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Annals of Allergy, Asthma & Immunology... Jun 2024Atopic dermatitis (AD) is one of the main risk factors for infants in the development of food allergy. Oral immunotherapy therapy (OIT) in early childhood has been... (Review)
Review
Atopic dermatitis (AD) is one of the main risk factors for infants in the development of food allergy. Oral immunotherapy therapy (OIT) in early childhood has been demonstrated to be highly effective and safe in preschoolers with and without AD, especially in young infants. Delays in initiation of OIT in infants and children due to uncontrolled AD risks expansion of the number of foods children develop allergy to via unnecessary avoidance of multiple foods. Parents and caregivers may attribute eczema flares to OIT doses, which physicians usually ascribe to non-food triggers such as weather changes, psychological stress, and infection. There is a lack of published literature confirming OIT as a trigger of AD flares, and the degree to which OIT may be associated with AD flares needs to be further studied. We describe eight case scenarios with varying degrees of AD flare before and during OIT. We propose management algorithms for children with pre-existing concurrent AD and food allergy who are being considered for starting OIT, and children with AD flares during OIT. Optimizing AD control strategies and providing adequate AD care education prior to starting OIT can reduce confusion for both parents and allergists if rashes arise during OIT, thus improving adherence to OIT.
PubMed: 38879162
DOI: 10.1016/j.anai.2024.05.022 -
Journal of Experimental & Clinical... Jun 2024Pancreatic ductal adenocarcinoma (PDAC) is the most lethal cancer with an aggressive metastatic phenotype and very poor clinical prognosis. Interestingly, a lower...
BACKGROUND
Pancreatic ductal adenocarcinoma (PDAC) is the most lethal cancer with an aggressive metastatic phenotype and very poor clinical prognosis. Interestingly, a lower occurrence of PDAC has been described in individuals with severe and long-standing asthma. Here we explored the potential link between PDAC and the glucocorticoid (GC) budesonide, a first-line therapy to treat asthma.
METHODS
We tested the effect of budesonide and the classical GCs on the morphology, proliferation, migration and invasiveness of patient-derived PDAC cells and pancreatic cancer cell lines, using 2D and 3D cultures in vitro. Furthermore, a xenograft model was used to investigate the effect of budesonide on PDAC tumor growth in vivo. Finally, we combined genome-wide transcriptome analysis with genetic and pharmacological approaches to explore the mechanisms underlying budesonide activities in the different environmental conditions.
RESULTS
We found that in 2D culture settings, high micromolar concentrations of budesonide reduced the mesenchymal invasive/migrating features of PDAC cells, without affecting proliferation or survival. This activity was specific and independent of the Glucocorticoid Receptor (GR). Conversely, in a more physiological 3D environment, low nanomolar concentrations of budesonide strongly reduced PDAC cell proliferation in a GR-dependent manner. Accordingly, we found that budesonide reduced PDAC tumor growth in vivo. Mechanistically, we demonstrated that the 3D environment drives the cells towards a general metabolic reprogramming involving protein, lipid, and energy metabolism (e.g., increased glycolysis dependency). This metabolic change sensitizes PDAC cells to the anti-proliferative effect of budesonide, which instead induces opposite changes (e.g., increased mitochondrial oxidative phosphorylation). Finally, we provide evidence that budesonide inhibits PDAC growth, at least in part, through the tumor suppressor CDKN1C/p57Kip2.
CONCLUSIONS
Collectively, our study reveals that the microenvironment influences the susceptibility of PDAC cells to GCs and provides unprecedented evidence for the anti-proliferative activity of budesonide on PDAC cells in 3D conditions, in vitro and in vivo. Our findings may explain, at least in part, the reason for the lower occurrence of pancreatic cancer in asthmatic patients and suggest a potential suitability of budesonide for clinical trials as a therapeutic approach to fight pancreatic cancer.
