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Sarcopenia is characterised by loss of muscle mass and strength. Although ageing is the most likely risk factor of sarcopenia, sarcopenia is prevalent even in non-elderly people. Type 2 diabetes (T2D) is a risk factor for sarcopenia, as T2D shares with sarcopenia several aetiological factors. Meanwhile, gestational diabetes mellitus (GDM) is characterised by metabolic alterations that resemble those observed in T2D, including increased insulin resistance (present even in physiologic pregnancies). Hence, GDM presents two major risk factors for sarcopenia, that is, dysglycaemia and insulin resistance. Moreover, the number of pregnancies at age >40 years is increasing, which is in an age range in which sarcopenia prevalence is already not negligible. However, data on the prevalence of sarcopenia prevalence in GDM and its effect on pregnancy outcomes are limited. Thus, this study aims to evaluate the prevalence of sarcopenia in women with GDM (and in pregnant women without GDM), identify risk factors and determine its effect on delivery and maternal and fetal outcomes.
For this study, 100 each of women with and without GDM will be recruited. Women will undergo an oral glucose tolerance test within weeks 24–28 for possible GDM diagnosis (in weeks 16–18 for high-risk women). Muscle/physical performance tests will be conducted at weeks 28–32 for possible diagnosis of sarcopenia/presarcopenia. Cognitive function will also be assessed. For all women, information regarding pregnancy progression, along with any complications, will be collected. Collected data will be analysed according to the main objectives of the study: (i) determine the prevalence of sarcopenia/presarcopenia in pregnancy with and without GDM, (ii) identify factors associated with sarcopenia risk, (iii) determine the effect of sarcopenia/presarcopenia on pregnancy outcomes, (iv) explore the relationship between sarcopenia and cognitive function. Therefore, this study will provide information on sarcopenia/presarcopenia prevalence in GDM and, possibly, in pregnancy not complicated by dysglycaemia. Furthermore, the study will provide knowledge on the main factors associated with sarcopenia/presarcopenia in GDM/pregnancy. The identification of such factors will be relevant for an initial guidance for treatments that may prevent sarcopenia in GDM/pregnant women. This will become of even greater interest if sarcopenia/presarcopenia influences pregnancy outcomes, especially in GDM women.
The study protocol has been approved by the Comitato Etico Regione Toscana - Area Vasta Nord Ovest (CEAVNO) on 25 July 2024 and by the Local Ethics Committee of the Medical University of Vienna on 17 June 2024. Participants’ enrolment began in May 2025. The results of the study will be presented at national and international conferences and in peer-reviewed journals.
ClinicalTrials.gov Identifier: NCT06876090; Registration Date: 2025-03-14
Evidence-based practice (EBP) is widely endorsed as a cornerstone for high-quality, patient-centered care. However, its integration into daily clinical routines remains inconsistent, particularly in settings where cultural, educational, and organizational challenges persist. Reliable, contextually adapted tools are essential to measure EBP implementation and guide improvement efforts.
This study aimed to validate the Italian versions of the EBP Implementation Scale and its short-form (3-item) version.
A cross-sectional survey design was adopted. Both versions of the EBP Implementation Scale were translated and culturally adapted in accordance with internationally recognized guidelines. Data were gathered from a national sample of 405 nurses through a combination of convenience and snowball sampling. Psychometric assessment encompassed confirmatory and Bayesian factor analyses, evaluation of internal consistency and test–retest reliability, and measurement invariance testing. All analyses were performed in R Studio.
Confirmatory factor analyses confirmed that both versions (long and short) of the scale measure a single underlying construct. The instruments demonstrated high reliability (ω = 0.96 and 0.87 respectively). Measurement invariance across educational groups was partially established, as the partial scalar invariance model demonstrated acceptable fit (CFI = 0.991, RMSEA = 0.045), suggesting consistent interpretation of the scale across different levels of EBP training. Latent profile analysis revealed distinct subgroups of EBP implementers, with notable differences in latent means (p < 0.001) associated with previous education in evidence-based practice.
The Italian EBP Implementation Scales are valid and reliable tools for assessing EBP implementation behaviors. They can support education planning, monitor practice changes over time, and inform interventions aimed at enhancing evidence-based care.
by Giacinto Angelo Sgarro, Paride Vasco, Domenico Santoro, Luca Grilli, Marco Giglio, Natale Daniele Brunetti, Luigi Traetta, Giuseppe Cibelli, Anna Antonia Valenzano
Sudden Cardiac Death (SCD) is a critical and unexpected condition that occurs due to cardiac causes within one hour of the onset of acute cardiovascular symptoms or twenty-four hours in unwitnessed cases. Despite advancements in cardiovascular medicine, practical methods for predicting SCD are still lacking, and there are no standardized systems to identify individuals at risk, especially in seemingly healthy populations such as athletes. In this study, we employed hierarchical clustering and principal component analysis (PCA) on data from 711 competitive athletes, revealing distinct patterns and cluster distributions in PCA space. Specifically, Clustering revealed characteristic feature combinations associated with increased SCD risk in athletes. Notably, certain clusters shared traits, including participation in Class C sports, sinus tachycardia, ventricular pre-excitation, personal or family history of heart disease, T-wave inversions, and prolonged QTc intervals. PCA helped visualize these patterns in distinct spatial regions, highlighting underlying structures and aiding intuitive risk interpretation. These results enable scientists to derive cluster metrics that serve as reference points for classifying new individuals and visually representing risk patterns in a clear graphical format. These findings establish a foundation for predictive tools that, with additional clinical validation, could aid in the prevention of SCD. The dataset used in this study, along with the clustering and PCA results, is available to the scientific community in an open format, together with the necessary tools and scripts to enable independent experimentation and further analysis.
FreshRSS 