MAFLD and glomerular hyperfiltration in subjects with normoglycemia, prediabetes and type 2 diabetes: A cross-sectional population study.

BACKGROUND: Metabolic dysfunction-associated fatty liver disease (MAFLD, 2020 diagnostic criteria) and glomerular hyperfiltration share common risk factors, including obesity, insulin resistance, impaired glucose tolerance, diabetes, dyslipidemia, and hypertension. AIMS: To assess the prevalence of MAFLD and its association with glomerular hyperfiltration and age-related worsening of kidney function in subjects with normoglycemia, prediabetes and type 2 diabetes mellitus (T2DM). METHODS: We analysed data recorded during occupational health visits of 125,070 Spanish civil servants aged 18-65 years with a de-indexed glomerular filtration rate (GFR) estimated with the chronic-kidney-disease-epidemiological (CKD-EPI) equation (estimated glomerular filtration rate [eGFR]) ≥60 mL/min. Subjects were categorised according to fasting plasma glucose levels <100 mg/dL (normoglycemia), ≥100 and ≤ 125 mg/dL (prediabetes), or ≥126 mg/dL and/or antidiabetic treatment (T2DM). The association between MAFLD and glomerular hyperfiltration, defined as a de-indexed eGFR above the age- and gender-specific 95th percentile, was assessed by multivariable logistic regression. RESULTS: In the whole study group, MAFLD prevalence averaged 19.3%. The prevalence progressively increased from 14.7% to 33.2% and to 48.9% in subjects with normoglycemia, prediabetes and T2DM, respectively (p < 0.001 for trend). Adjusted odds ratio (95% CI) for the association between MAFLD and hyperfiltration was 9.06 (8.53-9.62) in the study group considered as a whole, and 8.60 (8.03-9.21), 9.52 (8.11-11.18) and 8.31 (6.70-10.30) in subjects with normoglycemia, prediabetes and T2DM considered separately. In stratified analyses, MAFLD amplified age-dependent eGFR decline in all groups (p < 0.001). CONCLUSIONS: MAFLD prevalence increases across the glycaemic spectrum. MAFLD is significantly associated with hyperfiltration and amplifies the age-related eGFR decline.

Evaluation of different screening tools for detection of malnutrition in hospitalised patients.

AIMS AND OBJECTIVES: To assess the prevalence of malnutrition in hospitalised adult patients, and to evaluate the accuracy of the most commonly used nutritional screening tools for identifying individuals at risk of malnutrition. METHODS: A prospective cross-sectional study was conducted on a total of 248 hospitalised patients in internal medicine wards (mean age: 75.2 years; 39.5% females). Nutritional screening was performed within 48 h of admission using the following tools: Malnutrition Universal Screening Tool (MUST), Nutrition Risk Screening Tool (NRS-2002), Malnutrition Screening Tool (MST), Short Nutritional Assessment Questionnaire (SNAQ), and Mini Nutritional Assessment Short Form (MNA-SF). The criteria of the European Society for Clinical Nutrition and Metabolism (ESPEN) were used as the gold standard for defining malnutrition. Patients were also evaluated using the Subjective Global Assessment (SGA) and the Global Leadership Initiative on Malnutrition (GLIM) criteria. Accuracy was determined by examining sensitivity, specificity, and positive and negative predictive values, and diagnostic agreement was determined by calculation of Cohen's kappa (κ). The study is reported as per the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. RESULTS: The ESPEN criteria classified 20.2% of the hospitalised patients as malnourished. Overall, the MUST had the highest sensitivity (80.0%), specificity (74.7%) and positive predictive value (44.4%). For the subgroup of patients aged >65 years, the MNA-SF had high sensitivity (94.4%) but low specificity (39.0%). Based on Cohen's κ, the SGA and GLIM criteria showed low agreement with the ESPEN criteria. CONCLUSION: The MUST was the most accurate nutritional screening tool, through the MST is more easily applied in many clinical settings. A comprehensive assessment of malnutrition that considers muscle mass is crucial for the reliable diagnosis of malnutrition. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: The present findings underscore the importance of accurate assessment of the malnutrition status of hospitalised patients and the need for a reliable screening tool. No patient or public contribution.

[Sociodemographic and environmental factors associated with mask use during the COVID-19 pandemic]. / Factores sociodemográficos y ambientales relacionados con el uso de mascarillas en la población durante la pandemia por la COVID-19.

