Paediatric apnoeas are not related to a specific respiratory virus, and parental reports predict hospitalisation.

AIM: The aim of this study was to determine the frequency of apnoeas in previously healthy young infants with acute respiratory tract infection (ARI) and correlate their occurrence with isolated micro-organisms, clinical findings, disease severity and outcome. METHODS: We performed reverse transcriptase real-time polymerase chain reaction (RT-PCR) on the nasal wash specimens of a prospective cohort study of 582 children with ARI. Clinical data on a subgroup of 241 infants under three months of age, with and without apnoeas, were compared. RESULTS: Our study found that 19 (7.9%) of the 241 infants under three months old had a history of apnoeas: eight had a respiratory syncytial virus (RSV), five had a different virus than RSV and seven RT-PCR results were negative. Infants with apnoeas were more likely to have cyanosis, had longer hospital stays and required extra oxygen for a longer period. Most patients with parental reported apnoeas also experienced apnoeas during hospitalisation. CONCLUSION: This study observed apnoeas irrespective of the isolated micro-organism, and we hypothesise that they were related to the pathophysiology of the respiratory infection and not to the micro-organism itself. Parental reported apnoeas were a major warning sign and predicted that apnoeas would occur in hospital.

Comparative spectra analysis (CoSA): spectra as three-dimensional molecular descriptors for the prediction of biological activities.

A novel 3D QSAR approach, comparative spectra analysis (CoSA), in which molecular spectra are used as three-dimensional molecular descriptors for the prediction of biological activities, is presented and discussed. To this purpose, experimentally determined 1H NMR, mass, and IR spectra, as well as simulated IR and 13C NMR spectra, for a set of 45 diverse progestagens are converted by a program, SpecMat, into matrixes, which are subsequently employed in a multivariate regression analysis (PLS). The results are compared with those resulting from a comparative molecular field analysis (CoMFA). When used individually, spectral descriptors yield better correlations and predictions than molecular field descriptors. A combination of spectral descriptors with other descriptors, either spectral or molecular field in nature, leads in most cases to models that are statistically superior to the ones obtained by their corresponding individual spectral or molecular field descriptors.