Unveiling the hippocampal subfield changes across the Alzheimer's disease continuum: a systematic review of neuroimaging studies.

Studies exploring the hippocampal subfield atrophy in Alzheimer's disease (AD) have shown contradictory results. This review aims to disentangle such heterogeneity by investigating the dynamic changes of hippocampal subfields across the AD continuum. We systematically searched the PubMed and EMBASE databases for case-control studies.

Predicting amyloid-PET status in a memory clinic: The role of the novel antero-posterior index and visual rating scales.

Introduction: Visual rating scales are increasingly utilized in clinical practice to assess atrophy in crucial brain regions among patients with cognitive disorders. However, their capacity to predict Alzheimer's disease (AD)-related pathology remains unexplored, particularly within a heterogeneous memory clinic population. This study aims to assess the accuracy of a novel visual rating assessment, the antero-posterior index (API) scale, in predicting amyloid-PET status.

Cost-effectiveness and diagnostic accuracy of focused cardiac ultrasound in the pre-participation screening of athletes: the SPORT-FoCUS study.

Aims: The role of pre-participation screening (PPS) modalities in preventing sudden cardiac death (SCD) in athletes is debated due to a high false-positive rate. Focused cardiac ultrasound (FoCUS) has shown higher sensitivity and specificity, but its cost-effectiveness remains uncertain. This study aimed to determine the diagnostic performance and cost-effectiveness of FoCUS use in PPS.

Sars-CoV2 infection in pregnant women with multiple sclerosis.

Background: In the general population, maternal SARS-CoV-2 infection during pregnancy is associated with worse maternal outcomes; however, only one study so far has evaluated COVID-19 clinical outcomes in pregnant and postpartum women with multiple sclerosis, showing no higher risk for poor COVID-19 outcomes in these patients.

Objective: In this multicenter study, we aimed to evaluate COVID-19 clinical outcomes in pregnant patients with multiple sclerosis.

Methods: We recruited 85 pregnant patients with multiple sclerosis who contracted COVID-19 after conception and were prospectively followed-up in Italian and Turkish Centers, in the period 2020-2022.

Insight into Elderly ALS Patients in the Emilia Romagna Region: Epidemiological and Clinical Features of Late-Onset ALS in a Prospective, Population-Based Study.

Few studies have focused on elderly (>80 years) amyotrophic lateral sclerosis (ALS) patients, who represent a fragile subgroup generally not included in clinical trials and often neglected because they are more difficult to diagnose and manage. We analyzed the clinical and genetic features of very late-onset ALS patients through a prospective, population-based study in the Emilia Romagna Region of Italy. From 2009 to 2019, 222 (13.

Busulfan or Treosulfan Conditioning Platform for Allogeneic Stem Cell Transplantation in Patients Aged >60 Y With Acute Myeloid Leukemia/Myelodysplastic Syndrome: A Subanalysis of the GITMO AlloEld Study.

Unlabelled: The conditioning regimens with different alkylators at different doses can influence the outcome of allogeneic stem cell transplantation (SCT), but conclusive data are missing.

Methods: With the aim to analyze real-life allogeneic SCTs performed in Italy between 2006 and 2017 in elderly patients (aged >60 y) with acute myeloid leukemia or myelodysplastic syndrome, we collected 780 first transplants data. For analysis purposes, patients were grouped according to the type of alkylator included in the conditioning (busulfan [BU]-based; n = 618; 79%; treosulfan [TREO]-based; n=162; 21%).

Patients with multiple sclerosis choose a collaborative role in making treatment decision: results from the Italian multicenter SWITCH study.

Background: Clinicians are increasingly recognizing the importance of shared decision-making in complex treatment choices, highlighting the importance of the patient's rationale and motivation for switching therapies. This study aimed to evaluate the association between different modalities of changing multiple sclerosis (MS) treatments, cognitive profile and attitude and preferences of patients concerning treatment choice.

Methods: This multicenter cross-sectional study was conducted at 28 Italian MS centers in the period between June 2016 and June 2017.

An Impairment in Resting and Exertional Breathing Pattern May Occur in Long-COVID Patients with Normal Spirometry and Unexplained Dyspnoea.

Background: Long-term sequelae, called Long-COVID (LC), may occur after SARS-CoV-2 infection, with unexplained dyspnoea as the most common symptom. The breathing pattern (BP) analysis, by means of the ratio of the inspiratory time (TI) during the tidal volume (VT) to the total breath duration (TI/TTOT) and by the VT/TI ratio, could further elucidate the underlying mechanisms of the unexplained dyspnoea in LC patients. Therefore, we analysed TI/TTOT and VT/TI at rest and during maximal exercise in LC patients with unexplained dyspnoea, compared to a control group.

Revisiting a Prognosticating Algorithm from Cardiopulmonary Exercise Testing in Chronic Heart Failure (from the MECKI Score Population).

Cardiopulmonary exercise testing is a prognostic tool in heart failure with reduced left ventricular ejection fraction (HFrEF). Prognosticating algorithms have been proposed, but none has been validated. In 2017, a predictive algorithm, based on peak oxygen consumption (VO), ventilatory response to exercise (ventilation [VE] carbon dioxide production [VCO2], the VE/VCO slope), exertional oscillatory ventilation (EOV), and peak respiratory exchange ratio, was recommended, according treatment with β blockers: patients with HFrEF registered in the metabolic exercise test data combined with cardiac and kidney indexes (MECKIs) database were used to validated this algorithm.

Machine learning for prediction of in-hospital mortality in coronavirus disease 2019 patients: results from an Italian multicenter study.

Background: Several risk factors have been identified to predict worse outcomes in patients affected by SARS-CoV-2 infection. Machine learning algorithms represent a novel approach to identifying a prediction model with a good discriminatory capacity to be easily used in clinical practice. The aim of this study was to obtain a risk score for in-hospital mortality in patients with coronavirus disease infection (COVID-19) based on a limited number of features collected at hospital admission.

Pick Your Threshold: A Comparison Among Different Methods of Anaerobic Threshold Evaluation in Heart Failure Prognostic Assessment.

Background: In clinical practice, anaerobic threshold (AT) is used to guide training and rehabilitation programs, to define risk of major thoracic or abdominal surgery, and to assess prognosis in heart failure (HF). AT of oxygen uptake (V.O; V.

Cost-Utility Analysis of Dupilumab for the Treatment of Chronic Rhinosinusitis with Nasal Polyps (CRSwNP) in Italy.

The objective of this analysis was to estimate the incremental cost-utility ratio (ICUR) of dupilumab as an add-on treatment to best supportive care (BSC), versus BSC alone, in Italy for severe uncontrolled chronic rhinosinusitis with nasal polyps (CRSwNP). A simulation of outcomes and costs was undertaken using a 1-year decision tree, followed by a lifetime horizon Markov model. Clinical data were derived from a pooled analysis of two studies (SINUS-24 NCT02912468 and SINUS-52 NCT02898454).