Evidence map›Paper›PMID 38664650›Full record

ArticleBMC pediatrics2024

The current clinical landscape of neonatal respiratory failure in Jiangsu Province of China: patient demographics, NICU treatment interventions, and patient outcomes.

Na Wang, Ke-Yu Lu, Shan-Yu Jiang, Hong-Wei Wu, Rui Cheng, Zhao-Jun Pan, Huai-Yan Wang, Jiangsu Provincial Collaborative Study Group for Neonatal Respiratory Diseases

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in BMC pediatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.3field-weighted citation impact, top 20% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
  2. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 1 country.

Na Wang *Department of Neonatology, The Affiliated Suqian First People's Hospital of Nanjing Medical University, Suqian, Jiangsu, China.
Ke-Yu LuDepartment of Neonatology, Children's Hospital of Nanjing Medical University, Gulou District, No.72, Guangzhou Road, Nanjing, 210008, Jiangsu, China.
Shan-Yu Jiang *Department of Neonatology, Wuxi Maternity and Child Health Care Hospital, Wuxi, Jiangsu, China.
Hong-Wei Wu *Department of Neonatology, Xuzhou Children's Hospital Affiliated to Xuzhou medical University, Xuzhou, Jiangsu, China.
Rui ChengDepartment of Neonatology, Children's Hospital of Nanjing Medical University, Gulou District, No.72, Guangzhou Road, Nanjing, 210008, Jiangsu, China. chengrui350@163.com.
Zhao-Jun PanDepartment of Neonatology, Huai'an maternal and child health care center, Huai'an City, No. 104, Renmin South Road, Qingpu District, Jiangsu, 223001, China. 1276684451@qq.com.
Huai-Yan WangDepartment of Neonatology, Changzhou Maternity and Child Health Care Hospital, Nanjing Medical University, No.16 Dingxiang Road, Changzhou, 213003, Jiangsu, China. czwhy522@163.com.
Jiangsu Provincial Collaborative Study Group for Neonatal Respiratory Diseases
Nanjing Maternity and Child Health Care Hospital · CNXuzhou Medical College · CNNanjing Children's Hospital · CNNanjing Medical University · CN

Funding

National Natural Science Foundation of China No. 82171705Suqian Sci&Tech Program No.SY202303the Nanjing Medical University Special Disease Cohort Foundation grant number NMUC2020043
6 · The paper itself

Abstract

introductionNeonatal respiratory failure (NRF) is a serious condition that often has high mortality and morbidity, effective interventions can be delivered in the future by identifying the risk factors associated with morbidity and mortality. However, recent advances in respiratory support have improved neonatal intensive care units (NICUs) care in China. We aimed to provide an updated review of the clinical profile and outcomes of NRF in the Jiangsu province.

methodsInfants treated for NRF in the NICUs of 28 hospitals between March 2019 and March 2022 were retrospectively reviewed. Data collected included baseline perinatal and neonatal parameters, NICU admission- and treatment-related data, and patient outcomes in terms of mortality, major morbidity, and survival without major morbidities.

resultsA total of 5548 infants with NRF were included in the study. The most common primary respiratory disorder was respiratory distress syndrome (78.5%). NRF was managed with non-invasive and invasive respiratory support in 59.8% and 14.5% of patients, respectively. The application rate of surfactant therapy was 38.5%, while that of neonatal extracorporeal membrane oxygenation therapy was 0.2%. Mortality and major morbidity rates of 8.5% and 23.2% were observed, respectively. Congenital anomalies, hypoxic-ischemic encephalopathy, invasive respiratory support only and inhaled nitric oxide therapy were found to be significantly associated with the risk of death. Among surviving infants born at < 32 weeks of gestation or with a birth weight < 1500 g, caffeine therapy and repeat mechanical ventilation were demonstrated to significantly associate with increased major morbidity risk.

conclusionOur study demonstrates the current clinical landscape of infants with NRF treated in the NICU, and, by proxy, highlights the ongoing advancements in the field of perinatal and neonatal intensive care in China.

Indexed as

Intensive Care Units, NeonatalRespiratory Distress Syndrome, NewbornChinaExtracorporeal Membrane OxygenationFemaleHumansInfant, NewbornMalePulmonary SurfactantsRespiration, ArtificialRespiratory InsufficiencyRetrospective StudiesTreatment OutcomePulmonary SurfactantsMorbidityMortalityNeonatal intensive careNeonatologyRespiratory failure

Identifiers

PMID38664650
PMCPMC11044282
OpenAlexW4395677739

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.