The psychometric evaluation of the Italian version of the Surgical Fear Questionnaire in adult patients waiting for major cardiac surgery.

Background and aim: Preoperative surgical fear is an emotional reaction that can be observed in many patients who are waiting to undergo a surgical procedure. The Surgical Fear Questionnaire was originally developed to determine the level of fear in patients who are expected to undergo elective surgery. This study aims to test the validity and reliability of this Italian version in a population of patients waiting for major cardiac surgery. Study design: Methodological research model. Methods: The population of this methodological study included the patients who presented to Lecco Hospital in Italy between January 2022 and October 2023 and were scheduled to undergo valve surgery, aortic surgery or coronary surgery; the sample involved 416 patients who met the inclusion criteria. Results: Results of the analyses showed that the Surgical Fear Questionnaire can be used with two subscales; the "Surgical Fear Questionnaire-S", which shows the fear of the short-term consequences of cardiac-surgery, and the "Surgical Fear Questionnaire-L", which shows the fear of the long-term consequences of cardiac-surgery. The mean score of the patients was 26.32+9.23 on the former, 27.62+11.89 on the latter, and 53.94 +19.16 for the entire questionnaire. The Cronbach's α coefficient was 0.952 for the "Surgical Fear Questionnaire-S", 0.920 for the "Surgical Fear Questionnaire-L", and 0.914 for the entire questionnaire. Conclusion: Based on the validity and reliability tests, we consider the questionnaire adaptable to the Italian reality, specifically to the population waiting for major cardiac surgery.

Strain Monitoring and Crack Detection in Masonry Walls under In-Plane Shear Loading Using Smart Bricks: First Results from Experimental Tests and Numerical Simulations.

A diffuse and continuous monitoring of the in-service structural response of buildings can allow for the early identification of the formation of cracks and collapse mechanisms before the occurrence of severe consequences. In the case of existing masonry constructions, the implementation of tailored Structural Health Monitoring (SHM) systems appears quite significant, given their well-known susceptibility to brittle failures. Recently, a new sensing technology based on smart bricks, i.e., piezoresistive brick-like sensors, was proposed in the literature for the SHM of masonry constructions. Smart bricks can be integrated within masonry to monitor strain and detect cracks. At present, the effectiveness of smart bricks has been proven in different structural settings. This paper contributes to the research by investigating the strain-sensitivity of smart bricks of standard dimensions when inserted in masonry walls subjected to in-plane shear loading. Real-scale masonry walls instrumented with smart bricks and displacement sensors were tested under diagonal compression, and numerical simulations were conducted to interpret the experimental results. At peak condition, numerical models provided comparable strain values to those of smart bricks, i.e., approximately equal to 10-4, with similar trends. Overall, the effectiveness of smart bricks in strain monitoring and crack detection is demonstrated.

Co-infections in critically ill adults with severe acute respiratory syndrome coronavirus 2 infection: an Italian multi-center prospective study.

BACKGROUND: To date, few studies have described Hospital-acquired infections (HAIs) during COVID-19 outbreak. To examine the incidence of HAIs in critically ill adult patients with SARS-CoV-2 infection and to observe risk factors, and the impact on outcome of HAI. METHODS: A prospective multicenter study was conducted that included adult patients with SARS-CoV-2 infection admitted to 18 Italian Intensive Care Units from September 2020 to November 2021. RESULTS: A total of 589 patients were included. A total of 233 patients were diagnosed with at least one HAI (39.6%). The co-infection/co-colonization rate >48 hours after admission was 31.0 per 1000 person-days (95% CI 18.8-34.8). Age, length of ICU stay >7 days, obesity, type 2 diabetes mellitus, cardiovascular disease, inserted central venous catheter, intubation, APACHE II score >25, mechanical ventilation (MV) >48 hours, obesity and inserted urinary catheter are associated outcomes for infection acquisition. The overall mortality rate of patients was found to be significantly higher in patients who had acquired a HAI (RR=4.37; 95% CI 3.30-5.78; P<0.001). CONCLUSIONS: Associated factors for HAI acquisition and mortality in ICU patients were identified and cause for revision of existing infection control policies.

