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Prepare questions for a child's rare eye diagnosis with Claude Code

WorkedEvidence: Described by posterPosted Last checked

Claude Code helped Alessandro Rodi prepare doctor questions before the clinic confirmed a son's Coats disease, a rare eye condition.

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  4. Send it, then read the answer before acting on it.
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Prompt

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What the prompt labels mean

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My four-year-old son was sent to an eye clinic after a pediatrician found poor vision in the right eye. I've put the medical data, a timeline of events and the exam images in this folder. Read everything, tell me which conditions the findings could fit, and write a list of questions to ask the doctors at tomorrow's appointment.

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Sends the Recreated prompt shown above. ChatGPT and Grok open with it filled in, and ChatGPT may send it straight away. Gemini and Claude open empty, so we copy the prompt for you to paste. Every button also copies it.

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Optional stronger version

Our rewrite with extra checks. The poster didn't test it.

Before you start, ask me 1–3 short questions about the details below and wait for my answers. Once I've answered, confirm the plan in one line and run the whole task start to finish.

Goal: Help me understand a family member's test results and prepare good questions for the specialist, without treating anything as a diagnosis.

Questions to ask me first:
- Who is the patient (age), and what did the doctors find so far?
- When is the next appointment, and with which specialist?
- Which records and images do you have?

Inputs (fill in or confirm):
- Patient age and main problem: [AGE / PROBLEM]
- Timeline of events and visits: [TIMELINE]
- Reports, test results and images: [FILES]
- Next appointment: [DATE / SPECIALIST]

Rules:
- Explain findings in plain language and say which record each point comes from.
- List possible explanations the findings could fit, and say what would support or rule out each one.
- Don't present any condition as the diagnosis; the doctors examine the patient and decide.
- If you quote statistics, say where they come from and that they may not fit this patient.

Checkpoint: Before the question list, show me your plain-language summary so I can correct anything you misread.

If you get stuck: If an image or report is unreadable or missing, tell me instead of guessing.

Verify before you finish: Check every claim against the records I gave you and mark anything that is general knowledge rather than from the records.

Output: A short plain-language summary, possible explanations with what would confirm each, and a numbered list of questions for the doctor.

Done when: I have a clear list of questions to bring to the appointment.

AI tool

Claude Code

Outcome

During a routine check on February 13, 2026, a pediatrician noticed that Alessandro Rodi's four-year-old son couldn't see properly from the right eye. Weeks of specialist visits followed, and the first suspicion was damage from a hard hit to the face months earlier. The evening before a results appointment at the Zurich University Hospital eye clinic, Rodi put the medical data, a timeline of events and the exam images in a folder and gave it all to Claude Code. Claude pointed to Coats disease, a rare condition unrelated to trauma, and helped Rodi prepare questions for the doctors. The next day, after four more hours of checks, the doctors confirmed Coats disease without Rodi mentioning it. Rodi kept using Claude to research the condition and walked into each appointment with organized questions, which made the conversations more productive.

Evidence: Described by posterThe person describes what happened in words, without screenshots or video.

Source

Posted
by Alessandro Rodi (personal blog)
Last checked
Method:
How we verify

https://coorasse.com/blog/how-ai-helped-me-prepare-for-my-sons-diagnosis/

Context: Claude's outcome statistics were more pessimistic than the surgeon's assessment of this case. Rodi calls AI a research assistant: the doctors made the diagnosis and the treatment decisions.

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