Pediatric allergy and immunology in Spain

Interpretable machine learning for allergic rhinitis prediction among preschool children in Urumqi, China

This study aimed to investigate the advantages and applications of machine learning models in predicting the risk of allergic rhinitis (AR) in children aged 2-8, compared to traditional logistic regression. The study analyzed questionnaire data from 7131 children aged 2-8, which was randomly divided into training, validation, and testing sets in a ratio of 55:15:30, repeated 100 times. Predictor variables included parental allergy, medical history during the child's first year (cfy), and early life environmental factors. The time of first onset of AR was restricted to after the age of 1 year to establish a clear temporal relationship between the predictor variables and the outcome. Feature engineering utilized the chi-square test and the Boruta algorithm, refining the dataset for analysis. The construction utilized Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting Tree (XGBoost) as the models. Model performance was evaluated using the area under the receiver operating characteristic curve (AUROC), and the optimal decision threshold was determined by weighing multiple metrics on the validation sets and reporting results on the testing set. Additionally, the strengths and limitations of the different models were comprehensively analyzed by stratifying gender, mode of birth, and age subgroups, as well as by varying the number of predictor variables. Furthermore, methods such as Shapley additive explanations (SHAP) and purity of node partition in Random Forest were employed to assess feature importance, along with exploring model stability through alterations in the number of features. In this study, 7131 children aged 2-8 were analyzed, with 524 (7.35%) diagnosed with AR, with an onset age ranging from 2 to 8 years. Optimal parameters were refined using the validation set, and a rigorous process of 100 random divisions and repeated training ensured robust evaluation of the models on the testing set. The model construction involved incorporating fourteen variables, including the history of allergy-related diseases during the child's first year, familial genetic factors, and early-life indoor environmental factors. The performance of LR, SVM, RF, and XGBoost on the unstratified data test set was 0.715 (standard deviation = 0.023), 0.723 (0.022), 0.747 (0.015), and 0.733 (0.019), respectively; the performance of each model was stable on the stratified data, and the RF performance was significantly better than that of LR (paired samples t-test: p < 0.001). Different techniques for evaluating the importance of features showed that the top5 variables were father or mother with AR, having older siblings, history of food allergy and father's educational level. Utilizing strategies like stratification and adjusting the number of features, this study constructed a random forest model that outperforms traditional logistic regression. Specifically designed to detect the occurrence of allergic rhinitis (AR) in children aged 2-8, the model incorporates parental allergic history and early life environmental factors. The selection of the optimal cut-off value was determined through a comprehensive evaluation strategy. Additionally, we identified the top 5 crucial features that greatly influence the model's performance. This study serves as a valuable reference for implementing machine learning-based AR prediction in pediatric populations.

Analysis of Multimorbidity of Moderate to Severe Allergic Rhinitis in Children: A Real-World Study

INTRODUCTION

Allergic rhinitis (AR) in children is associated with various comorbidities, posing challenges for treatment and management. There have been few investigations of these multimorbidities in Chinese children with AR. Here, we investigated the prevalence of multimorbidities in children with moderate to severe AR and analyzed the influencing factors using real-world data.

METHODS

In total, 600 children who visited the outpatient clinic of our hospital and were diagnosed with moderate-severe AR were prospectively enrolled. All children underwent allergen detection and electronic nasopharyngoscopy. Parents or guardians completed a questionnaire that included age, sex, mode of delivery, feeding pattern, and familial history of allergy. The multimorbidities investigated included atopic dermatitis (AD), asthma, allergic conjunctivitis (AC), chronic rhinosinusitis (CRS), adenoid hypertrophy (AH), tonsil hypertrophy (TH), recurrent epistaxis, and recurrent respiratory tract infections (RRTIs).

RESULTS

The AR multimorbidities reported in children were as follows: recurrent epistaxis (46.5%), AC (46.3%), AD (40.7%), asthma (22.5%), RRIs (21.3%), CRS (20.5%), AH (19.7%), and TH (12.5%). In univariate logistic regression analysis, age (<6 years), birth mode, familial history of allergy, and single dust mite allergy were associated with AR multimorbidity (p < 0.05). Multivariate logistic regression revealed that a familial history of allergy was an independent risk factor for AC (odds ratio [OR] = 1.539, 95% confidence interval [CI]: 1.104-2.145) and AH (OR = 1.506, 95% CI: 1.000-2.267) (p < 0.05). Age (<6 years) was independently associated with the risk of AD (OR = 1.405, 95% CI: 1.003-1.969) and RRTIs (OR = 1.869, 95% CI: 1.250-2.793) (p < 0.05), cesarean section with AR and CRS risk (OR = 1.678, 95% CI: 1.100-2.561), and single dust mite allergy with asthma (OR = 1.590, 95% CI: 1.040-2.432) and CRS (OR = 1.600, 95% CI: 1.018-2.515) risk (p < 0.05). Further, non-dust mite allergy was independently associated with AR and CRS (OR = 2.056, 95% CI: 1.084-3.899).