Topics: Humans; Budesonide; Mice; Pancreatic Neoplasms; Energy Metabolism; Cell Proliferation; Animals; Cell Line, Tumor; Carcinoma, Pancreatic Ductal; Xenograft Model Antitumor Assays; Cell Movement
PubMed: 38877560
DOI: 10.1186/s13046-024-03072-1 -
BMC Health Services Research Jun 2024To reduce the impact of chronic diseases (cardiovascular disease, diabetes mellitus type 2, and chronic lung disease (asthma or chronic obstructive pulmonary disease...
BACKGROUND
To reduce the impact of chronic diseases (cardiovascular disease, diabetes mellitus type 2, and chronic lung disease (asthma or chronic obstructive pulmonary disease (COPD)), it is imperative that care is of high quality and suitable to patients' needs. Patients with intellectual disabilities (ID) differ from the average patient population in general practice because of their limitations in adaptive behaviour and intellectual functioning, and concomitant difficulties recognising and reacting to disease symptoms, proactively searching health information, and independently managing diseases effectively. Because of these differences, information on their care needs is essential for suitable chronic disease management (CDM). Inadequate recognition of the care needs of this vulnerable population may hamper the harmonisation of evidence-based and person-centred care, compounded by issues such as stigma, misconceptions, and diagnostic overshadowing. This study therefore aimed to explore the needs of patients with ID from perspectives of both patients and of healthcare providers (HCPs) in the context of CDM in general practice.
METHODS
This qualitative study recruited patients with ID for face-to-face individual interviews and HCPs for focus groups. With the Chronic Care Model as the underlying framework, semi-structured interviews and focus-group guides were defined to explore patients' care needs and HCPs' perspectives. All interviews and focus groups were audio-recorded and transcribed verbatim. Using Atlas.ti software, data were analysed using reflexive thematic analysis.
RESULTS
Between June and September 2022, 14 patients with ID and cardiovascular disease, diabetes mellitus type 2, and/or asthma/COPD were interviewed; and 32 general practitioners and practice nurses participated in seven focus groups. We identified six care needs underpinning suitable CDM: trusting relationship between patient and HCP; clear expectations about the CDM process; support in disease management; directive decision-making; support in healthy lifestyle; accessible medical information.
CONCLUSIONS
This vulnerable patient population has complex care needs that must be acknowledged for suitable CDM. Although HCPs largely recognise these needs, organisational factors and lack of training or experience with patients with ID hamper HCPs' ability to fully adjust care provision to these needs. Access to, and knowledge of, easy-language information on chronic diseases and communication guidelines could aid HCPs to facilitate patients in managing their diseases more adequately.
Topics: Humans; Chronic Disease; Male; Netherlands; Female; Intellectual Disability; Middle Aged; General Practice; Qualitative Research; Focus Groups; Adult; Aged; Health Services Needs and Demand; Needs Assessment; Interviews as Topic; Pulmonary Disease, Chronic Obstructive; Diabetes Mellitus, Type 2; Asthma
PubMed: 38877510
DOI: 10.1186/s12913-024-11155-0 -
Spatial and Spatio-temporal Epidemiology Jun 2024This paper contributes to the field by addressing the critical issue of enhancing the spatial and temporal resolution of health data. Although Bayesian methods are...
This paper contributes to the field by addressing the critical issue of enhancing the spatial and temporal resolution of health data. Although Bayesian methods are frequently employed to address this challenge in various disciplines, the application of Bayesian spatio-temporal models to burden of disease (BOD) studies remains limited. Our novelty lies in the exploration of two existing Bayesian models that we show to be applicable to a wide range of BOD data, including mortality and prevalence, thereby providing evidence to support the adoption of Bayesian modeling in full BOD studies in the future. We illustrate the benefits of Bayesian modeling with an Australian case study involving asthma and coronary heart disease. Our results showcase the effectiveness of Bayesian approaches in increasing the number of small areas for which results are available and improving the reliability and stability of the results compared to using data directly from surveys or administrative sources.