Carbon Microfiber-Doped Smart Concrete Sensors for Strain Monitoring in Reinforced Concrete Structures: An Experimental Study at Various Scales.

Concrete constructions need widespread monitoring for the control of their state of integrity during their service life. In particular, after critical events such as earthquakes, this type of structure may experience the formation and development of cracks and damage. A quick and affordable assessment of structural behavior is indicated to identify conditions of danger for users and the incipient collapse of structural elements. This work presents investigations on multifunctional concretes with self-sensing capabilities to carry out static and dynamic monitoring. The materials were produced by the addition of conductive carbon microfibers to the concrete matrix. Electrical and sensing tests were carried out on samples with small-, medium-, and full-scale dimensions. The tests demonstrated the good electrical and electromechanical properties of the proposed smart concrete sensors, which appear promising for their use in civil elements or structures. In particular, tests on real-scale beams demonstrated the capability of the material to monitor the dynamic behavior of full-scale structural elements.

Impact of COVID-19 outbreak on ICU nurses' mental health. An Italian multicenter study. / Impatto dell'epidemia di COVID-19 sulla salute mentale degli infermieri di Terapia Intensiva. Uno studio multicentrico Italiano.

AIM: AIM: The aim of this study was to evaluate variations in ICU nurses ' mental health status over the COVID-19 outbreak by quantifying the extent of symptoms of depression, anxiety and PTSD over time. METHODS: METHODS: This study was an Italian multicenter prospective cohort study assessing caseness of anxiety, depression and PTSD at 6 and 12 months from the beginning of the COVID-19 outbreak in Italy. RESULTS: RESULTS: A total of 359 nurses, 233 (64.9%) were males and 126 (35.1%) were females were enrolled. At 6 months the caseness prevalence for anxiety, depression and PTSD were 31.3%, 32.1% and 18.7% respectively. At 12 months the caseness prevalence for anxiety, depression and PTSD were 34.8%, 36.4% and 24.1 % respectively. No statistically significant increase between 6 and 12 months was recorded for the caseness prevalence anxiety (p= .29) and depression (p= .19). However, an increase for the caseness prevalence PTSD at 12 months was observed (p= .049). The significant risk factors for the 221 patients with at least one disorders were age 31-40 (RR= 1.44, IC= 1.25-1.89; p < .001), female gender (RR= 1.31, IC= 1.02-1.51; p=. 042) and had 0-5 years of professional experience (RR= 1.36, IC= 1.02-1.63; p = .031). CONCLUSION: The results of our study may provide support for the implementation of some interventions for well-being in COVID-19 outbreak condition.

A Multichannel Strain Measurement Technique for Nanomodified Smart Cement-Based Sensors in Reinforced Concrete Structures.

Nanomodified smart cement-based sensors are an emerging self-sensing technology for the structural health monitoring (SHM) of reinforced concrete (RC) structures. To date, several literature works demonstrated their strain-sensing capabilities, which make them suited for damage detection and localization. Despite the most recent technological improvements, a tailored measurement technique allowing feasible field implementations of smart cement-based sensors to concrete structures is still missing. In this regard, this paper proposes a multichannel measurement technique for retrieving strains from smart cement-based sensors embedded in RC structures using a distributed biphasic input. The experiments performed for its validation include the investigation on an RC beam with seven embedded sensors subjected to different types of static loading and a long-term monitoring application on an RC plate. Results demonstrate that the proposed technique is effective for retrieving time-stable simultaneous strain measurements from smart cement-based sensors, as well as for aiding the identification of the changes in their electrical outputs due to the influence of environmental effects variable over time. Accordingly, the proposed multichannel strain measurement technique represents a promising approach for performing feasible field implementations of smart cement-based sensors to concrete structures.

