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Introduction. This study aimed to estimate the incidence of SARS-CoV-2 infection among pregnant women during the first pandemic wave in Italy, and to describe CO-VID-19 disease characteristics and maternal and perinatal outcomes. Materials and methods. National population-based prospective cohort study collecting information on women with SARS-CoV-2 diagnosis, confirmed within 7 days from hospital admission. Results. The national SARS-CoV-2 rate was 6.04 per 1,000 births (95% CI 5.62-6.49) among pregnant women and 7.54 (95% CI 7.47-7.61) among women in reproductive age. 72.1% of the cohort developed mild COVID-19 disease without pneumonia nor need for ventilatory support. Severe disease was significantly associated with women’s previous comorbidities (OR 2.55; 95% CI 0.98-6.90), obesity (OR 4.76; 95% CI 1.79-12.66) and citizenship from High Migration Pressure Countries (OR 3.43; 95% CI 1.27-9.25). Conclusions. During the first pandemic wave in Italy, the SARS-CoV-2 rate among pregnant women was lower compared to that detected among women of reproductive age, and risks of severe COVID-19 disease and adverse maternal and perinatal outcomes were rare.

BackgroundNext generation sequencing (NGS) has increased detection sensitivity of intermediate chromosome copy number variations (CNV) consistent with chromosomal mosaicism. Recently, this methodology has found application in preimplantation genetic testing (PGT) of trophectoderm (TE) biopsies collected from IVF-generated human embryos. As a consequence, the detection rate of intermediate CNV states in IVF embryos has drastically increased, posing questions about the accuracy in identifying genuine mosaicism in highly heterogeneous biological specimens. The association between analytical values consistent with mosaicism and the reproductive potential of the embryo, as well as newborn’s chromosomal normalcy, have not yet been thoroughly determined.MethodsWe conducted a multicentre, double-blinded, non-selection trial including 1,190 patients undergoing in a total of 1,337 IVF with preimplantation genetic testing for aneuploidies (PGT-A) treatment cycles. NGS was performed on clinical TE biopsies collected from blastocyst-stage embryos. All embryos were reported as euploid if all autosomes had a chromosomal copy number value below the threshold of 50% abnormal cells per sample. After embryo transfer, three comparative classes were analysed: uniformly euploid profiles (ResultsLBR after transfer of uniformly euploid embryos, low-degree, and moderate-degree mosaic embryos were 43.4% (95% C.I. 38.9 - 47.9), 42.9% (95% C.I. 37.1 - 48.9) and 42% (95% C.I. 33.4 - 50.9), respectively. No difference was detected for this primary outcome between euploid and mosaic low/moderate categories (OR= 0.96; 95% CI 0.743 to 1.263; P=0.816). The non-inferiority endpoint was met as the confidence interval for the difference fell below the planned 7.5% margin (95% C.I. −5.7 - 7.3). Likewise, no statistically significant difference was observed comparing moderate versus low degree mosaic embryos (P=0.92). Neonatal karyotypes were also similar and no instances of mosaicism or uniparental disomies (UPDs) were detected in babies born following putative low or moderate-degree mosaic embryo transfer. Should the embryos with low or moderate-degree mosaic TE biopsies had been classified as chromosomally abnormal and thus discarded for clinical use, LBR per cycle would have decreased by 36% without any clinical benefit.ConclusionsThis prospective non-selection trial provides substantial evidence that reporting and/or not transferring embryos with low/moderate-degree mosaicism for whole chromosomes have no clinical utility. Moreover, dismissing these embryos from clinical use has the counterproductive effect of reducing overall embryo availability, thus reducing the chance of successful outcome derived from an IVF treatment without any clinical benefit. (Funded by Igenomix; ClinicalTrials.gov number, NCT03673592)

The knowledge of the fungal mycobiota of arthropods, including the vectors of human and animal diseases, is still limited. Here, we investigated the mycobiota associated with the sand fly Phlebotomus perniciosus, the main vector of leishmaniasis in the western Mediterranean area, by a culture-dependent approach (microbiological analyses and sequencing of the 26S rRNA gene), internal transcribed spacer (ITS) rRNA amplicon-based next-generation sequencing, fluorescence in situ hybridisation (FISH), and genome sequencing of the dominant yeast species. The dominant species was Meyerozyma guilliermondii, known for its biotechnological applications. We focused the attention on this yeast and we investigated its prevalence in adults, pupae and larvae of reared sand flies (overall prevalence: 57.5%) and of field-collected individuals (overall prevalence: 9%). Using whole-mount FISH and microscopic examination, we further showed that M. guilliermondii colonizes the midgut of females, males and larvae and the distal part of Malpighian tubules of female sand flies, suggesting a possible role in urate degradation. Finally, the sequencing and analysis of the genome of M. guilliermondii allowed to predict the complete uric acid degradation pathway, suggesting that the yeast could contribute to the removal of the excess of nitrogenous wastes after the blood meal of the insect host.

