Evidence map›Paper›PMID 42037697›Full record

ArticleFrontiers in neurology

Predictive accuracy of diaphragm ultrasound and diaphragmatic rapid shallow breathing index combined assessment for successful weaning in neurocritical patients on mechanical ventilation.

Liping Liao, Ying Gao, Lei Xu, Peng Chen, Ke Wang, Yongbing Deng, Xiaosu Wu, Cui Huang

Abstract read
In one paragraph

Article in Frontiers in neurology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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.

Liping Liao *School of Nursing, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
Ying Gao *Department of Nursing, Chongqing Emergency Medical Center, Chongqing, China.
Lei XuDepartment of Neurosurgery, Chongqing Emergency Medical Center, Chongqing, China.
Peng ChenDepartment of Neurosurgery, Chongqing Emergency Medical Center, Chongqing, China.
Ke WangDepartment of Neurosurgery, Chongqing Emergency Medical Center, Chongqing, China.
Yongbing DengDepartment of Neurosurgery, Chongqing Emergency Medical Center, Chongqing, China.
Xiaosu WuDepartment of Neurosurgery, Chongqing Emergency Medical Center, Chongqing, China.
Cui HuangDepartment of Neurosurgery, Chongqing Emergency Medical Center, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study explores the predictive value of diaphragm ultrasound combined with the Diaphragmatic Rapid Shallow Breathing Index (D-RSBI) in determining weaning outcomes for patients with severe neurological conditions on mechanical ventilation. Methods: A retrospective analysis was conducted on 128 patients admitted to the Department of Neurosurgery, Chongqing Emergency Medical Center, who required mechanical ventilation. Based on weaning outcomes, patients were categorized into successful ( Results: The results revealed that the traditional RSBI (RR/tidal volume) and D-RSBI in the successful weaning group at the end of mechanical ventilation were lower than those in the failed weaning group, while DE and DTF were higher, the differences between the two groups were statistically significant ( Conclusion: In conclusion, diaphragm ultrasound parameters combined with D-RSBI effectively predict weaning outcomes in neurocritical patients on mechanical ventilation. This combined approach shows promising predictive value but requires external validation.

Indexed as

diaphragmatic rapid shallow breathing indexdiaphragm ultrasoundmechanical ventilationsevere neurologicalweaning machine

Identifiers

PMID42037697
PMCPMC13106020

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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.