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Close Loop Smart Weaning for INO With PPHN

NCT: NCT06832163 · RECRUITING

NCT識別子NCT06832163
ステータスRECRUITING
開始日2025-10-01
完了2026-12-31
SponsorChildren's Hospital of Fudan University (OTHER)
First posted
Last updated

概要

In contemporary clinical practice concerning the administration of inhaled nitric oxide (iNO) within neonatal intensive care units (NICUs), a stepwise reduction approach is frequently employed in accordance with established neonatal guidelines. Nonetheless, the comparative advantages of a linear reduction strategy-characterized by a gradual decrease in inhalation concentration-over the traditional stepwise method in terms of efficacy and safety have yet to be conclusively established. Furthermore, existing iNO delivery devices necessitate that healthcare professionals manually adjust parameters at intervals dictated by the patient's condition. This reliance on subjective clinical judgment often results in variability and a lack of standardization in the duration of the weaning process. Additionally, the protracted and intricate nature of the weaning procedure considerably heightens the workload for healthcare staff. Importantly, the development of a scientifically grounded, standardized, and real-time feedback mechanism for weaning may enhance clinical outcomes for patients and mitigate the risks associated with inappropriate weaning practices or inconsistent manual interventions. Consequently, this study seeks to leverage the newly introduced "intelligent closed-loop weaning" feature of the latest generation of iNO devices to facilitate automated linear concentration reduction during the weaning process. This innovation aims to alleviate the burden on healthcare personnel while establishing a more standardized and scientifically robust weaning protocol. However, it is noteworthy that there is currently a lack of clinical evidence, both domestically and internationally, regarding the safety and efficacy of this device's weaning protocol, underscoring the urgent need to validate its safety and effectiveness in real-world clinical settings.

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