Relación entre la dieta, aspectos nutricionales y la calidad del sueño en población pediátrica / Relationship between diet, nutritional aspects and sleep quality in a pediatric population

La relación entre la dieta y el sueño ha sido escasamente estudiada en la población pediátrica. El objetivo de esta revisión fue analizar de forma narrativa la relación existente entre la dieta, determinados aspectos nutricionales y la calidad del sueño en esta población. Se seleccionaron estudios que midieran la dieta y valorasen el estado nutricional y el sueño en población infantil mediante la utilización de distintas herramientas. El riesgo de sesgo de los 14 estudios seleccionados se determinó con herramientas validadas. La adhesión a algunos patrones dietéticos como el mediterráneo, el alto consumo de frutas y verduras, la ingesta de triptófano o la sustitución de los ácidos grasos saturados por grasas insaturadas se relacionaron con una mejor calidad del sueño. El consumo de los productos ultraprocesados y la ingesta alta de azúcares simples dificultan un descanso adecuado. Por otro lado, se observó una asociación entre un índice de masa corporal alto y la falta de sueño en los jóvenes menores de 14 años. En conclusión, los estudios recogidos mostraron una asociación significativa entre algunos patrones dietéticos, grupos de alimentos y nutrientes con la calidad del sueño. Los factores dietéticos “poco saludables” se asociaron a una peor calidad del sueño. Sin embargo, hábitos y dietas más saludables y recomendados se relacionaron con una mejora de la higiene del sueño. Por otro lado, la falta de horas de descanso en la población juvenil se relaciona con el aumento de peso.(AU)

The relationship between diet and sleep has been studied in adults. However, there is little evidence in the pediatric population. The objective of this review was to analyze in a narrative way the relationship between diet, some nutritional aspects and sleep quality in population under 14 years. A quick review was performed in MEDLINE (PubMed) and Cochrane with a search strategy combining MeSH terms and keywords. Studies were selected to estimate diet and evaluate nutritional status and sleep in children using different tools. The risk of bias from the 14 selected studies was determined with validated tools (AMSTAR 2, Newcastle Ottawa scale [NOS] and Risk of Bias [Rob2]). Adherence to some dietary patterns such as the Mediterranean, high consumption of fruits and vegetables, tryptophan intake or substitution of saturated fatty acids by unsaturated fats were associated with better sleep quality. The consumption of ultra-processed products, the “unhealthy fast food” or the high intake of simple sugars hinder an adequate rest. On the other hand, an association between a high body mass index and lack of sleep was observed in young people under 14. In conclusion, the collected studies showed a significant association between some dietary patterns, food groups and nutrients with sleep quality. “Unhealthy” dietary factors were associated with poorer sleep quality. However, healthier and recommended habits and diets were associated with improved sleep hygiene. On the other hand, the lack of hours of rest in the youth population increases height, weight and BMI. Further research is needed in this direction.(AU)

Identifying prehospital trauma patients from ambulance patient care records; comparing two methods using linked data in New South Wales, Australia.

BACKGROUND: Linked datasets for trauma system monitoring should ideally follow patients from the prehospital scene to hospital admission and post-discharge. Having a well-defined cohort when using administrative datasets is essential because they must capture the representative population. Unlike hospital electronic health records (EHR), ambulance patient-care records lack access to sources beyond immediate clinical notes. Relying on a limited set of variables to define a study population might result in missed patient inclusion. We aimed to compare two methods of identifying prehospital trauma patients: one using only those documented under a trauma protocol and another incorporating additional data elements from ambulance patient care records. METHODS: We analyzed data from six routinely collected administrative datasets from 2015 to 2018, including ambulance patient-care records, aeromedical data, emergency department visits, hospitalizations, rehabilitation outcomes, and death records. Three prehospital trauma cohorts were created: an Extended-T-protocol cohort (patients transported under a trauma protocol and/or patients with prespecified criteria from structured data fields), T-protocol cohort (only patients documented as transported under a trauma protocol) and non-T-protocol (extended-T-protocol population not in the T-protocol cohort). Patient-encounter characteristics, mortality, clinical and post-hospital discharge outcomes were compared. A conservative p-value of 0.01 was considered significant RESULTS: Of 1 038 263 patient-encounters included in the extended-T-population 814 729 (78.5 %) were transported, with 438 893 (53.9 %) documented as a T-protocol patient. Half (49.6 %) of the non-T-protocol sub-cohort had an International Classification of Disease 10th edition injury or external cause code, indicating 79644 missed patients when a T-protocol-only definition was used. The non-T-protocol sub-cohort also identified additional patients with intubation, prehospital blood transfusion and positive eFAST. A higher proportion of non-T protocol patients than T-protocol patients were admitted to the ICU (4.6% vs 3.6 %), ventilated (1.8% vs 1.3 %), received in-hospital transfusion (7.9 vs 6.8 %) or died (1.8% vs 1.3 %). Urgent trauma surgery was similar between groups (1.3% vs 1.4 %). CONCLUSION: The extended-T-population definition identified 50 % more admitted patients with an ICD-10-AM code consistent with an injury, including patients with severe trauma. Developing an EHR phenotype incorporating multiple data fields of ambulance-transported trauma patients for use with linked data may avoid missing these patients.

