Evidence map›Paper›PMID 41790660›Full record

ArticleMedicine2026

Development and validation of a nomogram for predicting the probability of successful extubation among patients with severe stroke receiving mechanical ventilation.

Meiqi Liu, Xuehui Zhang, Yuanqing Li, Xiuping Zhang, Anhao Liu, Chunyuan Zhao, Ranran Yan, Dongmei Wu

Abstract readValidation Study
In one paragraph

Article in Medicine, 2026. 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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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

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0 citing papers 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.

Meiqi LiuShandong First Medical University (Shandong Academy of Medical Sciences), School of Nursing, Jinan City, Shandong Province, China.ORCID 0009-0009-3279-657
Xuehui ZhangJining Medical University, School of Nursing, Jining City, Shandong Province, China.
Yuanqing LiShandong First Medical University (Shandong Academy of Medical Sciences), School of Nursing, Jinan City, Shandong Province, China.
Xiuping ZhangJining Medical University, School of Continuing Education, Jining City, Shandong Province, China.
Anhao LiuShandong First Medical University (Shandong Academy of Medical Sciences), School of Nursing, Jinan City, Shandong Province, China.
Chunyuan ZhaoJining Medical University, School of Nursing, Jining City, Shandong Province, China.
Ranran YanThe First ICU Ward, Affiliated Hospital of Jining Medical College, Jining City, Shandong Province, China.
Dongmei WuJining Medical University, School of Nursing, Jining City, Shandong Province, China.ORCID 0009-0001-8747-1299

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To address the lack of stroke-specific risk prediction tools for extubation failure, this study aimed to develop and validate a multidimensional nomogram integrating neurological function, respiratory parameters, and systemic status, to provide a basis for individualized clinical decision-making regarding extubation. We retrospectively enrolled 324 mechanically ventilated stroke patients admitted to the intensive care unit of Jining Medical University Affiliated Hospital from January 2022 to May 2024 as the training cohort, and 81 patients from June to December 2024 as the temporal validation cohort. The least absolute shrinkage and selection operator regression was used to screen risk factors from 43 candidate predictors. A nomogram was constructed using multivariate logistic regression. Model performance was evaluated using the receiver operating characteristic curve, calibration curve, decision curve analysis, and clinical impact curve. The developed nomogram integrates neurological function and dynamic respiratory parameters and can effectively identify intensive care unit stroke patients at high risk of extubation failure, potentially providing a tool for optimizing respiratory support strategies. The extubation failure rates were 46.6% (151/324) in the training cohort and 48.1% (39/81) in the validation cohort. Baseline data were well matched between cohorts. Least absolute shrinkage and selection operator regression identified 7 independent predictors. Multivariate logistic regression showed that the National Institutes of Health Stroke Scale score (odds ratio [OR] = 1.09, 95% confidence interval [CI]: 1.03-1.15, P = .003), Acute Physiology and Chronic Health Evaluation II score (OR = 1.08, 95% CI: 1.03-1.13, P = .001), duration of mechanical ventilation (OR = 1.06, 95% CI: 1.02-1.10, P = .001), fraction of inspired oxygen (FiO2) (OR = 1.06, 95% CI: 1.02-1.11, P = .004), hemoglobin level (OR = 0.98, 95% CI: 0.97-0.99, P = .005), ischemic stroke type (OR = 0.47, 95% CI: 0.26-0.85, P = .012), and history of neurological disease (OR = 0.46, 95% CI: 0.27-0.77, P = .004) were independent influencing factors for extubation failure. The nomogram demonstrated areas under the curve of 0.789 (95% CI: 0.740-0.837) and 0.745 (95% CI: 0.639-0.851) in the training and validation cohorts, with sensitivities/specificities of 74.8%/82.1% and 70.5%/77.6%, respectively. The calibration curve showed minimal deviation (Hosmer-Lemeshow test P = .325), and decision curve analysis indicated a clinical net benefit across a threshold probability range of 15%-98%.

Indexed as

Airway ExtubationNomogramsRespiration, ArtificialStrokeAgedFemaleHumansIntensive Care UnitsLogistic ModelsMaleMiddle AgedRetrospective StudiesRisk FactorsROC Curveextubation failureintensive caremechanical ventilationnomogramprediction modelstroke

Identifiers

PMID41790660
PMCPMC12975247

What Socratic holds

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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 Socratic graph.