Evidence map›Paper›PMID 24672766›Full record

ArticleJournal of medical signals and sensors2013

Prediction of Arterial Blood pH and Partial Pressure of Carbon dioxide from Venous Blood Samples in Patients Receiving Mechanical Ventilation.

Kamran Tavakol, Bahareh Ghahramanpoori, Mohammad Fararouei

Open access · diamondAbstract read
In one paragraph

Article in Journal of medical signals and sensors, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 97% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
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 3 institutions in 1 country.

Kamran TavakolDepartment of Anesthesiology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
Bahareh GhahramanpooriDepartment of Anesthesiology, School of Medicine, Islamic Azad University, Najafabad Branch, Najafabad, Iran.
Mohammad FararoueiDepartment of Epidemiology and Statistics, Yasuj University of Medical Sciences, Yasuj, Iran.
Isfahan University of Medical Sciences · IRIslamic Azad University of Najafabad · IRYasuj University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Substitution of arterial with venous blood samples to estimate blood gas status is highly preferable due to practical and safety concerns. Numerous studies support the substitution of arterial by venous blood samples, reporting strong correlations between arterial and venous values. This study further investigated the predictive ability of venous blood samples for arterial Acid-Base Balance (pH) and pressure of carbon dioxide (pCO2). Participants were 51 post-brain surgery patients receiving mechanical ventilation, who had blood samples taken simultaneously from radial artery of the wrist and elbow vein. Results showed significant associations between arterial and venous pH and pCO2. However, the variation of regression residuals was not homogenous, and the regression line did not fit properly to the data, indicating that simple linear regression is sub-optimal for prediction of arterial pH and pCO2 by venous blood sample. Although highly significant correlations were found between arterial and venous blood pH and pCO2, the results did not support the reliability of prediction of arterial blood pH and pCO2 by venous blood samples across a range of concentrations.

Indexed as

Acid-base balanceblood gas analysiscarbon dioxiderespiratory insufficiencyveins

Identifiers

PMID24672766
PMCPMC3959008
OpenAlexW1541850026

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.