Predictive analytics for cardiovascular patient readmission and mortality: An explainable approach.

BACKGROUND: Cardiovascular patients experience high rates of adverse outcomes following discharge from hospital, which may be preventable through early identification and targeted action. This study aimed to investigate the effectiveness and explainability of machine learning algorithms in predicting unplanned readmission and death in cardiovascular patients at 30 days and 180 days from discharge. METHODS: Gradient boosting machines were trained and evaluated using data from hospital electronic medical records linked to hospital administrative and mortality data for 39,255 patients admitted to four hospitals in New South Wales, Australia between 2017 and 2021. Sociodemographic variables, admission history, and clinical information were used as potential predictors. The performance was compared to LASSO regression, as well as the HOSPITAL and LACE risk score indices. Important risk factors identified by the gradient-boosting machine model were explored using Shapley values. RESULTS: The models performed well, especially for the mortality outcomes. Area under the receiver operating characteristic curve values were 0.70 for readmission and 0.87-0.90 for mortality using the full gradient boosting machine algorithms. Among the top predictors for 30-day and 180-day readmission were increased red cell distribution width, old age (especially above 80 years), high measured troponin and urea levels, not being married or in a relationship, and low albumin levels. For mortality, these included increased red cell distribution width, old age (especially older than 70 years), high measured troponin and urea levels, high neutrophil and monocyte counts, and low eosinophil and lymphocyte counts. The Shapley values gave clear insight into the dynamics of decision-tree-based models. CONCLUSIONS: We demonstrated an explainable predictive algorithm to identify cardiovascular patients who are at high risk of readmission or death at discharge from the hospital and identified key risk factors.

Serum Phthalate Concentrations and Biomarkers of Oxidative Stress in Adipose Tissue in a Spanish Adult Cohort.

The relationship between phthalates, a group of chemical pollutants classified as endocrine disruptors, and oxidative stress is not fully understood. The aim of the present hospital-based study was to explore the associations between circulating levels of 10 phthalate metabolites and 8 biomarkers of oxidative stress in adipose tissue. The study population (n = 143) was recruited in two hospitals in the province of Granada (Spain). Phthalate metabolite concentrations were analyzed by isotope diluted online-TurboFlow-LC-MS/MS in serum samples, while oxidative stress markers were measured by commercially available kits in adipose tissue collected during routine surgery. Statistical analyses were performed by MM estimators' robust linear regression and weighted quantile sum regression. Mainly, positive associations were observed of monomethyl phthalate (MMP), monoiso-butyl phthalate (MiBP), and mono-n-butyl phthalate (MnBP) (all low molecular weight phthalates) with glutathione peroxidase (GPx) and thiobarbituric acid reactive substances (TBARS), while an inverse association was found between monoiso-nonyl phthalate (MiNP) (high molecular weight phthalate) and the same biomarkers. WQS analyses showed significant effects of the phthalate mixture on GSH (ß = -30.089; p-value = 0.025) and GSSG levels (ß = -19.591; p-value = 0.030). Despite the limitations inherent to the cross-sectional design, our novel study underlines the potential influence of phthalate exposure on redox homeostasis, which warrants confirmation in further research.

Predicting Adverse Outcomes Following Catheter Ablation Treatment for Atrial Flutter/Fibrillation.