Hybrid Carbon Microfibers-Graphite Fillers for Piezoresistive Cementitious Composites.

Multifunctional structural materials are very promising in the field of engineering. Particularly, their strain sensing ability draws much attention for structural health monitoring applications. Generally, strain sensing materials are produced by adding a certain amount of conductive fillers, around the so-called "percolation threshold", to the cement or composite matrix. Recently, graphite has been found to be a suitable filler for strain sensing. However, graphite requires high amounts of doping to reach percolation threshold. In order to decrease the amount of inclusions, this paper proposes cementitious materials doped with new hybrid carbon inclusions, i.e., graphite and carbon microfibers. Carbon microfibers having higher aspect ratio than graphite accelerate the percolation threshold of the graphite particles without incurring into dispersion issues. The resistivity and strain sensitivity of different fibers' compositions are investigated. The electromechanical tests reveal that, when combined, carbon microfibers and graphite hybrid fillers reach to percolation faster and exhibit higher gauge factors and enhanced linearity.

Smart Graphite-Cement Composite for Roadway-Integrated Weigh-In-Motion Sensing.

Smart multifunctional composites exhibit enhanced physical and mechanical properties and can provide structures with new capabilities. The authors have recently initiated a research program aimed at developing new strain-sensing pavement materials enabling roadway-integrated weigh-in motion (WIM) sensing. The goal is to achieve an accurate WIM for infrastructure monitoring at lower costs and with enhanced durability compared to off-the-shelf solutions. Previous work was devoted to formulating a signal processing algorithm for estimating the axle number and weights, along with the vehicle speed based on the outputs of a piezoresistive pavement material deployed within a bridge deck. This work proposes and characterizes a suitable low-cost and highly scalable cement-based composite with strain-sensing capabilities and sufficient sensitivity to meet WIM signal requirements. Graphite cement-based smart composites are presented, and their electromechanical properties are investigated in view of their application to WIM. These composites are engineered for scalability owing to the ease of dispersion of the graphite powder in the cement matrix, and can thus be used to build smart sections of road pavements. The research presented in this paper consists of electromechanical tests performed on samples of different amounts of graphite for the identification of the optimal mix in terms of signal sensitivity. An optimum inclusion level of 20% by weight of cement is obtained and selected for the fabrication of a plate of 30 × 15 × 5 cm3. Results from load identification tests conducted on the plate show that the proposed technology is capable of WIM.

Long-term consequences in survivors of critical illness. Analysis of incidence and risk factors.

AIM: This study investigates the incidence of long-term consequences in survivors of critical illness 6 months after ICU care. A retrospective analysis of the risk factors was also completed. METHODS: A mixed-method design was used. A qualitative design was used in the questionnaire study (phase 1), and a quantitative design was used for the retrospective study (phase 2). RESULTS: 116 patients were interviewed. Forty-eight patients (41.4%) reported at least one long-term consequence 6 months after ICU discharge. The most frequent consequences were anxiety (n = 33, 28.4%), depression (n = 32, 27.6%) and chronic pain (n = 24, 20.7%). The interview showed the concurrent caseness of PTSD, anxiety and depression in 14 (12.1%) patients. Observed risk factors were age > 60 years (OR = 2.65, IC = 1.23-5.69; p = 0.0119), trauma diagnosis (OR = 5.3, IC = 1.60-17.76; p = 0.0033), length of mechanical ventilation > 7 days (OR = 2.18, IC = 1-4.74; p = 0.0471) length of ICU stay > 10 days (OR = 2.47, IC = 1.16-5.26; p = 0.0185) and clinical conditions at the ICU admission. The quality of life score was lower if the respondent had long-term consequences. DISCUSSION: A high incidence of long-term consequences is found in survivors of critical illness. In future, studies that investigate interventions to prevent these issues after ICU care are need.