Background Lupus nephritis (LN) presentation changed over time following earlier diagnosis and treatment. Objectives To evaluate changes in LN clinical and histological presentation in the last 5 decades. Methods This is a retrospective multicentric study on prospectively collected data in four Italian hospital centres. Patients diagnosed between 1970 and 2016 were recruited provided they had a biopsy-proven LN that was retrospectively reclassified according to the ISN/RPS classification criteria. Follow-up was subdivided into three periods (P) based on the year of LN diagnosis: P1:1970–1895; P2:1986–2000; P3:2001–2016. Predictors of patient and renal survival were investigated by univariate and multivariate analysis; survival curves were compared by log-rank test. Clinical pictures at presentation included isolated urinary abnormalities, nephrotic syndrome, nephritic syndrome, rapidly progressive renal failure. Outcome at last observation was defined as complete renal remission or partial renal remission, or poor renal outcome, including chronic kidney disease (CKD) or end stage renal disease (ESRD). Results 499 patients were included (85.6% females) with a median follow-up of 10.6 years (IQR 4–18). We observed an increase in both age at diagnosis of LN (P1 28.4±10.4; P2 29±11.5; P3 34.4±13.3 years) and disease duration before LN diagnosis (P1 1.3±1.3; P2 2.6±4.5; P3 4.6±6.3 years) from 1970 to 2016 (p

Objectives: To identify common methodological challenges and review relevant initiatives related to the re-use of patient data collected in routine clinical care, as well as to analyze the economic benefits derived from the secondary use of this data. Through the use of several examples, this article aims to provide a glimpse into the different areas of application, namely clinical research, genomic research, study of environmental factors, and population and health services research. This paper describes some of the informatics methods and Big Data resources developed in this context, such as electronic phenotyping, clinical research networks, biorepositories, screening data banks, and wide association studies. Lastly, some of the potential limitations of these approaches are discussed, focusing on confounding factors and data quality. Methods: A series of literature searches in main bibliographic databases have been conducted in order to assess the extent to which existing patient data has been repurposed for research. This contribution from the IMIA working group on "Data mining and Big Data analytics" focuses on the literature published during the last two years, covering the timeframe since the working group's last survey. Results and Conclusions: Although most of the examples of secondary use of patient data lie in the arena of clinical and health services research, we have started to witness other important applications, particularly in the area of genomic research and the study of health effects of environmental factors. Further research is needed to characterize the economic impact of secondary use across the broad spectrum of translational research.

Background: Anti-IgE treatment represents a major breakthrough in the therapeutic management of severe allergic asthma. To date, omalizumab is the only biological drug currently licensed as add-on therapy in children aged > 6 years with moderate-to-severe and severe allergic asthma uncontrolled after treatment with high dose of inhaled corticosteroids plus long-acting inhaled beta2-agonist. The clinical efficacy and safety of omalizumab treatment in the pediatric population has been extensively documented in specific trials and consistently expanded from real-life studies. Our aim is to describe the impact of omalizumab on asthma management, by reporting the results of the first Italian multicenter observational study conducted in children and adolescents with severe allergic asthma. Methods: The study was a 1-year real-life multicenter survey conducted in 13 pediatric allergy and pulmonology tertiary centers in Italy. All patients with confirmed severe allergic asthma from whom Omalizumab add-on treatment was initiated between 2007 and 2015 were included in the study. Results: Forty-seven patients with severe allergic asthma were included in the study. A significant reduction in the number of asthma exacerbations was observed during treatment with omalizumab, when compared with the previous year (1.03 vs 7.2 after 6 months (p

We propose a model for the incorporation of risk in association rule application. We validate this model using data gathered in a randomized controlled trial from a recommender system for medication reviews in primary care. The model’s outcomes are found to have predictive value when tested against decisions made by physicians on 261 patients’ health records.

Causal discovery is an increasingly popular method for data analysis in the field of medical research. In this paper we consider two challenges in causal discovery that occur very often when working with medical data: a mixture of discrete and continuous variables and a substantial amount of missing values. To the best of our knowledge there are no methods that can handle both challenges at the same time. In this paper we develop a new method that can handle these challenges based on the assumption that data is missing completely at random and that variables obey a non-paranormal distribution. We demonstrate the validity of our approach for causal discovery for empiric data from a monetary incentive delay task. Our results may help to better understand the etiology of attention deficit-hyperactivity disorder (ADHD).

We present a Naive Bayes classification model where the features are temporal association rules (TARs) annotated with their possible recurrence patterns, referred to as periodic TARs. To analyze clinical time series we rely on several Temporal Data Mining (TDM) methods, like temporal abstractions (TAs). We used this approach to diagnose coronary heart disease (CHD) based on patient history. Firstly, we exploited TAs to preprocess data and obtain qualitative and trend temporal patterns. Secondly, we applied a temporal pattern mining algorithm able to detect TARs by identifying the most frequent temporal relationships among the TAs. Finally, the classifier incorporates periodic TARs as its features, by considering the possible recurrence patterns of each TAR within the relevant patient history. A key claim of this research is that where long time periods are of significance in some medical domain, such as the CHD domain, higher order temporal abstractions can yield better performance. The viability of this claim is demonstrated by comparing the performance of the classifier with periodic TARs as its features with that of a baseline classifier whose features are simple TARs representing the occurrence or not of temporal relationships, without consideration of possible periodic occurrences of the given temporal relationships. The results obtained illustrate the comparatively high performance of the periodic TAR classifier over the baseline, simple TARs classifier, thus demonstrating the effectiveness of the proposed approach.