BACKGROUND & AIM: To develop prognostic survival models for predicting adverse outcomes after catheter ablation treatment for non-valvular atrial fibrillation (AF) and/or atrial flutter (AFL). METHODS: We used a linked dataset including hospital administrative data, prescription medicine claims, emergency department presentations, and death registrations of patients in New South Wales, Australia. The cohort included patients who received catheter ablation for AF and/or AFL. Traditional and deep survival models were trained to predict major bleeding events and a composite of heart failure, stroke, cardiac arrest, and death. RESULTS: Out of a total of 3,285 patients in the cohort, 177 (5.3%) experienced the composite outcome-heart failure, stroke, cardiac arrest, death-and 167 (5.1%) experienced major bleeding events after catheter ablation treatment. Models predicting the composite outcome had high-risk discrimination accuracy, with the best model having a concordance index >0.79 at the evaluated time horizons. Models for predicting major bleeding events had poor risk discrimination performance, with all models having a concordance index <0.66. The most impactful features for the models predicting higher risk were comorbidities indicative of poor health, older age, and therapies commonly used in sicker patients to treat heart failure and AF and AFL. DISCUSSION: Diagnosis and medication history did not contain sufficient information for precise risk prediction of experiencing major bleeding events. Predicting the composite outcome yielded promising results, but future research is needed to validate the usefulness of these models in clinical practice. CONCLUSIONS: Machine learning models for predicting the composite outcome have the potential to enable clinicians to identify and manage high-risk patients following catheter ablation for AF and AFL proactively.

[Relationship between diet, nutritional aspects and sleep quality in a pediatric population]. / Relación entre la dieta, aspectos nutricionales y la calidad del sueño en población pediátrica.

The relationship between diet and sleep has been studied in adults. However, there is little evidence in the pediatric population. The objective of this review was to analyze in a narrative way the relationship between diet, some nutritional aspects and sleep quality in population under 14 years. A quick review was performed in MEDLINE (PubMed) and Cochrane with a search strategy combining MeSH terms and keywords. Studies were selected to estimate diet and evaluate nutritional status and sleep in children using different tools. The risk of bias from the 14 selected studies was determined with validated tools (AMSTAR 2, Newcastle Ottawa scale [NOS] and Risk of Bias [Rob2]). Adherence to some dietary patterns such as the Mediterranean, high consumption of fruits and vegetables, tryptophan intake or substitution of saturated fatty acids by unsaturated fats were associated with better sleep quality. The consumption of ultra-processed products, the "unhealthy fast food" or the high intake of simple sugars hinder an adequate rest. On the other hand, an association between a high body mass index and lack of sleep was observed in young people under 14. In conclusion, the collected studies showed a significant association between some dietary patterns, food groups and nutrients with sleep quality. "Unhealthy" dietary factors were associated with poorer sleep quality. However, healthier and recommended habits and diets were associated with improved sleep hygiene. On the other hand, the lack of hours of rest in the youth population increases height, weight and BMI. Further research is needed in this direction.

Association of monetary diet cost of foods and diet quality in Spanish older adults.

Background: A major barrier to a healthy diet may be the higher price of healthy foods compared to low-quality foods. Objectives: This study aimed to assess the association between the monetary cost of food and diet quality in Spanish older adults at high risk of cardiovascular disease. Methods: Cross-sectional analysis was carried out in Spanish older adults (n = 6,838; 48.6% female). A validated food frequency questionnaire was used to assess dietary intake. Metabolic syndrome severity, adherence to the Mediterranean diet (MedDiet), adherence to a provegetarian dietary pattern, and dietary inflammatory index were assessed. The economic cost of the foods was obtained from the Spanish Ministry of Agriculture Fisheries and Food database (2015-2017, the period of time when the participants were recruited). The total cost of diet adjusted per 1,000 kcal was computed. Results: The healthier dietary pattern was associated with a higher cost of the diet. Higher adherence to the MedDiet, anti-inflammatory diet, and the healthy version of the provegetarian dietary pattern were related to higher costs of the diet. Conclusion: Higher diet quality was associated with a higher dietary cost of the diet per 1,000 kcal/day. Food prices can be an important component of interventions and policies aimed at improving people's diets and preventing diet-related chronic diseases. Clinical trial registry number: The trial was registered in 2014 at the International Standard Randomized Controlled Trial (ISRCT; http://www.isrctn.com/ISRCTN89898870) with the number 89898870.

Web-Based Application Based on Human-in-the-Loop Deep Learning for Deidentifying Free-Text Data in Electronic Medical Records: Development and Usability Study.

