Use of a Large Language Model to Identify and Classify Injuries With Free-Text Emergency Department Data.

This cross-sectional study assesses the accuracy, sensitivity, and specificity of a large language model used to process unstructured, non-English emergency department (ED) data in medical records.

CMR Predictors of Favorable Outcome in Myocarditis: A Single-Center Experience.

Background: Cardiovascular magnetic resonance (CMR) has emerged as the most accurate, non-invasive method to support the diagnosis of clinically suspected myocarditis and as a risk-stratification tool in patients with cardiomyopathies. We aim to assess the diagnostic and prognostic role of CMR at diagnosis in patients with myocarditis. Methods: We enrolled consecutive single-center patients with 2013 ESC consensus-based endomyocardial biopsy (EMB)-proven or clinically suspected myocarditis undergoing CMR at diagnosis. The pre-specified outcome was defined as NYHA class > I and echocardiographic left ventricular ejection fraction (LVEF) < 50% at follow-up. Results: We included 207 patients (74% male, median age 36 years; 25% EMB-proven). CMR showed the highest sensitivity in myocarditis with infarct-like presentation. Patients with EMB-proven myocarditis were more likely to have diffuse LGE and right ventricular LGE (p < 0.001), which was also more common among patients with arrhythmic presentation (p = 0.001). The outcome was met in 17 patients at any follow-up time point, more commonly in those with larger biventricular volumes (p < 0.001), CMR-based diagnosis of dilated cardiomyopathy (p < 0.001), and ischemic LGE (p = 0.005). Higher biventricular systolic function (p < 0.001) and greater LGE extent (p = 0.033) at diagnosis had a protective effect. Conclusions: In our single-center cohort of rigorously defined myocarditis patients, higher biventricular systolic function and greater LGE extent on CMR at diagnosis identified patients with better functional class and higher left ventricular ejection fraction at follow-up. Conversely, larger biventricular volumes, CMR-based DCM features, and the presence of an ischemic LGE pattern at diagnosis were predictors of worse functional class and LV systolic dysfunction at follow-up. Larger prospective studies are warranted to extend our findings to multi-center cohorts.

Management of Pediatric Foreign Body Injuries during the COVID-19 Pandemic: Results of an International Survey.

The COVID-19 pandemic has had direct and indirect effects on daily life. In hospitals, the impact of the pandemic was observed in the diagnostic and therapeutic workflow. In this work, we explored potential changes in activities related to the treatment of foreign body injuries (FBIs) in children and the behavioral habits of physicians during the first wave of the pandemic. An online survey was conducted among physicians of the Susy Safe network. The survey comprised items related to respondent information, reference center characteristics, the treatment of FBIs during the COVID-19 pandemic, and a modified COVID-19 Anxiety Scale (CAS). The survey was distributed among the Susy Safe project international network surveillance registry for FBIs. A total of 58 physicians responded to the survey, including 18 (32%) from Europe and 16 (28%) from South America. The respondents indicated that the estimated number of aspirated foreign bodies during the pandemic was lower than or the same as that before the pandemic (43, 74%), and the same was observed for ingested foreign bodies (43, 74%). In univariable logistic regression, no single predictor was associated with a delay in routine care for children or an increasing tendency of medical personnel to avoid procedures. The workflow of physicians involved in the management of FBIs in children has not changed drastically during the COVID-19 pandemic, especially in emergency departments.

Association of Vegetarian and Vegan Diets with Cardiovascular Health: An Umbrella Review of Meta-Analysis of Observational Studies and Randomized Trials.

