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In developed countries, sudden infant death syndrome (SIDS) is the most common cause of death for infants between 1 month and 1 year of age. The etiology of SIDS is likely to be multifactorial, and current paradigms often describe three overlapping elements of risk. Those elements are a critical developmental period, a vulnerable infant, and one or more exogenous stressors. In the triple-risk model, SIDS infants are described as having an underlying vulnerability in cardiorespiratory control in the central nervous system during a critical period when autonomic control is developing. This vulnerability might affect the response to exogenous stressors, including prone sleeping position, hypoxia, and increased carbon dioxide. In the common bacterial hypothesis and fatal triangle, the focus is on the stressors. In the first, a combination of common respiratory infections can cause SIDS in an infant during a developmentally vulnerable period. This theory also includes 3 factors of vulnerability: a genetic predisposition, a vulnerable developmental age, and infectious stressors. In the fatal triangle theory, infection, inflammation, and genetics each play a role in triggering a SIDS fatality. From our work in an animal model, we have found that rat pups die from a combination of infectious insults during a critical time of development. This is exacerbated by perinatal nicotine exposure, a condition shown to alter the autonomic response in exposed offspring. We are proposing that shock and cardiovascular collapse is a key element that links these theories. [ABSTRACT FROM AUTHOR]

The article presents a study seeking to qualify and compare the survival expectations of patients with heart failure to model-predicted life expectancy in order to identify discrepancies in prognosis. The design and setting of the prospective face-to-face survey of heart failure disease patients and the use of model-predicted life expectancy based on the Seattle Heart Failure Model are described. The outcomes measured include life-expectancy ratio, defined as the ratio of model-predicted to patient-predicted life expectancy. Results showed that ambulatory heart failure patients significantly overestimated their life expectancy compared to model-predictions for survival.