A Weigh-in-Motion Characterization Algorithm for Smart Pavements Based on Conductive Cementitious Materials.

Smart materials are promising technologies for reducing the instrumentation cost required to continuously monitor road infrastructures, by transforming roadways into multifunctional elements capable of self-sensing. This study investigates a novel algorithm empowering smart pavements with weigh-in-motion (WIM) characterization capabilities. The application domain of interest is a cementitious-based smart pavement installed on a bridge over separate sections. Each section transduces axial strain provoked by the passage of a vehicle into a measurable change in electrical resistance arising from the piezoresistive effect of the smart material. The WIM characterization algorithm is as follows. First, basis signals from axles are generated from a finite element model of the structure equipped with the smart pavement and subjected to given vehicle loads. Second, the measured signal is matched by finding the number and weights of appropriate basis signals that would minimize the error between the numerical and measured signals, yielding information on the vehicle's number of axles and weight per axle, therefore enabling vehicle classification capabilities. Third, the temporal correlation of the measured signals are compared across smart pavement sections to determine the vehicle weight. The proposed algorithm is validated numerically using three types of trucks defined by the Eurocodes. Results demonstrate the capability of the algorithm at conducting WIM characterization, even when two different trucks are driving in different directions across the same pavement sections. Then, a noise study is conducted, and the results conclude that a given smart pavement section operating with less than 5% noise on measurements could yield good WIM characterization results.

[Burnout syndrome among Italian nursing staff during the COVID 19 emergency. Multicentric survey study]. / Sindrome di Burnout tra il personale infermieristico italiano durante l'emergenza COVID 19. Indagine conoscitiva multicentrica.

AIM: To analyze the prevalence of Burnout defined by the MBI-GS among Italian nursing staff during the COVID-19 emergency. INTRODUCTION: The recent health emergency which in the first half of 2020 has seen Italy involved in the management of patients with COVID-19 (COronaVIrus Disease 19), has led to further stress for hospitals both in terms of beds and in terms of workload for healthcare workers. METHOD: A multicenter study was conducted. A convenience sample of 208 nurses participated in the study. Between March 20 and July 20, 2020, the Maslach Burnout Inventory-General Survey (MBI-GS) questionnaire was made available online by using the Google Forms platform in order to detect and measure the severity of Burnout Syndrome (BOS). RESULTS: BOS-related symptoms (medium or high score) for individual MBI-GS domains were identified in at least 68% of nurses. One hundred and sixty-one nurses (77.4%) had a risk of emotional exhaustion, 143 (68.7%) of depersonalization, and 162 (77.9%) of reduced professional accomplishment. High risk was observed among nurses who managed COVID patients at their own operating unit (RR = 1.27, p = 0.016). Severe BOS risk was observed in 146 nurses analyzed (70.2%) with an increased risk among Intensive Care nurses. CONCLUSIONS: Our results suggest that the nurses during the coronavirus pandemic, had high levels of work-related suffering and were at risk of physical and emotional exhaustion. Further research should be undertaken to establish causal relationships between BOS and personal and environmental risk factors among healthcare professionals in relation to the COVID-19.

Effect of PCM on the Hydration Process of Cement-Based Mixtures: A Novel Thermo-Mechanical Investigation.

The use of Phase Change Material (PCM) for improving building indoor thermal comfort and energy saving has been largely investigated in the literature in recent years, thus confirming PCM’s capability to reduce indoor thermal fluctuation in both summer and winter conditions, according to their melting temperature and operation boundaries. Further to that, the present paper aims at investigating an innovative use of PCM for absorbing heat released by cement during its curing process, which typically contributes to micro-cracking of massive concrete elements, therefore compromising their mechanical performance during their service life. The experiments carried out in this work showed how PCM, even in small quantities (i.e., up to 1% in weight of cement) plays a non-negligible benefit in reducing differential thermal increases between core and surface and therefore mechanical stresses originating from differential thermal expansion, as demonstrated by thermal monitoring of cement-based cubes. Both PCM types analyzed in the study (with melting temperatures at 18 and 25 ∘ C) were properly dispersed in the mix and were shown to be able to reduce the internal temperature of the cement paste by several degrees, i.e., around 5 ∘ C. Additionally, such small amount of PCM produced a reduction of the final density of the composite and an increase of the characteristic compressive strength with respect to the plain recipe.

