Evidence map›Paper›PMID 36421102›Full record

ArticleBioengineering (Basel, Switzerland)2022

Toward Evaluating Critical Factors of Extubation Outcome with XCSR-Generated Rules.

Po-Hsun Huang, Lian-Yu Chen, Wei-Chan Chung, Chau-Chyun Sheu, Tzu-Chien Hsiao, Jong-Rung Tsai

Abstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2022. 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
–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

0 citing papers in PubMed.

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

6 authors.

Po-Hsun HuangInstitute of Computer Science and Engineering, College of Computer Science, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan.ORCID 0000-0003-0013-9793
Lian-Yu ChenInstitute of Computer Science and Engineering, College of Computer Science, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan.
Wei-Chan ChungDivision of Respiratory Therapy, Kaohsiung Medical University Hospital, Kaohsiung 80708, Taiwan.
Chau-Chyun SheuDivision of Pulmonary and Critical Care Medicine, Kaohsiung Medical University Hospital, Kaohsiung 80708, Taiwan.ORCID 0000-0002-7979-3749
Tzu-Chien HsiaoDepartment of Computer Science, College of Computer Science, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan.ORCID 0000-0003-2493-3780
Jong-Rung TsaiDepartment of Internal Medicine, Kaohsiung Municipal Cijin Hospital, Kaohsiung 80544, Taiwan.ORCID 0000-0002-3222-0409

Funding

Kaohsiung Medical University NCTUKMU 108-AI-09National Yang Ming Chiao Tung University NCTUKMU 108-AI-09
6 · The paper itself

Abstract

Predicting the correct timing for extubation is pivotal for critically ill patients with mechanical ventilation support. Evidence suggests that extubation failure occurs in approximately 15-20% of patients, despite their passing of the extubation evaluation, necessitating reintubation. For critically ill patients, reintubation invariably increases mortality risk and medical costs. The numerous parameters that have been proposed for extubation decision-making, which constitute the key predictors of successful extubation, remains unclear. In this study, an extended classifier system capable of processing real-value inputs was proposed to select features of successful extubation. In total, 40 features linked to clinical information and variables acquired during spontaneous breathing trial (SBT) were used as the environmental inputs. According to the number of "don't care" rules in a population set, Prob

Indexed as

extended classifier systemmechanical ventilationspontaneous breathing trialsuccessful extubation

Identifiers

PMID36421102
PMCPMC9687848

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.