BACKGROUND: Cardiovascular diseases (CVDs) are leading global causes of mortality. Unhealthy diets have been linked to an increased risk of CVD, while plant-based diets have shown potential protective effects. This umbrella review summarizes the evidence on the association between vegetarian diets and cardiovascular and cerebrovascular diseases. METHODS: PubMed, Scopus, Embase, CINAHL, Cochrane, and Web of Science were consulted. Meta-analyses grouped by author and outcome were performed. The heterogeneity was evaluated using I2 statistics. RESULTS: There was a 41.2% risk reduction for cerebrovascular disease. CVD incidence had a 29% reduced risk. CVD mortality had a 13.8% risk reduction, while IHD incidence had a 24.1% reduction, but with high heterogeneity. IHD mortality showed a significant 32.1% risk reduction. Ischemic stroke had a significant 32.9% risk reduction across six studies. Stroke incidence showed a significant 39.1% risk reduction in a single study. There was a non-significant 11.6% risk reduction for stroke mortality with moderate heterogeneity. CONCLUSION: Healthier diets are associated with reduced risks of cerebrovascular disease, CVD incidence, IHD mortality, and ischemic stroke. However, evidence quality and consistency vary, emphasizing the need for more research. Policymakers and healthcare professionals should prioritize promoting healthy diets for CVD prevention.

Characterization of Non-Food Foreign Bodies Aspirated by Children: A Systematic Review of the Literature.

BACKGROUND: Foreign Body Aspiration (FBA) represents a leading cause of death among unintentional injuries in children less than one year of age. This study reviewed case reports and case series reporting non-food FBA in children to characterize aspirated foreign bodies, describing the clinical presentations and the outcomes. METHODS: A systematic review was conducted according to the PRISMA checklist. Case reports and case series presenting non-food FBA in children (up to 18 years) were eligible to be included. Information regarding study characteristics, child demographics, foreign body characteristics, clinical presentation, and outcome were extracted. RESULTS: The review included 248 articles published between 1965 and 2023, corresponding to 294 cases. The male gender was the most prevalent (194 cases, 66%), and the median age was 3.5 years (Interquartile Range: 1-8 years). Button batteries were the objects most frequently reported (21 cases, 7.1%). Objects were located most often in the bronchus (102 cases, 35%). The most common symptom was cough (181 cases, 62%), followed by respiratory distress (160 cases, 54%) and wheezing/stridor (127 cases, 43%). CONCLUSIONS: The present systematic review may have relevant public health implications, since characterizing objects that cause foreign body injuries is essential to reduce the burden of this phenomenon.

Physical activity assessment with wearable devices in rheumatic diseases: a systematic review and meta-analysis.

OBJECTIVES: In the management of rheumatic musculoskeletal disorders (RMDs), regular physical activity (PA) is an important recognized non-pharmacological intervention. This systematic review and meta-analysis aims to evaluate how the use of wearable devices (WDs) impacts physical activity in patients with noninflammatory and inflammatory rheumatic diseases. METHODS: A comprehensive search of articles was performed in PubMed, Embase, CINAHL and Scopus. A random-effect meta-analysis was carried out on the number of steps and moderate-vigorous physical activity (MVPA). Univariable meta-regression models were computed to assess the possibility that the study characteristics may act as modifiers on the final meta-analysis estimate. RESULTS: In the analysis, 51 articles were included, with a total of 7488 participants. Twenty-two studies considered MVPA outcome alone, 16 studies considered the number of steps alone, and 13 studies reported information on both outcomes. The recommended PA threshold was reached for MVPA (36.35, 95% CI 29.39, 43.31) but not for daily steps (-1092.60, -1640.42 to -544.77). Studies on patients with fibromyalgia report a higher number (6290, 5198.65-7381.62) of daily steps compared with other RMDs. Patients affected by chronic inflammatory arthropathies seemed to fare better in terms of daily steps than the other categories. Patients of younger age reported a higher overall level of PA than elderly individuals for both the number of steps and MVPA. CONCLUSION: Physical activity can be lower than the recommended threshold in patients with RMDs when objectively measured using WD. WDs could be a useful and affordable instrument for daily monitoring physical activity in RMDs and may support an increase in activity levels. PROSPERO TRIAL REGISTRATION: CRD42021227681, https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=227681.

