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NCT00732537COMPLETEDanonymous

Inhaled Nitric Oxide in Neonates With Elevated A-aDO2 Gradients Not Requiring Mechanical Ventilation

Sponsor

Source record

University of Alabama at Birmingham

Phase

Source record

PHASE4

Modality

AI-normalized

small molecule

Target

AI-normalized

inhaled Nitric Oxide, Oxygen (>90% by hood) - standard therapy

Indication / condition

AI-normalized

Respiratory Failure

Intervention

Source record

inhaled Nitric Oxide, Oxygen (>90% by hood) - standard therapy

Source & freshness

Source record

NCT ID

NCT00732537

Original source

ClinicalTrials.gov

Source last updated

Aug 12, 2008

Ingested at

May 21, 2026

Internal sync

May 23, 2026

Model version

trialsignal-ai-v1

Normalized confidence

96%

Validation status

validated

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View original source fields

NCT ID

NCT00732537

Title

Inhaled Nitric Oxide in Neonates With Elevated A-aDO2 Gradients Not Requiring Mechanical Ventilation

Sponsor

University of Alabama at Birmingham

Status

COMPLETED

Phase

PHASE4

Condition raw

Respiratory Failure, Infant, Persistent Fetal Circulation

Condition normalized

Respiratory Failure, Infant, Persistent Fetal Circulation

Modality raw

small molecule

Modality normalized

small molecule

Target raw

inhaled Nitric Oxide, Oxygen (>90% by hood) - standard therapy

Target normalized

inhaled Nitric Oxide, Oxygen (>90% by hood) - standard therapy

Interventions

inhaled Nitric Oxide, Oxygen (>90% by hood) - standard therapy

Public preview

Source record

Inhaled nitric oxide (iNO) improves oxygenation in term infants with respiratory failure. However, iNO has been primarily used in infants receiving mechanical ventilation. This study is a pilot study to determine if iNO given into an oxygen hood is effective in improving oxygenation in term and near-term infants who have poor oxygenation but who are not yet mechanically ventilated.

AI-generated analysis supports research triage only. Verify source records, publications, sponsor disclosures and IP databases before making diligence decisions. Model: trialsignal-ai-v1.

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