CONCLUSION

AR was found to be accompanied by different comorbidities, including both allergic and non-allergic comorbidities, complicating disease treatment. These findings demonstrated that age (<6 years), familial history of allergy, types of allergens, and cesarean section were risk factors for different multimorbidities associated with AR.

Allergic Rhinitis: A Clinical and Pathophysiological Overview

Allergic rhinitis (AR) represents a global health concern where it affects approximately 400 million people worldwide. The prevalence of AR has increased over the years along with increased urbanization and environmental pollutants thought to be some of the leading causes of the disease. Understanding the pathophysiology of AR is crucial in the development of novel therapies to treat this incurable disease that often comorbids with other airway diseases. Hence in this mini review, we summarize the well-established yet vital aspects of AR. These include the epidemiology, clinical and laboratory diagnostic criteria, AR in pediatrics, pathophysiology of AR, Th2 responses in the disease, as well as pharmacological and immunomodulating therapies for AR patients.

Harmonizing allergy care-integrated care pathways and multidisciplinary approaches

There is a wide time gap between the publication of evidence and the application of new knowledge into routine clinical practice. The consequence is sub-optimal outcomes, particularly concerning for long-term relapsing/remitting conditions such as allergic diseases. In response, there has been a proliferation of published guidelines which systematically review evidence for the gold-standard management of most allergic disorders. However, this has not necessarily been followed by improved outcomes, partly due to a lack of coordination across the patient pathway. This has become known as the "second translational gap". A proposed solution is the development and implementation of integrated care pathways (ICPs) to optimize patient outcomes, with the notion that evidence-based medicine requires evidence-based implementation. ICP implementation is shown to improve short-term outcomes for acute conditions and routine surgery, including reduced length of hospital stay, improved documentation and improved patient safety. However, this improvement is not reflected in patient experience or patient-centered functional outcomes. The implementation of life-long, cost-effective interventions within comprehensive pathways requires a deep appreciation for complexity within allergy care. We promote an evidence-based methodology for the implementation of ICPs for allergic disorders in which all stakeholders in allergy care are positioned equally and encouraged to contribute, particularly patients and their caregivers. This evidence-based process commences with scoping the unmet needs, followed by stakeholder mapping. All stakeholders are invited to meetings to develop a common vision and mission through the generation of action/effect diagrams which helps build concordance across the agencies. Dividing the interventions into achievable steps and reviewing with plan/do/study/act cycles will gradually modify the pathway to achieve the best outcomes. While the management guidelines provide the core knowledge, the key component of implementation involves education, training, and support of all healthcare professionals (HCPs), patients and their caregivers. The pathways should define the level of competence required for each clinical task. It may be useful to leave the setting of care delivery or the specific HCP involved undefined to account for variable patterns of health service delivery as well as local socioeconomic, ethnic, environmental, and political imperatives. In all cases, where competence is exceeded, it is necessary to refer to the next stage in the pathway. The success and sustainability of ICPs would ideally be judged by patient experience, health outcomes, and health economics. We provide examples of successful programs, most notably from Finland, but recommend that further research is required in diverse settings to optimize outcomes worldwide.

Analysis of the impact of allergic rhinitis on the children with sleep disordered breathing

OBJECTIVES

We assessed the influence of allergic rhinitis (AR) on sleep disordered breathing (SDB) in children with adenotonsillar hypertrophy (ATH), and compared sleep quality and polysomnographic data in habitually snoring children with or without AR.

METHODS

Children with snoring resulting from adenoid/tonsils hypertrophy were recruited between Jan 1st, 2018 and Jun 30th, 2018. The exclusion criteria were congenital disorders, metabolic disorders, neurological disorders and pulmonary diseases, such as, asthma etc. Overnight polysomnography (PSG) and Sleep Questionnaire (SQ) were assessed on each participant to identify children with obstructive sleep apnea (OSA). Cross-sectional study design was used to examine PSG and SQ data. The diagnosis of AR was based upon history of allergies and positive clinical examinations, then confirmed by allergen test. Participants were categorized into four groups (AR and Non-OSA group; AR and OSA group; Non-AR and Non-OSA group; Non-AR and OSA group). Non-parametric rank sum test was used for statistical analysis.

