Based on prior knowledge, it is difficult to know for certain how the presence of paroxysms of atrial fibrillation on an ECG at the time of admission to the hospital (n_r_ecg_p_05) relates to the presence of chronic heart failure in a patient.

To analyze the relationship, we would need access to data and perform statistical tests or machine learning models. However, we can still create a dictionary that provides the available information based on the given feature description.

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

Since the feature is categorical, it has two possible values: "no" and "yes". According to the description, these are the categories representing the presence or absence of paroxysms of atrial fibrillation on an ECG. 

Even though it is difficult to predict the relationship between this feature and chronic heart failure, we can still create a dictionary that lists the possible values of the feature for each target class.