Prevalence, Outcome, and Prevention of Congenital Cytomegalovirus Infection in Neonates Born to Women With Preconception Immunity (CHILd Study)

Background. Human cytomegalovirus (HCMV) is the leading infectious cause of congenital disabilities. We designed a prospective study to investigate the rate, outcome, and risk factors of congenital CMV (cCMV) infection in neonates born to immune women, and the potential need and effectiveness of hygiene recommendations in this population.Methods. The study was composed of 2 sequential parts: an epidemiology (part 1) and a prevention (part 2) study. Performance of part 2 depended upon a cCMV rate >0.4%. Women enrolled in part 1 did not receive hygiene recommendations. Newborns were screened by HCMV DNA testing in saliva and cCMV was confirmed by urine testing.Results. Saliva swabs were positive for HCMV DNA in 45/9661 newborns and cCMV was confirmed in 18 cases. The rate of cCMV was .19% (95% confidence interval [CI]: .11-.29%), and 3 out of 18 infants with cCMV had symptoms of CMV at birth. Age, nationality, occupation, and contact with children were similar between mothers of infected and noninfected newborns. Twin pregnancy (odds ratio [OR]: 7.2; 95% CI: 1.7-32.2; P=.037) and maternal medical conditions (OR: 3.9; 95% CI: 1.5-10.1; P= .003) appeared associated with cCMV. Given the rate of cCMV was lower than expected, the prevention part of the study was cancelled.Conclusions. Newborns from women with preconception immunity have a low rate of cCMV, which appears to be mostly due to reactivation of the latent virus. Therefore, serological screening in childbearing age would be pivotal to identify HCMV-seropositive women, whose newborns have a low risk of cCMV

Prevalence, Outcome, and Prevention of Congenital Cytomegalovirus Infection in Neonates Born to Women with Preconception Immunity (CHILd Study)

Background: Human cytomegalovirus (HCMV) is the leading infectious cause of congenital disabilities. We designed a prospective study to investigate the rate, outcome, and risk factors of congenital CMV (cCMV) infection in neonates born to immune women, and the potential need and effectiveness of hygiene recommendations in this population. Methods: The study was composed of 2 sequential parts: an epidemiology (part 1) and a prevention (part 2) study. Performance of part 2 depended upon a cCMV rate >0.4%. Women enrolled in part 1 did not receive hygiene recommendations. Newborns were screened by HCMV DNA testing in saliva and cCMV was confirmed by urine testing. Results: Saliva swabs were positive for HCMV DNA in 45/9661 newborns and cCMV was confirmed in 18 cases. The rate of cCMV was. 19% (95% confidence interval [CI]:. 11-.29%), and 3 out of 18 infants with cCMV had symptoms of CMV at birth. Age, nationality, occupation, and contact with children were similar between mothers of infected and noninfected newborns. Twin pregnancy (odds ratio [OR]: 7.2; 95% CI: 1.7-32.2; P =. 037) and maternal medical conditions (OR: 3.9; 95% CI: 1.5-10.1; P =. 003) appeared associated with cCMV. Given the rate of cCMV was lower than expected, the prevention part of the study was cancelled. Conclusions: Newborns from women with preconception immunity have a low rate of cCMV, which appears to be mostly due to reactivation of the latent virus. Therefore, serological screening in childbearing age would be pivotal to identify HCMV-seropositive women, whose newborns have a low risk of cCMV. Clinical trials registration: www.clinicaltrials.gov (NCT03973359)

Sonographic Charecterization, Doppler ultrasonography and tumor markers in the diagnosis of malignancy of ovarian masses

Minerva Gineco

Supervised semi-automated data analysis software for gas chromatography / differential mobility spectrometry (GC/DMS) metabolomics applications

Modern differential mobility spectrometers (DMS) produce complex and multi-dimensional data streams that allow for near-real-time or post-hoc chemical detection for a variety of applications. An active area of interest for this technology is metabolite monitoring for biological applications, and these data sets regularly have unique technical and data analysis end user requirements. While there are initial publications on how investigators have individually processed and analyzed their DMS metabolomic data, there are no user-ready commercial or open source software packages that are easily used for this purpose. We have created custom software uniquely suited to analyze gas chromatograph / differential mobility spectrometry (GC/DMS) data from biological sources. Here we explain the implementation of the software, describe the user features that are available, and provide an example of how this software functions using a previously-published data set. The software is compatible with many commercial or home-made DMS systems. Because the software is versatile, it can also potentially be used for other similarly structured data sets, such as GC/GC and other IMS modalities