Published

2022-07-14

Application of Binary Response Regression Models to Detect Factors Influencing the Occurrence of Infection in Dental Surgeries

Aplicación de modelos de regresión de respuesta binaria para detectar factores que inuyen en la aparición de infecciones en cirugías dentales

DOI:

https://doi.org/10.15446/rce.v45n2.97517

Keywords:

Chi-square test, Dentistry surgeries, Generalized linear models, Half-normal plot, Logistic regression (en)
Prueba de chi-cuadrado, Cirugías de odontología, Modelos lineales generalizados, Gráfico half normal, Regresión logística (es)

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Authors

  • Pollyane Silva Universidade de São Paulo
  • Valdemiro Vigas Instituto de Matemática, Universidade Federal
  • Cristiane Silva Departamento de Ciências Exatas, ESALQ, Universidade de São Paulo, Piracicaba, Brasil
  • Ananda Barreto Odontologia, Irmandade da Santa Casa de Misericórdia de Piracicaba, Piracicaba, Brasil
  • Paulo Oliveira Jr Odontologia, Irmandade da Santa Casa de Misericórdia de Piracicaba, Piracicaba, Brasil
  • Taciana Savian Departamento de Ciências Exatas, ESALQ, Universidade de São Paulo, Piracicaba, Brasil
  • Isis Santos Isis Santos Odontologia, Irmandade da Santa Casa de Misericórdia de Piracicaba, Piracicaba, Brasil

Postoperative infection is common in dental surgery, for example, in the removal of the third molar. To control these and other postoperative complications, various studies have reported the use of some drug protocols, namely the prophylact and the preemptive ones, using drugs such as dexamethasone and betamethasone. In this work, we used the generalized linear model via logistic regression to verify whether, in addition to the medicaments mentioned, some covariates that are frequently used in dental surgeries influence the occurrence, or not, of postoperative infection in surgeries for removal of the third molar. One of the main reasons that led us to employ such a model is because the response variable (having or not having infection) presents values of the binary type, in addition to being one of the most applied models in the area of health, among them, the dentistry area. The application of descriptive methods and analysis of association via statistical tests were also used to choose other factors that influence the response variable infection in addition to medications. The AIC (Akaike Information Criterion) selection criterion, analysis of the difeerence in the deviations, and the analysis of residual using the half-normal plot for selection and the assumption of the proposed model were employed. The data set under analysis consists of 113 patients submitted to dental surgery in a specialized clinic in the city of Piracicaba, SP-Brazil between 2003 and 2018. Through the proposed model, some important information the covariates in relation to the patients submitted to dental surgery. One of the key information is that characteristics as Age and Dental extractions are associated with the inflammatory processes after surgery. This relationship indicates that the older the patient, the chance of having an infection after surgery increases. The analysis is similar to the Number of extractions.

La infección postoperatoria es común en cirugía dental, por ejemplo, en la extracción del tercer molar. Para el control de estas y otras complicaciones postoperatorias, diversos estudios han reportado el uso de algunos protocolos farmacológicos, a saber, el profiláctico y el preventivo, utilizando fármacos como la dexametasona y la betametasona. En este trabajo utilizamos el modelo lineal generalizado mediante regresión logística para verificar si, además de los medicamentos mencionados, algunas covariables que se utilizan con frecuencia en las cirugías dentales influyen en la aparición o no de infección posoperatoria en las cirugías de extracción del tercer tercio molar. Una de las principales razones que nos llevó a emplear dicho modelo es porque la variable respuesta (tener o no tener infección) presenta valores de tipo binario, además de ser uno de los modelos más aplicados en el área de la salud, entre ellos, el área de odontología. También se utilizó la aplicación de métodos descriptivos y análisis de asociación a través de pruebas estadísticas para elegir otros factores que influyen en la variable respuesta infección además de los medicamentos. Se empleó el criterio de selección AIC (Akaike Information Criterion), el análisis de la diferencia en las desviaciones y el análisis de residuos utilizando la seminormal para la selección y la asunción del modelo propuesto. El conjunto de datos bajo análisis consta de 113 pacientes sometidos a cirugía dental en una clínica especializada en la ciudad de Piracicaba, SP-Brasil entre 2003 y 2018. A través del modelo propuesto, algunas informaciones importantes las covariables en relación a los pacientes sometidos a cirugía dental. Uno de los datos clave es que características como la edad y las extracciones dentales están asociadas a los procesos inflamatorios posteriores a la cirugía. Esta relación indica que a mayor edad del paciente, aumenta la probabilidad de tener una infección después de la cirugía. El análisis es similar al Número de extracciones.