A Machine-Learning Model for the Prognostic Role of C-Reactive Protein in Myocarditis.

Aims: The role of inflammation markers in myocarditis is unclear. We assessed the diagnostic and prognostic correlates of C-reactive protein (CRP) at diagnosis in patients with myocarditis. Methods and results: We retrospectively enrolled patients with clinically suspected (CS) or biopsy-proven (BP) myocarditis, with available CRP at diagnosis. Clinical, laboratory and imaging data were collected at diagnosis and at follow-up visits. To evaluate predictors of death/heart transplant (Htx), a machine-learning approach based on random forest for survival data was employed. We included 409 patients (74% males, aged 37 ± 15, median follow-up 2.9 years). Abnormal CRP was reported in 288 patients, mainly with CS myocarditis (p < 0.001), recent viral infection, shorter symptoms duration (p = 0.001), chest pain (p < 0.001), better functional class at diagnosis (p = 0.018) and higher troponin I values (p < 0.001). Death/Htx was reported in 13 patients, of whom 10 had BP myocarditis (overall 10-year survival 94%). Survival rates did not differ according to CRP levels (p = 0.23). The strongest survival predictor was LVEF, followed by anti-nuclear auto-antibodies (ANA) and BP status. Conclusions: Raised CRP at diagnosis identifies patients with CS myocarditis and less severe clinical features, but does not contribute to predicting survival. Main death/Htx predictors are reduced LVEF, BP diagnosis and positive ANA.

Identifying Predictors of Anal HPV Status in HPV-Vaccinated MSM: A Machine Learning Approach.

Anal human papillomavirus (HPV) infection has a high prevalence in men who have sex with men (MSM), resulting in an increased risk for anal cancer. The present work aimed to identify factors associated with HPV in a prospective cohort of HPV-vaccinated MSM using a random forest (RF) approach. This observational study enrolled MSM patients admitted to an Italian (sexually transmitted infection) STI-AIDS Unit. For each patient, rectal swabs for 28 different HPV genotype detection were collected. Two RF algorithms were applied to evaluate predictors that were most associated with HPV. The cohort included 135 MSM, 49% of whom were HIV-positive with a median age of 39 years. In model 1 (baseline information), age, age sexual debut, HIV, number of lifetime sex partners, STIs, were most associated with the HPV. In model 2 (follow-up information), age, age sexual debut, HIV, STI class, and follow-up. The RF algorithm exhibited good performances with 61% and 83% accuracy for models 1 and 2, respectively. Traditional risk factors for anal HPV infection, such as drug use, receptive anal intercourse, and multiple sexual partner, were found to have low importance in predicting HPV status. The present results suggest the need to focus on HPV prevention campaigns.

Epidemiology and Trends over Time of Foreign Body Injuries in the Pediatric Emergency Department.

This paper presents the epidemiology of foreign body injuries in the Pediatric Emergency Department (PED) of Padova (Italy) along with its trends over an eleven-year period based on administrative data. Annual incidence rates (IRs) of PED presentations for foreign body (FB) injuries per 1000 person-years were calculated. Univariable and multivariable generalized linear (GLM) Poisson models were estimated to evaluate the relationship between FB injury incidence and year, triage priority, nationality, injury site, and FB type. During the study period, there were 217,900 presentations of pediatric residents in the province of Padova; of these, 3084 (1.5%) reported FB injuries involving the ears, nose, throat, gastrointestinal tract or eyes. The annual IR of FB injury episodes increased from 10.45 for 1000 residents in 2007 (95% CI, 9.24, 11.77) to 12.66 for 1000 residents in 2018 (95% CI, 11.35, 14.08). Nonfood items were the FBs that were most frequently reported. The intermediate urgent triage code was the most represented for FB injuries, with IRs ranging from 5.44 (95% CI: 4.59, 6.40) in 2008 to 8.56 in 2018 (95% CI: 7.50, 9.74). A total of 170 patients who presented for FB injuries were hospitalized (5.5%). The annual FB-related injury IR has increased over time, although most episodes are not life threatening. Educational and prevention programs on FB-related injuries should be promoted and dedicated to childcare providers.