OBJECTIVE: During COVID-19 pandemic, prevention measures were implemented to mitigate the community transmission of SARS-CoV-2. Compliance with these measures was influenced by several sociodemographic and environmental factors. However, literature addressing compliance with these prevention measures among the general population remains limited. The study aimed to assess the association of sociodemographic and environmental factors and mask usage during close contact situations. METHODS: A cross-sectional study was conducted with a sample of 1,778 individuals identified through close contact tracing of individuals diagnosed with SARS-CoV-2 by the COVID-19 Coordination Center of Mallorca, from February to June 2021. A descriptive analysis was conducted, and a logistic regression model was utilized to evaluate factors associated with mask non-compliance. RESULTS: The mean age of the participants was 42.8±17.4 years, with 53.6% being female. Among close contacts, 60.8% (95% CI: 57.8-62.3) did not use masks during their contact. No significant differences were observed between genders or across age groups (p=0.497 and p=0.536, respectively). Factors linked to mask non-compliance included the home setting, indoor spaces without ventilation, and closer physical distances (p<0.001). CONCLUSIONS: Our findings indicate that mask adherence was notably lower among close contacts exposed to higher risk. In future public health crises, interventions should be developed to raise awareness about risks and promote adherence to preventive and control measures.

OBJECTIVE: Durante la pandemia de la COVID-19 se implementaron medidas de prevención con el propósito de reducir su transmisión comunitaria. El grado de cumplimiento con estas medidas estuvo influenciado por diversos factores sociodemográficos y ambientales. Sin embargo, existe escasa literatura científica que aborde el cumplimiento de las medidas preventivas en la población general. El objetivo de este estudio fue analizar la asociación entre factores sociodemográficos y ambientales, así como la adhesión al uso de mascarillas en contactos estrechos. METHODS: Se realizó un estudio transversal con 1.778 individuos, identificados mediante el rastreo de contactos estrechos de personas con SARS-CoV-2 por la Central de Coordinación de la COVID-19 de Mallorca, entre febrero y junio de 2021. Se realizó un análisis descriptivo y se utilizó un modelo de regresión logística para determinar los factores asociados al incumplimiento del uso de mascarillas. RESULTS: La edad media de los participantes fue de 42,8±17,4 años (53,6% de mujeres). El 60,8% (IC 95%: 57,8-62,3) de los contactos estrechos no utilizó mascarilla durante su contacto. No se observaron diferencias estadísticamente significativas en función del sexo o grupo etario (p=0,497 y p=0,536, respectivamente). Las situaciones de mayor incumplimiento con el uso de mascarillas se dieron en el entorno domiciliario, espacios cerrados sin ventilación y al mantener distancias cortas (p<0,001). CONCLUSIONS: Nuestros hallazgos indican una menor adhesión al uso de mascarillas en escenarios de mayor riesgo. Frente a futuras situaciones de crisis sanitaria, se deberían diseñar intervenciones que realcen la conciencia sobre los riesgos y que promuevan una mayor adhesión a medidas de prevención y control.

Validity of nutrition screening tools for risk of malnutrition among hospitalized adult patients: A systematic review and meta-analysis.

BACKGROUNDS & AIMS: Malnutrition is prevalent among hospitalized patients in developed countries, contributing to negative health outcomes and increased healthcare costs. Timely identification and management of malnutrition are crucial. The lack of a universally accepted definition and standardized diagnostic criteria for malnutrition has led to the development of various screening tools, each with varying validity. This complicates early identification of malnutrition, hindering effective intervention strategies. This systematic review and meta-analysis aimed to identify the most valid and reliable nutritional screening tool for assessing the risk of malnutrition in hospitalized adults. METHODS: A systematic literature search was conducted to identify validation studies published from inception to November 2023, in the Pubmed/MEDLINE, Embase, and CINAHL databases. This systematic review was registered in INPLASY (INPLASY202090028). The risk of bias and quality of included studies were assessed using the Quality Assessment of Diagnostic Accuracy Studies version 2 (QUADAS-2). Meta-analyses were performed for screening tools accuracy using the symmetric hierarchical summary receiver operative characteristics models. RESULTS: Of the 1646 articles retrieved, 60 met the inclusion criteria and were included in the systematic review, and 21 were included in the meta-analysis. A total of 51 malnutrition risk screening tools and 9 reference standards were identified. The meta-analyses assessed four common malnutrition risk screening tools against two reference standards (Subjective Global Assessment [SGA] and European Society for Clinical Nutrition and Metabolism [ESPEN] criteria). The Malnutrition Universal Screening Tool (MUST) vs SGA had a sensitivity (95% Confidence Interval) of 0.84 (0.73-0.91), and specificity of 0.85 (0.75-0.91). The MUST vs ESPEN had a sensitivity of 0.97 (0.53-0.99) and specificity of 0.80 (0.50-0.94). The Malnutrition Screening Tool (MST) vs SGA had a sensitivity of 0.81 (0.67-0.90) and specificity of 0.79 (0.72-0.74). The Mini Nutritional Assessment-Short Form (MNA-SF) vs ESPEN had a sensitivity of 0.99 (0.41-0.99) and specificity of 0.60 (0.45-0.73). The Nutrition Universal Screening Tool-2002 (NRS-2002) vs SGA had a sensitivity of 0.76 (0.58-0.87) and specificity of 0.86 (0.76-0.93). CONCLUSIONS: The MUST demonstrated high accuracy in detecting malnutrition risk in hospitalized adults. However, the quality of the studies included varied greatly, possibly introducing bias in the results. Future research should compare tools within a specific patient population using a valid and universal gold standard to ensure improved patient care and outcomes.

