Search Results (86)

This study investigates the combined effects of air pollution and socioeconomic factors on disease incidence and severity, addressing gaps in prior research that often analyzed these factors separately. Using data from 86,170 hospitalizations in Mexico City (2015–2019), we employed multivariate statistical methods (PCA and factor analysis) to construct composite measures of social and economic status and grouped correlated pollutants. Logistic and negative binomial regression models assessed their associations with hospitalization risk and frequency. Results showed that economic status significantly influenced diabetes complications, while social factors affected prenatal care-related diseases and hypertension. The ${\mathrm{PM}}_{10}$–${\mathrm{PM}}_{2.5}$–CO group increased the incidence of asthma, influenza, and epilepsy, whereas ${\mathrm{NO}}_2$–${\mathrm{NO}}_x$ impacted diabetes complication severity and influenza. Nonlinear effects and interactions (e.g., age and weight) were also identified, highlighting the need for integrated analyses in environmental health research. Full article

Background: Asthma is the most common chronic respiratory disease in children and adolescents, associated with high morbidity and healthcare costs. Telemedicine has emerged as a strategy to improve access to care, adherence to treatment and symptom control. However, its effectiveness in the pediatric population has not been clearly studied. Objective: To assess the clinical effectiveness of telemedicine interventions in asthma control and health-related quality of life in asthmatic children and adolescents. Methodology: A systematic review and meta-analysis were performed following PRISMA-2020 guidelines, with previous registration in PROSPERO (CRD42025251000837). Sixteen randomized clinical trials (n = 2642) with patients aged 2–18 years were included. The interventions included videoconferencing, mobile applications, web systems, interactive voice response and mobile units in schools. The outcomes were measured using validated quality-of-life (PAQLQ) and asthma control (ACT/c-ACT) questionnaires. Results: Seven studies were incorporated into the PAQLQ meta-analysis, whose overall effect was non-significant (mean difference = 0.06; 95% CI: −0.06 to 0.18; I² = 5.7%). Five studies provided ACT/c-ACT data, showing a significant effect in favor of telemedicine (mean difference = 0.61; 95% CI: 0.32 to 0.90; I² = 73%). Complementary qualitative analysis revealed improvements in adherence, reduction in exacerbations, emergency department visits and use of rescue medication. Conclusions: Telemedicine improves the clinical control of pediatric asthma, although its impact on the quality of life is limited. Multicenter trials with long-term follow-up and cost-effectiveness evaluation are required. Full article

Nirmatrelvir plus ritonavir (NPR) has been approved for treating mild to moderate COVID-19 in high-risk adults but concerns about rebound effects have limited its use. This study aimed to identify individuals at risk of seeking medical care among high-risk non-hospitalized patients treated with NPR from 1 January 2022 to 31 December 2022, at our institution. Our outcome variable was the composite of subsequent evaluation in the Emergency Department or inpatient admission within four weeks of their NPR treatment. Of 369 patients who received NPR treatment, the mean (SD) age was 59.3 (±13.8) years; 64% (236) were female, and 77.7% (281) were white. The incidence of the composite event was 6.8% (25/369). In multivariable logistic regression, factors for seeking medical care following NPR treatment were female sex (OR 4.6; 95% CI 1.4–15.3; p = 0.013), myocardial infarction (OR 4.1; 95% CI 1.4–11.8; p = 0.011), chronic lung disease (CLD) except asthma and chronic obstructive pulmonary disease (COPD) (OR = 3.9, 95% CI 1.1–13.5; p = 0.03), and diabetes mellitus with complications (OR 6.9; 95% CI 2.0–23.3; p = 0.002) while alcohol users (OR 0.39; 95% CI 0.2–0.9; p = 0.038) were less likely to seek medical care. Larger cohorts are necessary to further assess and confirm these risk factors. Full article