Assessment of Coronary Inflammation by Pericoronary Fat Attenuation Index in Clinically Suspected Myocarditis with Infarct-Like Presentation.

BACKGROUND: The pathophysiology of angina-like symptoms in myocarditis is still unclear. Perivascular fat attenuation index (pFAI) by coronary computed tomography angiography (CCTA) is a non-invasive marker of coronary inflammation (CI) in atherosclerosis. We explored the presence of CI in clinically suspected myocarditis with infarct-like presentation. METHODS: We retrospectively included 15 consecutive patients (67% male, age 30 ± 10 years) with clinically suspected infarct-like myocarditis who underwent CCTA to rule out coronary artery disease. Right coronary artery (RCA) pFAI mean value was compared with that of healthy volunteers. RESULTS: Mean RCA pFAI value was -92.8 ± 8.4 HU, similar to that of healthy volunteers (-95.2 ± 6.0, p = 0.8). We found no correlation between RCA pFAI mean values and peak Troponin I (r = -0.43, p = 0.11) and C-reactive protein at diagnosis (r = -0.25, p = 0.42). Patients with higher pFAI values showed higher biventricular end-systolic volumes (ESV) (p = 0.038 for left and p = 0.024 for right ventricle) and lower right ventricular ejection fraction (RVEF) (p = 0.038) on cardiovascular magnetic resonance. CONCLUSIONS: In clinically suspected myocarditis with infarct-like presentation, RCA pFAI values are lower than those validated in atherosclerosis. The correlation between higher pFAI values, higher biventricular ESV and lower RVEF, may suggest a role of pFAI in predicting non-atherosclerotic CI (i.e., infective/immune-mediated "endothelialitis").

Feasibility and Role of Right Ventricular Stress Echocardiography in Adult Patients.

BACKGROUND: The great technological advancements in the field of echocardiography have led to applications of stress echocardiography (SE) in almost all diagnostic fields of cardiology, from ischemic heart disease to valvular heart disease and diastolic function. However, the assessment of the right ventricle (RV) in general, and in particular in regard to the contractile reserve of the RV, is an area that has not been previously explored. We, therefore, propose a study to investigate the potential use of SE for the assessment of RV function in adult patients. AIMS AND OBJECTIVES: The primary aim is to evaluate the feasibility of right ventricular SE. The secondary aim is to assess right ventricular contractile reserve. MATHERIALS AND METHODS: Eighty-one patients undergoing a physical or dobutamine stress echocardiogram for cardiovascular risk stratification or chest pain were the subject of the study. An exercise leg cycle using a standard WHO protocol was used to simultaneously assess the right and left ventricular global and regional function as well as acquiring Doppler data. Whereas the patient had limitations in mobility, a dobutamine SE was be performed. We evaluated the average values of tricuspid annular plane systolic excursion (TAPSE), fractional area change (FAC), S-wave, systolic pulmonary artery pressure (sPAP), and right ventricle global longitudinal (free wall) strain (RVGLS) during baseline and at the peak of the effort. RV contractile reserve was defined as the change in RVGLS from rest to peak exercise. We also assessed the reproducibility of these measurements between two different expert operators (blind analysis). RESULTS: At least 3 over 5 RV function parameters were measurable both during baseline and at the peak of the effort in 95% of patients, while all 5 parameters in 65% of our population, demonstrating an excellent feasibility. All RV-studied variables showed a statistically significant increase (P < 0.001) at peak compared to the baseline. The average percentage increases at peak were 31.1% for TAPSE, 24.8% for FAC, 50.6% for S-wave, 55.2% for PAPS, and 39.8% for RV strain. The reproducibility between operators at baseline and peak was excellent. Our study demonstrates that TAPSE, FAC, and S-wave are highly feasible at rest and at peak, while TAPSE, S-wave, and sPAP are the most reliable measurements during RV stress echo. CONCLUSION: RVGLS is useful in the assessment of RV contractile reserve in patients with good acoustic window. Further studies are needed to evaluate the impact of contrast echocardiography in improving RV contractile reserve assessment during SE.