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How to Cite

APA

Silva, P., Vigas, V., Silva, C., Barreto, A., Oliveira Jr, P., Savian, T. and Isis Santos, I. S. (2022). Application of Binary Response Regression Models to Detect Factors Influencing the Occurrence of Infection in Dental Surgeries. Revista Colombiana de Estadística, 45(2), 327–340. https://doi.org/10.15446/rce.v45n2.97517

ACM

[1]
Silva, P., Vigas, V., Silva, C., Barreto, A., Oliveira Jr, P., Savian, T. and Isis Santos, I.S. 2022. Application of Binary Response Regression Models to Detect Factors Influencing the Occurrence of Infection in Dental Surgeries. Revista Colombiana de Estadística. 45, 2 (Jul. 2022), 327–340. DOI:https://doi.org/10.15446/rce.v45n2.97517.

ACS

(1)
Silva, P.; Vigas, V.; Silva, C.; Barreto, A.; Oliveira Jr, P.; Savian, T.; Isis Santos, I. S. Application of Binary Response Regression Models to Detect Factors Influencing the Occurrence of Infection in Dental Surgeries. Rev. colomb. estad. 2022, 45, 327-340.

ABNT

SILVA, P.; VIGAS, V.; SILVA, C.; BARRETO, A.; OLIVEIRA JR, P.; SAVIAN, T.; ISIS SANTOS, I. S. Application of Binary Response Regression Models to Detect Factors Influencing the Occurrence of Infection in Dental Surgeries. Revista Colombiana de Estadística, [S. l.], v. 45, n. 2, p. 327–340, 2022. DOI: 10.15446/rce.v45n2.97517. Disponível em: https://revistas.unal.edu.co/index.php/estad/article/view/97517. Acesso em: 14 jan. 2025.

Chicago

Silva, Pollyane, Valdemiro Vigas, Cristiane Silva, Ananda Barreto, Paulo Oliveira Jr, Taciana Savian, and Isis Santos Isis Santos. 2022. “Application of Binary Response Regression Models to Detect Factors Influencing the Occurrence of Infection in Dental Surgeries”. Revista Colombiana De Estadística 45 (2):327-40. https://doi.org/10.15446/rce.v45n2.97517.

Harvard

Silva, P., Vigas, V., Silva, C., Barreto, A., Oliveira Jr, P., Savian, T. and Isis Santos, I. S. (2022) “Application of Binary Response Regression Models to Detect Factors Influencing the Occurrence of Infection in Dental Surgeries”, Revista Colombiana de Estadística, 45(2), pp. 327–340. doi: 10.15446/rce.v45n2.97517.

IEEE

[1]
P. Silva, “Application of Binary Response Regression Models to Detect Factors Influencing the Occurrence of Infection in Dental Surgeries”, Rev. colomb. estad., vol. 45, no. 2, pp. 327–340, Jul. 2022.

MLA

Silva, P., V. Vigas, C. Silva, A. Barreto, P. Oliveira Jr, T. Savian, and I. S. Isis Santos. “Application of Binary Response Regression Models to Detect Factors Influencing the Occurrence of Infection in Dental Surgeries”. Revista Colombiana de Estadística, vol. 45, no. 2, July 2022, pp. 327-40, doi:10.15446/rce.v45n2.97517.

Turabian

Silva, Pollyane, Valdemiro Vigas, Cristiane Silva, Ananda Barreto, Paulo Oliveira Jr, Taciana Savian, and Isis Santos Isis Santos. “Application of Binary Response Regression Models to Detect Factors Influencing the Occurrence of Infection in Dental Surgeries”. Revista Colombiana de Estadística 45, no. 2 (July 14, 2022): 327–340. Accessed January 14, 2025. https://revistas.unal.edu.co/index.php/estad/article/view/97517.

Vancouver

1.
Silva P, Vigas V, Silva C, Barreto A, Oliveira Jr P, Savian T, Isis Santos IS. Application of Binary Response Regression Models to Detect Factors Influencing the Occurrence of Infection in Dental Surgeries. Rev. colomb. estad. [Internet]. 2022 Jul. 14 [cited 2025 Jan. 14];45(2):327-40. Available from: https://revistas.unal.edu.co/index.php/estad/article/view/97517

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