Introduction: Asthma and chronic obstructive pulmonary disease (COPD) are chronic respiratory illnesses frequently accompanied by anxiety and depression. These psychological symptoms often go undetected due to their overlap with somatic complaints. According to the regulatory theory of temperament (RTT), biologically based temperament traits may influence emotional responses to chronic illness. This study examined whether RTT-defined temperament traits predict depression and anxiety severity in patients with asthma and/or COPD. Material and Methods: The study included 210 adult patients with asthma and/or COPD recruited from a university hospital and pulmonology clinics. Individuals with a prior history of mental illness were excluded. Participants completed three validated questionnaires: the Formal Characteristics of Behavior–Temperament Inventory (FCB-TI), the Beck Depression Inventory (BDI), and the State–Trait Anxiety Inventory (STAI). Additional demographic and clinical data were collected. Multiple linear regression was used to assess the predictive value of six temperament traits for depression, state anxiety, and trait anxiety. A significance threshold of α = 0.05 was used in all statistical tests. Results: Temperament structure significantly predicted all three mental health outcomes: depression (R² = 0.37), state anxiety (R² = 0.45), and trait anxiety (R² = 0.35). Briskness negatively correlated with all outcomes, while emotional reactivity showed a positive correlation. No significant associations were found for the remaining four traits. Socioeconomic and lifestyle factors were not significant predictors. Conclusions: Temperament traits, particularly briskness and emotional reactivity, significantly influence depression and anxiety severity in asthma and COPD. Temperament assessment may serve as a low-cost, telemedicine-compatible tool to identify at-risk patients and support integrated, personalized care. Full article

Background: Severe acute asthma (SAA) in children can be life-threatening. There has been a significant rise in paediatric intensive care unit (PICU) admissions due to SAA over the past two decades. While asthma is a heterogeneous disease, its underlying pathophysiological pathways remain underexplored. This study aimed to assess the value of non-invasive targeted exhaled breath metabolomics analysis to better characterise SAA. Methods: Breath samples from 17 children admitted to the PICU with SAA (cases) and 27 children with controlled severe asthma (controls) were analysed using thermal desorption gas chromatography–mass spectrometry (TD-GC-MS). Results: A targeted volatile organic compound (VOC) analysis identified 25 compounds, of which 16 were shared between groups. Four VOCs were significantly more often present in SAA, and nine VOCs exhibited higher concentrations in SAA. Longitudinal analysis of VOCs from follow-up samples of 10 cases showed no significant temporal differences, reinforcing the reproducibility of identified biomarkers. Conclusions: This study exemplifies the potential of exhaled breath analysis to provide insights into the molecular background of SAA. Breath metabolomics may enable early recognition of severe asthma attacks and preventive therapeutic interventions in children with severe asthma. Full article

Asthma is a respiratory condition affecting millions of individuals worldwide, often exacerbated by poor management and worsening weather conditions. As healthcare and weather data continue to expand, identifying the most appropriate and sustainable artificial intelligence (AI) models for asthma care has become a challenging task. Additionally, the integration of multi-modal data through advanced pre-processing and feature selection techniques has emerged as a critical innovation in developing more effective and robust models. This study examines the current state and potential of AI methods in respiratory care, utilizing available data sources to enhance outcomes. The novelty of this work highlights the progression from classical to advanced models, including machine learning, deep learning, and ChatGPT, applied to diverse data in asthma analysis, while outlining key challenges and discussing potential solutions and future directions. The aim of the study is to highlight how machine learning, deep learning, and hybrid model architectures contribute to effective asthma classification, while also demonstrating ChatGPT’s potential as a reliable support tool for physicians in asthma management and administration. It is projected that the review’s findings on key challenges and opportunities will provide insights and uncover potential research directions in asthma assessment through the application of AI models. Full article

Background/Objectives: Radiological imaging is crucial in intensive care settings, particularly for the differential diagnosis of fever and sepsis. Computed tomography (CT) is the preferred method for detecting infectious foci in critically ill ICU patients. Methods: This study prospectively analyzed non-ECG-gated chest and abdominal CT scans from ICU patients to assess CT’s diagnostic utility. Data from prior imaging modalities (CT, radiography, MRI, ultrasound), microbiological assays (blood cultures, bronchoalveolar lavage, urinalysis), and enzymatic profiles (transaminases, pancreatic enzymes) were included. The predictive value of clinical and laboratory parameters was evaluated via correlation analysis. Results: A total of 112 patients were evaluated, with 99 exhibiting 147 inflammatory foci (92 thoracic, 55 abdominal). Definitive diagnoses were made in 58.5% of cases, while 41.5% remained classified as possible. Prior diagnostic procedures identified inflammatory origins in 57.1% of cases. Fewer CT-detected foci were observed in patients with bronchial asthma or type 2 diabetes mellitus (p = 0.049 and p = 0.006). Conclusions: CT imaging plays a central role in identifying infectious foci in ICU patients with unexplained syndromes, particularly in the thoracic region. CT scanning is recommended for sepsis management when other diagnostic evidence is lacking. Conditions such as bronchial asthma or diabetes mellitus may prompt earlier suspicion of infectious foci due to elevated inflammatory markers. Full article

