This paper investigates the zero-shot multilingual capabilities of open-source Large Language Models (LLMs) for extracting comorbidity information from Italian Electronic Health Records (EHRs). The study reveals that these LLMs struggle to generalize across various diseases and do not perform as well as traditional pattern matching or human annotations in this specific healthcare use case.