A Machine Learning Approach for Investigating Delirium as a Multifactorial Syndrome.

Delirium is a psycho-organic syndrome common in hospitalized patients, especially the elderly, and is associated with poor clinical outcomes. This study aims to identify the predictors that are mostly associated with the risk of delirium episodes using a machine learning technique (MLT). A random forest (RF) algorithm was used to evaluate the association between the subject's characteristics and the 4AT (the 4 A's test) score screening tool for delirium. RF algorithm was implemented using information based on demographic characteristics, comorbidities, drugs and procedures. Of the 78 patients enrolled in the study, 49 (63%) were at risk for delirium, 32 (41%) had at least one episode of delirium during the hospitalization (38% in orthopedics and 31% both in internal medicine and in the geriatric ward). The model explained 75.8% of the variability of the 4AT score with a root mean squared error of 3.29. Higher age, the presence of dementia, physical restraint, diabetes and a lower degree are the variables associated with an increase of the 4AT score. Random forest is a valid method for investigating the patients' characteristics associated with delirium onset also in small case-series. The use of this model may allow for early detection of delirium onset to plan the proper adjustment in healthcare assistance.

The Surplus Transplant Lung Allocation System in Italy: An Evaluation of the Allocation Process via Stochastic Modeling.

BACKGROUND: Lung transplantation is a specialized procedure used to treat chronic end-stage respiratory diseases. Due to the scarcity of lung donors, constructing fair and equitable lung transplant allocation methods is an issue that has been addressed with different strategies worldwide. This work aims to describe how Italy's "national protocol for the management of surplus organs in all transplant programs" functions through an online app to allocate lung transplants. We have developed two probability models to describe the allocation process among the various transplant centers. An online app was then created. The first model considers conditional probabilities based on a protocol flowchart to compute the probability for each area and transplant center to receive each n-th organ in the period considered. The second probability model is based on the generalization of the binomial distribution to correlated binary variables, which is based on Bahadur's representation, to compute the cumulative probability for each transplant center to receive at least nth organs. Our results show that the impact of the allocation of a surplus organ depends mostly on the region where the organ was donated. The discrepancies shown by our model may be explained by a discrepancy between the northern and southern regions in relation to the number of organs donated.

Monitoring Patients Reported Outcomes after Valve Replacement Using Wearable Devices: Insights on Feasibility and Capability Study: Feasibility Results.

Wearable devices (WDs) can objectively assess patient-reported outcomes (PROMs) in clinical trials. In this study, the feasibility and acceptability of using commercial WDs in elderly patients undergoing transcatheter aortic valve replacement (TAVR) or surgical aortic valve replacement (SAVR) will be explored. This is a prospective observational study. Participants were trained to use a WD and a smartphone to collect data on their physical activity, rest heart rate and number of hours of sleep. Validated questionnaires were also used to evaluate these outcomes. A technology acceptance questionnaire was used at the end of the follow up. In our participants an overall good compliance in wearing the device (75.1% vs. 79.8%, SAVR vs. TAVR) was assessed. Half of the patients were willing to continue using the device. Perceived ease of use is one of the domains that scored higher in the technology acceptance questionnaire. In this study we observed that the use of a WD is accepted in our frail population for an extended period. Even though commercial WDs are not tailored for clinical research, they can produce useful information on patient behavior, especially when coordinated with intervention tailored to the single patient.

The SYSTEMIC Project: A Pilot Study to Develop a Registry of Patients With an Ostomy for Predictive Modeling of Outcomes.

