A spatio-temporal model based on discrete latent variables for the analysis of COVID-19 incidence

We propose a model based on discrete latent variables, which are spatially associated and time specific, for the analysis of incident cases of SARS-CoV-2 infections. We assume that for each area the sequence of latent variables across time follows a Markov chain with initial and transition probabilities that also depend on latent variables in neighboring areas. The model is estimated by a Markov chain Monte Carlo algorithm based on a data augmentation scheme, in which the latent states are drawn together with the model parameters for each area and time. As an illustration we analyze incident cases of SARS-CoV-2 collected in Italy at regional level for the period from February 24, 2020, to January 17, 2021, corresponding to 48 weeks, where we use number of swabs as an offset. Our model identifies a common trend and, for every week, assigns each region to one among five distinct risk groups

A nonparametric multidimensional latent class IRT model in a Bayesian framework

We propose a nonparametric Item Response Theory model for dichotomously scored items in a Bayesian framework. Partitions of the items are defined on the basis of inequality constraints among the latent class success probabilities. A Reversible Jump type algorithm is described for sampling from the posterior distribution. A consequence is the possibility to make inference on the number of dimensions (i.e., number of groups of items measuring the same latent trait) and to cluster items when unidimensionality is violated

Dimension reduction for longitudinal multivariate data by optimizing class separation of projected latent Markov models

We present a method for dimension reduction of multivariate longitudinal data, where new variables are assumed to follow a latent Markov model. New variables are obtained as linear combinations of the multivariate outcome as usual. Weights of each linear combination maximize a measure of separation of the latent intercepts, subject to orthogonality constraints. We evaluate our proposal in a simulation study and illustrate it using an EU-level data set on income and living conditions, where dimension reduction leads to an optimal scoring system for material deprivation. An R implementation of our approach can be downloaded from https://github.com/afarcome/LMdim

Diversity of cervical microbiota in asymptomatic chlamydia trachomatis genital infection: a pilot study

Chlamydia trachomatis genital infection continues to be an important public health problem worldwide due to its increasing incidence. C. trachomatis infection can lead to severe sequelae, such as pelvic inflammatory disease, obstructive infertility, and preterm birth. Recently, it has been suggested that the cervico-vaginal microbiota may be an important defense factor toward C. trachomatis infection as well as the development of chronic sequelae. Therefore, the investigation of microbial profiles associated to chlamydial infection is of the utmost importance. Here we present a pilot study aiming to characterize, through the metagenomic analysis of sequenced 16s rRNA gene amplicons, the cervical microbiota from reproductive age women positive to C. trachomatis infection. The main finding of our study showed a marked increase in bacterial diversity in asymptomatic C. trachomatis positive women as compared to healthy controls in terms of Shannon's diversity and Shannon's evenness (P = 0.031 and P = 0.026, respectively). More importantly, the cervical microbiota from C. trachomatis positive women and from healthy controls significantly separated into two clusters in the weighted UniFrac analysis (P = 0.0027), suggesting that differences between the two groups depended entirely on the relative abundance of bacterial taxa rather than on the types of bacterial taxa present. Furthermore, C. trachomatis positive women showed an overall decrease in Lactobacillus spp. and an increase in anaerobes. These findings are part of an ongoing larger epidemiological study that will evaluate the potential role of distinct bacterial communities of the cervical microbiota in C. trachomatis infection

Testicular histopathology, semen analysis and FSH, predictive value of sperm retrieval: supportive counseling in case of reoperation after testicular sperm extraction (TESE)

Background: To provide indicators for the likelihood of sperm retrieval in patients undergoing testicular sperm extraction is a major issue in the management of male infertility by TESE. The aim of our study was to determine the impact of different parameters, including testicular histopathology, on sperm retrieval in case of reoperation in patients undergoing testicular sperm extraction. Methods: We retrospectively analyzed 486 patients who underwent sperm extraction for intracytoplasmic sperm injection and testicular biopsy. Histology was classified into: normal spermatogenesis; hypospermatogenesis (reduction in the number of normal spermatogenetic cells); maturation arrest (absence of the later stages of spermatogenesis); and Sertoli cell only (absence of germ cells). Semen analysis and serum FSH, LH and testosterone were measured. Results: Four hundred thirty patients had non obstructive azoospermia, 53 severe oligozoospermia and 3 necrozoospermia. There were 307 (63%) successful sperm retrieval. Higher testicular volume, lower levels of FSH, and better histological features were predictive for sperm retrieval. The same parameters and younger age were predictive factors for shorter time for sperm recovery. After multivariable analysis, younger age, better semen parameters, better histological features and lower values of FSH remained predictive for shorter time for sperm retrieval while better semen and histology remained predictive factors for successful sperm retrieval. The predictive capacity of a score obtained by summing the points assigned for selected predictors (1 point for Sertoli cell only, 0.33 points for azoospermia, 0.004 points for each FSH mIU/ml) gave an area under the ROC curve of 0.843. Conclusions: This model can help the practitioner with counseling infertile men by reliably predicting the chance of obtaining spermatozoa with testicular sperm extraction when a repeat attempt is planne

Estimating COVID-19-induced excess mortality in Lombardy, Italy

We compare the expected all-cause mortality with the observed one for different age classes during the pandemic in Lombardy, which was the epicenter of the epidemic in Italy. The first case in Italy was found in Lombardy in early 2020, and the first wave was mainly centered in Lombardy. The other three waves, in Autumn 2020, March 2021 and Summer 2021 are also characterized by a high number of cases in absolute terms. A generalized linear mixed model is introduced to model weekly mortality from 2011 to 2019, taking into account seasonal patterns and year-specific trends. Based on the 2019 year-specific conditional best linear unbiased predictions, a significant excess of mortality is estimated in 2020, leading to approximately 35000 more deaths than expected, mainly arising during the first wave. In 2021, instead, the excess mortality is not significantly different from zero, for the 85+ and 15-64 age classes, and significant reductions with respect to the 2020 estimated excess mortality are estimated for other age classes

Hepatitis C virus eradication with directly acting antivirals improves health-related quality of life and psychological symptoms

BACKGROUND Alterations in health-related quality of life (HRQoL) and neuropsychological disorders were described in the hepatitis C virus (HCV) patients. Although several studies investigated the modifications of HRQoL after HCV eradication, no data exists on the modifications of neuropsychological symptoms. AIM To investigate the effect of directly acting antivirals (DAAs) treatment on HRQoL and neuropsychological symptoms. METHODS Thirty nine patients with HCV infection underwent a neuropsychological assessment, including Zung-Self Depression-Rating-Scale, Spielberg State-Trait Anxiety Inventory Y1-Y2 and the Toronto-Alexithymia Scale-20 items before and after DAAs treatment. HRQoL was detected by Short-Form-36 (SF-36). RESULTS All HRQoL domains, but role limitation physical and bodily pain, significantly improved after treatment. Interestingly, after DAAs treatment, all domains of HRQoL returned similar to those of controls. Each neuropsychological test significantly improved after HCV eradication. A significant correlation was observed among each psychological test and the summary components of SF-36. At multiple linear regression analysis including each psychological test as possible covariates, Zung-Self Depression Rating Scale (Zung-SDS) score was independently and significantly related to summary components of the SF-36 in the basal state and the difference between Zung-SDS score before and after treatment was the only variable significantly and independently related to the modification of HRQoL induced by the treatment. CONCLUSION Neuropsychological symptoms strongly influenced HRQoL in HCV patients and there was a significant improvement of neuropsychological tests and HRQoL after DAAs treatment