Topics: Bayes Theorem; Humans; Australia; Asthma; Spatio-Temporal Analysis; Cost of Illness; Coronary Disease; Prevalence; Male; Female; Models, Statistical
PubMed: 38876559
DOI: 10.1016/j.sste.2024.100663 -
Environment International Jun 2024Previous studies of air pollution and respiratory disease often relied on aggregated or lagged acute respiratory disease outcome measures, such as emergency department...
Previous studies of air pollution and respiratory disease often relied on aggregated or lagged acute respiratory disease outcome measures, such as emergency department (ED) visits or hospitalizations, which may lack temporal and spatial resolution. This study investigated the association between daily air pollution exposure and respiratory symptoms among participants with asthma and chronic obstructive pulmonary disease (COPD), using a unique dataset passively collected by digital sensors monitoring inhaled medication use. The aggregated dataset comprised 456,779 short-acting beta-agonist (SABA) puffs across 3,386 people with asthma or COPD, between 2012 and 2019, across the state of California. Each rescue use was assigned space-time air pollution values of nitrogen dioxide (NO), fine particulate matter with diameter ≤ 2.5 µm (PM) and ozone (O), derived from highly spatially resolved air pollution surfaces generated for the state of California. Statistical analyses were conducted using linear mixed models and random forest machine learning. Results indicate that daily air pollution exposure is positively associated with an increase in daily SABA use, for individual pollutants and simultaneous exposure to multiple pollutants. The advanced linear mixed model found that a 10-ppb increase in NO, a 10 μg m increase in PM, and a 30-ppb increase in O were respectively associated with incidence rate ratios of SABA use of 1.025 (95 % CI: 1.013-1.038), 1.054 (95 % CI: 1.041-1.068), and 1.161 (95 % CI: 1.127-1.233), equivalent to a respective 2.5 %, 5.4 % and 16 % increase in SABA puffs over the mean. The random forest machine learning approach showed similar results. This study highlights the potential of digital health sensors to provide valuable insights into the daily health impacts of environmental exposures, offering a novel approach to epidemiological research that goes beyond residential address. Further investigation is warranted to explore potential causal relationships and to inform public health strategies for respiratory disease management.
PubMed: 38875815
DOI: 10.1016/j.envint.2024.108810 -
Immunobiology Jun 2024Recent evidence has shown that T cell exhaustion is implicated in Allergen-specific Immunotherapy (AIT). However, how T cell exhaustion plays a role in AIT is far from...
Recent evidence has shown that T cell exhaustion is implicated in Allergen-specific Immunotherapy (AIT). However, how T cell exhaustion plays a role in AIT is far from clear. Our study aimed to investigate T cell exhaustion associated with allergen exposure during AIT in mice. Ovalbumin (OVA) - sensitized C57BL/6J asthma mouse and AIT mouse models were constructed. Quantitative real-time PCR (qRTPCR) and flow cytometry were used to monitor the occurrence of local and systemic CD4 T cells and Th2T cells exhaustion in OVA-sensitized mice. The inhibitory surface marker programmed cell death protein 1 (PD-1) on CD4 T cells and Th2T cells was significantly upregulated in AIT mice compared with asthmatic and control mice. The level of PD-1 on the surface of CD4T cells of asthma mice was significantly higher than that of control mice. The inhibitory surface marker cytotoxic T lymphocyte-associated protein 4 (CTLA-4) on CD4 T cells and Th2T cells showed no significant difference between the AIT, asthma and control mice. Collectively, our study indicated that the expression of PD-1 on CD4 T cells and Th2T cells was increased in AIT. Allergen exposure promotes the expression of PD-1 on the surface of CD4 T cells. T cell exhaustion plays an important role in AIT.
PubMed: 38875763
DOI: 10.1016/j.imbio.2024.152824 -
JMIR Biomedical Engineering Oct 2023Accurate and portable respiratory parameter measurements are critical for properly managing chronic obstructive pulmonary diseases (COPDs) such as asthma or sleep apnea,...
BACKGROUND
Accurate and portable respiratory parameter measurements are critical for properly managing chronic obstructive pulmonary diseases (COPDs) such as asthma or sleep apnea, as well as controlling ventilation for patients in intensive care units, during surgical procedures, or when using a positive airway pressure device for sleep apnea.
