A new proposal for phenotypic classification and outcome assessment of dermatomyositis based on clinical manifestations and serological testing.

BACKGROUND: Dermatomyositis (DM) is an infrequent disease subgroup of idiopathic inflammatory myopathies characterized by distinct skin lesions. However, high heterogeneity makes clinical diagnosis and treatment of DM very challenging. OBJECTIVES: Unsupervised classification in DM patients and analysis of key factors related to clinical outcomes. METHODS: This retrospective study was conducted between 2017 and 2022 at the Department of Rheumatology, Xiangya Hospital, Central South University. 162 DM patients were enrolled for unsupervised hierarchical cluster analysis. In addition, we divided the clinical outcomes of DM patients into four subgroups: withdrawal, stabilization, aggravation, and death, and compared the clinical profiles amongst the subgroups. RESULTS: Out of 162 DM patients, three clusters were defined. Cluster 1 (n = 40) was mainly grouped by patients with prominent muscular involvement and mild Interstitial Lung Disease (ILD). Cluster 2 (n = 72) grouped patients with skin rash, anti-Melanoma Differentiation Associated protein 5 positive (anti-MDA5+), and Rapid Progressive Interstitial Lung Disease (RP-ILD). Cluster 3 (n = 50) grouped patients with the mildest symptoms. The proportion of death increased across the three clusters (cluster 3 < cluster 1 < cluster 2). STUDY LIMITATIONS: The number of cases was limited for the subsequent construction and validation of predictive models. We did not review all skin symptoms or pathological changes in detail. CONCLUSIONS: We reclassified DM into three clusters with different risks for poor outcome based on diverse clinical profiles. Clinical serological testing and cluster analysis are necessary to help clinicians evaluate patients during follow-up and conduct phenotype-based personalized care in DM.

Children's Interstitial and Diffuse Lung Disease. Progress and Future Horizons.

Children's interstitial and diffuse lung disease (chILD) is a term that encompasses a large and diverse group of rare pediatric diseases and disorders. Significant progress has been made over the last 2 decades in classification, clinical care, research, and organizational structure to enhance the care of children with these high-morbidity and -mortality diseases. New diseases have been defined clinically and genetically, classification systems developed and applied, organizations formed such as the chILD Research Network (chILDRN) and chILD Foundation, and basic and translational science expanded to focus on chILD diseases. Multidisciplinary collaborations and efforts to advance understanding and treatment of chILD have been extended worldwide. The future horizon holds great promise to expand scientific discoveries, collaborate more broadly, and bring new treatment to these children. An overview of key historical past developments, major clinical and research updates, and opportunities for the future in chILD is reviewed in this Perspective.

Childhood interstitial lung disease: A systematic review.

OBJECTIVES: Childhood interstitial lung disease (chILD) is a group of rare chronic and complex disorders of variable pathology. There has been no systematic review of published chILD research. This study aimed to describe chILD classification systems, epidemiology, morbidity, treatments, outcomes, and the impact of chILD on families and the burden on health services. METHODS: A systematic literature search for original studies on chILD was undertaken in the major biomedical databases to the end of December 2013. Epidemiological studies, case series and studies describing classification systems were included. Single case studies were excluded. RESULTS: The search yielded 37 publications that met study criteria. Four different chILD classification systems have been proposed in the past decade. The incidence of chILD has been estimated at 0.13-16.2 cases/100,000 children/year. One to five new cases presented to individual hospitals each year. In developed countries, the median mortality was 13% (6-19%). Morbidity and outcomes were highly variable and not systematically reported. Corticosteroids and hydroxychloroquine were the most common treatments. The impact of chILD on families and the burden on health services has not been studied. CONCLUSIONS: The heterogeneity of the chILD group of disorders, different determinations of what constitutes a chILD disorder and, a paucity of large epidemiological studies precludes consolidation of results across studies. Consensus on chILD classification is needed to support diagnosis and allow direct comparisons of research evidence. Active disease surveillance and international patient registries are required to advance understanding and management of chILD.

Research in progress: put the orphanage out of business.

Paediatric interstitial lung disease (ILD) is rare and diverse, meaning no single centre will see sufficient children to perform the studies needed to make progress. This EU FP-7 grant will standardise the evaluation of these rare conditions by establishing pan-European multidisciplinary expert panels and establish consensus on treatment protocols and standard operating procedures across Europe. We will work with patient groups to determine optimal treatment end-points and biomarkers. A biobank will be established as a Europe-wide resource for mechanistic studies. Ultimately we aim to do the first randomised controlled trial of a pharmacological treatment in paediatric ILD.

Assessment of multichannel lung sounds parameterization for two-class classification in interstitial lung disease patients.

This work deals with the assessment of different parameterization techniques for lung sounds (LS) acquired on the whole posterior thoracic surface for normal versus abnormal LS classification. Besides the conventional technique of power spectral density (PSD), the eigenvalues of the covariance matrix and both the univariate autoregressive (UAR) and the multivariate autoregressive models (MAR) were applied for constructing feature vectors as input to a supervised neural network (SNN). The results showed the effectiveness of the UAR modeling for multichannel LS parameterization, using new data, with classification accuracy of 75% and 93% for healthy subjects and patients, respectively.

Usual interstitial pneumonia. Quantitative assessment of high-resolution computed tomography findings by computer-assisted texture-based image analysis.

RATIONALE AND OBJECTIVES: The authors developed a texture-based pattern recognition and segmentation tool for the quantitation of high-resolution computed tomography (HRCT) findings in usual interstitial pneumonia (UIP). METHODS: In HRCT images of five patients with UIP and five patients without UIP, 1022 regions of interest (ROIs) of 5 x 5 pixels were classified by the examiner to be normal, emphysematous, ground-glass lesion, intralobular fibrosis, vessel, or bronchus section. The classes and the texture parameters calculated in the ROIs were the basis for the decision rule, using a multivariate discrimination analysis. The classification was compared with the examiner's diagnosis in 1889 new randomly selected ROIs. RESULTS: Depending on the structure, the sensitivity (the probability that a structure would be recognized correctly) was 68.7% to 80.7%. If the system classified a structure as normal, ground glass or fibrotic region, this was correct in 77.3% to 88.1%. However, the system's diagnosis of a bronchus section was correct in only 16.2%. The overall accuracy was 70.7%. CONCLUSIONS: Texture-based segmentation may be a valuable tool to aid the quantitative assessment of parenchymal disease in HRCT images.