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Urine Proteomics in Kawasaki Disease Pawan Sharma 15 th October 2013.

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Presentation on theme: "Urine Proteomics in Kawasaki Disease Pawan Sharma 15 th October 2013."— Presentation transcript:

1 Urine Proteomics in Kawasaki Disease Pawan Sharma 15 th October 2013

2 Kawasaki Disease Uncommonly common systemic vasculitis. 6 months to 4 years age. Significant mortality and morbidity esp with delayed diagnosis. No pathognomic test for early diagnosis.

3 GOAL To discover and validate diagnostic markers of KD in a prospective cohort..

4 Study participants Over 39 months in Tertiary care hospital. Approved by Boston Children’s Hospital Committee. Patients under the age of 18 with possible diagnosis of KD. Exclusion criteria: neoplastic, renal or urologic disease. Total patients mentioned 236 (234).

5 Study design Discovery phase. Validation phase: First cohort based on possible KD, but before determination of final diagnosis. Second cohort utilized serum specimens collected as a part of Pediatric Heart Network Study of KD.

6 Out come measures Paediatric Rheumatologist Use of Published Diagnostic Criteria for KD. Atypical KD was established using American Heart association guideline.

7 DF candidate diagnostic marker Analysed 15 patients. 6 KD patients (3 with and 3 without Coronary heart disease). 6 non-KD patients (2 non specific, 3 adeno and 1 Pyelonephritis). 3 matched specimen from treated patients with KD (after 1 month). 190 proteins specific to KD. Meprin A and Filamin C chosen.

8 Urine proteomics for discovery of improved diagnostic markers of Kawasaki disease EMBO Molecular Medicine Volume 5, Issue 2, pages , 20 DEC 2012 DOI: /emmm Volume 5, Issue 2,

9 Validation Prospectively measured concentration in urine. Investigators blinded to Final diagnosis. Mean age 3 years. 53 (49%) final diagnosis of KD. All treated with IVIg and Aspirin, 30% required repeat treatment. All studied patients received a Final Outcome.

10 Table 2. Final diagnosis of the 107 study patients Final diagnosisNumber of patients Kawasaki disease53 (49%) Viral syndrome33 (61%) Adenovirus6 Serum sickness3 Pyelonephritis2 group A streptococcal pharyngitis2 Cytomegalovirus1 Epstein-Barr virus1 Group A streptococcal pharyngitis1 Lyme disease1 Otitis media1 Pneumonia1 Respiratory syncytial virus1 Systemic arthritis1

11 KDNon KD Filamin C Meprin A Atypical KDNon KD Filamin C173.7 Meprin A Mean values

12 Blinded case control study

13 Response to treatment

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15 2 nd Cohort 112 archived samples collected from KD patient analysed. Compared them with Non-KD febrile illness. Serum samples used. Results were: KDNon KD Filamin C Meprin A

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17 Mouse model

18 What do we think Clear question for study address? Was there a comparison with appropriate standard? Did all patients get diagnostic test and reference standard? Could the result have been influenced? Is disease status clearly described? Were methods described in clear details? What are the results? Can the results be applied to our patients?

19 Summary Potential approaches for improving diagnosis. Discover phase: very small group. Mechanism of how this markers accumulate shall be important direction for future work. Limitations: Renal or Urologic disease, sever dehydration or ? Shock. Thank you!

20 The Receiver Operating Characteristic Curve. true positive rate (Sensitivity) is plotted in function of the false positive rate (100-Specificity) for different cut-off points. Each point on the ROC curve represents a sensitivity/specificity pair corresponding to a particular decision threshold. A test with perfect discrimination has a ROC curve that passes through the upper left corner (100% sensitivity, 100% specificity). Therefore the closer the ROC curve is to the upper left corner, the higher the overall accuracy of the test.

21 ROC Chart


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