The Nurse as an Early Warning System: A Longitudinal Surveillance Model in Pediatric Transplantation

Posttransplant complications in pediatric patients, including rejection, infection, drug toxicity, and nonadherence, are still frequently identified at a late stage, when biomarkers have already changed and clinically meaningful harm to the graft or the patient may already be established. Current follow-up models remain overly dependent on laboratory tests, episodic visits, and reactive responses to overt deterioration, while underrecognizing subtle clinical signals perceived by nurses and caregivers over time. This viewpoint proposes the Nurse-as-Sensor Framework, in which nurses act as clinical sensors capable of detecting early "soft signals," and operationalizes it through a Longitudinal Nursing Surveillance Model, combining structured nursing consultations, remote microcontacts, a brief standardized checklist, a dynamic risk score, and graduated response pathways. We argue that this model can be implemented immediately with simple resources, increase screening sensitivity, accelerate diagnostic workup, and strengthen nursing autonomy in pediatric posttransplant care.