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
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Date
2022-04-08Author(s)
Yarasca Berrocal, Enrique
Huamani Echaccaya, José
Tolmos Valdivia, Rita
Tolmos Regal, Luis
López Gurreonero, Carlos
Cervantes Ganoza, Luis A.
Cayo Rojas, César F.
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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.
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