Evidence map›Paper›PMID 35126898›Full record

ReviewJournal of healthcare engineering2022

Safety Influencing Factors and Management Countermeasures of Patients Transferred from ICU in Transition Period Based on Intelligent Processor Three-Dimensional Quality Model.

Ping Huang, Li Zhu, Qi Wu, Weishu Hu

Abstract readReview
In one paragraph

Review in Journal of healthcare engineering, 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

4 authors.

Ping HuangCritical Care Medicine, Chongqing People's Hospital, Chongqing 400013, China.
Li ZhuCritical Care Medicine, Chongqing People's Hospital, Chongqing 400013, China.
Qi WuCritical Care Medicine, Chongqing People's Hospital, Chongqing 400013, China.
Weishu HuDepartment of Hepatobiliary and Pancreatic Surgery, Chongqing People's Hospital, Chongqing 400013, China.ORCID 0000-0001-6243-2923

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the development of science and technology of the times, the level of medical care is constantly improving. For patients transferred from ICU, the intelligent processor 3D quality model technology has gradually played an important role in clinical treatment and has become a new type of attention. In order to understand the implementation status of transitional care and the feelings of transitional care for patients transferred from ICU and understand the views of transitional care-related department doctors on transitional patient care and the role that the intelligent processor three-dimensional quality model can play, this article passed a review of the city ICU transferred patients from a hospital that conducted related investigations, reviewed related literature, conducted interviews with professionals, etc., collected relevant information, constructed case templates, and created a clinical research model using comprehensive quantitative and qualitative analysis methods. The results of the study found that, after treatment, patients transferred from the ICU based on the intelligent processor's three-dimensional quality model have higher physical activity than patients treated by other methods, the ratio is more than 20%, and the postoperative recovery efficiency of patients is higher than 15% and more. This shows that the three-dimensional quality model based on the intelligent processor can improve the important role in the transition period of patients transferred from ICU.

Indexed as

Intensive Care UnitsHumans

Identifiers

PMID35126898
PMCPMC8808119

What OpenQuestion holds

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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.