OBJECTIVE
The purpose of this research is to develop a new nonprescription portable measurement device that utilizes relative humidity sensors (RHS) to accurately measure key respiratory parameters at a cost that is approximately 10 times less than the industry standard.
METHODS
We present the development, implementation, and assessment of a wearable respiratory measurement device using the commercial Bosch BME280 RHS. In the initial stage, the RHS was connected to the pneumotach (PNT) gold standard device via its external connector to gather breathing metrics. Data collection was facilitated using the Arduino platform with a Bluetooth Low Energy connection, and all measurements were taken in real time without any additional data processing. The device's efficacy was tested with 7 participants (5 men and 2 women), all in good health. In the subsequent phase, we specifically focused on comparing breathing cycle and respiratory rate measurements and determining the tidal volume by calculating the region between inhalation and exhalation peaks. Each participant's data were recorded over a span of 15 minutes. After the experiment, detailed statistical analysis was conducted using ANOVA and Bland-Altman to examine the accuracy and efficiency of our wearable device compared with the traditional methods.
RESULTS
The perfused air measured with the respiratory monitor enables clinicians to evaluate the absolute value of the tidal volume during ventilation of a patient. In contrast, directly connecting our RHS device to the surgical mask facilitates continuous lung volume monitoring. The results of the 1-way ANOVA showed high P values of .68 for respiratory volume and .89 for respiratory rate, which indicate that the group averages with the PNT standard are equivalent to those with our RHS platform, within the error margins of a typical instrument. Furthermore, analysis utilizing the Bland-Altman statistical method revealed a small bias of 0.03 with limits of agreement (LoAs) of -0.25 and 0.33. The RR bias was 0.018, and the LoAs were -1.89 and 1.89.
CONCLUSIONS
Based on the encouraging results, we conclude that our proposed design can be a viable, low-cost wearable medical device for pulmonary parametric measurement to prevent and predict the progression of pulmonary diseases. We believe that this will encourage the research community to investigate the application of RHS for monitoring the pulmonary health of individuals.
PubMed: 38875670
DOI: 10.2196/47146 -
JMIR AI Dec 2023An early warning tool to predict attacks could enhance asthma management and reduce the likelihood of serious consequences. Electronic health records (EHRs) providing... (Review)
Review
BACKGROUND
An early warning tool to predict attacks could enhance asthma management and reduce the likelihood of serious consequences. Electronic health records (EHRs) providing access to historical data about patients with asthma coupled with machine learning (ML) provide an opportunity to develop such a tool. Several studies have developed ML-based tools to predict asthma attacks.
OBJECTIVE
This study aims to critically evaluate ML-based models derived using EHRs for the prediction of asthma attacks.
METHODS
We systematically searched PubMed and Scopus (the search period was between January 1, 2012, and January 31, 2023) for papers meeting the following inclusion criteria: (1) used EHR data as the main data source, (2) used asthma attack as the outcome, and (3) compared ML-based prediction models' performance. We excluded non-English papers and nonresearch papers, such as commentary and systematic review papers. In addition, we also excluded papers that did not provide any details about the respective ML approach and its result, including protocol papers. The selected studies were then summarized across multiple dimensions including data preprocessing methods, ML algorithms, model validation, model explainability, and model implementation.
RESULTS
Overall, 17 papers were included at the end of the selection process. There was considerable heterogeneity in how asthma attacks were defined. Of the 17 studies, 8 (47%) studies used routinely collected data both from primary care and secondary care practices together. Extreme imbalanced data was a notable issue in most studies (13/17, 76%), but only 38% (5/13) of them explicitly dealt with it in their data preprocessing pipeline. The gradient boosting-based method was the best ML method in 59% (10/17) of the studies. Of the 17 studies, 14 (82%) studies used a model explanation method to identify the most important predictors. None of the studies followed the standard reporting guidelines, and none were prospectively validated.
