Multiplex real-time PCR in non-invasive respiratory samples to reduce antibiotic use in community-acquired pneumonia: a randomised trial.

We assessed whether multiplex real-time PCR plus conventional microbiological testing is safe and more effective than conventional microbiological testing alone for reducing antibiotic use in community-acquired pneumonia (CAP). In this randomised trial, we recruited adults hospitalised with CAP at four Spanish hospitals. Patients were randomly assigned (1:1) to undergo either multiplex real-time PCR in non-invasive respiratory samples plus conventional microbiological testing or conventional microbiological testing alone. The primary endpoint was antibiotic use measured by days of antibiotic therapy (DOT). Between February 20, 2020, and April 24, 2023, 242 patients were enrolled; 119 were randomly assigned to multiplex real-time PCR plus conventional microbiological testing and 123 to conventional microbiological testing alone. All but one of the patients allocated to multiplex real-time PCR plus conventional microbiological testing underwent PCR, which was performed in sputum samples in 77 patients (65.2%) and in nasopharyngeal swabs in 41 (34.7%). The median DOT was 10.04 (IQR 7.98, 12.94) in the multiplex PCR plus conventional microbiological testing group and 11.33 (IQR 8.15, 16.16) in the conventional microbiological testing alone group (difference -1.04; 95% CI, -2.42 to 0.17; p = 0.093). No differences were observed in adverse events and 30-day mortality. Our findings do not support the routine implementation of multiplex real-time PCR in the initial microbiological testing in hospitalised patients with CAP. Clinicaltrials.gov registration: NCT04158492.

γδ+ T-Cells Is a Useful Biomarker for the Differential Diagnosis between Celiac Disease and Non-Celiac Gluten Sensitivity in Patients under Gluten Free Diet.

BACKGROUND: The differential diagnosis between patients with celiac disease (CD) and non-celiac gluten sensitivity (NCGS) is difficult when a gluten-free diet (GFD) has been initiated before the diagnostic work-up. Isolated increases in TCRγδ+ and celiac lymphogram (increased TCRγδ+ plus decreased CD3-) may enable differential diagnosis in this challenging clinical setting. This study evaluated: (1) the accuracy of %TCRγδ+ and celiac lymphogram for diagnosing CD before and after GFD and for differentiation with NCGS; (2) TCRγδ+ kinetics at baseline and after starting GFD in both CD and NCGS. METHODS: The inclusion criteria were patients with CD (n = 104), NCGS (n = 37), and healthy volunteers (n = 18). An intestinal biopsy for intraepithelial lymphogram by flow cytometry was performed at baseline and after GFD. The optimal cutoff for CD diagnostic accuracy was established by maximizing the Youden index and via logistic regression. RESULTS: %TCRγδ+ showed better diagnostic accuracy than celiac lymphogram for identifying CD before and after GFD initiation. With a cutoff > 13.31, the accuracy for diagnosing CD in patients under GFD was 0.88 [0.80-0.93], whereas the accuracy for diagnosing NCGS (%TCRγδ+ ≤ 13.31) was 0.84 [0.76-0.89]. The percentage of TCRγδ+ cells showed differential kinetics between CD (baseline 22.7% [IQR, 16.4-33.6] vs. after GFD 26.4% [IQR, 17.8-36.8]; p = 0.026) and NCGS (baseline 9.4% [IQR, 4.1-14.6] vs. after GFD 6.4% [IQR, 3.2-11]; p = 0.022). CONCLUSION: TCRγδ+ T cell assessment accurately diagnoses CD before and after a GFD. Increased TCRγδ+ was maintained in the long term after GFD in CD but not in NCGS. Altogether, this suggests the potential usefulness of this marker for the differential diagnosis of these two entities in patients on a GFD.

Clinical sub-phenotypes of Staphylococcus aureus bacteraemia.

