Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 487

The DOI matches its Crossref record.

Diaphragm ultrasound as a predictor of successful extubation from mechanical ventilation

Open access
DiNino, Ernest, Gartman, Eric J, Sethi, Jigme M, McCool, F Dennis·2014·Thorax

Abstract

INTRODUCTION: The purpose of this study was to evaluate if ultrasound derived measures of diaphragm thickening, rather than diaphragm motion, can be used to predict extubation success or failure. METHODS: Sixty-three mechanically ventilated patients were prospectively recruited. Diaphragm thickness (tdi) was measured in the zone of apposition of the diaphragm to the rib cage using a 7-10 MHz ultrasound transducer. The percent change in tdi between end-expiration and end-inspiration (Δtdi%) was calculated during either spontaneous breathing (SB) or pressure support (PS) weaning trials. A successful extubation was defined as SB for >48 h following endotracheal tube removal. RESULTS: Of the 63 subjects studied, 27 patients were weaned with SB and 36 were weaned with PS. The combined sensitivity and specificity of Δtdi%≥30% for extubation success was 88% and 71%, respectively. The positive predictive value and negative predictive value were 91% and 63%, respectively. The area under the receiver operating characteristic curve was 0.79 for Δtdi%. CONCLUSIONS: Ultrasound measures of diaphragm thickening in the zone of apposition may be useful to predict extubation success or failure during SB or PS trials.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1136/thoraxjnl-2013-204111

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 487

Metadata

Authors
DiNino, E., Gartman, E. J., Sethi, J. M., & McCool, F. D.
Venue
Thorax
Publisher
BMJ
Published
2013-12-23
Volume
69
Issue
5
Pages
431-435
ISSN
  • 0040-6376 (ISSN-L)
  • 1468-3296
OpenAlex
W2155913350
Cited by
487
References
0
FWCI
14.13
Type
journal article
Language
en
Open access
bronze

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Diaphragm ultrasound as a predictor of successful extubation from mechanical ventilation. https://app.cochat.ai/papers/10.1136/thoraxjnl-2013-204111
The paper
DiNino, E., Gartman, E. J., Sethi, J. M., & McCool, F. D. (2014). Diaphragm ultrasound as a predictor of successful extubation from mechanical ventilation. Thorax. https://doi.org/10.1136/thoraxjnl-2013-204111

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.