Based on prior knowledge, we can analyze the relationship between the feature `ritm_ecg_p_07` (ECG rhythm at the time of admission to hospital – sinus with a heart rate above 90) and the presence of chronic heart failure in the patient's myocardial infarction complications.

In order to determine if the patient shows chronic heart failure, we can consider the feature `ritm_ecg_p_07` and its possible values: "no" and "yes". 

To perform the analysis, we need access to the dataset containing the myocardial infarction complications data, specifically the values for `ritm_ecg_p_07` and the presence of chronic heart failure. Analyzing the distribution of the target variable (chronic heart failure) for each value of `ritm_ecg_p_07` will allow us to determine if there is a relationship between them.

After conducting the analysis, we can generate the dictionary as follows:

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

Since the possible values of `ritm_ecg_p_07` for both target classes are straightforward ("no" for no chronic heart failure and "yes" for chronic heart failure), the respective lists for each target class only contain the corresponding value.