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Chhikara, Raj S.

Publications and source records attributed to Chhikara, Raj S..

Cox Proportional Hazards Models for Modeling the Time to Onset of Decompression Sickness in Hypobaric Environments

In this paper we fit Cox proportional hazards models to a subset of data from the Hypobaric Decompression Sickness Databank. The data bank contains records on the time to decompression sickness (DCS) and venous gas emboli (VGE) for over 130,000 person-exposures to high altitude in chamber tests. The subset we use contains 1,321 records, with 87% censoring, and has the most recent experimental tests on DCS made available from Johnson Space Center. We build on previous analyses of this data set by considering more expanded models and more detailed model assessments specific to the Cox model. Our model - which is stratified on the quartiles of the final ambient pressure at altitude - includes the final ambient pressure at altitude as a nonlinear continuous predictor, the computed tissue partial pressure of nitrogen at altitude, and whether exercise was done at altitude. We conduct various assessments of our model, many of which are recently developed in the statistical literature, and conclude where the model needs improvement. We consider the addition of frailties to the stratified Cox model, but found that no significant gain was attained above a model that does not include frailties. Finally, we validate some of the models that we fit.

Thompson, Laura A.↗

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

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.

Thompson, Laura A.↗