Incidence and risk factors of hospitalization for bronchiolitis in preterm children: a retrospective longitudinal study in Italy

<p>Abstract</p> <p>Background</p> <p>Bronchiolitis is a distressing, potentially life-threatening respiratory condition that affects infants. We evaluated the incidence and risk factors of hospitalization for broncholitis in preterm infants (i.e., a gestational age of <36 weeks) born between 2000 and 2006, and the use and impact of Palivizumab, a monoclonal antibody that in randomized clinical trials has been shown to lessen the severity of RSV-related bronchiolitis.</p> <p>Methods</p> <p>Retrospective cohort study that linked data from four health administrative databases in the Lazio region (a region of central Italy): the birth register, the hospital discharge register, and two ad-hoc databases that record the doses of Palivizumab administered at two local health units.</p> <p>Results</p> <p>Among 2407 preterm infants, 137 had at least one hospitalization for bronchiolitis in the first 18 months of life, an overall incidence rate of 4.70 per 100 person-years (95%CI: 3.98-5.56); similar incidence rates were observed by calendar year. A multiple Poisson model showed that the following characteristics were associated with higher incidence: younger age of the infant, the period between October-April, male gender, low Apgar score at birth, low birth weight, and low maternal educational level. At least one dose of Palivizumab was administered to 324 (13.5%) children; a dramatic increase from 2000 (2.8%) to 2006 (19.1%) (p < 0.01) was observed. Other factors independently associated with more frequent Palivizumab use were older maternal age, Italian-born mothers, female gender, low Apgar score, low birth weight, shorter gestational age, a diagnosis of broncho-dysplasia, and the month of birth. It is of note that none of the 34 children with congenital heart disease were prescribed Palivizumab. Performing several multiple Poisson models that also considered Palivizumab use as covariate, although the point estimates were in agreement with previous clinical trial results, we did not find in most of them a significant reduction for immunized children to be hospitalized for bronchiolitis.</p> <p>Conclusion</p> <p>In Italy the incidence of hospitalization for bronchiolitis, and its associated risk factors, are similar to that found in other countries. Although Palivizumab use is associated with the most important characteristics of severe prematurity, other aspects of its non-use in children with congenital heart disease, the age and the birth country of the mother suggest the need for public health measures that can reduce these health disparities. Finally, the estimated effectiveness of Palivizumab in routine practice, although not significant, confirms the results of previous clinical trials, but its impact on modifying the temporal trend in this population is still negligible.</p

Artificial Intelligence Predictive Models of Response to Cytotoxic Chemotherapy Alone or Combined to Targeted Therapy for Metastatic Colorectal Cancer Patients: A Systematic Review and Meta-Analysis

Simple Summary Metastatic colorectal cancer (mCRC) has high incidence and mortality. Nevertheless, innovative biomarkers have been developed for predicting the response to therapy. We have examined the ability of learning methods to build prognostic and predictive models to predict response to chemotherapy, alone or combined with targeted therapy in mCRC patients, by targeting specific narrative publications. After a literature search, 26 original articles met inclusion and exclusion criteria and were included in the study. We showed that all investigations conducted in this field provided generally promising results in predicting the response to therapy or toxic side-effects, using a meta-analytic approach. We found that radiomics and molecular biomarker signatures were able to discriminate response vs. non-response by correctly identifying up to 99% of mCRC patients who were responders and up to 100% of patients who were non-responders. Our study supports the use of computer science for developing personalized treatment decision processes for mCRC patients. Tailored treatments for metastatic colorectal cancer (mCRC) have not yet completely evolved due to the variety in response to drugs. Therefore, artificial intelligence has been recently used to develop prognostic and predictive models of treatment response (either activity/efficacy or toxicity) to aid in clinical decision making. In this systematic review, we have examined the ability of learning methods to predict response to chemotherapy alone or combined with targeted therapy in mCRC patients by targeting specific narrative publications in Medline up to April 2022 to identify appropriate original scientific articles. After the literature search, 26 original articles met inclusion and exclusion criteria and were included in the study. Our results show that all investigations conducted on this field have provided generally promising results in predicting the response to therapy or toxic side-effects. By a meta-analytic approach we found that the overall weighted means of the area under the receiver operating characteristic (ROC) curve (AUC) were 0.90, 95% C.I. 0.80-0.95 and 0.83, 95% C.I. 0.74-0.89 in training and validation sets, respectively, indicating a good classification performance in discriminating response vs. non-response. The calculation of overall HR indicates that learning models have strong ability to predict improved survival. Lastly, the delta-radiomics and the 74 gene signatures were able to discriminate response vs. non-response by correctly identifying up to 99% of mCRC patients who were responders and up to 100% of patients who were non-responders. Specifically, when we evaluated the predictive models with tests reaching 80% sensitivity (SE) and 90% specificity (SP), the delta radiomics showed an SE of 99% and an SP of 94% in the training set and an SE of 85% and SP of 92 in the test set, whereas for the 74 gene signatures the SE was 97.6% and the SP 100% in the training set

Molecular Characterization of Autochthonous Chikungunya Cluster in Latium Region, Italy

We report partial molecular characterization of isolates from an autochthonous chikungunya virus cluster in the Latium Region of Italy. E1 sequences from 3 patients differ substantially from sequences from the 2007 outbreak in Italy and lack the A226V substitution associated with increased viral fitness in the Aedes albopictus mosquito vector

Inverse correlation between plasma 2‐arachidonoylglycerol levels and subjective severity of depression

Objective: Endocannabinoids have been implicated in the pathophysiology of Major Depressive Disorder (MDD) and might represent potential targets for therapeutic intervention. Objectives of the study were: (1) to measure plasma levels of endocannabinoids in a group of antidepressant-free depressed outpatients; (2) to explore their relationship with the severity of depressive symptoms as subjectively perceived by the patients; and (3) to investigate the effect of the selective serotonin reuptake inhibitor escitalopram on endocannabinoid levels. Methods: We measured plasma levels of the two major endocannabinoids, 2-arachidonoylglycerol (2-AG) and N-arachidonoylethanolamine (anadamide), in 12 drug-free outpatients diagnosed with MDD and in 12 matched healthy controls. In the patient group, endocannabinoids plasma levels were assessed at baseline and after 2 months of treatment with escitalopram. Results: Baseline plasma levels of the two endocannabinoids did not differ between depressed patients and healthy controls. However, there was a significant inverse correlation between 2-arachidonoylglycerol levels and the severity of subjectively perceived depressive symptoms. Treatment with escitalopram did not change endocannabinoid levels in depressed patients, although it caused the expected improvement of depressive symptoms. Conclusions: Our results suggest that 2-arachidonylglycerol, the most abundant endocannabinoid in the central nervous system, might act to mitigate depressive symptoms, and raise the interesting possibility that 2-arachidonylglycerol and anandamide are differentially regulated in patients affected by MDD. Also, our data suggest but do not prove that the endocannabino