An Experimental Study on Static and Dynamic Strain Sensitivity of Embeddable Smart Concrete Sensors Doped with Carbon Nanotubes for SHM of Large Structures.

The availability of new self-sensing cement-based strain sensors allows the development of dense sensor networks for Structural Health Monitoring (SHM) of reinforced concrete structures. These sensors are fabricated by doping cement-matrix mterials with conductive fillers, such as Multi Walled Carbon Nanotubes (MWCNTs), and can be embedded into structural elements made of reinforced concrete prior to casting. The strain sensing principle is based on the multifunctional composites outputting a measurable change in their electrical properties when subjected to a deformation. Previous work by the authors was devoted to material fabrication, modeling and applications in SHM. In this paper, we investigate the behavior of several sensors fabricated with and without aggregates and with different MWCNT contents. The strain sensitivity of the sensors, in terms of fractional change in electrical resistivity for unit strain, as well as their linearity are investigated through experimental testing under both quasi-static and sine-sweep dynamic uni-axial compressive loadings. Moreover, the responses of the sensors when subjected to destructive compressive tests are evaluated. Overall, the presented results contribute to improving the scientific knowledge on the behavior of smart concrete sensors and to furthering their understanding for SHM applications.

Regular and moderate exercise initiated in middle age prevents age-related amyloidogenesis and preserves synaptic and neuroprotective signaling in mouse brain cortex.

Although the beneficial responses induced in the central nervous system by early-initiated exercise have been broadly investigated, the effects of a chronic and moderate lately-initiated exercise on biochemical hallmarks of very early brain senescence have not been extensively studied. We previously reported that a midlife-initiated regimen of moderate running was able not only to prevent the age-related decay of antioxidative and detoxification functions in mouse brain cortex, but also to preserve neurotrophic support and molecular integrity. On this basis, this work investigated whether and how a 2-mo or 4-mo midlife-initiated running protocol could affect the activity of those systems involved in maintaining neuronal function and in preventing the onset of neurodegeneration within the brain cortex of middle-aged CD-1 mice. In particular, we analyzed the production of the peptide amyloid-ß and the expression of synapsin Ia, which is known to play a key role in neurotransmission and synaptic plasticity. In addition, we studied the expression of sirtuin 3, as a protein marker of neuroprotection against age-dependent mitochondrial dysfunction, as well as the pro-death pathway induced by proBDNF through the interaction with p75NTR and the co-receptor sortilin. The midlife-initiated 4-mo running program triggered multiple responses within the mouse brain cortex, through the activation of anti-amyloidogenic, pro-survival, synaptogenic and neuroprotective pathways. However, most of the beneficial actions of the exercise regimen appeared only after 4months, since 2-mo-exercised mice showed marked impairments of the endpoints we considered. This could imply that a midlife-initiated regimen of moderate treadmill running may require an adequate time lag to activate beneficial compensative mechanisms within the mouse brain cortex.

Late-onset running biphasically improves redox balance, energy- and methylglyoxal-related status, as well as SIRT1 expression in mouse hippocampus.