BACKGROUND: Staphylococcus aureus bacteraemia (SAB) is a clinically heterogeneous disease. The ability to identify sub-groups of patients with shared traits (sub-phenotypes) is an unmet need that could allow patient stratification for clinical management and research. We aimed to test the hypothesis that clinically-relevant sub-phenotypes can be reproducibly identified amongst patients with SAB. METHODS: We studied three cohorts of hospitalised adults with monomicrobial SAB: a UK retrospective observational study (Edinburgh cohort, n=458), the UK ARREST randomised trial (n=758), and the Spanish SAFO randomised trial (n=214). Latent class analysis was used to identify sub-phenotypes using routinely-collected clinical data, without considering outcomes. Mortality and microbiologic outcomes were then compared between sub-phenotypes. RESULTS: Included patients had predominantly methicillin-susceptible SAB (1366/1430,95.5%). We identified five distinct, reproducible clinical sub-phenotypes: (A) SAB associated with older age and comorbidity, (B) nosocomial intravenous catheter-associated SAB in younger people without comorbidity, (C) community-acquired metastatic SAB, (D) SAB associated with chronic kidney disease, and (E) SAB associated with injection drug use. Survival and microbiologic outcomes differed between the sub-phenotypes. 84-day mortality was highest in sub-phenotype A, and lowest in B and E. Microbiologic outcomes were worse in sub-phenotype C. In a secondary analysis of the ARREST trial, adjunctive rifampicin was associated with increased 84-day mortality in sub-phenotype B and improved microbiologic outcomes in sub-phenotype C. CONCLUSIONS: We have identified reproducible and clinically-relevant sub-phenotypes within SAB, and provide proof-of-principle of differential treatment effects. Through clinical trial enrichment and patient stratification, these sub-phenotypes could contribute to a personalised medicine approach to SAB.

Radiomics and Clinical Data for the Diagnosis of Incidental Pulmonary Nodules and Lung Cancer Screening: Radiolung Integrative Predictive Model.

INTRODUCTION: Early diagnosis of lung cancer (LC) is crucial to improve survival rates. Radiomics models hold promise for enhancing LC diagnosis. This study assesses the impact of integrating a clinical and a radiomic model based on deep learning to predict the malignancy of pulmonary nodules (PN). METHODOLOGY: Prospective cross-sectional study of 97 PNs from 93 patients. Clinical data included epidemiological risk factors and pulmonary function tests. The region of interest of each chest CT containing the PN was analysed. The radiomic model employed a pre-trained convolutional network to extract visual features. From these features, 500 with a positive standard deviation were chosen as inputs for an optimised neural network. The clinical model was estimated by a logistic regression model using clinical data. The malignancy probability from the clinical model was used as the best estimate of the pre-test probability of disease to update the malignancy probability of the radiomic model using a nomogram for Bayes' theorem. RESULTS: The radiomic model had a positive predictive value (PPV) of 86%, an accuracy of 79% and an AUC of 0.67. The clinical model identified DLCO, obstruction index and smoking status as the most consistent clinical predictors associated with outcome. Integrating the clinical features into the deep-learning radiomic model achieves a PPV of 94%, an accuracy of 76% and an AUC of 0.80. CONCLUSIONS: Incorporating clinical data into a deep-learning radiomic model improved PN malignancy assessment, boosting predictive performance. This study supports the potential of combined image-based and clinical features to improve LC diagnosis.

REDCapDM: An R package with a set of data management tools for a REDCap project.

BACKGROUND: Research Electronic Data CAPture (REDCap) is a web application for creating and managing online surveys and databases. Clinical data management is an essential process before performing any statistical analysis to ensure the quality and reliability of study information. Processing REDCap data in R can be complex and often benefits from automation. While there are several R packages available for specific tasks, none offer an expansive approach to data management. RESULTS: The REDCapDM is an R package for accessing and managing REDCap data. It imports data from REDCap to R using either an API connection or the files in R format exported directly from REDCap. It has several functions for data processing and transformation, and it helps to generate and manage queries to clarify or resolve discrepancies found in the data. CONCLUSION: The REDCapDM package is a valuable tool for data scientists and clinical data managers who use REDCap and R. It assists in tasks such as importing, processing, and quality-checking data from their research studies.

Easy-Amanida: An R Shiny application for the meta-analysis of aggregate results in clinical metabolomics using Amanida and Webchem.

