Predictive Formulas for CPAP Titration; a Comparison and Reassessment

Tofts, Ryu; Dozier, Jordan; Daco, Jonothan; Urakov, Timur; Hernandez, Marlow; Okafor, Ndubuisi; Rahaghi, Franck; Ferrer, Gustavo; Oliveirã, Eurico C.; Smolley, Laurence; Ramírez, José Marcos Artiles; Hadeh, Anas

doi:10.1378/chest.1114949

Cited by 2 publications

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“…After screening the studies, forty-six of them were potentially relevant and the full-text versions were downloaded for detailed evaluation [ 13 – 52 , 55 – 60 ] and four studies were identified after reading the references and they were also downloaded [ 60 – 64 ]. After detailed review of the fifty studies, the authors came to a consensus for twenty-six studies [ 13 – 15 , 19 , 20 , 31 , 32 , 34 , 35 , 38 , 43 – 45 , 47 – 51 , 55 – 61 , 63 , 64 ] which presented equations that met the inclusion and exclusion criteria (see Figure 1 ). There were 4,436 patients in the development phases and 3,489 patients in the validation phases for the combined studies included in this review.…”

Section: Resultsmentioning

confidence: 99%

“…Second, polysomnographic variables were also important during the multiple linear regressions analyses. Apnea-hypopnea index was a variable in mathematical equations for seventeen studies [ 13 , 20 , 32 , 35 , 38 , 43 – 45 , 56 – 60 , 64 , 66 ] and RDI for four studies [ 31 , 34 , 55 , 65 ]. The coefficient for AHI ranged between 0.01 and 0.18 and for RDI ranged between 0.01301 and 0.041.…”

Section: Discussionmentioning

confidence: 99%

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Mathematical Equations to Predict Positive Airway Pressures for Obstructive Sleep Apnea: A Systematic Review

et al. 2015

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Objective. To systematically review the international literature for mathematical equations used to predict effective pressures for positive airway pressure (PAP) devices. Methods. Google Scholar, PubMed, Scopus, Embase, Web of Science, CINAHL, and The Cochrane Library were searched through June 27, 2015. The PRISMA statement was followed. There was no language limitation. Results. 709 articles were screened, fifty were downloaded, and twenty-six studies presented equations that met the inclusion and exclusion criteria. In total, there were 4,436 patients in the development phases and 3,489 patients in the validation phases. Studies performed multiple linear regressions analyses as part of the equation(s) development and included the following variables: physical characteristics, polysomnography data, behavioral characteristics, and miscellaneous characteristics, which were all predictive to a variable extent. Of the published variables, body mass index (BMI) and mean oxygen saturation are the most heavily weighted, while BMI (eighteen studies), apnea-hypopnea index (seventeen studies), and neck circumference (eleven studies) were the variables most frequently used in the mathematical equations. Ten studies were from Asian countries and sixteen were from non-Asian countries. Conclusion. This systematic review identified twenty-six unique studies reporting mathematical equations which are summarized. Overall, BMI and mean oxygen saturation are the most heavily weighted.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Mathematical Equations to Predict Positive Airway Pressures for Obstructive Sleep Apnea: A Systematic Review

et al. 2015

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“…The results revealed a significant underestimation by the Hoffstein equation [27]. Tofts et al reported that both the Hoffstein and Loredo predictive equations underestimate CPAP titration pressures and proposed the use of the Cleveland Clinic Predictor formula as a more accurate option; however, it was only able to accurately predict CPAP in 74% of patients [28]. It seems that instead of further modifying and improving any formula to maximize the accuracy, identifying those who are very unlike to be accurately predicted by the formula, the "outliers", may be more important and perhaps more effective compared to formula optimization.…”

Section: Discussionmentioning

confidence: 98%

Factors Associated with the Underestimation of Manual CPAP Titration Pressure

et al. 2023

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During the SARS-CoV-2 pandemic, the use of in-laboratory positive airway pressure (PAP) titration studies was not routinely suggested. PAP pressure prediction calculations are emerging as alternative methods for the treatment of these patients. The underestimation of PAP titration pressure usually leads to unsatisfactory results for PAP therapy. This study aimed to evaluate the factors associated with the underestimation of PAP titration pressure when using PAP pressure prediction equations. Estimated PAP pressure formulas based on body mass index (BMI) and apnea-hypopnea index (AHI) were chosen to validate the accuracy of equations in the successful prediction of titration pressure. Among 341 adult patients diagnosed with obstructive sleep apnea (OSA) by overnight polysomnography (PSG) and who received overnight PAP titration in order to select a successful pressure, the mean age of the total subjects was 55.4 years old and 78.9% of patients were male. The average BMI and AHI scores were 27.1 ± 4.8 and 37 ± 21.7, respectively. After multivariate stepwise regression analysis, the odds ratio of participants with a pretitration AHI was 1.017 (95% CI: 1.005–1.030). Only the severity of OSA was significantly different between the underestimated group and the adequately assessed group. In conclusion, a high AHI, but not BMI, is associated with an underestimated CPAP titration pressure in adult patients with OSA.

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Predictive Formulas for CPAP Titration; a Comparison and Reassessment

Cited by 2 publications

References 0 publications

Mathematical Equations to Predict Positive Airway Pressures for Obstructive Sleep Apnea: A Systematic Review

Mathematical Equations to Predict Positive Airway Pressures for Obstructive Sleep Apnea: A Systematic Review

Factors Associated with the Underestimation of Manual CPAP Titration Pressure

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