I had my monthly visit to the clinic this past Thursday for labs. Right on time, I received a text that they were ready and used the Fresenius PatientHub to review the first results, and then download a PDF of the entire report. Nothing out of the ordinary thus far but wait. Here’s where it gets interesting.
I went to Google’s ever-improving NotebookLM where I uploaded the PDF and asked it to generate a podcast embedded below of my lab results. I also queried it about the most significant abnormalities present in my bloodwork. These follow:
●Low red blood cell count (RBC), hemoglobin, and hematocrit: These values are all significantly lower than the reference range, indicating anemia.
●High red blood cell distribution width (RDW): This suggests there is a wide variation in the size of the patient’s red blood cells, which is often seen in anemia.
●High glucose: This could indicate hyperglycemia, which may be a sign of diabetes or other metabolic disorders.
●High iron: This is unusual in the setting of anemia and may warrant further investigation.
●High transferrin saturation (Tsat) and serum iron, along with normal ferritin: This pattern can be seen in iron overload disorders, such as hemochromatosis. However, it is important to note that other factors can also influence iron studies, and further testing may be needed to confirm a diagnosis.
●High hemoglobin A1c (HbA1c): This reflects elevated average blood glucose levels over the past 2-3 months, further supporting the possibility of diabetes.
The podcast link follows:
The lab report used to generate the AI-driven response(s) is below:
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