BACKGROUND: Stomal and peristomal skin complications represent a significant burden on the physical and psychological well-being of patients. PURPOSE: To develop a predictive tool for identifying the risk of complications in patients following ostomy surgery. METHODS: The oStomY regiSTry prEdictive ModelIng outCome (SYSTEMIC) project was developed to improve patient-oriented outcomes. Demographic, medical history, and stoma-related variables were obtained from patients at the wound ostomy clinic of the University Hospital of Padova, Italy. A follow-up assessment was completed 30 days after stoma surgery. Two (2) Bayesian machine learning approaches (naïve Bayes) were carried out to define an automatic peristomal complication predictive tool. A sensitivity analysis was performed to evaluate the possible effects of the prior choices on naïve Bayes performance. RESULTS: The algorithms were based on preliminary data from 52 patients (28 [53.3%] had a colostomy and 24 [46.7%] had an ileostomy). In terms of postoperative complications, no significant differences were observed between patients with different body mass indices (P = .16), those who underwent elective surgery compared with those who underwent emergency surgery (P = .66), and those who had or had not been preoperatively sited (P = .44). The algorithms showed an overall moderate ability to correctly classify patients according to the presence of peristomal complications (accuracy of nearly 70% in both models). In the the data-driven prior model, the probability of developing complications was greater for  participants with malignancies or other diseases (0.3314 for both levels) than for patients with diverticula and bowel perforation (0.1453) or inflammatory bowel disease (0.1918). CONCLUSION: The development of an easy-to-use algorithm may help nonspecialized nurses evaluate the likelihood of future peristomal complications in patients with an ostomy and implement preemptive measures.

Propensity Score Analysis with Partially Observed Baseline Covariates: A Practical Comparison of Methods for Handling Missing Data.

(1) Background: Propensity score methods gained popularity in non-interventional clinical studies. As it may often occur in observational datasets, some values in baseline covariates are missing for some patients. The present study aims to compare the performances of popular statistical methods to deal with missing data in propensity score analysis. (2) Methods: Methods that account for missing data during the estimation process and methods based on the imputation of missing values, such as multiple imputations, were considered. The methods were applied on the dataset of an ongoing prospective registry for the treatment of unprotected left main coronary artery disease. The performances were assessed in terms of the overall balance of baseline covariates. (3) Results: Methods that explicitly deal with missing data were superior to classical complete case analysis. The best balance was observed when propensity scores were estimated with a method that accounts for missing data using a stochastic approximation of the expectation-maximization algorithm. (4) Conclusions: If missing at random mechanism is plausible, methods that use missing data to estimate propensity score or impute them should be preferred. Sensitivity analyses are encouraged to evaluate the implications methods used to handle missing data and estimate propensity score.

Using Social Networks to Estimate the Number of COVID-19 Cases: The Incident (Hidden COVID-19 Cases Network Estimation) Study Protocol.

Recent literature has reported a high percentage of asymptomatic or paucisymptomatic cases in subjects with COVID-19 infection. This proportion can be difficult to quantify; therefore, it constitutes a hidden population. This study aims to develop a proof-of-concept method for estimating the number of undocumented infections of COVID-19. This is the protocol for the INCIDENT (Hidden COVID-19 Cases Network Estimation) study, an online, cross-sectional survey with snowball sampling based on the network scale-up method (NSUM). The original personal network size estimation method was based on a fixed-effects maximum likelihood estimator. We propose an extension of previous Bayesian estimation methods to estimate the unknown network size using the Markov chain Monte Carlo algorithm. On 6 May 2020, 1963 questionnaires were collected, 1703 were completed except for the random questions, and 1652 were completed in all three sections. The algorithm was initialized at the first iteration and applied to the whole dataset. Knowing the number of asymptomatic COVID-19 cases is extremely important for reducing the spread of the virus. Our approach reduces the number of questions posed. This allows us to speed up the completion of the questionnaire with a subsequent reduction in the nonresponse rate.

Profiling Delirium Progression in Elderly Patients via Continuous-Time Markov Multi-State Transition Models.