BACKGROUND: The narrative free-text data in electronic medical records (EMRs) contain valuable clinical information for analysis and research to inform better patient care. However, the release of free text for secondary use is hindered by concerns surrounding personally identifiable information (PII), as protecting individuals' privacy is paramount. Therefore, it is necessary to deidentify free text to remove PII. Manual deidentification is a time-consuming and labor-intensive process. Numerous automated deidentification approaches and systems have been attempted to overcome this challenge over the past decade. OBJECTIVE: We sought to develop an accurate, web-based system deidentifying free text (DEFT), which can be readily and easily adopted in real-world settings for deidentification of free text in EMRs. The system has several key features including a simple and task-focused web user interface, customized PII types, use of a state-of-the-art deep learning model for tagging PII from free text, preannotation by an interactive learning loop, rapid manual annotation with autosave, support for project management and team collaboration, user access control, and central data storage. METHODS: DEFT comprises frontend and backend modules and communicates with central data storage through a filesystem path access. The frontend web user interface provides end users with a user-friendly workspace for managing and annotating free text. The backend module processes the requests from the frontend and performs relevant persistence operations. DEFT manages the deidentification workflow as a project, which can contain one or more data sets. Customized PII types and user access control can also be configured. The deep learning model is based on a Bidirectional Long Short-Term Memory-Conditional Random Field (BiLSTM-CRF) with RoBERTa as the word embedding layer. The interactive learning loop is further integrated into DEFT to speed up the deidentification process and increase its performance over time. RESULTS: DEFT has many advantages over existing deidentification systems in terms of its support for project management, user access control, data management, and an interactive learning process. Experimental results from DEFT on the 2014 i2b2 data set obtained the highest performance compared to 5 benchmark models in terms of microaverage strict entity-level recall and F1-scores of 0.9563 and 0.9627, respectively. In a real-world use case of deidentifying clinical notes, extracted from 1 referral hospital in Sydney, New South Wales, Australia, DEFT achieved a high microaverage strict entity-level F1-score of 0.9507 on a corpus of 600 annotated clinical notes. Moreover, the manual annotation process with preannotation demonstrated a 43% increase in work efficiency compared to the process without preannotation. CONCLUSIONS: DEFT is designed for health domain researchers and data custodians to easily deidentify free text in EMRs. DEFT supports an interactive learning loop and end users with minimal technical knowledge can perform the deidentification work with only a shallow learning curve.

Efficacy and Safety of New B Cell-Targeted Biologic Agent for the Treatment of Systemic Lupus Erythematosus: A Systematic Review and Meta-Analysis.

BACKGROUND: B cells are central to the pathogenesis of systemic lupus erythematosus (SLE). We aimed to analyze the efficacy and safety of new B cell-targeted drug therapies for SLE. METHODS: A systematic review of randomized controlled trials (RCTs) and reference lists of relevant articles published from inception to 2022 were selected from PubMed, Scopus and Web of Science databases. Random effects meta-analyses were performed to estimate an overall effect size for the risk of adverse events (AEs) and serious adverse events (SAEs) with belimumab and tabalumab treatment. Heterogeneity was assessed using the I2 statistic and meta-regression. Funnel asymmetry was evaluated using Egger's test. RESULTS: This study included 13 RCTs, of which three showed high risk of bias. Egger's test showed no asymmetry. The risk of SAEs and AEs was lower in the treatment group with belimumab treatment. The risk of AEs for tabalumab treatment was lower in the treatment group and lower for SAEs. CONCLUSION: Belimumab and tabalumab therapies are effective and safe in the treatment of SLE, although tabalumab does not show sufficient statistical power. Advances in understanding the underlying mechanisms of SLE will be directed towards correlating clinical manifestations with specific pathogenic pathways and the development of precision medicine.

Metabolic syndrome criteria and severity and carbon dioxide (CO2) emissions in an adult population.

BACKGROUND: Metabolic syndrome (MetS) has become a growing risk factor of some non-communicable diseases. Increase of greenhouse gas emissions affects the planet. AIMS: To assess the association between MetS severity and amount of carbon dioxide (CO2) emitted in an adult population. DESIGN: Cross-sectional study (n = 6646; 55-76-year-old-men; 60-75-year-old-women with MetS). METHODS: Dietary habits were assessed using a pre-validated semi quantitative 143-item food frequency questionnaire. The amount of CO2 emitted due to the production of food consumed by person and day was calculated using a European database, and the severity of the MetS was calculated with the MetS Severity Score. RESULTS: Higher glycaemia levels were found in people with higher CO2 emissions. The risk of having high severe MetS was related to high CO2 emissions. CONCLUSIONS: Low CO2 emissions diet would help to reduce MetS severity. Advantages for both health and the environment were found following a more sustainable diet. TRIAL REGISTRATION: ISRCTN, ISRCTN89898870 . Registered 05 September 2013.

