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Low diagnostic accuracy for common knee conditions, highlights the weakness of the medical model, computer and web based algorithms.
Author(s):
Deo S. (United Kingdom)
,
Deo S. (United Kingdom)
Affiliations:
thorne fiona
,
thorne fiona
Affiliations:
lotz b.
lotz b.
Affiliations:
ESSKA Academy. deo s. May 9, 2018; 209643; P11-1383 Topic: Knee
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Abstract
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Objectives: The medical model of history, examination and investigation forms the bedrock of diagnosis and management of all patients. The essence is the recognition of patterns of symptoms and signs. In the modern era there are an increasing number of non-medical resources ranging from web-based information, computer diagnostic aids and non-specialist healthcare professionals to provide a diagnosis and commence management of a wide range of conditions, including knee problems.

Methods: We analysed the quality and patterns of clinical presentation in order to answer the question how clinical symptoms and examination findings correlate to diagnosis and in the context of definitive MRI scan and/or arthroscopic findings.
The analysis was a dataset of a consecutive series of patients, aged 18 to 45, with no past history of knee problems or end stage arthritis, presenting to a single specialist physiotherapist who fully completed a standardised knee assessment proforma of presenting symptoms and signs to an orthopaedic department of a district general hospital. The study comprises 95 patients. We analysed this data in the context of diagnostic findings of the MRI scan or arthroscopy to determine definitive intra-articular diagnosis. Based on standard textbook descriptions of common presentations, we went on to define the patients' presentation history and examination as typical or atypical. The null hypothesis is that patients would have a high chance of typical presentations particularly for common knee conditions.

Results: In the 75% of patients with a significant intra-articular pathology we found that 44% of patients had atypical symptoms and 71% had atypical clinical signs, 30% of the symptoms and signs were not matched, only 26% of the cohort had both typical symptoms and signs together, reflecting a surprisingly low positive predictive probability of symproms and signs in this group of patients with non-arthritic problems. In this cohort, 57% of the cohort has 3 or more multiple diagnoses.

Conclusions: Clinical symptoms and signs are surprisingly inaccurate in guiding intra-articular pathology within the knee, even in a sub-group considered the relatively easy and straightforward to assess. This should act as a warning to health care commissioners and developers of web-based patient focussed self-diagnosis and primary care algorithms.

Keywords:
clinical assessment knee knee conditions
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