Evidence map›Paper›PMID 35256870›Full record

ArticleIEEE transactions on instrumentation and measurement2021

Differential Pressure Spirometry for Mechanical Ventilation Using Dichotomic Search.

Noe A Rodriguez-Olivares, Luciano Nava-Balanzar, Leonardo Barriga-Rodriguez

Open access · hybridAbstract read
In one paragraph

Article in IEEE transactions on instrumentation and measurement, 2021. 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
1.2field-weighted citation impact, top 20% of its field
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, 12 citations in OpenAlex.

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 at 2 institutions in 1 country.

Noe A Rodriguez-OlivaresDivision of Electrical Engineering and ElectronicsCenter for Engineering and Industrial Development (CIDESI) Queretaro 76125 Mexico.ORCID https://orcid.org/0000-0001-5892-0625
Luciano Nava-BalanzarDivision of Electrical Engineering and ElectronicsCenter for Engineering and Industrial Development (CIDESI) Queretaro 76125 Mexico.ORCID https://orcid.org/0000-0003-4789-4489
Leonardo Barriga-RodriguezDivision of Electrical Engineering and ElectronicsCenter for Engineering and Industrial Development (CIDESI) Queretaro 76125 Mexico.ORCID https://orcid.org/0000-0003-4698-1345
Center for Engineering and Industrial Development · MXUniversidad Anáhuac Querétaro · MX

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In invasive mechanical ventilation (IMV), it is critical that the flow value is estimated correctly, as it is used as a trigger variable for ventilatory assistance. Furthermore, the numerical integration of the flow allows the calculation of the total volume per breath (tidal volume), which clinicians use to identify trauma or lung capacity in the patient. The current COVID-19 pandemic has demonstrated the need to develop safe and efficient techniques for measuring this spirometry variable because many mechanical ventilators delivered to hospitals were unable to measure it directly. A good device to estimate flow is a D-lite sensor, which works by the Venturi effect, is cheap, reusable, and proximal to the patient. However, the regressions applied to the flow estimation model are limited for use in real conditions. This article presents a flow estimation method that uses a D-Lite device, a fraction of inspired oxygen (FiO

Indexed as

Binary search algorithmCOVID-19dichotomic searchD-liteFiO₂flow estimationmechanical ventilationspirometrytidal volumeventuri

Identifiers

PMID35256870
PMCPMC8769036
OpenAlexW3203076749

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.