Identifying the interplay between protective measures and settings on the SARS-CoV-2 transmission using a Bayesian network.

Contact tracing played a crucial role in minimizing the onward dissemination of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) in the recent pandemic. Previous studies had also shown the effectiveness of preventive measures such as mask-wearing, physical distancing, and exposure duration in reducing SARS-CoV-2 transmission. However, there is still a lack of understanding regarding the impact of various exposure settings on the spread of SARS-CoV-2 within the community, as well as the most effective preventive measures, considering the preventive measures adherence in different daily scenarios. We aimed to evaluate the effect of individual protective measures and exposure settings on the community transmission of SARS-CoV-2. Additionally, we aimed to investigate the interaction between different exposure settings and preventive measures in relation to such SARS-CoV-2 transmission. Routine SARS-CoV-2 contact tracing information was supplemented with additional data on individual measures and exposure settings collected from index patients and their close contacts. We used a case-control study design, where close contacts with a positive test for SARS-CoV-2 were classified as cases, and those with negative results classified as controls. We used the data collected from the case-control study to construct a Bayesian network (BN). BNs enable predictions for new scenarios when hypothetical information is introduced, making them particularly valuable in epidemiological studies. Our results showed that ventilation and time of exposure were the main factors for SARS-CoV-2 transmission. In long time exposure, ventilation was the most effective factor in reducing SARS-CoV-2, while masks and physical distance had on the other hand a minimal effect in this ventilation spaces. However, face masks and physical distance did reduce the risk in enclosed and unventilated spaces. Distance did not reduce the risk of infection when close contacts wore a mask. Home exposure presented a higher risk of SARS-CoV-2 transmission, and any preventive measures posed a similar risk across all exposure settings analyzed. Bayesian network analysis can assist decision-makers in refining public health campaigns, prioritizing resources for individuals at higher risk, and offering personalized guidance on specific protective measures tailored to different settings or environments.

Personal protective measures and settings on the risk of SARS-COV-2 community transmission: a case-control study.

Background: During the SARS-CoV-2 pandemic, nurses of primary health care has been an important role in Spain. Even so, the data obtained in the tracing have been scarcely used to investigate the possible mechanisms of transmission. Few studies focused on community transmission, evaluating the effectiveness of individual protective measures and exposure environment. The main aim of the study was to evaluate the association between individual protective measures and SARS-CoV-2 transmission in the community and to compare secondary attack rates in different exposure settings. Methods: A case-control study from contact tracing of SARS-CoV-2 index patients. COVID-19 contact tracing was led by nurses at the COVID-19 Coordinating Centre in Majorca (Spain). During the systematic tracing, additional information for this study was collected from the index patient (social-demographic variables, symptoms, the number of close contacts). And also, the following variables from their close contacts: contact place, ventilation characteristics mask-wearing, type of mask, duration of contact, shortest distance, case-contact relationship, household members, and handwashing, the test result for SARS-CoV-2 diagnostic. Close contacts with a positive test for SARS-CoV-2 were classified as "cases" and those negative as "controls." Results: A total of 1,778 close contacts from 463 index patients were identified. No significant differences were observed between the sexes but between age groups. Overall Secondary Attack Rate (SAR) was 24.0% (95% CI: 22.0-26.0%), 36.9% (95% CI: 33.2-40.6%) in closed spaces without ventilation and 50.7% (95% CI: 45.6-55.8%) in exposure time > 24 h. A total of 49.2% of infections occurred among household members. Multivariate logistic regression analysis showed that open-air setting (OR 0.43, 95% CI: 0.27-0.71), exposure for less than 1 h (OR 0.19, 95% CI: 0.11-0.32), and wearing a mask (OR 0.49, 95% CI: 0.28-0.85) had a protective effect transmission of SARS-CoV-2 in the community. Conclusion: Ventilation of the space, mask-wearing and shorter exposure time were associated with a lower risk of transmission in the community. The data obtained allowed an assessment of community transmission mechanisms and could have helped to improve and streamline tracing by identifying close contacts at higher risk.