Patient: M.T., 44-year-old warehouse supervisor
Chief concern (Day 1): “Bad low-back pain after lifting a box.”
Home AI tool: Patient uses the health system’s portal symptom-checker chatbot. After entering “low back pain,”
“both legs tingling,” “can’t feel when wiping,” and “peeing less than usual,” the bot outputs “likely muscular
strain home care; clinic visit in 3–5 days.” No red-flag alert is displayed.
Course:
• Day 2–3: Pain worsens; bilateral sciatica, saddle numbness, and urinary retention (“I haven’t peed since
last night unless I strain”). The bot again recommends home care.
• Day 4 (ED): Patient febrile, hypotensive, confused. Bladder scan >1200 mL; purulent urine after
catheterization. MRI lumbar: massive central L4–L5 disc herniation compressing cauda equina.
• Labs: Leukocytosis, lactate 5.2 mmol/L, creatinine bump.
• Outcome: Despite urgent decompression and broad-spectrum antibiotics/ICU care, the patient develops
uroseptic shock with multi-organ failure and dies on Day 6.
Studies show online/AI symptom-checkers vary widely in diagnostic/triage accuracy and may miss
emergencies; WHO and AHRQ urge caution and human oversight for clinical AI
Gerontology Clinical Experience 1
Weekly Clinical Experience 1 Describe your clinical experience for this week with a 65 year old female with a history of uncontrolled diabetes · Did you face any challenges, any success? If so, what were they? · Describe the assessment of a patient, detailing the signs and symptoms (S&S), assessment,