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Griese, Matthias; Seidl, Elias; Hengst, Meike; Reu, Simone; Rock, Hans; Anthony, Gisela; Kiper, Nural; Emiralioglu, Nagehan; Snijders, Deborah; Goldbeck, Lutz; Leidl, Reiner; Ley-Zaporozhan, Julia; Krüger-Stollfuss, Ingrid; Kammer, Birgit; Wesselak, Traudl; Eismann, Claudia; Schams, Andrea; Neuner, Doerthe; MacLean, Morag; Nicholson, Andrew G.; Lauren, McCann; Clement, Annick; Epaud, Ralph; Blic, Jacques de; Ashworth, Michael; Aurora, Paul; Calder, Alistair; Wetzke, Martin; Kappler, Matthias; Cunningham, Steve; Schwerk, Nicolaus; Bush, Andy (2018): International management platform for children’s interstitial lung disease (chILD-EU). In: Thorax, Vol. 73, No. 3: pp. 231-239
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Abstract

Background Children's interstitial lung diseases (chILD) cover many rare entities, frequently not diagnosed or studied in detail. There is a great need for specialised advice and for internationally agreed subclassification of entities collected in a register. Our objective was to implement an international management platform with independent multidisciplinary review of cases at presentation for long-term follow-up and to test if this would allow for more accurate diagnosis. Also, quality and reproducibility of a diagnostic subclassification system were assessed using a collection of 25 complex chILD cases. Methods A web-based chILD management platform with a registry and biobank was successfully designed and implemented. Results Over a 3-year period, 575 patients were included for observation spanning a wide spectrum of chILD. In 346 patients, multidisciplinary reviews were completed by teams at five international sites (Munich 51%, London 12%, Hannover 31%, Ankara 1% and Paris 5%). In 13%, the diagnosis reached by the referring team was not confirmed by peer review. Among these, the diagnosis initially given was wrong (27%), imprecise (50%) or significant information was added (23%). The ability of nine expert clinicians to subcategorise the final diagnosis into the chILD-EU register classification had an overall exact inter-rater agreement of 59% on first assessment and after training, 64%. Only 10% of the 'wrong' answers resulted in allocation to an incorrect category. Subcategorisation proved useful but training is needed for optimal implementation. Conclusions We have shown that chILD-EU has generated a platform to help the clinical assessment of chILD.