Pandemic-related stress in pregnant women during the first COVID-19 lockdown and neonatal development.

BACKGROUND: Maternal stress and psychopathology have a negative effect on mothers and neonates. Maternal stress may affect neonatal growth and development both physically and psychologically. PURPOSE: To study the impact of pandemic-related pregnancy stress and maternal psychopathological symptoms during the COVID-19 lockdown in 2020 on neonatal development. METHODS: A two-phase prospective study was carried out on a sample of 181 pregnant women ranged from 18 to 40 years old in Spain (Europe). Phase 1: Pandemic-related pregnancy stress (PREPS), Prenatal Distress Questionnaire (PDQ), Perceived Stress Scale (PSS) and the revised version of the Symptom Checklist-90 (SCL-90-R) were used to assess psychological symptoms during the lockdown. In the follow-up (Phase 2), obstetric, birth-related and anthropometric variables were collected from 81 pregnant women-neonates dyads. RESULTS: Primiparous women showed higher psychopathological symptoms and higher levels of pandemic-related pregnancy stress than multiparous women. A multiple linear regression model showed that pandemic-related pregnancy stress could predict the length of neonate by adjusting for maternal age and gestational age, especially for primiparous women. IMPLICATIONS FOR RESEARCH: Studies assessing neonates development should evaluate the long-term effect of the COVID-19 pandemic on neonates´ length. IMPLICATIONS FOR PRACTICE: States the relation between pandemic-related pregnancy stress and neonatal development by being able to track the effects on neonates whose mothers had high levels of stress during the COVID-19 pandemic.

Differences in Psychological Symptoms in Pregnancy and Postpartum before and during COVID-19: A Cross-sectional Study / Las diferencias en los síntomas psicológicos durante el embarazo y el postparto antes y después del COVID-19: un estudio transversal

Rationale: Pregnant women are especially vulnerable to mental health problems, including stress, anxiety, and depression. This risk has been increased during the COVID-19 pandemic and differences in psychological symptoms in pregnancy and postpartum before and during COVID-19 exists. Mental health problems can have adverse effects on both the woman, and the neonate, including miscarriages, premature births, low birth weight, and higher rates of cesarean sections and instrument-assisted deliveries. Aim: To evaluate the prevalence of psychological symptoms of pregnant women before and during the COVID-19 pandemic. Method: A cross-sectional study was carried out to assess the psychological profile in a sample of pregnant women selected before the pandemic and a sample of women studied during the first wave of the pandemic. A total of 122 women were selected prior to the pandemic and 181 women during the COVID-19 outbreak. The Symptom Checklist-90 Revised (SCL-90-R) was used to assess depression and anxiety during pregnancy and in the postpartum period. Results: The prevalence of symptoms of depression and anxiety during pregnancy were higher in the sample of women studied during the pandemic (SCL-90-R: M = 54.6 vs. 42.6 and M = 62.6 vs. 51.7 respectively). In the postpartum the difference between both samples of women was even higher for depression and anxiety (SCL-90-R: M = 50.4 vs. 35.0 and M = 51.3 vs. 36.0 respectively). Being a pregnant woman at the COVID-19 outbreak was directly associated with a higher score of depression symptoms (aOR = 8.67, 95% CI [3.26, 23.02], p < .001). Anxiety during childbirth was more frequently reported by women before the pandemic (aOR = 5.13, 95% CI [2.53, 10.44], p < .001). The variable stage (before /during pandemic) was also associated with having a clinical SCL-90-R score above 70 (aOR = 7.61, 95% CI [2.7, 21.47], p < .001). (AU)