Background/Objectives: This study assesses parent reports of adolescent- and parent-level factors related to friendships among adolescents with asthma. This study serves to inform physicians and other health care professionals of factors related to difficulties making friends for adolescents with asthma, providing information from parent reports to identify risk and resilience factors related to friendships. Methods: Adolescents aged 12–17 years with current asthma from the 2022 National Survey of Children’s Health (NSCH) were selected for the study (n = 1812). A weighted logistic regression analysis was performed to explore predictors related to making and keeping friends. Adolescent-level predictors were asthma severity, allergies, body mass index, having behavioral problems, and adolescent sex and race/ethnicity (non-Hispanic White, and others, including Hispanic). Parent-level predictors were parent stress and coping. Results: Adolescents who were female, non-Hispanic White, had moderate/severe asthma symptoms, had current allergies, were overweight, and had behavioral problems were more likely to have difficulty making and keeping friends than adolescents who were male, non-White, had mild asthma, did not have allergies, were a normal weight or underweight, and did not have behavioral problems. Parents who reported difficulty coping with parenthood and its associated stressors were more likely to report that their adolescents had difficulty making friends. Conclusions: Pediatric moderate-to-severe asthma patients whose parents had difficulty coping with stress were more likely to exhibit greater difficulty making and keeping friends. Health care professionals managing these patients should incorporate questions into their history that address behavioral problems and parental household stress growing up to determine optimal strategies for improving friendship relationships. Whether this strategy leads to better asthma control and outcomes requires further investigation. In future studies, case studies with information about changes in friendships over time for adolescents with asthma should be carried out. The case studies could potentially highlight social strategies to use to improve friendship skills, and ultimately friendship-making for this vulnerable group. Full article

Background and Objectives: Childhood asthma represents a significant global public health issue and is the most common chronic disease among children. Hospitalization costs, especially for intensive care, are quite high. This study aimed to evaluate the characteristics, prognosis, and preventable risk factors of patients admitted to the Pediatric Intensive Care Unit (PICU) due to severe asthma exacerbations. Materials and Methods: We assessed patients admitted to the Ankara Bilkent City Hospital PICU from January 2013 to December 2022 diagnosed with asthma based on The Global Initiative for Asthma (GINA) criteria. The collected data encompassed demographic and clinical characteristics, intensive care treatments, hospitalization duration, atopic conditions, and respiratory viral panel results. The current clinical status was assessed using hospital records and caregiver interviews, with a focus on recent emergency admissions, ongoing treatments, exacerbation frequency, and asthma control based on GINA guidelines. Results: The study comprised 83 patients with a mean age of 72.9 (±45.5) months, predominantly male (63.9%). The average follow-up duration post-discharge was 40.7 ± 26.9 months. Patients received respiratory support in the PICU for a mean of 3.8 (±2.8) days and systemic steroid therapy for 4 (±1.5) days. Respiratory viral panel results identified pathogens in 42 patients, with rhinovirus being the most frequent. Post-discharge, 72.3% of patients continued follow-up at pediatric allergy clinics. Of the 60 patients contacted, 67.5% were on current asthma treatment and 48.2% had experienced an exacerbation in the past year. Asthma management steps remained unchanged for 33 patients, decreased for 13, and increased for 47 (44.6%). Asthma maintenance treatments pre-admission and post-discharge showed that 44.6% (n = 47) of the patients required an increase in their GINA treatment step after PICU admission, which was statistically significant (p < 0.001). History of atopic dermatitis was a significant risk factor for escalating treatment steps in both univariate and multivariate analyses (p = 0.018, p = 0.03). Conclusions: We found that admission to the PICU due to severe asthma exacerbation not only increases the risk of recurrent asthma exacerbations but also serves as a risk factor for stepping up maintenance treatment according to GINA guidelines during long-term follow-up. Full article

Background/Objectives: Respiratory syncytial virus (RSV) represents a significant cause of acute respiratory infections (ARIs) in adults aged 60 years and older, often leading to severe clinical outcomes and high healthcare costs. This study aimed to evaluate the clinical and economic burden of RSV compared to other ARIs, focusing on specific age groups, comorbidities, and demographic factors. Methods: A retrospective observational study was conducted using the electronic medical records of adults aged ≥60 years hospitalized for ARIs, including RSV, in Spain. Direct costs related to hospitalizations, intensive care unit (ICU) admissions, and treatments were analyzed. The study also assessed demographic, clinical, and comorbidity-related factors influencing the economic burden. Results: RSV infections resulted in significantly higher direct costs compared to other ARIs, particularly in patients aged 70–80 years. Comorbidities such as asthma and smoking history were associated with increased costs in RSV cases. Although ICU costs were comparable between groups, hospitalizations for RSV required longer stays and more intensive treatments, amplifying the overall economic burden. Differences in costs by age and sex highlighted the need for tailored clinical management strategies. Conclusions: RSV poses a substantial economic and clinical burden on adults aged 60 years and older, particularly in those with comorbidities. Preventive measures, such as vaccination, could reduce healthcare costs and improve outcomes in this vulnerable population. These findings support the inclusion of RSV vaccines in immunization programs, especially in aging populations like Spain, to alleviate healthcare pressures during peak respiratory disease seasons. Full article

