Evidence map›Paper›PMID 35498146›Full record

ArticleApplied bionics and biomechanics2022

Application of Emergency Specialist Nursing Combined with Green Channel Mode in Patients with Limb Amputation.

Zaiyun Qian, Min Wang, Tonglong Xu

RetractedAbstract readRetracted Publication
In one paragraph

Article in Applied bionics and biomechanics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Zaiyun QianWuxi 9th People's Hospital Affiliated to Soochow University, Liangxi Road, No. 999, Binhu District, Wuxi, Jiangsu, China.
Min WangWuxi 9th People's Hospital Affiliated to Soochow University, Liangxi Road, No. 999, Binhu District, Wuxi, Jiangsu, China.
Tonglong XuWuxi 9th People's Hospital Affiliated to Soochow University, Liangxi Road, No. 999, Binhu District, Wuxi, Jiangsu, China.ORCID https://orcid.org/0000-0001-5964-3236

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The treatment of limb amputation is always a challenge to emergency medical staff. The success of replantation of severed limbs requires not only emergency professional nursing measures but also rapid transport against time. We that found emergency specialist nursing combined with green channel mode can effectively improve the success rate of amputated limb replantation surgery. Methods: From September 2017 to August 2020, the medical records of 80 patients with severed limb replantation treated by the emergency department of our hospital were collected and divided into the control group and the experimental group. 36 patients in the control group were emergency patients treated from September 2017 to May 2019. These patients did not take appropriate emergency specialist nursing measures and opened green channels at that time; the other 44 patients were in the experimental group, for emergency patients treated from June 2019 to August 2020. These patients have received emergency specialist care and opened a green channel. We recorded the gender, age, preoperative examination time, and success rate of amputated limb replantation surgery of the two groups of patients. Results: The age of the patients in the control group was 41.17 ± 8.00 years old, and the age of the patients in the experimental group was 41.07 ± 7.31 years old ( Conclusion: Standardized emergency specialist nursing measures combined with green channel mode can effectively shorten the preoperative examination time and help improve the success rate of amputated limb replantation surgery.

Identifiers

PMID35498146
PMCPMC9042639

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.