Poor recognition of delirium among hospitalized elderlies is a typical challenge for health care professionals. Considering methodological insufficiency for assessing time-varying diseases, a continuous-time Markov multi-state transition model (CTMMTM) was used to investigate delirium evolution in elderly patients. This is a longitudinal observational study performed in September 2016 in an Italian hospital. Change of delirium states was modeled according to the 4AT score. A Cox model (CM) and a CTMMTM were used for identifying factors affecting delirium onset both with a two-state and three-state model. In this study, 78 patients were enrolled and evaluated for 5 days. Both the CM and the CTMMTM show that urine catheter (UC), aging, drugs, and invasive devices (ID) are risk factors for delirium onset. The CTMMTM model shows that transition from no-delirium/cognitive impairment to delirium was associated with aging (HR = 1.14; 95%CI, 1.05, 1.23) and neuroleptics (HR = 4.3; 1.57, 11.77), dopaminergic drugs (HR = 3.89; 1.2, 12.6), UC (HR = 2.92; 1.09, 7.79) and ID (HR = 1.67; 103, 2.71). These results are confirmed by the multivariable model. Aging, ID, antibiotics, drugs affecting the central nervous system, and absence of moving ability are identified as the significant predictors of delirium. Additionally, it seems that modeling with CTMMTM may show associations that are not directly detectable with the traditional CM.

Resting Energy Expenditure in the Elderly: Systematic Review and Comparison of Equations in an Experimental Population.

Elderly patients are at risk of malnutrition and need an appropriate assessment of energy requirements. Predictive equations are widely used to estimate resting energy expenditure (REE). In the study, we conducted a systematic review of REE predictive equations in the elderly population and compared them in an experimental population. Studies involving subjects older than 65 years of age that evaluated the performance of a predictive equation vs. a gold standard were included. The retrieved equations were then tested on a sample of 88 elderly subjects enrolled in an Italian nursing home to evaluate the agreement among the estimated REEs. The agreement was assessed using the intraclass correlation coefficient (ICC). A web application, equationer, was developed to calculate all the estimated REEs according to the available variables. The review identified 68 studies (210 different equations). The agreement among the equations in our sample was higher for equations with fewer parameters, especially those that included body weight, ICC = 0.75 (95% CI = 0.69-0.81). There is great heterogeneity among REE estimates. Such differences should be considered and evaluated when estimates are applied to particularly fragile populations since the results have the potential to impact the patient's overall clinical outcome.

[The Healthcare-associated infections (HAIs) and infection Control link nurse as a strategy to face them: review of literature]. / Le Infezioni Correlate all'Assistenza (ICA) e i Link Nurse come strategia per combatterle: analisi di letteratura.

INTRODUCTION: Healthcare-associated infections (HAIs) are the most common adverse event in hospitals and a major public health problem with a negative impact on morbidity, mortality and quality of life. Governmental and non-governmental organizations are developing and strengthening plans to improve Infection and Prevention Control (IPC) programmes. Adopting reliable, effective and integrated IPC programmes can prevent 50% of HAIs. Implementation of a Infection Control Link Nurse (ICLN) system at the health care facility level is one of these. AIM: To obtain from a literature review evidence-based recommendations and practical instruments for developing and implementing a training course for ICLN. METHODS: A literature review was conducted by searching the Cochrane Library, PubMed, Cinahl without time limits, until July 2019. PICO methodology was adopted to build the research question and the Prisma Flow Diagram chosen for the selection of studies. Results The final review included 4 studies which dealt with the following main topics: selection of the personnel, profile, educational pathway, activities and factors that affects ICLN. DISCUSSION: Even though there is no accordance on duration and contents of LN training courses, its usefulness is well accepted. Using expert clinical nurses on prevention, control and management of HAIs for LN programmes is useful when they are capable of being opinion leaders and trainers among their teams, as well as a formal connection to management areas and administrators.