June 16, 2024

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FLAIR model: Interstitial lung disease risk prediction model

FLAIR model: Interstitial lung disease risk prediction model

FLAIR model: Interstitial lung disease risk prediction model.  Interstitial lung disease (ILD) is based on diffuse lung parenchyma, alveolitis and interstitial fibrosis as the basic pathological changes, with active dyspnea, diffuse shadows on X-ray chest radiographs, restrictive ventilation disorders, Diffusion function (DLCO) reduction and hypoxemia are the general term for clinical pathological entities composed of different types of disease groups with clinical manifestations.

ILD is usually not malignant, nor is it caused by a known infectious pathogen. Although the disease has an acute phase, the onset is often insidious, and the course of the disease is chronic. The body initially reacts to it as an inflammatory reaction in the lungs and alveolar walls, leading to alveolitis, and finally the inflammation will spread to the adjacent interstitium. Part and blood vessels eventually produce interstitial fibrosis, leading to scarring and destruction of lung tissue, reducing ventilation. Inflammation can also involve trachea and bronchiole, often accompanied by organizing pneumonia, which is also a manifestation of interstitial pneumonia .

FLAIR model: Interstitial lung disease risk prediction model 

On May 16, 2020, the internationally renowned medical journal “Chest” (Impact Factor 9.656″ published online the latest research results of Professor Bao Chunde’s research team from the Department of Rheumatology, Renji Hospital, Shanghai Jiaotong University School of Medicine: Amyopathy-related dermatomyositis Qualitative lung disease death risk prediction model (FLAIR model). This is the first international model for predicting the death risk of this disease. Its establishment will not only help early identification of high-risk patients, but more importantly, it can be based on This risk stratification provides patients with precise treatment plans, which is conducive to greatly reducing the mortality of such patients.

FLAIR model: Interstitial lung disease risk prediction model

According to Professor Bao Chunde, amyopathic dermatomyositis (ADM) is a rare autoimmune disease with a very high fatality rate, which occurs in East Asian populations. In addition to the anti-melanoma differentiation-related gene (MDA5) antibody, which is a serological marker, patients usually present with characteristic skin rash, relatively mild myopathy, and rapidly progressing interstitial lung disease. When ADM patients are accompanied by interstitial Lung disease (ILD) often dies from rapidly progressive interstitial lung disease and respiratory failure within one year of onset, and the mortality rate within one year is as high as 50%-60%.

Bao Chunde’s team has been committed to clinical and basic research on the disease for many years. The prospective observational cohort study initiated by him has continuously collected ADM-ILD patients and followed up closely since 2012. After 7 years before and after the study, a total of 207 ADM-ILD patients were enrolled, with a follow-up time of 78 months, which is the largest ADM-ILD study cohort that has been reported in the world.

Bao Chunde pointed out that the establishment of the model is conducive to identifying those high-risk groups, and is conducive to international colleagues to jointly understand the disease and its outcome, and actively intervene and treat it. The FLAIR model created by the research team includes the following indicators:

  • F, Ferritin (Ferritin);
  • L, lactate dehydrogenase (lactate dehydrogenase);
  • A, antibody, anti-MDA5 antibody;
  • I, image, HRCT imaging score;
  • R, Rapidly progressive interstitial lung disease (RP-ILD).

Scores from 0-4 are divided into low-risk group, 5-9 are divided into intermediate-risk group, and 10-13 are divided into high-risk group. We use Index of Prediction Accuracy (IPA) to verify the accuracy of the model. This score will predict and stratify the severity of the disease and the risk of death, and help guide further treatment options. In particular, it helps clinicians identify high-risk patients so that intensive treatment can be carried out as soon as possible to improve overall survival.






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