Recombinant fragment of human surfactant protein D to prevent neonatal chronic lung disease (RESPONSE): a protocol for a phase I safety trial in a tertiary neonatal unit

Authors

Neil Marlow (ORCID: https://orcid.org/0000-0001-5890-2953)
Kathy Chant (ORCID: https://orcid.org/0009-0007-4276-4622)
Reena Bhatt (ORCID: https://orcid.org/0000-0002-7537-9911)
Jens Madsen (ORCID: https://orcid.org/0000-0003-1664-7645)
Howard Clark (ORCID: https://orcid.org/0000-0001-7354-2028)
T. Castillo Hernandez (ORCID: https://orcid.org/0000-0002-9492-855X)
Hakim-Moulay Dehbi

Institutions

University College Hospital (GB)
London Women's Clinic (GB)
University College London (GB)

Publication Details

Journal: BMJ Open
Published: 2024-08-01
DOI: https://doi.org/10.1136/bmjopen-2024-086394
Citations: 3
Primary Topic: Neonatal Respiratory Health Research
Type: article
Field-Weighted Citation Impact: 1.26

Funders

University College London Hospitals NHS Foundation Trust
Medical Research Council

Controls

|||

ALL TIME

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

article

Recombinant fragment of human surfactant protein D to prevent neonatal chronic lung disease (RESPONSE): a protocol for a phase I safety trial in a tertiary neonatal unit

Neil Marlow, Kathy Chant, Reena Bhatt, Jens Madsen et al.

Aug 1, 2024

3 citations

BMJ Open

Neonatal Respiratory Health Research

1.26

article

Recombinant fragment of human surfactant protein D to prevent neonatal chronic lung disease (RESPONSE): a protocol for a phase I safety trial in a tertiary neonatal unit

Neil Marlow, Kathy Chant, Reena Bhatt, Jens Madsen, Howard Clark, T. Castillo Hernandez, Hakim-Moulay Dehbi

August 1, 2024article en

3 citations

Abstract

No abstract available for this paper.

BMJ OpenVol. 14(8)

University College Hospital (GB), London Women's Clinic (GB), University College London (GB)

University College London Hospitals NHS Foundation Trust, Medical Research Council

Good health and well-being

Openalex Percentile: Top 19%

Neonatal Respiratory Health Research

1.26

DOI Open Access PDF OpenAlex

AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.