[Prevalence of temporomandibular disorders according to the simplified fonseca anamnestic index in dentistry students of the juárez university of the state of durango, mexico]

Predictability and Accuracy of the Short-Form Fonseca Anamnestic Index in Relation to the Modified Helkimo Index for the Diagnosis of Temporomandibular Disorders: A Cross-Sectional Study

Aim

The aim of this study was to evaluate the predictability and accuracy of the Short-Form Fonseca Anamnestic Index (SFAI) in relation to the modified Helkimo Index for the diagnosis of temporomandibular disorders (TMDs).

Materials and Methods

A cross-sectional, prospective, and analytical predictive study was conducted in 240 students of a public institute of higher technological education in Ica, Peru during the months of February to May 2018. The SFAI of 10 closed questions and the Helkimo Index modified by Maglione (gold standard) were used as instruments to diagnose TMDs. For the analysis of concordance between both instruments, Cohen's Kappa Index was applied. To evaluate the association according to gender and age group, Pearson's chi-square test was used. For validity of the SFAI in relation to accuracy, sensitivity and specificity were calculated, and they were verified by receiver operating characteristics (ROC) to determine the best cutoff points (area under the curve [AUC]) considering a P value < 0.05. Regarding the predictability of the SFAI, the positive and negative predictive value was calculated by applying Bayes' theorem.

Results

The SFAI was highly significantly associated with the modified Helkimo Index according to gender (P < 0.001), age group (P < 0.001), and overall (P < 0.001) moderate overall agreement (k = 0.416; 95% confidence interval [CI] = 0.287-0.545); better concordance was obtained in individuals older than 20 years (k = 0.490, CI = 0.302-0.679) and women (k = 0.565, CI = 0.371-0.759). The ROC curve analysis of the SFAI showed good accuracy (0.852, CI = 0.800-0.905) and was highly significant (P < 0.001), with an optimal cutoff point of 17.5 and good sensitivity (80.10%) and specificity (74.36%). In addition, a very good positive predictive value (PPV) (94.15%) and a fair negative predictive value (NPV) (42.02%) were obtained.

Conclusions

Although there was moderate concordance between the SFAI and the modified Helkimo Index for the diagnosis of TMDs, the SFAI obtained good accuracy in the overall analysis of sensitivity and specificity. In addition, it demonstrated a high predictive efficacy for detecting positive TMD cases, whereas its ability to rule out positive cases was fair.