Volltext-Downloads (blau) und Frontdoor-Views (grau)
The search result changed since you submitted your search request. Documents might be displayed in a different sort order.
  • search hit 45 of 94
Back to Result List

Bitte verwenden Sie diesen Link, wenn Sie dieses Dokument zitieren oder verlinken wollen: https://nbn-resolving.org/urn:nbn:de:gbv:9-opus-29005

Patient’s Experience in Pediatric Primary Immunodeficiency Disorders: Computerized Classification of Questionnaires

  • Introduction Primary immunodeficiency disorders (PIDs) are a heterogeneous group of more than 200 rare diseases. Timely diagnosis is of uttermost importance. Therefore, we aimed to develop a diagnostic questionnaire with computerized pattern-recognition in order to support physicians to identify suspicious patient histories. Materials and methods Standardized interviews were conducted with guardians of children with PID. The questionnaire based on parental observations was developed using Colaizzis’ framework for content analysis. Answers from 64 PID patients and 62 controls were analyzed by data mining methods in order to make a diagnostic prediction. Performance was evaluated by k-fold stratified cross-validation. Results The diagnostic support tool achieved a diagnostic sensitivity of up to 98%. The analysis of 12 interviews revealed 26 main phenomena observed by parents in the pre-diagnostic period. The questions were systematically phrased and selected resulting in a 36-item questionnaire. This was answered by 126 patients with or without PID to evaluate prediction. Item analysis revealed significant questions. Discussion Our approach proved suitable for recognizing patterns and thus differentiates between observations of PID patients and control groups. These findings provide the basis for developing a tool supporting physicians to consider a PID with a questionnaire. These data support the notion that patient’s experience is a cornerstone in the diagnostic process.

Download full text files

Export metadata

Additional Services

Search Google Scholar

Statistics

frontdoor_oas
Metadaten
Author: Urs Mücke, Christian Klemann, Ulrich Baumann, Almut Meyer-Bahlburg, Xiaowei Kortum, Frank Klawonn, Werner M. Lechner, Lorenz Grigull
URN:urn:nbn:de:gbv:9-opus-29005
DOI:https://doi.org/10.3389/fimmu.2017.00384
ISSN:1664-3224 (eISSN)
Publisher:Frontiers Media S.A.
Document Type:Article
Language:English
Date of first Publication:2017/04/05
Release Date:2020/03/11
Tag:Colaizzi; data mining; diagnostic support; primary immunodeficiency disease; questionnaire
GND Keyword:-
Volume:8
Faculties:Universitätsmedizin / Klinik und Poliklinik für Kinder- und Jugendmedizin
Licence (German):License LogoCreative Commons - Namensnennung