CONCLUSIONS
Our review indicates that this research field is still underdeveloped, given the limited body of evidence, heterogeneity of methods, lack of external validation, and suboptimally reported models. We highlighted several technical challenges (class imbalance, external validation, model explanation, and adherence to reporting guidelines to aid reproducibility) that need to be addressed to make progress toward clinical adoption.
PubMed: 38875586
DOI: 10.2196/46717 -
The World Allergy Organization Journal Jun 2024Asthma has been suggested to be a risk factor for cardiovascular diseases (CVDs), although the evidence supporting this relationship is inconclusive. This study aimed to...
BACKGROUND
Asthma has been suggested to be a risk factor for cardiovascular diseases (CVDs), although the evidence supporting this relationship is inconclusive. This study aimed to explore the long-term associations between asthma and asthma exacerbations with the occurrence of cardiovascular diseases (CVDs) such as ischemic heart disease (IHD), heart failure (HF), and cerebral stroke, utilizing data from a nationwide cohort.
MATERIALS AND METHODS
This study utilized data from the Korean National Health Insurance Service-Health Screening Cohort database (2002-2015), including information on 111,316 asthma patients and an equal number of 1:1 matched control participants. A propensity score overlap-weighted Cox proportional hazards regression model was used to analyze the overlap-weighted hazard ratios (HRs) of asthma and exacerbated asthma for cardiovascular diseases (CVDs) within this cohort.
RESULTS
During the follow-up period, the incidence rate (IR) of IHD per 1000 person-years (PYs) was 7.82 in patients with asthma and 5.79 in controls. The IR of HF was 2.53 in asthmatic patients and 1.36 in controls. After adjustment for covariates, asthmatic patients exhibited 1.27-fold and 1.56-fold higher HRs for IHD (95% confidence interval (CI) = 1.23-1.37, P < 0.001) and HF (95% CI = 1.36-1.63, P < 0.001) than the controls, respectively. In addition, there was an increased HR for IHD and HF in the asthma exacerbation group compared with the nonexacerbated asthma group (adjusted HR, 1.29, 95% CI = 1.24-1.34, P < 0.001 for IHD and aHR 1.68, 95% CI = 1.58-1.79, P < 0.001 for HF). However, the occurrence of stroke was decreased in asthmatic patients compared with controls (aHR = 0.96, 95% CI = 0.93-0.99, P = 0.008).
CONCLUSIONS
Adults with asthma are more likely to develop CVDs. Additionally, severe asthma exacerbations are significantly associated with an increased occurrence of CVDs.
PubMed: 38873616
DOI: 10.1016/j.waojou.2024.100907 -
Frontiers in Pediatrics 2024Food allergy can often cause a significant burden on patients, families, and healthcare systems. The complexity of food allergy management requires a multidisciplinary... (Review)
Review
IMPORTANCE
Food allergy can often cause a significant burden on patients, families, and healthcare systems. The complexity of food allergy management requires a multidisciplinary approach involving different types of healthcare providers, including allergists, dieticians, psychologists, nurses, family practitioners and, of particular relevance for this article, pediatric primary caretakers. Pediatricians may be the first-line healthcare providers for food allergy: strategies for management and guideline adherence have been highlighted.
OBSERVATIONS
This review article summarizes the up-to-date recommendations on the role of pediatricians in the diagnosis, management, and prevention of IgE-mediated food allergy. Early introduction of allergenic foods like peanut is known to be of importance to reduce the development of peanut allergy in infants, and pediatricians are essential for educating and supporting parents in this decision. In scenarios of limited allergist availability, as is often the case among rural, Medicaid and minority populations, pediatricians can assist in the evaluation and management of food allergy, and provide action plans, education and counselling for patients and families.
CONCLUSIONS AND RELEVANCE
Pediatric primary caretakers play a key role in the diagnosis, management, and prevention of IgE-mediated food allergy. As more diagnostic tools and therapies in food allergy become available, the need for a multidisciplinary team is paramount to optimize patient care.
PubMed: 38873581
DOI: 10.3389/fped.2024.1373373