Evidence map›Paper›PMID 34232177›Full record

ArticleMedicine2021

Epidemiological analysis of single center of acute poisoning cases based on poisoning treatment platform.

Shen Jun-Hua, Zhang Jin-Song, Qiao Li, Wang Lei, Zhu Bao-Feng, Li Jia, Liu Ying, Cheng Jian-Rong

Abstract read
In one paragraph

Article in Medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Providing a Population Based Registry Model of Drug Poisoning in Iran.Iranian journal of pharmaceutical research : IJPR · 2022
    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

8 authors.

Shen Jun-HuaThe Second Affiliated Hospital of Nantong University.
Zhang Jin-SongThe first Affiliated Hospital with Nanjing Medical University, China.
Qiao LiThe first Affiliated Hospital with Nanjing Medical University, China.
Wang LeiThe Second Affiliated Hospital of Nantong University.ORCID 0000-0003-4530-3526
Zhu Bao-FengThe Second Affiliated Hospital of Nantong University.
Li JiaThe Second Affiliated Hospital of Nantong University.
Liu YingThe Second Affiliated Hospital of Nantong University.
Cheng Jian-RongThe Second Affiliated Hospital of Nantong University.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

abstractTo studied epidemiological characteristics of 493 cases of acute poisoning in Nantong city, Jiangsu province.Based on the analysis platform of poisoning treatment, adopted single center and prospective investigation method, analyzed data of acute poisoning patients from May 2015 to December 2018 in the second affiliated hospital of Nantong University.Among 493 patients with acute poisoning, men 227 (46.04%), women 266 (53.96%). Age ranged from 12 to 89 years old, average age 41.6 years. In the occupational distribution, farmers were 30.02%; 351 cases (71.20%) visited the hospital within 6 hours after exposure. Oral exposure poisoning 415 cases (84.18%). Pesticide poisoning accounted for 45.45% of deaths.Using the poisoning treatment platform to analyze the clinical characteristic had accurately and reliably in Nantong. The fatality rate of pesticide poisoning in cases of acute poisoning is high. Management of highly toxic pesticides should be continued and effective health education on pesticide use should be carried out.

Indexed as

Disease ManagementSeasonsAcute DiseaseAdolescentAdultAgedAged, 80 and overChildFemaleHumansIncidenceMaleMiddle AgedOccupational ExposurePesticidesPoisoningPesticides

Identifiers

PMID34232177
PMCPMC8270618

What OpenQuestion holds

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LicenceCC BY
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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.