Evidence map›Paper›PMID 40394686›Full record

ArticleJournal of cardiothoracic surgery2025

miR-221-3p, arterial blood gas, and lung ultrasound: a multimodal approach for predicting neonatal respiratory distress syndrome outcomes.

Meixin Liang, Tao Pan, Yanan Hou, Zhihua Liu, Zhiqiang Liu, Jing Mo, Yang Zhang, Jinfeng Wen

Abstract read
In one paragraph

Article in Journal of cardiothoracic surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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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.

Meixin Liang *Department of Ultrasonography Medicine, Qinzhou Maternal and Child Health Care Hospital, Qinzhou, Guangxi, China.
Tao Pan *Department of Ultrasound, Seventh Medical Center of Chinese PLA General Hospital, Beijing, 100700, China.
Yanan HouShengli Oilfield Central Hospital, Paediatric Ward 1, No.31, Jinan Road, Dongying District, Dongying, 257000, Shandong, China.
Zhihua LiuShengli Oilfield Central Hospital, Paediatric Ward 1, No.31, Jinan Road, Dongying District, Dongying, 257000, Shandong, China.
Zhiqiang LiuShengli Oilfield Central Hospital, Paediatric Ward 1, No.31, Jinan Road, Dongying District, Dongying, 257000, Shandong, China.
Jing MoOutpatient Department, Shengli Oilfield Central Hospital, Dongying, Shandong, China.
Yang ZhangShengli Oilfield Central Hospital, Paediatric Ward 1, No.31, Jinan Road, Dongying District, Dongying, 257000, Shandong, China. Zhangyangslchos@163.com.
Jinfeng WenDepartment of Ultrasound Medicine, Huanggang Central Hospital, No.126, Qi'an Avenue, Huanggang City, 438000, Hubei Province, China. Wenjinfenghg@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNeonatal respiratory distress syndrome (NRDS) is one of the critical illnesses causing early death in infants due to alveolar surface-active substance deficiency, and the prognosis may show varying degrees of sequelae. Some miRNAs are valuable in the prognosis of NRDS infants. The objective of this research was to assess the predictive value of combining the three factors on the prognosis of NRDS infants by analyzing miR-221-3p levels, arterial blood gas analysis parameters and lung ultrasound (LUS) scores in NRDS infants with good and poor prognosis.

methodsSerum miR-221-3p levels were measured by qRT-PCR. Effect of miR-221-3p expression in prognosis of NRDS infants using Kaplan-Meier curve and COX analyses. Arterial blood gas parameters were analyzed, as well as LUS score was recorded for NRDS infants. Role of miR-221-3p combined with arterial blood gas parameters and LUS score in prognosis of NRDS infants was assessed by ROC curves. Pearson correlation was applied to assess the association of miR-221-3p with arterial blood gas analysis parameters and LUS score.

resultsSerum miR-221-3p was notably greater in NRDS infants than in healthy newborns. High miR-221-3p level was related to poor prognosis for NRDS infants. pH and PaO

conclusionsElevated miR-221-3p may be related to poor survival outcomes in NRDS infants. miR-221-3p in combination with arterial blood gas parameters and LUS score has a high accuracy in determining the survival outcome of NRDS infants and may be a useful tool for clinical NRDS prognosis.

Indexed as

Blood Gas AnalysisLungMicroRNAsRespiratory Distress Syndrome, NewbornBiomarkersFemaleHumansInfant, NewbornMalePredictive Value of TestsPrognosisROC CurveUltrasonographyBiomarkersMicroRNAsArterial blood gas analysisLUS scoremiR-221-3pNRDSPrognosis

Identifiers

PMID40394686
PMCPMC12093823

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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.