Justificación: Las mujeres embarazadas son especialmente vulnerables a los problemas de salud mental, como el estrés, la ansiedad y la depresión. Este riesgo se ha incrementado durante la pandemia de COVID-19, habiendo diferencias en los síntomas psicológicos en el embarazo y el puerperio antes y después de la pandemia. Los problemas de salud mental pueden tener efectos perjudiciales tanto en la mujer como en el recién nacido, como abortos espontáneos, partos prematuros, bajo peso al nacer y tasas más altas de cesáreas y partos asistidos. Objetivo: Evaluar la prevalencia de síntomas psicológicos de gestantes antes y durante la pandemia de COVID-19. Método: Se realizó un estudio transversal para evaluar el perfil psicológico en una muestra de mujeres embarazadas seleccionadas antes de la pandemia y una muestra de mujeres estudiadas durante la primera ola de la pandemia. Se seleccionó un total de 122 mujeres antes de la pandemia y 181 mujeres durante el brote de COVID-19. Se utilizó la Inventario de Verificación de Síntomas-90 Revisada (SCL-90-R) para evaluar la depresión y la ansiedad durante el embarazo y el puerperio. Resultados: La prevalencia de síntomas de depresión y ansiedad durante el embarazo fue mayor en la muestra de mujeres estudiadas durante la pandemia (SCL-90-R: M = 54.6 vs. 42.6 y M = 62.6 vs. 51.7 respectivamente). En el postparto la diferencia entre ambas muestras de mujeres fue aún mayor para depresión y ansiedad (SCL-90-R: M = 50.4 vs. 35.0 y M = 51.3 vs. 36.0 respectivamente). Ser mujer embarazada en el brote de COVID-19 se asoció directamente con una mayor puntuación de síntomas de depresión (aOR = 8.67, IC 95% [3.26, 23.02, p < .001). Las mujeres manifestaron ansiedad durante el parto con mayor frecuencia antes de la pandemia (aOR = 5.13, IC 95% 2.53, 10.44], p < .001). La variable estadio (antes/durante la pandemia) también se asoció con tener una puntuación clínica SCL-90-R superior a 70 (aOR = 7.61, IC 95% [2.7, 21.47], p < .001). (AU)

Wearable-Triggered Ecological Momentary Assessments Are Feasible in People With Advanced Cancer and Their Family Caregivers: Feasibility Study from an Outpatient Palliative Care Clinic at a Cancer Center.

Background: Emerging digital health approaches could play a role in better personalized palliative care. Aim: We conducted a feasibility study testing wearable sensor (WS)-triggered ecological momentary assessments (EMAs) and electronic patient-reported outcomes in community palliative care with patient-caregiver dyads. Design: All wore consumer-grade WS for five weeks. Sensor-detected "stress" (heart rate variability algorithm) that passed individualized thresholds triggered a short smartphone survey. Daily sleep surveys, weekly symptom surveys (Integrated Palliative care Outcome Scale), and a poststudy experience survey were conducted. Setting/Participants: Fifteen dyads (n = 30) were recruited from an outpatient palliative care clinic for people with cancer. Results: Daytime sensor wear-time had 73% adherence. Participants perceived value in this support. Quantity and severity of "stress" events were higher in patients. Sleep disturbance was similar but for different reasons: patients (physical symptoms) and caregivers (worrying about the patient). Conclusions: EMAs are feasible and valued in community palliative care.

Researchers in rheumatology should avoid categorization of continuous predictor variables.

BACKGROUND: Rheumatology researchers often categorize continuous predictor variables. We aimed to show how this practice may alter results from observational studies in rheumatology. METHODS: We conducted and compared the results of two analyses of the association between our predictor variable (percentage change in body mass index [BMI] from baseline to four years) and two outcome variable domains of structure and pain in knee and hip osteoarthritis. These two outcome variable domains covered 26 different outcomes for knee and hip combined. In the first analysis (categorical analysis), percentage change in BMI was categorized as ≥ 5% decrease in BMI, < 5% change in BMI, and ≥ 5% increase in BMI, while in the second analysis (continuous analysis), it was left as a continuous variable. In both analyses (categorical and continuous), we used generalized estimating equations with a logistic link function to investigate the association between the percentage change in BMI and the outcomes. RESULTS: For eight of the 26 investigated outcomes (31%), the results from the categorical analyses were different from the results from the continuous analyses. These differences were of three types: 1) for six of these eight outcomes, while the continuous analyses revealed associations in both directions (i.e., a decrease in BMI had one effect, while an increase in BMI had the opposite effect), the categorical analyses showed associations only in one direction of BMI change, not both; 2) for another one of these eight outcomes, the categorical analyses suggested an association with change in BMI, while this association was not shown in the continuous analyses (this is potentially a false positive association); 3) for the last of the eight outcomes, the continuous analyses suggested an association of change in BMI, while this association was not shown in the categorical analyses (this is potentially a false negative association). CONCLUSIONS: Categorization of continuous predictor variables alters the results of analyses and could lead to different conclusions; therefore, researchers in rheumatology should avoid it.