Meta-analysis is a useful tool in clinical research, as it combines the results of multiple clinical studies to improve precision when answering a particular scientific question. While there has been a substantial increase in publications using meta-analysis in various clinical research topics, the number of published meta-analyses in metabolomics is significantly lower compared to other omics disciplines. Metabolomics is the study of small chemical compounds in living organisms, which provides important insights into an organism's phenotype. However, the wide variety of compounds and the different experimental methods used in metabolomics make it challenging to perform a thorough meta-analysis. Additionally, there is a lack of consensus on reporting statistical estimates, and the high number of compound naming synonyms further complicates the process. Easy-Amanida is a new tool that combines two R packages, "amanida" and "webchem", to enable meta-analysis of aggregate statistical data, like p-value and fold-change, while ensuring the compounds naming harmonization. The Easy-Amanida app is implemented in Shiny, an R package add-on for interactive web apps, and provides a workflow to optimize the naming combination. This article describes all the steps to perform the meta-analysis using Easy-Amanida, including an illustrative example for interpreting the results. The use of aggregate statistics metrics extends the use of Easy-Amanida beyond the metabolomics field.

Long-Term Effects of a Stepwise, Multimodal, Non-Restrictive Antimicrobial Stewardship Programme for Reducing Broad-Spectrum Antibiotic Use in the ICU.

Information on the long-term effects of non-restrictive antimicrobial stewardship (AMS) strategies is scarce. We assessed the effect of a stepwise, multimodal, non-restrictive AMS programme on broad-spectrum antibiotic use in the intensive care unit (ICU) over an 8-year period. Components of the AMS were progressively implemented. Appropriateness of antibiotic prescribing was also assessed by monthly point-prevalence surveys from 2013 onwards. A Poisson regression model was fitted to evaluate trends in the reduction of antibiotic use and in the appropriateness of their prescription. From 2011 to 2019, a total of 12,466 patients were admitted to the ICU. Antibiotic use fell from 185.4 to 141.9 DDD per 100 PD [absolute difference, -43.5 (23%), 95% CI -100.73 to 13.73; p = 0.13] and broad-spectrum antibiotic fell from 41.2 to 36.5 [absolute difference, -4.7 (11%), 95% CI -19.58 to 10.18; p = 0.5]. Appropriateness of antibiotic prescribing rose by 11% per year [IRR: 0.89, 95% CI 0.80 to 1.00; p = 0.048], while broad-spectrum antibiotic use showed a dual trend, rising by 22% until 2015 and then falling by 10% per year since 2016 [IRR: 0.90, 95% CI 0.81 to 0.99; p = 0.03]. This stepwise, multimodal, non-restrictive AMS achieved a sustained reduction in broad-spectrum antibiotic use in the ICU and significantly improved appropriateness of antibiotic prescribing.

Bayesian spatio-temporal analysis of the COVID-19 pandemic in Catalonia.

In this study, we modelled the incidence of COVID-19 cases and hospitalisations by basic health areas (ABS) in Catalonia. Spatial, temporal and spatio-temporal incidence trends were described using estimation methods that allow to borrow strength from neighbouring areas and time points. Specifically, we used Bayesian hierarchical spatio-temporal models estimated with Integrated Nested Laplace Approximation (INLA). An exploratory analysis was conducted to identify potential ABS factors associated with the incidence of cases and hospitalisations. High heterogeneity in cases and hospitalisation incidence was found between ABS and along the waves of the pandemic. Urban areas were found to have a higher incidence of COVID-19 cases and hospitalisations than rural areas, while socio-economic deprivation of the area was associated with a higher incidence of hospitalisations. In addition, full vaccination coverage in each ABS showed a protective effect on the risk of COVID-19 cases and hospitalisations.

The Impact of the Mediterranean Diet and Lifestyle Intervention on Lipoprotein Subclass Profiles among Metabolic Syndrome Patients: Findings of a Randomized Controlled Trial.

