Early detection and treatment have been shown to be effective in reducing disability severity caused by Autistic Spectrum Disorders (ASDs). As Spanish pediatricians have no detection tool, the ...Modified Checklist for Autism in Toddlers (M-CHAT) was first translated into and culturally adapted to Spanish. Validity and reliability studies were carried out in two different geographical areas of Spain, where M-CHAT was administered to two different samples, namely: 2,480 high- and low-risk children; and 2,055 low-risk children. The results obtained were similar to those yielded by the original M-CHAT studies. Differences were found in positive predictive value, due to the low ASD frequency observed in this study. M-CHAT is still being studied in a large population-based screening program in Spain.
Abstract The assessment of body fat of children in primary care requires consideration of the dynamic changes in height, weight, lean mass, and fat mass during childhood growth. To achieve this, we ...aim to develop a predictive equation based on anthropometric values, with optimal diagnostic utility. This is a cross-sectional observational study, involving schoolgoers aged 11–17 years in the Vigo metropolitan area. Out of 10,747 individuals, 577 were randomly recruited. Variables: age, sex, ethnicity/country of origin, weight, height, 8 skinfolds, 3 diameters, 7 perimeters, and 85% percentile of body fat mass as the gold standard. Generalized additive regression was selected by cross-validation and compared using receiver operating characteristic curves (ROC curves). Sensitivity, specificity, positive and negative predictive values, true positive and true negative values, false positive and false negative values, accuracy, and positive and negative likelihood ratios were calculated. Two models were identified. The optimal model includes sex, weight, height, leg perimeter, and arm perimeter, with sensitivity of 0.93 (0.83–1.00), specificity of 0.91 (0.83–0.96), accuracy of 0.91 (0.84–0.96), and area under the curve (AUC) of 0.957 (0.928–0.986). The second model includes sex, age, and body mass index, with sensitivity of 0.93 (0.81–1.00), specificity of 0.90 (0.80–0.97), accuracy of 0.90 (0.82–0.96), and an AUC of 0.944 (0.903–0.984). Conclusion : Two predictive models, with the 85th percentile of fat mass as the gold standard, built with basic anthropometric measures, show very high diagnostic utility parameters. Their calculation is facilitated by a complementary online calculator. What is Known: • In routine clinical practice, mainly in primary care, BMI is used to determine overweight and obesity. This index has its weaknesses in the assessment of children. What is New: • We provide a calculator whose validated algorithm, through the determination of fat mass by impedanciometry, makes it possible to determine the risk of overweight and obesity in the community setting, through anthropometric measurements, providing a new practical, accessible and reliable model that improves the classification of overweight and obesity in children with respect to that obtained by determining BMI.
The objective was to describe the prevalence and intensity of neuropsychiatric symptoms (NPSs) isolated and grouped into subsyndromes in patients with dementia in primary care (PC) to analyse their ...distribution based on stages of dementia and the relationship between them and the intensity of symptoms.
Design: Cross-sectional study.
Patients with dementia, not institutionalized, in a PC follow-up.
Sociodemographic and clinical variables. Assessment instruments: The frequency and intensity of NPSs were measured with the Neuropsychiatric Inventory (NPI), and the stages of dementia with the Global Deterioration Scale (GDS).
The number of NPSs per patient, the mean NPI value, and the prevalence and intensity of NPSs isolated and grouped into subsyndromes were calculated, as were their 95% confidence intervals (CIs). The analyses were performed on an overall basis and by GDS scores. To analyse the association between the NPI and GDS scores, multivariate analysis was performed with a generalized linear model.
Overall, 98.4% (95% CI 94.5;99.8) of the patients presented some type of NPS, with an average of five symptoms per patient. The most frequent symptoms were apathy 69.8% (95% CI 61.1;77.5), agitation 55.8% (95% CI 46.8;64.5) and irritability 48.8% (95% CI 39.9;57.8). The more intense NPSs were apathy NPI 3.2 (95% CI 2.5;3.8) and agitation NPI 3.2 (95% CI 2.5;4.0). For subsyndromes, hyperactivity predominated 86.0% (95% CI 78.8;91.5), followed by apathy 77.5% (95% CI 69.3;84.4). By phase of dementia, the most common isolated symptom was apathy (60.7-75.0%). Affective symptoms and irritability predominated in the initial stages, and psychotic symptoms predominated in advanced stages. The mean NPI score was 24.9 (95% CI 21.5;28.4) and increased from 15.6 (95% CI 8.2;23.1) for GDS 3 to 28.9 (95% CI 12.6;45.1) for GDS 7. Patients with in the most advanced stages of dementia presented an NPI score 7.6 (95% CI 6.8;8.3) points higher than the score for mild dementia with adjustment for the other variables.
A high prevalence of NPSs was found among patients with dementia treated in PC. Symptoms change and increase in intensity as the disease progresses. Scales such as the NPI allow these symptoms to be identified, which may facilitate more stage-appropriate management.
Abstract
Background
Caregiver burden is related to personal factors and patient characteristics and is greater when neuropsychiatric symptoms (NPSs) are present. Objective: Estimate the prevalence of ...burden among caregivers of dementia patients and its association with NPSs and identify NPSs causing greater caregiver distress according to dementia stage.