Background/Objectives: Recent research has focused on the study of the epigenetic role of nutrition as a tool which is expected to introduce new perspectives in the field of disease prevention and management. Although maternal nutrition is one of the best-studied mechanisms of epigenetic modifications of the fetus/newborn, less is known on the impact of childhood/adolescent nutrition on the regulation of epigenetic mecha-nisms after the first year of life. The aim of the present study was the assessment of the epigenetic role of nutrition in the health and development of children and adolescents. Methods: A systematic review was performed according to the Preferred Reported Items for Systematic Reviews and Meta-analyses guidelines in five databases (PubMed, Cochrane, Science Direct, Scopus, and Google Scholar) up to 31 October 2024, which yielded 17 eligible studies. The Newcastle–Ottawa Scale and the Cochrane Collabora-tion Risk of Bias-2 tool were used for the evaluation of risk of bias in observational studies and randomized trials, respectively. Results: Three studies investigated the epi-genetic modifications due to lifestyle interventions combining changes both in diet and physical activity; the remaining 14 studies examined the role of dietary nutrients in the regulation of epigenetic mechanisms in various health conditions, such as Angelman’s syndrome, parenteral nutrition in Intensive Care Units, attention deficit hyperactivity disorder, risk of cardiovascular diseases, asthma or food sensitization, obesity, insulin resistance, and type 2 diabetes or evaluated epigenetic markers as new tools for the comprehension and prediction of the participants’ response to nutritional interven-tions. Conclusions: The important impact of diet on the regulation of epigenetic mech-anisms and the expression of various genes and gene pathways could be utilized for personalized nutritional interventions in various pediatric health conditions. Full article

This study investigates the effect of urban forests in reducing particulate matter (PM) concentrations and its subsequent impact on the number of asthma care visits. Understanding the mechanisms behind the relationship between the greenness of blocking forests and the reduction in PM is crucial for assessing the associated human health benefits. This study analyzed the influencing factors for reducing long-term PM₁₀ concentrations, utilizing the vegetation index and meteorological variables. Results showed that the reduction in PM₁₀ began in 2011, five years after the establishment of the blocking forest. The annual mean PM₁₀ concentrations decreased significantly, driven primarily by summer wind speed and summer Enhanced Vegetation Index (EVI), explaining approximately 62% of the variation. A decrease in the number of asthma care visits was observed, similar to the trend of PM₁₀ reduction in the residential area and the increase in the greenness of the blocking forest. The influx of PM into the city, primarily driven by prevailing northwesterly winds, may have been mitigated by the growing blocking forest, contributing to a reduction in asthma-related medical visits among urban residents. In particular, since the onset of the COVID-19 pandemic in 2020, the increase in the PM_2.5/PM₁₀ ratio in residential areas has become more closely linked to the increase in asthma-related medical visits. It suggests another PM_2.5 emission source in the residential area. The number of asthma care visits among children (under 11) and the elderly (over 65) exhibited a strong positive correlation with PM₁₀ levels and a negative correlation with the Normalized Difference Vegetation Index (NDVI). This suggests a link between air quality improvement from the greenness of blocking forests with their capacity to capture PM and respiratory health outcomes, especially for the vulnerable groups to asthma. These findings highlight the need to manage pollutant sources such as transportation and the heating system in residential areas beyond industrial emissions as the point pollution source. The management policies have to focus on protecting vulnerable populations, such as children and the elderly, by implementing small-sized urban forests to adsorb the PM_2.5 within the city and establishing blocking forests to prevent PM₁₀ near the industrial complex. Full article