RESULTS

Six hundred and sixty children (age between 3yrs and 14yrs) with SDB were enrolled in the study (mean age 6.7 ± 2.1yrs, 67.4% male). The number of children diagnosed with OSA was 495 (74.3%). The prevalence of AR among all participating SDB children was 25.8%, and AR with OSA was19.4%. The behavioral problems scores in SQ showed significant difference among SDB children with AR (P<.0001). No difference was observed in the OAHI (obstructive apnea-hypopnea index) and AHI (apnea-hypopnea index) between the groups of children with and without AR regardless whether OSA was coexisting. The percentage of time spent in the rapid eye movement (REM) sleep stage was shortened among children with AR without OSA (P = 0.031), however, the percentage of time spent in the REM sleep stage was not different among children with OSA (P = 0.98). The total sleep time was shorter among children with AR (OSA P = 0.02; without OSA P = 0.03).

CONCLUSIONS

Despite the high prevalence of AR in patients with SDB, AR is not an aggravating factor for the severity of AHI. High risk behavioral problems link to SDB with AR. AR is associated with shortened REM sleep stage in children with SDB without sleep apnea, and shortened total sleep time in children with SDB.

Multimorbidities of Pediatric Allergic Rhinitis

PURPOSE OF REVIEW

Most children and adolescents with allergic rhinitis (AR) present extra-nasal multimorbid conditions, including conjunctivitis, asthma, atopic dermatitis, rhinosinusitis, or seromucous otitis. Additionally, they may present nasal obstructive disorders, such as septal deformity, turbinate enlargement, and adenoidal hyperplasia, which worsen nasal symptoms, especially nasal obstruction. This is a narrative review on the current state of the concomitant presence of AR and one or more multimorbidities.

RECENT FINDINGS

The presence of AR and one or more accompanying multimorbidities is associated to a higher severity and duration of the disease, a negative impact on quality of life, with worse control and lack of improvement with medical treatment. Therefore, AR needs to be managed with a multidisciplinary collaborative approach. Pediatric AR needs to be considered in the context of a systemic disease, which requires a coordinated therapeutic strategy.

Prevalence of atopic dermatitis in infants during the first six months of life: authors' observations

Introduction

Atopic dermatitis (AD) is a frequent chronic skin disease in infants. It creates great difficulties, both diagnostic and therapeutic.

Aim

To assess the prevalence of atopic dermatitis in infants during the first 6 months of life.

Material and methods

The analysis comprised 2256 children at the age of not more than 6 months, treated at the 2^nd Department of Paediatrics and Allergology of the Polish Mother's Memorial Hospital in Lodz, Poland, during seven years. Out of all the patients, children with cutaneous changes were isolated, and the location, type and aetiology of changes were assessed.

Results

Dermal changes were diagnosed in 471 children, including 391 (17.3% of all the patients) with atopic dermatitis. Out of the children with AD, IgE-dependent allergy was identified in 39.9%. Cow's milk protein was the most frequent sensitising allergen. In 71.6% of the infants, cutaneous changes were disseminated and involved at least two areas of the body. All of them were strongly itching. An applied elimination diet, together with anti-allergic medications in some of the children, provided a clear clinical improvement.

Conclusions

Performed studies demonstrated the prevalence of atopic dermatitis in 17.3% of examined children. The changes in children with AD were disseminated, what was confirmed already at the infantile age. The obtained clinical improvement after the applied therapy indicates a relationship between the observed symptoms and allergic disease.

Long-term follow-up of de novo allergy in pediatric liver transplantation--10 yr experience of a single center

We conducted a study to clarify the incidence, clinical course, and risk factors of de novo allergies after liver transplantation. Ninety-three patients who had been followed longer than one yr and who had no previous allergy history were included. Forty-two patients (45.2%) developed de novo allergy. Of them, food allergy developed in 35 (37.6%). Respiratory allergy was observed in three (3.2%), and a patient (1.1%) had drug allergy. Fifty-two (55.9%) of the 93 patients developed eosinophilia. The median age of patients with de novo allergy was 15 months (IR 11.3-20 months). De novo allergy developed five months after liver transplantation (IR 2.3-9.5 months) and lasted for 16 months (IR 8-34.5 months). Younger age at liver transplantation displayed statistically significant differences in development of allergy between allergy and non-allergy groups. Twenty-nine (69.0%) patients improved from allergy during the follow-up period. No patient with de novo gastrointestinal allergy progressed to any respiratory allergy such as asthma. Older age at transplantation, EBV non-risk, and CMV non-risk had statistical significance in allergy improvement. Younger age at transplant predisposes to the development of allergy, while improvement of allergy is achieved more in older age.