Modeling Grade IV Gas Emboli using a Limited Failure Population Model with Random Effects

Details Modeling Grade IV Gas Emboli using a Limited Failure Population Model with Random Effects Modeling Grade IV Gas Emboli using a Limited Failure Population Model with Random Effects

May 2002

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2002stin...0244432t&link_type=abstract

Technical Report, NASA/TP-2002-210781; S-891; NAS 1.60:210781

Mathematics

Aeroembolism, Decompression Sickness, Goodness Of Fit, Random Processes, Parameter Identification, Mathematical Models, Censored Data (Mathematics), Denitrogenation, Extravehicular Activity, Data Correlation

Scientific paper

Venous gas emboli (VGE) (gas bubbles in venous blood) are associated with an increased risk of decompression sickness (DCS) in hypobaric environments. A high grade of VGE can be a precursor to serious DCS. In this paper, we model time to Grade IV VGE considering a subset of individuals assumed to be immune from experiencing VGE. Our data contain monitoring test results from subjects undergoing up to 13 denitrogenation test procedures prior to exposure to a hypobaric environment. The onset time of Grade IV VGE is recorded as contained within certain time intervals. We fit a parametric (lognormal) mixture survival model to the interval-and right-censored data to account for the possibility of a subset of "cured" individuals who are immune to the event. Our model contains random subject effects to account for correlations between repeated measurements on a single individual. Model assessments and cross-validation indicate that this limited failure population mixture model is an improvement over a model that does not account for the potential of a fraction of cured individuals. We also evaluated some alternative mixture models. Predictions from the best fitted mixture model indicate that the actual process is reasonably approximated by a limited failure population model.

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