Background/Objectives: This study aimed to assess and compare the rates of medication error (ME) using the PediSTAT application compared to the conventional method of calculating the correct dose and determining the appropriate route of medication administration for common pediatric emergencies. Methods: A prospective cross-sectional study design was used for the study. Data were collected using a questionnaire that was distributed to certified paramedics holding a bachelor’s degrees or higher and working in Riyadh City, Saudi Arabia. Alternate simple random sampling was used to recruit the participants into two groups using the same questionnaire: the PediSTAT group and the conventional method group. The questionnaire contained four pediatric emergency vignettes: cardiac arrest, asthma exacerbation, seizures, and hypoglycemia. Results: A total of 63 participants agreed to the study. Almost 80% of them were males, 81% held bachelor’s degrees, and 87% were certified in pediatric resuscitation courses. The findings of the study showed that the use of the PediSTAT application increased accuracy and reduced the risk of ME for common pediatric emergencies. This was shown to be statistically significant for asthma medication dose (p-value < 0.001, 95% CI 0.034–0.352), midazolam dose (p-value = 0.012, 95% CI 0.030–0.764), and hypoglycemia medication dose (p-value < 0.001, 95% CI 0.046, 0.452). Conclusions: The study findings supported the use of standardized precalculated applications such as PediSTAT, which was shown to reduce the risk of ME in prehospital care for pediatric emergencies. Full article

Asthma remains a prevalent chronic condition, impacting millions globally and presenting significant clinical and economic challenges. This study develops a predictive model for asthma outcomes, leveraging automated machine learning (AutoML) and explainable AI (XAI) to balance high predictive accuracy with interpretability. Using a comprehensive dataset of demographic, clinical, and respiratory function data, we employed AutoGluon to automate model selection, optimization, and ensembling, resulting in a model with 98.99% accuracy and a 0.9996 ROC-AUC score. SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-Agnostic Explanations) were applied to provide both global and local interpretability, ensuring that clinicians can trust and understand model predictions. Additionally, counterfactual analysis enabled hypothetical scenario exploration, supporting personalized asthma management by allowing clinicians to assess potential interventions for individual patient risk profiles. To facilitate clinical adoption, a Streamlit v1.41.0 application was developed for real-time access to predictions and interpretability. This study addresses key gaps in asthma prediction, notably in model transparency and generalizability, while providing a practical tool for enhancing personalized care. Future research could expand the validation across diverse patient populations to reinforce the model’s robustness in broader clinical environments. Full article

Background/Objectives: The objective of this study was to provide real-world data on prognostic factors in children with severe eosinophilic asthma and to assess biomarkers of outcome. Methods: Fifty-nine children (aged 6–17 years) were included in a prospective cohort attended in a Severe Asthma Unit of a tertiary care teaching hospital in Badalona (Barcelona, Spain) and visited at baseline and at 1-year follow-up. Study variables included asthma control using the Asthma Control Test (ACT), forced expiratory volume in one second (FEV₁), exacerbation episodes, fractional exhaled nitric oxide (FeNO), and inflammatory biomarkers (blood tests, sputum cells, immunoallergic tests, and levels of cytokines and effector cells in blood and sputum). Results: There were 36 boys and 23 girls, with a mean (SD) age of 11.9 (2.8) years. Uncontrolled severe asthma was diagnosed in 83.1% of cases, with poor symptom control (ACT score < 20) in 52.5%, obstructive pattern (FEV₁ < 80% predicted) in 35.6%, and more than one exacerbation in the previous year in 30.5%. The mean duration of asthma was 9.2 (3.6) years. Positive prick tests were recorded in 55 patients, with polysensitization in 6. The mean percentage of sputum eosinophils was 2.5% (3.1%), and the mean eosinophil blood count 543.4 (427.7) cells/µL. Ten patients (32%) showed sputum eosinophilia (>3% eosinophils). Sputum eosinophils did not correlate with blood eosinophils, FeNO, and serum periostin. At 12 months, 13 (22%) children had uncontrolled asthma and 46 (78%) had controlled asthma. Variables significantly associated with uncontrolled asthma were duration of asthma (OR = 1.23, 95% CI 1.01–1.49, p = 0.04) and an ACT score < 20 (OR = 0.80, 95% CI 0.69–0.93, p = 0.004). Lower serum levels of IL-9 appeared to be related with uncontrolled asthma, but statistical significance was not reached. Conclusions: Pediatric severe eosinophilic asthma showed a predominant allergic phenotype with symptomatic disease as a main contributor of uncontrolled asthma at 1 year. Predictive biomarkers of outcome were not identified. Further studies are needed to confirm the present findings especially considering additional variables for a better phenotypic characterization of severe eosinophilic asthma in children and to study in-depth the role of inflammatory biomarkers. Full article