BACKGROUND: There have been reports that optimal CPAP pressure can be predicted from a previously derived formula, with the Hoffstein formula being the most accurate and accepted in the literature so far. However, the validation of this predictive model has not been applied in different clinical settings. Our aim was to compare both the Hoffstein prediction formula and a newly derived formula to the CPAP pressure setting assessed during a formal CPAP titration study. METHODS: We prospectively studied 1,111 patients (871 males/240 females) with obstructive sleep apnea hypopnea syndrome (OSAHS) undergoing a CPAP titration procedure. In this large population sample, we tested the Hoffstein formula, utilizing body mass index (BMI), neck circumference and apnea/hypopnea index (AHI), and we compared it with our new formula that included not only AHI and BMI but also smoking history and gender adjustment. RESULTS: We found that using the Hoffstein prediction formula, successful prediction (predicted CPAP pressure within ±2 cm H(2)O compared to the finally assessed optimum CPAP pressure during titration) was accomplished in 873 patients (79%), with significant correlation between CPAP predicted pressure (CPAPpred(1)) and the optimum CPAP pressure (CPAPopt) [r = 0.364, p < 0.001]. With the new formula, including smoking history and gender adjustment, successful prediction was accomplished in 1,057 patients (95%), with significant correlation between CPAP predicted pressure (CPAPpred(2)) and the CPAPopt (r = 0.392, p < 0.001). However, there was a highly significant correlation between the two formulas (r = 0.918, p < 0.001). CONCLUSIONS: We conclude that the level of CPAP necessary to abolish sleep apnea can be successfully predicted from both equations, using common clinical measurements and prediction formulas that may be useful in calculating the starting pressure for initiating CPAP titration. It may also be possible to shorten CPAP titration and perhaps in selected cases to combine it with the initial diagnostic study.
BACKGROUND: There have been reports that optimal CPAP pressure can be predicted from a previously derived formula, with the Hoffstein formula being the most accurate and accepted in the literature so far. However, the validation of this predictive model has not been applied in different clinical settings. Our aim was to compare both the Hoffstein prediction formula and a newly derived formula to the CPAP pressure setting assessed during a formal CPAP titration study. METHODS: We prospectively studied 1,111 patients (871 males/240 females) with obstructive sleep apnea hypopnea syndrome (OSAHS) undergoing a CPAP titration procedure. In this large population sample, we tested the Hoffstein formula, utilizing body mass index (BMI), neck circumference and apnea/hypopnea index (AHI), and we compared it with our new formula that included not only AHI and BMI but also smoking history and gender adjustment. RESULTS: We found that using the Hoffstein prediction formula, successful prediction (predicted CPAP pressure within ±2 cm H(2)O compared to the finally assessed optimum CPAP pressure during titration) was accomplished in 873 patients (79%), with significant correlation between CPAP predicted pressure (CPAPpred(1)) and the optimum CPAP pressure (CPAPopt) [r = 0.364, p < 0.001]. With the new formula, including smoking history and gender adjustment, successful prediction was accomplished in 1,057 patients (95%), with significant correlation between CPAP predicted pressure (CPAPpred(2)) and the CPAPopt (r = 0.392, p < 0.001). However, there was a highly significant correlation between the two formulas (r = 0.918, p < 0.001). CONCLUSIONS: We conclude that the level of CPAP necessary to abolish sleep apnea can be successfully predicted from both equations, using common clinical measurements and prediction formulas that may be useful in calculating the starting pressure for initiating CPAP titration. It may also be possible to shorten CPAP titration and perhaps in selected cases to combine it with the initial diagnostic study.
Authors: T Hori; Y Sugita; E Koga; S Shirakawa; K Inoue; S Uchida; H Kuwahara; M Kousaka; T Kobayashi; Y Tsuji; M Terashima; K Fukuda; N Fukuda Journal: Psychiatry Clin Neurosci Date: 2001-06 Impact factor: 5.188
Authors: Thays Crosara Abrahão Cunha; Thais Moura Guimarães; Fernanda R Almeida; Fernanda L M Haddad; Luciana B M Godoy; Thulio M Cunha; Luciana O Silva; Sergio Tufik; Lia Bittencourt Journal: Braz J Otorhinolaryngol Date: 2018-12-12