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Complex Regional Pain Syndrome

Complex Regional Pain Syndrome. Features: Pain (allodynia, hyperesthesia) Sensory disturbances Impaired motor function Trophic changes Occurs after a (minor) injury Affects one or more extremities Bruehl et al 1999, Pain, 8(1-2): 147-54 Veldman et al 1993, Lancet, 342(8878):1012-6.

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Complex Regional Pain Syndrome

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  1. Complex Regional Pain Syndrome Features: • Pain (allodynia, hyperesthesia) • Sensory disturbances • Impaired motor function • Trophic changes Occurs after a (minor) injury Affects one or more extremities Bruehl et al 1999, Pain, 8(1-2): 147-54 Veldman et al 1993, Lancet, 342(8878):1012-6 with permission of dr. Roland Glinz, www.schmerzzentrum.ch

  2. Aetiology Four theories of underlying pathogenic mechanisms • Sympathetic dysregulation (α-adrenerg receptor) • Classic inflammation (TNFα, IL-1, IL-6) • Neurogenic inflammation (CGRP, SP) • Free radical damage/tissue hypoxia (free radicals, NO metabolism) Drumond et al 2004, Int J Low Extrem Wounds, 3(1): 35-42 Birklein et al 2001, Neurology, 75(12):2179-84 Huygen et al 2002, Mediators Inflamm, 11(1):47-51 Koban et al 2003, Pain, 1004(1-2): 149-57 Un-answered questions: • Individual susceptibility • Variety of precipitating events • Unpredictability of treatment effects

  3. Aim Increase insight in the molecular mechanisms underlying CRPS More insight in etiology Open new directions for further clinical research Approach Combined clinical and bioinformatics approach Application of a text mining/entity relationship tool PathwayAssist (Ariadne Genomics)

  4. PathwayAssist Parsing abstracts from Medline Medscan preprocessing Syntactic structure Semantic structure Ontology database NLP Module Molecule interactions

  5. Methodology CRPS knowledge incorporated into PathwayAssist: 1. Define a list of concepts related to CRPS based on: - literature search - ‘common medical knowledge’ - current treatment 2. Find concepts in PathwayAssist, or import if not found 3. Use the option find direct connections to create a network of connections between nodes

  6. Results

  7. New Hypothesis: NFB NFκB is a new node that is connected to most input nodes NFκB is related to 40 % of the imported nodes on CRPS NFκB is related to 7% of all possible input nodes NFκB probably relevant in the pathogenesis of CRPS

  8. Evaluation • Manual literature search for interactions between NFκB and CRPS related concepts • NFκB fits into a position where it can combine and link the existing theories about pathogenesis.

  9. Conclusion New Hypothesis: NFκB has a (key-player) role in the pathogenesis of CRPS • It might explain the diverse nature of precipitating events • Individual susceptibility might depend on variations in regulation of NFκB activity • NFκB might be a new option for drug targeting

  10. Applied Information Retrieval and Multidisciplinary Research: New Mechanistic Hypotheses in Complex Regional Pain Syndrome * Kristina M. Hettne, MSc; * Marissa de Mos, MSc, MD; Anke G.J. de Bruijn, Msc, MD; Marc Weeber; Erik van Mulligen; Johan van der Lei; Jordi Mestres; Monserrat Cases; Scott Boyer. Submitted to the Journal of American Medical Informatics Association, march 2006

  11. Next step: hypothesis testing Clinical/Biological/Epidemiological studies necessary to test the hypothesis Determinants of NFkB activity: • Prior to disease onset use of drugs that influence NFκB activity • Prior to disease onset of occurrence of viral infections (NFκB ↑) • Genetic variations in NFκB activity regulation, i.e. for ACE • NFκB activity in blood and interstitial fluids of acute CRPS patients

  12. Study population Setting: • Integrated Primary Care Information Database (IPCI) (department of Medical Informatics, Erasmus Medical Centre, Rotterdam) • General Practitioners Database, electronic medical records • Age and Gender representative for Dutch population • General Practitioner as gatekeeper of all patient information Van der Lei et al 1993; Vlug et al 1999

  13. IPCI: case definition Step 1: case finding - Search algorithm in free text: synonyms and abbreviations of CRPS - Search for prescription of DMSO in medication table Step 2: case validation - Questionnaires to GP’s: reconfirmation of diagnosis - Information of specialists correspondence: diagnostic criteria

  14. Source population 217,653 52 GP’s Search algorithm and first manual validation Possible cases 797 Prevalent 247 Incident 550 Questionnaires mailed to GP’s Reply 496 46 GP’s No reply 54 6 GP’s Validation based on questionnaires Reconfirmed 279 Unknown 4 Denied 213 Prevalent 41 Incident 238 Diagnosed by GP 61 Diagnosed by specialist 177 Validation by reconfirmation of the diagnosis

  15. Validation by diagnostic criteria (only for 95 cases possible) 1 Stanton-Hicks, 1995 2 Bruehl, 1999 3 Veldman, 1993

  16. Results CRPS incidence 1996-2005 Seasonal variation of CRPS

  17. Results Age distribution of CRPS Age distribution of fractures

  18. Plan: population based case-control studies • Cases: from IPCI • Controls: from IPCI, matched on age, gender, precipitating event • Outcome: CRPS • Exposure: determinants of NFkB (drugs, infections, genetics, co-morbidity) • Data collection: electronic medical records, questionnaires, blood samples

  19. First steps (In progress) • Create overview of all drugs used in CRPS patients and control prior to disease onset. • Which drugs are used more or less frequent in CRPS patients? • Link drugs to targets => common pathway • Perform cluster analysis on drug use. CRPS patients in one cluster?

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