Browsing School, Graduate by Subject "Malocclusion, Angle Class I"
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An In-Depth Analysis of Borderline Class I Malocclusions in Black Patients at the University of MarylandProblem: To determine if a group of UMB Orthodontic faculty determines there to be equal numbers of extraction and nonextraction cases in treatment planning borderline Class I malocclusions in black patients, and second, to determine the variables that are most important in the diagnosis and evidence-based treatment planning of these cases. Methods: All black patients treated in the UMB Orthodontic Graduate Clinic having completed initial orthodontic records over a three-year period were evaluated for the presence of a Borderline Class I Malocclusion. Of the initial 171, 15 subjects were statistically determined to be Borderline and were subsequently subjected to analysis by 14 orthodontic faculty members. Based on faculty analysis, 11 of the cases were categorized as extraction or non-extraction and were evaluated for those variables determined to be indicative of Borderline Class I malocclusions in black patients based on logistic regression. Results: Significantly more (X2=4.876, p = 0.027) extraction cases were reported (57.6%) than non-extraction cases (42.4%). 66.9% of the extraction plans involved only first bicuspids. The regression analysis showed that a 100% predictability of the evidence-based treatment plan was obtained by evaluating overbite, interarch midline discrepancy, WITS, lower crowding, overjet, IMPA, U1-SN, L1-NB and upper crowding. Overbite (p = 0.017) and interarch midline discrepancy (p = 0.019) were statistically significant in treatment planning. WITS approached significance (p = 0.096). Conclusions: Due to the limited study sample, one can make several inferences in regards to Borderline Class I malocclusions in black patients that must be interpreted with caution. The orthodontic faculty members extracted 57% of the time. The most common extraction pattern is four first bicuspids (~2/3 of the time). Dental overbite proved to be the most statistically significant variable when treatment planning. Interarch midline discrepancies proved to be the second most statistically significant variable when treatment planning. The WITS variable approached statistical significance. Lower crowding, overjet, IMPA, U1-SN, L1-NB and upper crowding were found to be non-significant in making the evidence-based treatment planning decision although a treatment plan with 100% predictability can be obtained by analyzing all nine variables.