Comparative effects of glucagon-like peptide-1 receptors agonists, 4-dipeptidyl peptidase inhibitors, and metformin on metabolic syndrome.

AIMS: To assess the comparative effects of glucagon-like peptide-1 receptor agonists (GLP-1RA), 4-dipeptidyl peptidase inhibitors (DPP-4I), and metformin treatment during one year on metabolic syndrome (MetS) components and severity in MetS patients. METHODS: Prospective study (n = 6165 adults) within the frame of PREDIMED-Plus trial. The major end-point was changes on MetS components and severity after one- year treatment of GLP-1RA, DPP-4I, and metformin. Anthropometric measurements (weight, height and waist circumference), body mass index (BM), and blood pressure were registered. Blood samples were collected after overnight fasting. Plasma glucose, glycosylated hemoglobin (HbA1c), plasma triglycerides and cholesterol were measured. Dietary intakes as well as physical activity were assessed through validated questionnaires. RESULTS: MetS parameters improved through time. The treated groups improved glycaemia compared with untreated (glycaemia ∆ untreated: -1.7 mg/dL(± 13.5); ∆ metformin: - 2.5(± 23.9) mg/dL; ∆ DPP-4I: - 4.5(± 42.6); mg/dL ∆ GLP-1RA: - 4.3(± 50.9) mg/dL; and HbA1c: ∆ untreated: 0.0(± 0.3) %; ∆ metformin: - 0.1(± 0.7) %; ∆ DPP-4I: - 0.1(± 1.0) %; ∆ GLP-1RA: - 0.2(± 1.2) %. Participants decreased BMI and waist circumference. GLP-1RA and DPP-4I participants registered the lowest decrease in BMI (∆ untreated: -0.8(± 1.6) kg/m2; ∆ metformin: - 0.8(± 1.5) kg/m2; ∆ DPP-4I: - 0.6(± 1.3) kg/m2; ∆ GLP-1RA: - 0.5(± 1.2) kg/m2. and their waist circumference (∆ untreated: -2.8(± 5.2) cm; ∆ metformin: - 2.6(± 15.2) cm; ∆ DPP-4I: - 2.1(± 4.8) cm; ∆ GLP-1RA: - 2.4(± 4.1) cm. CONCLUSION: In patients with MetS and healthy lifestyle intervention, those treated with GLP-1RA and DPP-4I obtained better glycemic profile. Anthropometric improvements were modest.

Analysis of the Genetic Relationship between Atherosclerosis and Non-Alcoholic Fatty Liver Disease through Biological Interaction Networks.

Non-alcoholic fatty liver disease (NAFLD) seems to have some molecular links with atherosclerosis (ATH); however, the molecular pathways which connect both pathologies remain unexplored to date. The identification of common factors is of great interest to explore some therapeutic strategies to improve the outcomes for those affected patients. Differentially expressed genes (DEGs) for NAFLD and ATH were extracted from the GSE89632 and GSE100927 datasets, and common up- and downregulated DEGs were identified. Subsequently, a protein-protein interaction (PPI) network based on the common DEGs was performed. Functional modules were identified, and the hub genes were extracted. Then, a Gene Ontology (GO) and pathway analysis of common DEGs was performed. DEGs analysis in NAFLD and ATH showed 21 genes that were regulated similarly in both pathologies. The common DEGs with high centrality scores were ADAMTS1 and CEBPA which appeared to be down- and up-regulated in both disorders, respectively. For the analysis of functional modules, two modules were identified. The first one was oriented to post-translational protein modification, where ADAMTS1 and ADAMTS4 were identified, and the second one mainly related to the immune response, where CSF3 was identified. These factors could be key proteins with an important role in the NAFLD/ATH axis.

Maternal Psychopathological Profile during Childbirth and Neonatal Development during the COVID-19 Pandemic: A Pre-Posttest Study.

