OBJECTIVE: The objectives of this study were to determine reference values for sniff nasal inspiratory pressure (SNIP) and to propose reference equations for the population of Brazil. METHODS: We evaluated 243 healthy individuals (111 males and 132 females), between 20 and 80 years of age, with an FVC and FEV1/FVC ratio > 80% and > 85% of the predicted value, respectively. All of the subjects underwent respiratory muscle strength tests to determine MIP, MEP, and SNIP. RESULTS: We found that SNIP values were higher in males than in females (p < 0.05) and that SNIP correlated negatively with age, for males (r = -0.29; p < 0.001) and for females (r = -0.33; p < 0.0001). Linear regression also revealed that age influenced the predicted SNIP, for males (R² = 0.09) and females (R² = 0.10). We obtained predicted SNIP values that were higher than those obtained for other populations. CONCLUSIONS: We have devised predictive equations for SNIP to be used in adults (20-80 years of age) in Brazil. These equations could help minimize diagnostic discrepancies among individuals.
OBJECTIVE: The objectives of this study were to determine reference values for sniff nasal inspiratory pressure (SNIP) and to propose reference equations for the population of Brazil. METHODS: We evaluated 243 healthy individuals (111 males and 132 females), between 20 and 80 years of age, with an FVC and FEV1/FVC ratio > 80% and > 85% of the predicted value, respectively. All of the subjects underwent respiratory muscle strength tests to determine MIP, MEP, and SNIP. RESULTS: We found that SNIP values were higher in males than in females (p < 0.05) and that SNIP correlated negatively with age, for males (r = -0.29; p < 0.001) and for females (r = -0.33; p < 0.0001). Linear regression also revealed that age influenced the predicted SNIP, for males (R² = 0.09) and females (R² = 0.10). We obtained predicted SNIP values that were higher than those obtained for other populations. CONCLUSIONS: We have devised predictive equations for SNIP to be used in adults (20-80 years of age) in Brazil. These equations could help minimize diagnostic discrepancies among individuals.
Authors: Aída L R Turquetto; Luiz F Canêo; Daniela R Agostinho; Patrícia A Oliveira; Maria Isabel C S Lopes; Patrícia F Trevizan; Frederico L A Fernandes; Maria A Binotto; Gabriela Liberato; Glaucia M P Tavares; Rodolfo A Neirotti; Marcelo B Jatene Journal: Pediatr Cardiol Date: 2017-05-12 Impact factor: 1.655
Authors: Morgana de Araújo Evangelista; Fernando Augusto Lavezzo Dias; Mário Emílio Teixeira Dourado Júnior; George Carlos do Nascimento; Antonio Sarmento; Lucien Peroni Gualdi; Andrea Aliverti; Vanessa Resqueti; Guilherme Augusto de Freitas Fregonezi Journal: PLoS One Date: 2017-06-08 Impact factor: 3.240
Authors: Kadja Benício; Vanessa R Resqueti; Fernando A L Dias; Francesca Pennati; Andrea Aliverti; Jéssica Danielle Medeiros da Fonseca; Guilherme A F Fregonezi Journal: PLoS One Date: 2021-07-22 Impact factor: 3.240
Authors: Catharinne C Farias; Vanessa Resqueti; Fernando A L Dias; Audrey Borghi-Silva; Ross Arena; Guilherme A F Fregonezi Journal: Braz J Phys Ther Date: 2014-05-02 Impact factor: 3.377
Authors: Kadja Benício; Fernando A L Dias; Lucien P Gualdi; Andrea Aliverti; Vanessa R Resqueti; Guilherme A F Fregonezi Journal: Braz J Phys Ther Date: 2015-11-17 Impact factor: 3.377