Objective: To describe the characteristics of craniocervical posture of children aged between 6 and 11 years and its relationship to their sagittal skeletal classification. Material and Methods: This descriptive cross-sectional study involved 107 children (55 girls-52 boys), aged between 6 and 11 years. The sample included no previous orthodontically/orthopedic treated and systemically healthy children. After proper calibration, lateral skull radiographs, taken for diagnosis purpose for maxillary orthopedic treatment, were obtained by the same operator in natural head position. A radiographic analysis was made using a NEMOTEC software: 13 variables were registered: age, gender, ANB angle (to classify sagittal skeletal relationships) and 10 variables related to craniocervical posture: cervical lordosis, hyoid triangle, craniocervical angle, intervertebral spaces: C0-C1, C1-C2 and distances NSL-Ver, NL-Ver, ML-Ver, OPT-Hor, CVT-Hor. To evaluate the reliability of measures, 15 randomly selected radiographs were re-measured by the same investigator two weeks after the initial analysis. Results: Intra-class correlation coefficients were in a range of 0.945-0.996. Lordosis, CCA, C1-C2, OPT-Hor y CVT-Hor, values were higher in male than in female children (p<0.05). No statistically significant differences were found among groups of sagittal skeletal relationships, but class III children had a tendency to higher craniocervical flexion; 66.3% of the studied group presented rectified lordotic curvature and class II subjects presented increased values of NSL-Ver, NL-Ver and ML-Ver. Class I children had the lowest values for OPT-Hor and CVT-Hor. Conclusion: All craniocervical postural variables were higher in boys than in girls. No differences were found in this study between cervical postural variables with different malocclusion.

Objective: To determine the association between occlusal and soft tissue characteristics with the presence of gingival smile (GS) in a pediatric population with inter-transitional mixed dentition. Material and Methods: Case-control study was performed with a probabilistic sample of 163 children in inter-transitional mixed dentition (age:8.8 years ±0.8). Cases were 37 children with GS, and controls were 126 children without GS. Occlusal variables were assessed through clinical examination, and soft tissue variables were assessed through photograms. Kappa test and intraclass correlation coefficient were done (0.87-0.96). The association between malocclusion, gender, and types of smile was assessed using a Chi square test. Comparison of quantitative variables in smile groups was made by Student t test. A multivariate binary logistic regression was performed. Results: Class II malocclusion, short upper lip at smile and short incisor clinical crown, were risk factors for gummy smile (OR= 10.4, 95%CI 3.07-34.95, OR= 2.1, 95%CI 1.44-3.13 and OR= 2.5 95%CI 1.34-4.54 respectively). Lower facial height was a protective factor against GS (OR= 0.76; 95%CI 0.69-0.85). The logistic regression model explains 48% of GS variability. Conclusion: Class II malocclusion is considered a risk factor for gummy smile. Other variables associated to gummy smile were short upper lip and short incisor clinical crown. Clinicians should considered these aspects in clinical examination of each patient to provide an adequate diagnostic and plan of treatment to control and/or correct a GS.

entre las características periodontales y la sonrisa gingival en niños: un estudio de casos y controles. Rev Nac Odontol. 2016;12(22):7-16. doi: http:// dx.doi.org/10.16925/od.v12i22.1201 Resumen. Introducción: la presencia de sonrisa gingival (sg) es uno de los aspectos más negativamente valorados. Su presencia en la vida adulta es un motivo de consulta constante, pero en la niñez tiende a ser considerado como normal. El objetivo de este estudio fue describir y comparar las características del periodonto de un grupo de niños, con diferentes maloclusiones, con y sin sonrisa gingival, y evaluar la influencia de las características gingivales sobre la presencia de sonrisa gingival. Métodos: en este estudio analítico de casos y controles, el tamaño muestral fue probabilístico. Se incluyeron 163 niños en dentición mixta silente que cumplieron los criterios de inclusión y exclusión: 37 casos con sonrisa gingival (sg) y 126 controles sin sonrisa gingival (nsg). Se les evaluaron las variables oclusales, de sonrisa y periodontales por medio de un examen clínico y de un fotograma. Los evaluadores estaban previamente calibrados (kappa 0,87 e icc 0,96). Resultados: la edad promedio de los pacientes en ambos grupos fue de 8,8 años con una desviación estándar de 0,9 para los casos y de 0,8 para los controles. La maloclusión más predominante fue la clase i (63,8% de la muestra). Las características periodontales fueron similares en ambos grupos. El biotipo periodontal grueso tuvo una tendencia a comportarse como factor de riesgo para sg (or 1,6) pero esta relación no fue estadísticamente significativa (ic = 95% 0,6 -4,1). Conclusiones: los factores periodontales no influyen sobre la presencia de sonrisa gingival en niños; su comportamiento en etapas posteriores deberá ser observado.Palabras clave: maloclusión, periodonto, sonrisa, tejidos blandos.

