Comput. Biol. Med. - Approach for streamlining measurement of complex physiological phenotypes of upper airway collapsibility.

Tópicos

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Resumo

LABELLED: The critical closing pressure (PCRIT), a quantitative assessment of upper airway collapsibility, is derived from pressure flow relationship during sleep. The analytic generation of the pressure flow relationships are non-standardized due to various regression models (linear, spline, median), breath characteristics (flow limited, non-flow limited) or known covariates (sleep stage, body position). We propose a GUI based PCRIT Analysis Software (PAS) to streamline PCRIT analysis and validate its reliability and accuracy compared to current analysis procedures.METHODS: Seventeen subjects underwent a physiology sleep study in which the PCRIT was determined during NREM sleep. Data analysis was performed independently using three paradigms: (1) PAS (Igor Pro; median regression), (2) non-graphic statistics application (SAS; spline regression), and (3) manual spreadsheet calculations (Excel; linear regression). The reliability and accuracy of the PAS was examined through the agreement between each approach using Bland-Altman plots of the mean difference and within-individual variation using intra-class correlation (ICC).RESULTS: There was no difference in the group mean values for PCRIT using the PAS (-1.7 ? 0.7 cm H2O) compared to spline regression (-1.6 ? 0.7 cm H2O; p=0.69) or linear regression (-2.1 ? 0.7 cm H2O; p=0.92). The Bland-Altman analysis did not demonstrate a systematic bias between the PAS and either approach. There was a mean difference of 0.39 ? 0.2 cm H2O between the PAS and linear regression approaches, with upper and lower limits of agreement of 1.81 and -1.02 cm H2O, respectively. The PAS and spline analyses demonstrated an even smaller mean difference of -0.10 ? 0.1cm H2O, with upper and lower limits of 0.90 and -1.08 cm H2O, respectively.CONCLUSION: PAS preserves the reliability and accuracy of the original PCRIT analysis methods while vastly improving their efficiency through graphic user interface and automation of analytic processes. Providing a standardized platform for physiologic data processing offers the ability to implement quality assurance and control procedures for multicenter studies as well as cost saving by improving the efficiency of complex repetitive tasks.

Resumo Limpo

label critic close pressur pcrit quantit assess upper airway collaps deriv pressur flow relationship sleep analyt generat pressur flow relationship nonstandard due various regress model linear spline median breath characterist flow limit nonflow limit known covari sleep stage bodi posit propos gui base pcrit analysi softwar pas streamlin pcrit analysi valid reliabl accuraci compar current analysi proceduresmethod seventeen subject underw physiolog sleep studi pcrit determin nrem sleep data analysi perform independ use three paradigm pas igor pro median regress nongraph statist applic sas spline regress manual spreadsheet calcul excel linear regress reliabl accuraci pas examin agreement approach use blandaltman plot mean differ withinindividu variat use intraclass correl iccresult differ group mean valu pcrit use pas cm ho compar spline regress cm ho p linear regress cm ho p blandaltman analysi demonstr systemat bias pas either approach mean differ cm ho pas linear regress approach upper lower limit agreement cm ho respect pas spline analys demonstr even smaller mean differ cm ho upper lower limit cm ho respectivelyconclus pas preserv reliabl accuraci origin pcrit analysi method vast improv effici graphic user interfac autom analyt process provid standard platform physiolog data process offer abil implement qualiti assur control procedur multicent studi well cost save improv effici complex repetit task

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