Methods
A cross-sectional observational study in caregivers of noninstitutionalized dementia patients was conducted. Caregiver variables were sociodemographic, time of care, NPS-associated distress based on the Neuropsychiatric Inventory Caregiver Distress Scale (NPI-D) and burden based on the Zarit Burden Interview (ZBI). Patient variables were time since disease onset, Global Deterioration Scale (GDS) disease stage, functional assessment and NPS presence and intensity according to the Neuropsychiatric Inventory (NPI). The mean ZBI score, prevalence of burden and NPI-D score with 95% CIs at each dementia stage were estimated. Factors associated with burden were identified by multivariate analysis.
Results
Of the 125 caregivers included, 77.6% were women, with a mean age of 60.7 (± 14.3) years; 78.4% (95%CI: 71.0; 86.0) experienced burden. The mean ZBI score was 12.3 (95%CI: 11.6; 12.9) and increased according to NPS number (p = 0.042). The NPSs causing the most burden were disinhibition (93.5%), irritability (87.3%) and agitation (86.1%). Agitation, apathy, and sleep disorders were the NPSs generating the greatest overall caregiver distress; depression (max NPI-D 1.9), hyperactivity (max NPI-D 2.1), and psychosis symptoms (max NPI-D 1.6) generated the greatest distress at stage GDS 3, stages GDS 4–5, and stages GDS 6–7, respectively. The NPI score (OR = 1.0, 95%CI 1.0; 1.1), intensity of irritability (OR = 1.2, 95%CI 1.0; 1.6), disinhibition (OR = 2.6, 95%CI 1.1; 5.8) and hyperactivity subsyndrome (OR = 1.1, 95%CI 1.0; 1.2) were associated with caregiver burden. Other associated factors were female gender (OR = 6.0, 95%CI 1.6; 22.8), ≥ 8 h daily care (OR = 5.6, 95%CI 1.4; 22.8), working outside the home (OR = 7.6, 95%CI 1.8; 31.8), living with the patient (OR = 4.5, 95%CI 1.1; 19.6), kinship (OR = 5.4, 95%CI 1.0; 28.2) and lower patient education (OR = 8.3, 95%CI 2.3; 30.3).
Conclusions
The burden on caregivers of dementia patients is high and associated with NPS presence and intensity. Disinhibition and irritability caused the highest burden. Depression, hyperactivity and psychosis produce more distress in mild, mild-moderate and severe dementia, respectively.
Next generation sequencing methods are widely used in evaluating the structure and functioning of microbial communities, especially those centered on 16S rRNA subunit. Since Illumina Miseq, the most ...used sequencing platform, does not allow the full sequencing of 16S rRNA gene, this study aims to evaluate whether the choice of different target regions might affect the outcome of microbiome studies regarding soil and saliva samples. V1V3, V3V4, V4V5 and V6V8 domains were studied, finding that while some regions showed differences in the detection of certain bacterial taxa and in the calculation of alpha diversity, especially in soil samples, the overall effect did not compromise the differentiation of any sample type in terms of taxonomic analysis at the genus level. 16S rRNA target regions did affect the detection of specific bacteria related to soil quality and development, and microbial genera used as health biomarkers in saliva. V1V3 region showed the closest similarity to internal sequencing control mock community B, suggesting it might be the most preferable choice regarding data reliability.
The increasing concern about bacterial resistance has made the rational prescription of antibiotics even more urgent. The non-pharmacological measures established to reduce the impact of the ...SARS-CoV-2 pandemic have modified the epidemiology of pediatric infections and, consequently, the use of antibiotics. Interrupted time series (ITS) analyses are quasi-experimental studies that allow for the estimation of causal effects with observational data in "natural experiments", such as changes in health policies or pandemics. The effect of the SARS-CoV-2 pandemic on the incidence of infectious diseases and the use of antibiotics between 2018 and 2020 in the Health Area of Vigo (Galicia, Spain) was quantified and analyzed. This paper outlines a real-world data study with administrative records from primary care services provided for the pediatric population. The records were related to episodes classified as infectious by the International Classification of Primary Care (ICPC-2) and oral medication in the therapeutic subgroup J01, corresponding to antibiotics for systemic use, according to the World Health Organization's Anatomical Therapeutic Chemical (ATC) classification system. The records were classified according to incident episodes, age, dose per inhabitant, and year. Segmented regression models were applied using an algorithm that automatically identifies the number and position of the change points. During the SARS-CoV-2 pandemic, the number of infectious diseases being transmitted between individuals, through the air and through the fecal-oral route, significantly decreased, and a slight decrease in infections transmitted via other mechanisms (urinary tract infections) was also found. In parallel, during the months of the pandemic, there has been a marked and significant reduction in antibacterial agent utilization, mainly of penicillins, cephalosporins, and macrolides.
