Prediction of persistent shoulder pain in general practice: Comparing clinical consensus from a Delphi procedure with a statistical scoring system

BMC Family Practice

Research Article

David Vergouw¹  Henrica CW de Vet¹  Henriëtte E van der Horst¹  Daniëlle AWM van der Windt²  Martijn W Heymans³ 

[1] Institute for Research in Extramural Medicine, VU University Medical Center Amsterdam, The Netherlands;Institute for Research in Extramural Medicine, VU University Medical Center Amsterdam, The Netherlands;Primary Care Musculoskeletal Research Centre, Keele University, Keele Staffordshire, UK;Institute for Research in Extramural Medicine, VU University Medical Center Amsterdam, The Netherlands;VU University, Institute for Health Sciences, Department of Methodology and Applied Biostatistics, Amsterdam, The Netherlands;

关键词: Predictive Performance;    Shoulder Pain;    Prognostic Model;    Panel Member;    Illness Perception;   

DOI  :  10.1186/1471-2296-12-63

 received in 2011-03-17, accepted in 2011-06-30,  发布年份 2011

来源: Springer

【 摘 要 】

BackgroundIn prognostic research, prediction rules are generally statistically derived. However the composition and performance of these statistical models may strongly depend on the characteristics of the derivation sample. The purpose of this study was to establish consensus among clinicians and experts on key predictors for persistent shoulder pain three months after initial consultation in primary care and assess the predictive performance of a model based on clinical expertise compared to a statistically derived model.MethodsA Delphi poll involving 3 rounds of data collection was used to reach consensus among health care professionals involved in the assessment and management of shoulder pain.ResultsPredictors selected by the expert panel were: symptom duration, pain catastrophizing, symptom history, fear-avoidance beliefs, coexisting neck pain, severity of shoulder disability, multisite pain, age, shoulder pain intensity and illness perceptions. When tested in a sample of 587 primary care patients consulting with shoulder pain the predictive performance of the two prognostic models based on clinical expertise were lower compared to that of a statistically derived model (Area Under the Curve, AUC, expert-based dichotomous predictors 0.656, expert-based continuous predictors 0.679 vs. 0.702 statistical model).ConclusionsThe three models were different in terms of composition, but all confirmed the prognostic importance of symptom duration, baseline level of shoulder disability and multisite pain. External validation in other populations of shoulder pain patients should confirm whether statistically derived models indeed perform better compared to models based on clinical expertise.

【 授权许可】

CC BY   
© Vergouw et al; licensee BioMed Central Ltd. 2011