Metabolic syndrome (MetS) is associated with alterations of lipoprotein structure and function that can be characterized with advanced lipoprotein testing (ADLT). The effect of the Mediterranean diet (MedDiet) and weight loss on the lipoprotein subclass profile has been scarcely studied. Within the PREDIMED-Plus randomized controlled trial, a sub-study conducted at Bellvitge Hospital recruiting center evaluated the effects of a weight loss program based on an energy-reduced MedDiet (er-MedDiet) and physical activity (PA) promotion (intervention group) compared with energy-unrestricted MedDiet recommendations (control group) on ADLT-assessed lipoprotein subclasses. 202 patients with MetS (n = 107, intervention; n = 95, control) were included. Lipid profiles were determined, and ADLT was performed at baseline, 6, and 12 months. Linear mixed models were used to assess the effects of intervention on lipoprotein profiles. Compared to the control diet, at 12 months, the er-MedDiet+PA resulted in a significant additional 4.2 kg of body weight loss, a decrease in body mass index by 1.4 kg/m2, reduction in waist circumference by 2.2 cm, decreased triglycerides, LDL-cholesterol and non-HDL-cholesterol, and increased HDL-cholesterol. In er-MedDiet+PA participants, ADLT revealed a decrease in small dense-LDL-cholesterol (sd-LDL-C), intermediate-density lipoproteins, VLDL-triglyceride, and HDL-Triglyceride, and an increase in large LDL and large VLDL particles. In conclusion, compared to an ad libitum MedDiet (control group), er-MedDiet+PA decreased plasma triglycerides and the triglyceride content in HDL and VLDL particles, decreased sd-LDL-C, and increased large LDL particles, indicating beneficial changes against cardiovascular disease.

Reliability and validity of the KIDSCREEN-52 questionnaire to measure health related quality of life in the 8 to 18 year-old Argentinean population / Fiabilidad y validez del cuestionario KIDSCREEN-52 para medir calidad de vida relacionada con la salud para población argentina de 8 a 18 años

Introduction. The KIDSCREEN questionnaire is an instrument to measure health-related quality of life (HRQoL). It allows to differentiate health levels or to assess the efficacy of interventions. The objective was to evaluate the reliability and validity of the Argentine version of the questionnaire in the population aged 8-18 years-old in the city of Bahía Blanca. Population and Methods. Cross sectional study conducted in public and private schools in 2008 using a district-stratified sampling. The questionnaire was self-administered and included the KIDSCREEN questionnaire (52 items) and questions about age, gender and family socioeconomic level (SEL). Reliability was analyzed using standard psychometric analysis techniques and the item response theory. The analysis of the factorial structure was performed using a confirmatory factor analysis (CFA), and that of the construct validity was conducted comparing dimension mean scores by age, gender and SEL. Results. Most dimensions had a Cronbach's alpha of >0.7 and 80% of items, and sufficient infit or outfit values (<0.8). The CFA showed an adequate data adjustment to the ten-dimension structure. The mean values of the dimensions confirmed lower scores in adolescents than in children, and lower scores in females than in males, as expected in several of the HRQoL dimensions. Conclusions. The reliability and validity of the Argentinean version of the KIDSCREEN-52 questionnaire were acceptable; therefore its use can be recommended for the 8-18 year-old Argentinean population.

Introducción. El cuestionario KIDSCREEN es una medida de la calidad de vida relacionada con la salud (CVRS). Permite discriminar niveles de salud o evaluar la eficacia de las intervenciones. El objetivo fue evaluar la fiabilidad y la validez de la versión argentina del cuestionario en población de 8-18 años de edad de la ciudad de Bahía Blanca. Población y métodos. Estudio transversal en escuelas públicas y privadas durante el año 2008 mediante un muestreo estratificado por delegación. El cuestionario fue autoadministrado e incluyó el KIDSCREEN (52 ítems) y preguntas sobre edad, sexo y el nivel socioeconómico (NSE) de la familia. Se analizó la fiabilidad mediante técnicas de análisis psicométrico clásicas, así como la teoría de respuesta al ítem. La estructura factorial fue analizada mediante un análisis factorial confirmatorio (AFC) y, la validez del constructo, comparando las puntuaciones medias de las dimensiones según edad, sexo y NSE. Resultados. La mayoría de las dimensiones presentaron un alfa de Cronbach >0,7 y el 80% de los ítems, valores de infit o de outfit suficientes (< 0,8). El AFC mostró un adecuado ajuste de los datos a la estructura de diez dimensiones. Las medias de las dimensiones confirmaron puntuaciones menores en adolescentes que en niños/as y menores en mujeres que en varones, como se esperaba en varias dimensiones de la CVRS. Conclusiones. La versión argentina del KIDSCREEN- 52 presentó una aceptable fiabilidad y validez, por lo que puede recomendarse su utilización en población argentina de 8-18 años.