Surrogate Predictions Research Articles

Computational and experimental study of JP-8, a surrogate, and its components in counterflow diffusion flames

Non-sooting counterflow diffusion flames have been studied both computationally and experimentally, using either JP-8, or a six-component JP-8 surrogate mixture, or its individual components. The computational study employs a counterflow diffusion flame model, the solution of which is coupled with arc length continuation to examine a wide variety of inlet conditions and to calculate extinction limits. The surrogate model includes a semi-detailed kinetic mechanism composed of 221 gaseous species participating in 5032 reactions. Experimentally, counterflow diffusion flames are established, in which multicomponent fuel vaporization is achieved through the use of an ultrasonic nebulizer that introduces small fuel droplets into a heated nitrogen stream, fostering complete vaporization without fractional distillation. Temperature profiles and extinction limits are measured in all flames and compared with predictions using the semi-detailed mechanism. These measurements show good agreement with predictions in single-component n-dodecane, methylcyclohexane, and iso-octane flames. Good agreement also exists between predicted and measured variables in flames of the surrogate, and the agreement is even better between the experimental JP-8 flames and the surrogate predictions.

Projection in surrogate decisions about life-sustaining medical treatments.

To honor the wishes of an incapacitated patient, surrogate decision makers must predict the treatment decisions patients would make for themselves if able. Social psychological research, however, suggests that surrogates' own treatment preferences may influence their predictions of others' preferences. In 2 studies (1 involving 60 college student surrogates and a parent, the other involving 361 elderly outpatients and their chosen surrogate decision maker), surrogates predicted whether a close other would want life-sustaining treatment in hypothetical end-of-life scenarios and stated their own treatment preferences in the same scenarios. Surrogate predictions more closely resembled surrogates' own treatment wishes than they did the wishes of the individual they were trying to predict. Although the majority of prediction errors reflected inaccurate use of surrogates' own treatment preferences, projection was also found to result in accurate prediction more often than counterprojective predictions. The rationality and accuracy of projection in surrogate decision making is discussed.

The accuracy of substituted judgments in patients with terminal diagnoses.

Patients' loved ones often make end-of-life treatment decisions, but the accuracy of their substituted judgments and the factors associated with accuracy are poorly understood. To assess the accuracy of judgments made by surrogate decision makers; ascertain the beliefs, practices, and clinical and sociodemographic factors associated with accuracy of surrogates' decisions; assess the preferences of patients for life-sustaining treatments; and compare differences in accuracy across diagnoses. Cross-sectional paired interviews. Outpatient practices of three university hospitals. 250 patients with terminal diagnoses of congestive heart failure, AIDS, amyotrophic lateral sclerosis, lung cancer, and chronic obstructive pulmonary disease (50 patient-surrogate pairs in each group) and 50 general medical patients and their surrogates. The accuracy of surrogate predictions was measured by using scales based on 10 potential treatments in each of three hypothetical clinical scenarios. Preferences varied according to mode of treatment and scenario. On average, surrogates made correct predictions in 66% of instances. Accuracy was better for the permanent coma scenario than for the scenarios of severe dementia or coma with a small chance of recovery (P < 0.001). In a binary logit model, the accuracy of substituted judgments was positively associated with the patient having spoken with the surrogate about end-of-life issues (odds ratio [OR], 1.9 [95% CI, 1.6 to 2.3]), the patient having private insurance (OR, 1.4 [CI, 1.1 to 1.7]), the surrogate's level of education (OR, 1.5 [CI, 1.2 to 1.9]), and the patient's level of education (OR, 1.7 [CI, 1.4 to 2.2]). Accuracy was negatively associated with the patient's belief that he or she would live longer than 10 years (OR, 0.6 [CI, 0.5 to 0.7]), surrogate experience with life-sustaining treatment (OR, 0.4 [CI, 0.3 to 0.5]), surrogate participation in religious services (OR, 0.67 [CI, 0.50 to 0.91]), and a diagnosis of heart failure (OR, 0.6 [CI, 0.5 to 0.8]). Age, ethnicity, marital status, religion, and advance directives were not associated with accuracy. The accuracy of substituted judgments is associated with multiple clinically apparent patient and surrogate factors. This information can help clinicians identify conditions under which substituted judgments are likely to be accurate or inaccurate and can help target populations for education designed to improve the accuracy of surrogate decision making.