The coronavirus SARS-CoV-2 generated an alert that became a state of emergency in health issues worldwide, a situation that affected the entire population, including pregnant women. The present study aims to understand the effect of the psychopathological profile of a sample of pregnant women at the time of the COVID-19 pandemic on themselves during childbirth (Phase 1) and after childbirth and the anthropometric measures of the neonate at birth (Phase 2). The total sample comprises 81 pregnant women aged 32.07 years (SD = 5.45) and their neonates. Sociodemographic and obstetric data of the sample were collected. During pregnancy, psychopathology was measured by means of the SCL-90, as well as other psychological measures on stress and social support. Cluster k-means techniques were used to uncover the heterogeneous profiles of psychopathology in Phase 1. Two main psychopathological profiles were found (Cluster 1: High psychopathological symptoms; Cluster 2: Low psychopathological symptoms). The clusters generated show significant differences in all the SCL-90-R subscales used and in the general index at Phase 1. After childbirth, high psychopathology profile membership was associated with a greater probability of having a non-eutocic delivery. On the other hand, the low psychopathological symptoms cluster shows higher levels of depressive symptoms, hostility, paranoid ideation, and psychotic symptoms in Phase 2. In conclusion, there seemed to exist two heterogeneous profiles of psychopathology in pregnant women during the pandemic; the stress related to the pandemic seemed uninfluential on the development of a profile of high psychopathological symptoms and the psychopathology profile may influence delivery and postpartum outcomes.

Carbon dioxide (CO2) emissions and adherence to Mediterranean diet in an adult population: the Mediterranean diet index as a pollution level index.

BACKGROUND: Research related to sustainable diets is is highly relevant to provide better understanding of the impact of dietary intake on the health and the environment. AIM: To assess the association between the adherence to an energy-restricted Mediterranean diet and the amount of CO2 emitted in an older adult population. DESIGN AND POPULATION: Using a cross-sectional design, the association between the adherence to an energy-reduced Mediterranean Diet (erMedDiet) score and dietary CO2 emissions in 6646 participants was assessed. METHODS: Food intake and adherence to the erMedDiet was assessed using validated food frequency questionnaire and 17-item Mediterranean questionnaire. Sociodemographic characteristics were documented. Environmental impact was calculated through greenhouse gas emissions estimations, specifically CO2 emissions of each participant diet per day, using a European database. Participants were distributed in quartiles according to their estimated CO2 emissions expressed in kg/day: Q1 (≤2.01 kg CO2), Q2 (2.02-2.34 kg CO2), Q3 (2.35-2.79 kg CO2) and Q4 (≥2.80 kg CO2). RESULTS: More men than women induced higher dietary levels of CO2 emissions. Participants reporting higher consumption of vegetables, fruits, legumes, nuts, whole cereals, preferring white meat, and having less consumption of red meat were mostly emitting less kg of CO2 through diet. Participants with higher adherence to the Mediterranean Diet showed lower odds for dietary CO2 emissions: Q2 (OR 0.87; 95%CI: 0.76-1.00), Q3 (OR 0.69; 95%CI: 0.69-0.79) and Q4 (OR 0.48; 95%CI: 0.42-0.55) vs Q1 (reference). CONCLUSIONS: The Mediterranean diet can be environmentally protective since the higher the adherence to the Mediterranean diet, the lower total dietary CO2 emissions. Mediterranean Diet index may be used as a pollution level index.

Association of Decrease in Body Mass Index With Reduced Incidence and Progression of the Structural Defects of Knee Osteoarthritis: A Prospective Multi-Cohort Study.

OBJECTIVE: To define the association between change in body mass index (BMI) and the incidence and progression of the structural defects of knee osteoarthritis as assessed by radiography. METHODS: Radiographic analyses of knees at baseline and at 4-5 years of follow-up were obtained from the following 3 independent cohort studies: the Osteoarthritis Initiative (OAI) study, the Multicenter Osteoarthritis Study (MOST), and the Cohort Hip and Cohort Knee (CHECK) study. Logistic regression analyses using generalized estimating equations, with clustering of both knees within individuals, were used to investigate the association between change in BMI from baseline to 4-5 years of follow-up and the incidence and progression of knee osteoarthritis. RESULTS: A total of 9,683 knees (from 5,774 participants) in an "incidence cohort" and 6,075 knees (from 3,988 participants) in a "progression cohort" were investigated. Change in BMI was positively associated with both the incidence and progression of the structural defects of knee osteoarthritis. The adjusted odds ratio (OR) for osteoarthritis incidence was 1.05 (95% confidence interval [95% CI] 1.02-1.09), and the adjusted OR for osteoarthritis progression was 1.05 (95% CI 1.01-1.09). Change in BMI was also positively associated with degeneration (i.e., narrowing) of the joint space and with degeneration of the femoral and tibial surfaces (as indicated by osteophytes) on the medial but not on the lateral side of the knee. CONCLUSION: A decrease in BMI was independently associated with lower odds of incidence and progression of the structural defects of knee osteoarthritis and could be a component in preventing the onset or worsening of knee osteoarthritis.