Urinary Colorimetric Sensor Array and Algorithm to Distinguish Kawasaki Disease from Other Febrile Illnesses

Diagnosis support systems for rare diseases: a scoping review

INTRODUCTION

Rare diseases affect approximately 350 million people worldwide. Delayed diagnosis is frequent due to lack of knowledge of most clinicians and a small number of expert centers. Consequently, computerized diagnosis support systems have been developed to address these issues, with many relying on rare disease expertise and taking advantage of the increasing volume of generated and accessible health-related data. Our objective is to perform a review of all initiatives aiming to support the diagnosis of rare diseases.

METHODS

A scoping review was conducted based on methods proposed by Arksey and O'Malley. A charting form for relevant study analysis was developed and used to categorize data.

RESULTS

Sixty-eight studies were retained at the end of the charting process. Diagnosis targets varied from 1 rare disease to all rare diseases. Material used for diagnosis support consisted mostly of phenotype concepts, images or fluids. Fifty-seven percent of the studies used expert knowledge. Two-thirds of the studies relied on machine learning algorithms, and one-third used simple similarities. Manual algorithms were encountered as well. Most of the studies presented satisfying performance of evaluation by comparison with references or with external validation. Fourteen studies provided online tools, most of which aimed to support the diagnosis of all rare diseases by considering queries based on phenotype concepts.

CONCLUSION

Numerous solutions relying on different materials and use of various methodologies are emerging with satisfying preliminary results. However, the variability of approaches and evaluation processes complicates the comparison of results. Efforts should be made to adequately validate these tools and guarantee reproducibility and explicability.

Biomarkers in vasculitis

PURPOSE OF REVIEW

Biomarkers are considered to be helpful in diagnosing, monitoring, predicting treatment response, and prognosis in clinical practice and as outcomes in clinical trials. In this article, we review the recent literature on new biomarkers and the expanding use of older ones in vasculitic conditions.

RECENT FINDINGS

In antineutrophil cytoplasmic antibody-associated vasculitis patients antineutrophil cytoplasmic antibody type may be useful as a predictor of relapse and response to rituximab. Moreover, serial measurements of proteinase-3 titer may help to predict relapse. Urinary soluble CD163 levels are promising for identifying active renal vasculitis. Imaging modalities such as positron emission tomography, computerized angiography tomography, and temporal artery ultrasound maintain their role in diagnosis and disease assessment in large vessel vasculitis. Fecal calprotectin is a useful marker of active gastrointestinal involvement in Behçet's syndrome.

SUMMARY

The publications reviewed here potentially may help to move the field of biomarkers in vasculitis management. However, more work toward understanding the underlying pathophysiology and effects of an intervention on the disease process are needed before true biomarkers can be realized. Further studies with appropriate control groups, using good definitions for disease states such as activity and remission are needed to guide our use of these markers correctly in the management of our patients.