Email updates

Keep up to date with the latest news and content from BMC Oral Health and BioMed Central.

Open Access Research article

Profiling the clinical presentation of diagnostic characteristics of a sample of symptomatic TMD patients

Luciana Pimenta e Silva Machado12, Marianita Batista de Macedo Nery2, Cláudio de Góis Nery1 and Cláudio Rodrigues Leles13*

Author Affiliations

1 School of Dentistry, Federal University of Goias, Goiania, Goias, Brazil

2 Private practice, Goiania, Goias, Brazil

3 DPRO/Faculdade de Odontologia, Praça Universitária, s/n. Setor Universitário, CEP 74.605-220, Goiania, Goias, Brazil

For all author emails, please log on.

BMC Oral Health 2012, 12:26  doi:10.1186/1472-6831-12-26

Published: 2 August 2012

Abstract

Background

Temporomandibular disorder (TMD) patients might present a number of concurrent clinical diagnoses that may be clustered according to their similarity. Profiling patients’ clinical presentations can be useful for better understanding the behavior of TMD and for providing appropriate treatment planning. The aim of this study was to simultaneously classify symptomatic patients diagnosed with a variety of subtypes of TMD into homogenous groups based on their clinical presentation and occurrence of comorbidities.

Methods

Clinical records of 357 consecutive TMD patients seeking treatment in a private specialized clinic were included in the study sample. Patients presenting multiple subtypes of TMD diagnosed simultaneously were categorized according to the AAOP criteria. Descriptive statistics and two-step cluster analysis were used to characterize the clinical presentation of these patients based on the primary and secondary clinical diagnoses.

Results

The most common diagnoses were localized masticatory muscle pain (n = 125) and disc displacement without reduction (n = 104). Comorbidity was identified in 288 patients. The automatic selection of an optimal number of clusters included 100% of cases, generating an initial 6-cluster solution and a final 4-cluster solution. The interpretation of within-group ranking of the importance of variables in the clustering solutions resulted in the following characterization of clusters: chronic facial pain (n = 36), acute muscle pain (n = 125), acute articular pain (n = 75) and chronic articular impairment (n = 121).

Conclusion

Subgroups of acute and chronic TMD patients seeking treatment can be identified using clustering methods to provide a better understanding of the clinical presentation of TMD when multiple diagnosis are present. Classifying patients into identifiable symptomatic profiles would help clinicians to estimate how common a disorder is within a population of TMD patients and understand the probability of certain pattern of clinical complaints.

Keywords:
Temporomandibular disorders; Cluster analysis; Clinical diagnosis; Diagnosis-related groups