Discussion of Leon J. Saul's Article, Sudden Death at Impasse

One of the rules in statistics and in the laws of probability is that the likelihood of two events coinciding may be found by multiplying together the likelihood of each event. If, for example, the likelihood of a man dying in his 45th year of a sudden heart attack is one in a hundred thousand and the likelihood of his being previously in utter despair is one in a thousand (both generous figures), then the two events will coincide with a frequency of one in a hundred million. But there are several million men in this country every year who are age 45, so that every few years, entirely through the operation of chance and with no cause and effect relationship, we should expect a man of 45 to reach a hopeless impasse and suddenly drop dead of a heart attack. The same holds true for a man of 40, and in status asthmaticus for a woman of 33. In fact, since we are equally impressed when a man or woman of any age becomes acutely depressed and drops dead of any “psychosomatic” cause, we should keep in mind that adding up the probabilities would quite likely lead us to expect events of this nature to occur by happenstance alone every few days somewhere in

the country. We would expect, further, that now and then a physician would come to know not only the facts about the death but also something of the emotional antecedents and wonder about the relationship. Rarely, it would seem, a psychoanalyst would find himself in the picture, or would be brought in, and he would not wonder, he would seem to know.

In courses in formal logic, one learns of “the error of the positive instance.” The Negro who commits rape is seen as “typical”; Negroes who do not commit rape and white men who do are ignored—these are negative instances. There are surely a great many men and women who reach impasse and do not die of heart attacks and status asthmaticus, and huge numbers who do die of these disorders while in a joyful state or peacefully asleep in bed. These considerations and the statistical o