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Asthma-I: Introduction

Asthma-I: Introduction

Asthma is a chronic respiratory ailment that requires careful management due to its varying symptoms and influencing factors. It is characterized by airway inflammation, bronchial hyperresponsiveness, and reversible airflow obstruction, leading to symptoms like wheezing, shortness of breath, chest tightness, and coughing. The symptom frequency and intensity may vary considerably over time. It is also linked to immune system responses to allergens and irritants, highlighting the complex...

Asthma-IV: Diagnostic and Management

Asthma-IV: Diagnostic and Management

The diagnosis and management of asthma are comprehensive, encompassing clinical assessments, lung function tests, and pharmacological interventions. Here's an overview:
Clinical Assessment for Asthma:
This is the first step in diagnosing and managing asthma. It includes:

Asthma-II: Pathophysiology and Classification

Asthma-II: Pathophysiology and Classification

Asthma is a prevalent chronic respiratory condition marked by inflammation and hyperresponsiveness of the airways. Its pathophysiology involves complex interactions among inflammatory pathways, immune responses, and neural mechanisms.
Additionally, environmental and genetic factors play crucial roles in determining an individual's susceptibility to asthma and the severity of their condition.
Critical processes in asthma pathophysiology include:

Asthma: Pathogenesis and Management

Asthma: Pathogenesis and Management

Asthma is a chronic pulmonary condition involving inflammation of the airways, hyper-reactivity, and reversible obstruction of the airways. This condition can significantly impact a person's quality of life, making breathing difficult and leading to distressing symptoms.
Asthma is classified as allergic and non-allergic. Allergens such as dust mites, pollen, and pet dander trigger allergic asthma, while factors like cold air, intense emotions, or exercise can induce non-allergic asthma.

Asthma-IV: Nursing Management

Asthma-IV: Nursing Management

The nursing management of asthma is a comprehensive approach that relies heavily on the expertise and dedication of healthcare professionals. It involves thorough assessment, accurate diagnosis, strategic planning, effective implementation, and diligent evaluation. By meticulously following this step-by-step process, healthcare professionals play a crucial role in providing the best possible care and treatment for patients with asthma, enhancing their overall health and well-being.
First, in...

Asthma-III: Symptoms and Complications

Asthma-III: Symptoms and Complications

Asthma, a common chronic respiratory condition, is classified considering the frequency and severity of symptoms alongside lung function impairment. Understanding this classification is essential for appropriate treatment and management. Here's a detailed look at the classification of asthma and its clinical features and complications:
Classification of Asthma

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A Reversible, Non-invasive Method for Airway Resistance Measurements and Bronchoalveolar Lavage Fluid Sampling in Mice

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Published on: April 13, 2010

Early Prediction of Asthma.

Sergio de Jesus Romero-Tapia¹, José Raúl Becerril-Negrete², Jose A Castro-Rodriguez³

¹Health Sciences Academic Division (DACS), Juarez Autonomous University of Tabasco (UJAT), Villahermosa 86040, Mexico.

Journal of Clinical Medicine

|August 26, 2023

Summary

Early asthma prediction in children is crucial. This review summarizes key factors, including lung function, allergies, medical history, and epigenetic markers like DNA methylation, to identify high-risk children using various prediction models.

Keywords:

asthma biomarkers epigenetics machine learning predictive models

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A Reversible, Non-invasive Method for Airway Resistance Measurements and Bronchoalveolar Lavage Fluid Sampling in Mice

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Published on: April 13, 2010

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Published on: May 14, 2012

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Published on: August 25, 2020

Area of Science:

Pediatric Pulmonology
Allergy and Immunology
Genetics and Epigenetics

Background:

Asthma in children presents with variable clinical manifestations and diverse underlying mechanisms.
Early identification of children at high risk for developing asthma is essential for timely intervention.
Asthma onset typically occurs within the first five years of life, necessitating robust prediction models.

Purpose of the Study:

To review and summarize predictive factors for childhood asthma.
To highlight epigenetic factors influencing asthma risk and progression.
To compare various asthma prediction tools, including machine learning approaches.

Main Methods:

Literature review focusing on predictive factors for childhood asthma.
Analysis of clinical data, including lung function, allergic comorbidities, and medical history.
Examination of epigenetic mechanisms such as DNA methylation, microRNA expression, and histone modification.
Evaluation of machine learning models for asthma prediction.

Main Results:

Lung function, allergic comorbidity, and medical history are significant predictors of asthma course.
Epigenetic factors including DNA methylation, microRNA expression, and histone modifications play a role in asthma risk.
Various prediction tools, including advanced machine learning algorithms, have been developed and show promise.

Conclusions:

Accurate early prediction of childhood asthma is achievable through comprehensive assessment of clinical, historical, and molecular data.
Epigenetic biomarkers offer novel avenues for identifying children at risk of developing asthma.
Integrating diverse predictive factors and utilizing advanced computational tools can improve asthma management strategies.