Based on prior knowledge, we can analyze the relationship between the feature "B_BLOK_S_n" and the task of determining whether the patient has chronic heart failure.

To analyze this relationship, we can look at the distribution of the feature values for each target class (yes and no).

Here is the dictionary with the analysis:

```json
{
    "no": ["no"],
    "yes": ["yes"]
}
```

Explanation:
- For the target class "no" (patients without chronic heart failure), the only possible value for the feature "B_BLOK_S_n" is "no". This means that patients without chronic heart failure do not use beta-blockers in the ICU.
- For the target class "yes" (patients with chronic heart failure), the only possible value for the feature "B_BLOK_S_n" is "yes". This indicates that patients with chronic heart failure have used beta-blockers in the ICU.

Therefore, based on this analysis, it can be concluded that the feature "B_BLOK_S_n" is directly related to the task of determining chronic heart failure in the myocardial infarction complications data, with "yes" indicating the presence of chronic heart failure and "no" indicating its absence.