Types of chest infections

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Common Types of Chest Infections

Chest infections are a broad group of diseases that affect the lungs and surrounding structures. The most common types include pneumonia, tuberculosis, COVID-19, fibrosis, and bronchiectasis. Other notable infections are caused by viruses, bacteria, or fungi, and can present as acute or chronic conditions. In children, recurrent chest infections may be due to viral infections, asthma, cystic fibrosis, immunodeficiency syndromes, or congenital abnormalities of the respiratory tract. In some cases, lung damage from a single severe pneumonia or inhalation of foreign material can also lead to repeated infections Ali2023Couriel2002Rehman2021.

Acute vs. Chronic Chest Infections

Chest infections can be classified as acute or chronic. Acute infections, such as pneumonia and COVID-19, develop quickly and can be severe, especially in vulnerable populations. Chronic chest infections, on the other hand, may persist over time and often involve the soft tissue, cartilage, or bone of the chest wall. Chronic infections can present as localized pain, masses, or draining sinuses, and are generally less severe than acute necrotizing infections .

Necrotizing and Non-Necrotizing Chest Wall Infections

Necrotizing soft tissue infections of the chest wall are rare but extremely serious. They often occur as complications of invasive procedures, such as tube thoracostomy for empyema or esophageal operations. These infections are highly lethal and require urgent surgical intervention. Non-necrotizing chronic chest wall infections, while still serious, are associated with lower morbidity and can often be managed with antimicrobial therapy and, in some cases, surgical resection Bergeron2017Urschel1997.

Diagnostic Approaches and Classification

Recent advances in medical imaging and artificial intelligence have improved the detection and classification of chest infections. Deep learning models using chest X-rays can now distinguish between multiple types of chest infections, including COVID-19, fibrosis, pneumonia, and tuberculosis, with high accuracy. Some models are capable of identifying up to 14 or 15 different types of chest infections, aiding clinicians in early and accurate diagnosis Ali2023Loura2022Rehman2021.

Risk Factors and Special Populations

Certain populations are at higher risk for developing chest infections. For example, patients who have suffered an acute stroke are more likely to develop chest infections, especially if they have risk factors such as mechanical ventilation, diabetes, pre-existing respiratory conditions, or atrial fibrillation. Monitoring these patients closely can help with early identification and treatment, improving outcomes .

Conclusion

Chest infections encompass a wide range of diseases, from common acute infections like pneumonia and COVID-19 to chronic and sometimes life-threatening conditions such as necrotizing soft tissue infections. Advances in diagnostic technology are improving detection and classification, while understanding risk factors and underlying causes is essential for effective management and prevention of complications Bergeron2017Ali2023Urschel1997+4 MORE.

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Most relevant research papers on this topic

Chronic Infections of the Chest Wall.

Chronic chest wall infections can be effectively managed with antimicrobial administration, wide surgical resection, or reconstruction.

2017·

27citations

·E. Bergeron et al.

Thoracic surgery clinics·

DOI

A CNN-Based Chest Infection Diagnostic Model: A Multistage Multiclass Isolated and Developed Transfer Learning Framework

The developed multistage CNN model accurately detects and distinguishes chest infections, including COVID-19, fibrosis, pneumonia, and tuberculosis, with minimal training time compared to publically available pretrained models.

2023·

24citations

·M. U. Ali et al.

Int. J. Intell. Syst.·

DOI

Necrotizing soft tissue infections of the chest wall.

Necrotizing soft tissue infections of the chest wall are highly lethal and require urgent and aggressive debridement, with diagnostic delay and inadequate debridement often leading to treatment failure.

Systematic Review

1997·

52citations

·J. Urschel et al.

The Annals of thoracic surgery·

DOI

Assessment of the child with recurrent chest infections.

Early and accurate diagnosis of recurrent chest infections in children is crucial for optimal treatment and minimizing lung damage.

Highly Cited

2002·

82citations

·J. Couriel

British medical bulletin·

DOI

Risk factors for the development of chest infections in acute stroke: a systematic review

Modifiable risk factors for chest infections in acute stroke patients include mechanical ventilation, diabetes, pre-existing respiratory conditions, and atrial fibrillation.

Meta-Analysis

2018·

18citations

·C. Chapman et al.

Topics in Stroke Rehabilitation·

DOI

Employability of Deep Learning Tools and Techniques for an Early Detection and Diagnosis of Pulmonary Infection

Deep learning-based medical picture classifiers can accurately identify 14 different chest infections from chest x-ray images, improving early detection and diagnosis of pulmonary infections.

2022·

1citation

·Sakshi Loura

International Journal of Research in Medical Sciences and Technology·

DOI

A Self-Activated CNN Approach for Multi-Class Chest-Related COVID-19 Detection

The proposed framework improves COVID-19 detection accuracy and increases predictability rates for other chest diseases using chest X-rays, outperforming other state-of-the-art models.

2021·

57citations

·Najam-ur Rehman et al.

Applied Sciences·

DOI

A Neutrosophic Set Approach on Chest X-rays for Automatic Lung Infection Detection

Using a neutrosophic set approach on chest X-rays, this study achieves a better accuracy of 97.33% in detecting different types of lung infections, such as viral and bacterial pneumonia.

2023·

20citations

·J. Sofia Jennifer et al.

Information Technology and Control·

DOI

The Link Between Chest Infections and Septicemia

Chest infections like pneumonia and bronchitis can lead to septicemia, which can be life-threatening, requiring early detection and treatment.

2021·

0citations

·Ahmed Alwazzan et al.

Futuristic Biotechnology·

DOI

Detection of pneumonia infection in lungs from chest X-ray images using deep convolutional neural network and content-based image retrieval techniques

The proposed Deep CNN model accurately detects pneumonia in lungs from chest X-ray images with 99.34% classification accuracy, outperforming state-of-the-art transfer learning techniques like AlexNet, VGG16Net, and InceptionNet.

2021·

66citations

·T. Rajasenbagam et al.

Journal of Ambient Intelligence and Humanized Computing·

DOI

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