Motivation: Web services technology is becoming the option of choice to deploy bioinformatics tools that are universally available. One of the major strengths of this approach is that it supports ...machine-to-machine interoperability over a network. However, a weakness of this approach is that various Web Services differ in their definition and invocation protocols, as well as their communication and data formats—and this presents a barrier to service interoperability. Results: jORCA is a desktop client aimed at facilitating seamless integration of Web Services. It does so by making a uniform representation of the different web resources, supporting scalable service discovery, and automatic composition of workflows. Usability is at the top of the jORCA agenda; thus it is a highly customizable and extensible application that accommodates a broad range of user skills featuring double-click invocation of services in conjunction with advanced execution-control, on the fly data standardization, extensibility of viewer plug-ins, drag-and-drop editing capabilities, plus a file-based browsing style and organization of favourite tools. The integration of bioinformatics Web Services is made easier to support a wider range of users. Availability and Implementation: jORCA binaries and extended documentation are freely available at http://www.bitlab-es.com/jorca under the Creative Commons Attribution-No Derivative Works 2.5 Spain License and jORCA source code (implemented in Java) is available under request. (GPL v3 license). jORCA has been tested under UNIX (Fedora 11, open SUSE 11 and Ubuntu 8.1), MS-Windows and Mac OS 10.5 operating systems. Java VM version 1.6.0 later is required. Contact: ots@uma.es or vickymr@uma.es Supplementary information: Supplementary data are available at Bioinformatics online.
In recent years, different tools have been developed to facilitate analysis of social determinants of health (SDH) and apply this to health policy. The possibility of generating predictive models of ...health outcomes which combine a wide range of socioeconomic indicators with health problems is an approach that is receiving increasing attention. Our objectives are twofold: (1) to predict population health outcomes measured as hospital morbidity, taking primary care (PC) morbidity adjusted for SDH as predictors; and (2) to analyze the geographic variability of the impact of SDH-adjusted PC morbidity on hospital morbidity, by combining data sourced from electronic health records and selected operations of the National Statistics Institute (
).
The following will be conducted: a qualitative study to select socio-health indicators using RAND methodology in accordance with SDH frameworks, based on indicators published by the
in selected operations; and a quantitative study combining two large databases drawn from different Spain's Autonomous Regions (ARs) to enable hospital morbidity to be ascertained, i.e., PC electronic health records and the minimum basic data set (MBDS) for hospital discharges. These will be linked to socioeconomic indicators, previously selected by geographic unit. The outcome variable will be hospital morbidity, and the independent variables will be age, sex, PC morbidity, geographic unit, and socioeconomic indicators.
To achieve the first objective, predictive models will be used, with a test-and-training technique, fitting multiple logistic regression models. In the analysis of geographic variability, penalized mixed models will be used, with geographic units considered as random effects and independent predictors as fixed effects.
This study seeks to show the relationship between SDH and population health, and the geographic differences determined by such determinants. The main limitations are posed by the collection of data for healthcare as opposed to research purposes, and the time lag between collection and publication of data, sampling errors and missing data in registries and surveys. The main strength lies in the project's multidisciplinary nature (family medicine, pediatrics, public health, nursing, psychology, engineering, geography).
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has already caused 6 million deaths worldwide. While asymptomatic individuals are responsible of many potential transmissions, the ...difficulty to identify and isolate them at the high peak of infection constitutes still a real challenge. Moreover, SARS-CoV-2 provokes severe vascular damage and thromboembolic events in critical COVID-19 patients, deriving in many related deaths and long-hauler symptoms. Understanding how these processes are triggered as well as the potential long-term sequelae, even in asymptomatic individuals, becomes essential.
We have evaluated, by application of a proteomics-based quantitative approach, the effect of serum from COVID-19 asymptomatic individuals over circulating angiogenic cells (CACs). Healthy CACs were incubated ex-vivo with the serum of either COVID-19 negative (PCR -/IgG -, n:8) or COVID-19 positive asymptomatic donors, at different infective stages: PCR +/IgG - (n:8) and PCR -/IgG + (n:8). Also, a label free quantitative approach was applied to identify and quantify protein differences between these serums. Finally, machine learning algorithms were applied to validate the differential protein patterns in CACs.
Our results confirmed that SARS-CoV-2 promotes changes at the protein level in the serum of infected asymptomatic individuals, mainly correlated with altered coagulation and inflammatory processes (Fibrinogen, Von Willebrand Factor, Thrombospondin-1). At the cellular level, proteins like ICAM-1, TLR2 or Ezrin/Radixin were only up-regulated in CACs treated with the serum of asymptomatic patients at the highest peak of infection (PCR + /IgG -), but not with the serum of PCR -/IgG + individuals. Several proteins stood out as significantly discriminating markers in CACs in response to PCR or IgG + serums. Many of these proteins particiArticle title: Kindly check and confirm the edit made in the article title.pate in the initial endothelial response against the virus.
The ex vivo incubation of CACs with the serum of asymptomatic COVID-19 donors at different stages of infection promoted protein changes representative of the endothelial dysfunction and inflammatory response after viral infection, together with activation of the coagulation process. The current approach constitutes an optimal model to study the response of vascular cells to SARS-CoV-2 infection, and an alternative platform to test potential inhibitors targeting either the virus entry pathway or the immune responses following SARS-CoV-2 infection.
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