<p><strong>Introducción: </strong>El impacto de las variables sociodemográficas sobre la prevalencia y las consecuencias de la maloclusión es difícil de determinar.<strong>Objetivo: </strong>Determinar la prevalencia y severidad de las características cefalométricas de pacientes y su relación con los hábitos orales y factores sociodemográficos. <strong>Material y métodos: </strong>Estudio observacional de corte transversal analítico mediante evaluación calibrada (Kappa &gt; 0.8) de 140 radiografías cefálicas laterales e historias clínicas, de pacientes que acudieron al Postgrado de Ortodoncia de la Universidad de Antioquia (Medellín) del 2012-2015 y cumplieron los criterios de selección. Se utilizaron pruebas paramétricas (p &lt; 0.05) para relacionar las características cefalométricas y sociodemográficas: coeficiente de correlación de Pearson y prueba t de Student para variables cuantitativas (p &lt; 0.05); razón de momios (RM) para indagar la relación de las características sociodemográficas y cefalométricas presentes en la maloclusión. <strong>Resultados: </strong>La mayoría fueron pacientes jóvenes (46.2%) de estratos bajo y medio-bajo (91.4%) y acudieron por razones estéticas, principalmente (85%). La maloclusión clase II fue la más prevalente (45.7%), mientras que la clase III se consultó por problemas funcionales (RM = 4.09; IC 95% 1.5-11.1). Se encontró una relación estadísticamente significativa entre la clasificación vertical de la maloclusión (hipo-, normo- e hiperdivergente) con los hábitos orales de succión (p = 0.019), deglución atípica (p = 0.045) y respiración bucal (p = 0.036). <strong>Conclusiones: </strong>Las características sociodemográficas no influyen en la maloclusión. Los hábitos orales se relacionan con maloclusiones verticales. El motivo primordial de consulta fue el estético. La maloclusión clase II fue la más común y los pacientes clase III parecen estar más conscientes de sus problemas funcionales.</p>

Aim The aim of the present study was to establish the relationship between lower facial third and smile type in silent mixed‐dentition patients. Methods This cross‐sectional study, approved by the ethics committee, was conducted in a population of 2760 children, from which a convenient sample of 198 was included: 75 with gingival smile (GS) and 123 without GS (1:1.64). Clinical examination and videos were taken. Occlusal relation, overjet (OJ), overbite (OB), superior lip length at rest, superior lip length while smiling (SLLS), lower facial third height (LFTH), mid‐facial third height (MFTH), clinical crown length, and lip lift ability (LLA) were measured by two calibrated examiners (intraclass correlation coefficient: ≥.95). A normality test and demographic and bivariate analyses were undertaken. A non‐paired Student's t test was carried out in order to observe statistically‐significant differences between variables. Results There were no differences between sexes or associations between LFTH and GS. Statistically‐significant differences (P < .05) in MFTH, SLLS, LLA, OJ, and OB were found. A logistic regression model showed that the sum of LLA (odds ratio [OR]: .65, 95% confidence intervals [CI]: .50,.83]) and OB (OR: .88, 95% CI: .82, .93]) were GS predictive factors in 81.3% of cases. Conclusions OB and LLA are GS predictive factors in prepubertal participants. There is no relation between LFTH and GS.

Objective: To evaluate and compare sensitivity and specificity of ANB, Wits, APDI and AF-BF to diagnose sagittal skeletal malocclusions, in children between 6 to 12 years old, using ROC curves, a widely accepted method for the analysis and evaluation of diagnostic tests. Material and Methods: A descriptive-comparative study of diagnostic tests was conducted. From a population of 3,000 children, a non-probabilistic sample of 209 was selected. The clinical classification of the patients as class I, II or III, made by a group of experts based on the visual inspection of models and photographs, was chosen as the gold standard. After calibration (ICC>0.94) the variables were measured in cephalograms. Eight ROC curves were plotted (I vs II, and I vs III for each one of the variables). The area under the curve was measured and compared (Ji-square test). Cut points were established. Results: To discriminate Class I from II, ANB showed the largest area under the curve (AUC) (0.876) and the cut point (best sensitivity and specificity) was at 5.75°. To discriminate class I from III, Wits showed the largest AUC (0.874) with a cut point of-3.25 mm. There were no statistical differences between the AUC for the four variables (p=0.48 y p=0.38 for class I-II and I-III). Conclusion: ANB and Wits performed better for the diagnosis of class II and III, respectively. Cut points in children were different from those reported in adults.