Evidence map›Paper›PMID 41327240›Full record

ArticleItalian journal of pediatrics2025

Nomogram-based prediction model for extubation failure in preterm infants with invasive mechanical ventilation.

Chao Tan, Ying Sui, Lili Wang

Abstract read
In one paragraph

Article in Italian journal of pediatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Chao TanDepartment of Pediatrics, Huzhou Maternity & Child Health Care Hospital, Huzhou, Zhejiang Province, China.
Ying SuiDepartment of Pediatrics, Huzhou Maternity & Child Health Care Hospital, Huzhou, Zhejiang Province, China. babyying19850204@163.com.
Lili WangDepartment of Pediatrics, First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China. wllwywz@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAchieving early and successful extubation was a critical aspect in the respiratory management of preterm infants. This study aims to identify variables for assessment and establish a predictive model to estimate preterm infants who may experience extubation failure following invasive mechanical ventilation.

methodsA retrospective analysis was conducted on 265 very low birth weight infants (VLBWIs) with neonatal respiratory distress syndrome (NRDS) who received invasive mechanical ventilation and intratracheal surfactant administration in the neonatal intensive care unit (NICU) of a tertiary hospital. Infants were divided into an extubation failure group and an extubation success group based on whether reintubation was required within 72 h after extubation. Independent risk factors for extubation failure were identified, and a nomogram prediction model was constructed. Additionally, 71 VLBWIs from another tertiary hospital, meeting the same inclusion criteria, were used as an external validation dataset to assess the model’s performance.

resultsGestational age, birth weight, patent ductus arteriosus (PDA) diameter, hematocrit (Hct) before extubation, and sepsis were identified as independent risk factors for extubation failure. The nomogram model based on these factors achieved a concordance index of 0.888 for internal validation (training set) and 0.862 for external validation (independent dataset), indicating robust consistency between predicted and observed probabilities. The sensitivity and specificity of the model were 89.8% and 77.8%, respectively, with an area under the receiver operating characteristic curve (AUC) of 0.888 (95% CI: 0.845–0.931). Calibration curves demonstrated a high degree of agreement between predicted and actual probabilities.

conclusionGestational age, birth weight, PDA diameter, hematocrit, and sepsis are key factors influencing initial extubation failure in preterm infants. The nomogram model based on these factors demonstrates excellent predictive accuracy and provides valuable guidance for clinical decision-making regarding extubation.

Indexed as

Airway ExtubationNomogramsRespiration, ArtificialRespiratory Distress Syndrome, NewbornFemaleGestational AgeHumansInfant, NewbornInfant, PrematureInfant, Very Low Birth WeightIntensive Care Units, NeonatalMalePrediction AlgorithmsRetrospective StudiesRisk AssessmentRisk FactorsExtubation failureNomogram prediction modelRisk factorsVery low birth weight

Identifiers

PMID41327240
PMCPMC12667049

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.