Despite the active research in this field, molecular mechanisms underlying exercise-induced beneficial effects on brain physiology and functions are still matter of debate, especially with regard to biological processes activated by regular exercise affecting the onset and progression of hippocampal aging in individuals unfamiliar with habitual physical activity. Since such responses seem to be mediated by changes in antioxidative, antiglycative and metabolic status, a possible exercise-induced coordinated response involving redox, methylglyoxal- and sirtuin-related molecular networks may be hypothesized. In this study, hippocampi of CD1 mice undergoing the transition from mature to middle age were analyzed for redox-related profile, oxidative and methylglyoxal-dependent damage patterns, energy metabolism, sirtuin1 and glyoxalase1 expression after a 2- or 4-mo treadmill running program. Our findings suggested that the 4-mo regular running lowered the chance of dicarbonyl and oxidative stress, activated mitochondrial catabolism and preserved sirtuin1-related neuroprotection. Surprisingly, the same cellular pathways were negatively affected by the first 2 months of exercise, thus showing an interesting biphasic response. In conclusion, the duration of exercise caused a profound shift in the response to regular running within the rodent hippocampus in a time-dependent fashion. This research revealed important details of the interaction between exercise and mammal hippocampus during the transition from mature to middle age, and this might help to develop non-pharmacological approaches aimed at retarding brain senescence, even in individuals unfamiliar with habitual exercise.

Long term running biphasically improves methylglyoxal-related metabolism, redox homeostasis and neurotrophic support within adult mouse brain cortex.

Oxidative stress and neurotrophic support decline seem to be crucially involved in brain aging. Emerging evidences indicate the pro-oxidant methylglyoxal (MG) as a key player in the age-related dicarbonyl stress and molecular damage within the central nervous system. Although exercise promotes the overproduction of reactive oxygen species, habitual exercise may retard cellular aging and reduce the age-dependent cognitive decline through hormetic adaptations, yet molecular mechanisms underlying beneficial effects of exercise are still largely unclear. In particular, whereas adaptive responses induced by exercise initiated in youth have been broadly investigated, the effects of chronic and moderate exercise begun in adult age on biochemical hallmarks of very early senescence in mammal brains have not been extensively studied. This research investigated whether a long-term, forced and moderate running initiated in adult age may affect the interplay between the redox-related profile and the oxidative-/MG-dependent molecular damage patterns in CD1 female mice cortices; as well, we investigated possible exercise-induced effects on the activity of the brain derived neurotrophic factor (BDNF)-dependent pathway. Our findings suggested that after a transient imbalance in almost all parameters investigated, the lately-initiated exercise regimen strongly reduced molecular damage profiles in brains of adult mice, by enhancing activities of the main ROS- and MG-targeting scavenging systems, as well as by preserving the BDNF-dependent signaling through the transition from adult to middle age.

Fifty hertz extremely low-frequency magnetic field exposure elicits redox and trophic response in rat-cortical neurons.

Large research activity has raised around the mechanisms of interaction between extremely low-frequency magnetic fields (ELF-MFs) and biological systems. ELF-MFs may interfere with chemical reactions involving reactive oxygen species (ROS), thus facilitating oxidative damages in living cells. Cortical neurons are particularly susceptible to oxidative stressors and are also highly dependent on the specific factors and proteins governing neuronal development, activity and survival. The aim of the present work was to investigate the effects of exposures to two different 50 Hz sinusoidal ELF-MFs intensities (0.1 and 1 mT) in maturing rat cortical neurons' major anti-oxidative enzymatic and non-enzymatic cellular protection systems, membrane peroxidative damage, as well as growth factor, and cytokine expression pattern. Briefly, our results showed that ELF-MFs affected positively the cell viability and concomitantly reduced the levels of apoptotic death in rat neuronal primary cultures, with no significant effects on the main anti-oxidative defences. Interestingly, linear regression analysis suggested a positive correlation between reduced glutathione (GSH) and ROS levels in 1 mT MF-exposed cells. On this basis, our hypothesis is that GSH could play an important role in the antioxidant defence towards the ELF-MF-induced redox challenge. Moreover, the GSH-based cellular response was achieved together with a brain-derived neurotrophic factor over-expression as well as with the interleukin 1beta-dependent regulation of pro-survival signaling pathways after ELF-MF exposure.