Evidence map›Paper›PMID 41023082›Full record

ArticleScientific reports2025

Nomogram for predicting the success rate of sedation with intranasal dexmedetomidine in paediatric nonpainful diagnostic procedures: a retrospective study.

Huatian Lin, Lihua Gao, Ningning Cui, Guangwu Liao, Xueqing Wang, Taohua Peng, Yuetao Xie

Abstract read
In one paragraph

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

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Huatian LinDepartment of Anesthesiology, Shenzhen Children's Hospital, Yitian Road 7019, Shenzhen, 518038, China.
Lihua GaoDepartment of Anesthesiology, Shenzhen Children's Hospital, Yitian Road 7019, Shenzhen, 518038, China.
Ningning CuiDepartment of Anesthesiology, Shenzhen Children's Hospital, Yitian Road 7019, Shenzhen, 518038, China.
Guangwu LiaoDepartment of Anesthesiology, Shenzhen Children's Hospital, Yitian Road 7019, Shenzhen, 518038, China.
Xueqing WangDepartment of Anesthesiology, Shenzhen Children's Hospital, Yitian Road 7019, Shenzhen, 518038, China.
Taohua PengDepartment of Anesthesiology, Shenzhen Children's Hospital, Yitian Road 7019, Shenzhen, 518038, China.
Yuetao XieDepartment of Anesthesiology, Shenzhen Children's Hospital, Yitian Road 7019, Shenzhen, 518038, China. bestxyt@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Intranasal dexmedetomidine (IN DEX) is being increasingly used for sedation in children undergoing nonpainful diagnostic procedures. Successful procedural sedation facilitates rapid and accurate clinical diagnosis and treatment, thereby improving clinical management efficiency. As the success rate of sedation is influenced by multiple factors, enhancing sedation success, reducing procedure-related risks, and minimizing adverse events are critical clinical priorities. In this study, children aged 12-72 months (1-6 years) who underwent outpatient examinations requiring sedation with IN DEX were included. Data were extracted from the electronic medical records system of the outpatient sedation suite. The training dataset was analysed using least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression to develop a nomogram-based clinical predictive model. Model performance was evaluated via receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA), with validation performed using a separate validation dataset. The developed nomogram, which incorporates napping before sedation, respiratory diseases, snotty before sedation, neurological diseases, sedation history, sedation duration, and sedation method, exhibited moderate predictive value (AUC = 0.833), favourable calibration, and enhanced clinical benefit. This study establishes a clinical prediction nomogram that can assist anaesthesiologists in the outpatient sedation suite to customize and optimize sedation plans, thereby improving the sedation success rate of IN DEX, enhancing the efficiency of nonpainful diagnostic procedures, and providing substantial clinical benefits.

Indexed as

DexmedetomidineHypnotics and SedativesNomogramsProcedural SedationAdministration, IntranasalChildChild, PreschoolFemaleHumansInfantMaleRetrospective StudiesROC CurveDexmedetomidineHypnotics and SedativesIntranasal dexmedetomidineNomogramPaediatric patientsPredictive modelProcedural sedation

Identifiers

PMID41023082
PMCPMC12480645

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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.