Based on the feature description, we have a categorical variable called ZSN_A which represents the presence of chronic heart failure in the anamnesis. The possible categories for this variable are ['there is no chronic heart failure', 'I stage', 'IIА stage', 'IIB stage'].

To analyze the relationship between the feature and the task of whether the myocardial infarction complications data of this patient shows chronic heart failure, we can look at the distribution of ZSN_A values for patients with and without chronic heart failure.

Let's assume that patients with chronic heart failure are labeled as "yes" and those without chronic heart failure are labeled as "no".

By analyzing the data, we can generate the dictionary as follows:

```json
{
	"no": ["there is no chronic heart failure"],  
	"yes": ["I stage", "IIА stage", "IIB stage"]
}
```

In this case, we have patients without chronic heart failure belonging to the "no" class, with the feature value of "there is no chronic heart failure". Patients with chronic heart failure belong to the "yes" class, with the possible values of "I stage", "IIА stage", and "IIB stage".

Please note that this analysis is based on the assumption that the provided categories are relevant to identifying chronic heart failure in the presence of myocardial infarction complications data.