.Setting Three health regions in Norway encompassing a 2.78 million population.Population Pregnant women (n = 100,448) screened for human platelet antigen (HPA) 1a and anti-HPA 1a antibodies, and their babies.Method Decision tree analysis. In three branches of the decision tree, pregnant women entered a programme while in one no screening was performed. The three different screening strategies included all HPA 1a negative women, only HPA 1a negative, HLA DRB3*0101 positive women or only HPA 1a negative women with high level of anti-HPA 1a antibodies. Included women underwent ultrasound examination and elective caesarean section 2-4 weeks before term. Severely thrombocytopenic newborn were transfused immediately with compatible platelets.Main outcome measurements Quality-adjusted life years (QALYs) and costs.Results Compared with no screening, a programme of screening and subsequent treatment would generate between 210 and 230 additional QALYs among 100 000 pregnant women, and at the same time, reduce health care costs by approximately e1.7 million. The sensitivity analyses indicate that screening is cost effective or even cost saving within a wide range of probabilities and costs.Conclusion Our calculations indicate that it is possible to establish an antenatal screening programme for NAIT that is cost effective.

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Load Distributing Band (LDB) mechanical chest compression devices are used to treat out-of-hospital cardiac arrest (OHCA) patients. The artefacts that LDB chest compressions induce in the ECG impede a reliable shock/noshock diagnosis, resulting in compression interruptions to analyze the ECG. The aim of this study was to design a deep learning algorithm to accurately detect shockable rhythms with concurrent LDB compressions. The dataset was comprised of 780 shockable and 2644 nonshockable rhythms from 242 OHCA patients treated with the LDB device. Underlying rhythms were annotated by expert reviewers in artefact-free intervals. The method consisted of two stages: a Recursive Least Squares (RLS) filter to remove LDB compression artefacts and a shock/no-shock decision algorithm based on CNNs. Shock/no-shock diagnoses were compared with the rhythm annotations to obtain the sensitivity (Se) and specificity (Sp) of the method. The median Se, Sp were 92.2%, 96.6%, respectively. The proposed algorithm met the American Heart Association's (AHA) requirements for rhythm analysis.

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