How to use spaCy Matcher to create a pattern for rule-based matching for a sequence that is only interpreted as a single token

I am new to nlp and spaCy but I am using it for my project. I am trying to use spaCy's Matcher class to create a pattern to extract information from clinical summaries, specifically mentions of IQ scores. I want to use Matcher to extract sequences in the clinical summaries that occur frequently such as "IQ=68". Initially it seemed relatively straight forward and I created the following pattern:

pattern2 = [{"LOWER": "iq"}, {"TEXT": "=", "OP": "?"}, {"IS_DIGIT": True}]

However, this hasn't worked and I think this is because spaCy's tokenization is treating the sequence "IQ=68" as a single token and so pattern2 does not work. Is there a solution to this using Matcher? I have been using Matcher as it has been helpful with creating patterns that extract IQ from sequences such as "IQ is 68" as this is treated as three easy to identify tokens, where a pattern can be easily made and used.

Any help would be really appreciated! Apologies for any incorrect terms used, I am still learning!

Thanks.
Tarran

Ah I think I solved it by using regex, I had a hunch that regex would be useful but didn't know how to incorporate it into the pattern. But after some playing around and looking at the documentation and spaCy guides https://spacy.io/usage/rule-based-matching I came up with this solution and it works by the looks of it:

pattern2 = [{"LOWER": {"REGEX":"iq[=><]\d+"}}]

Hope this helps others using spaCy and Matcher class!