Evidence map›Paper›PMID 36969682›Full record

Trial reportFrontiers in public health2023

Identification of risk factors for attempted suicide by self-poisoning and a nomogram to predict self-poisoning suicide.

Wenjing Zheng, Le Gao, Yanna Fan, Chunyan Wang, Yanqing Liu, Fei Tian, Min Yi, Xiaobo Peng, Chunzi Liu

Open access · goldFull text readRandomized Controlled Trial
In one paragraph

Trial report in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
6.9field-weighted citation impact, top 3% 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

7 citing papers in PubMed, 22 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

Wenjing ZhengDepartment of Chemical Poisoning Treatment, Senior Department of Hematology, The Fifth Medical Center of PLA General Hospital, Beijing, China.
Le GaoDepartment of Oncology, Senior Department of Oncology, The Fifth Medical Center of PLA General Hospital, Beijing, China.
Yanna FanDepartment of Radiation Oncology, Senior Department of Oncology, The Fifth Medical Center of PLA General Hospital, Beijing, China.
Chunyan WangDepartment of Chemical Poisoning Treatment, Senior Department of Hematology, The Fifth Medical Center of PLA General Hospital, Beijing, China.
Yanqing LiuDepartment of Chemical Poisoning Treatment, Senior Department of Hematology, The Fifth Medical Center of PLA General Hospital, Beijing, China.
Fei TianDepartment of Chemical Poisoning Treatment, Senior Department of Hematology, The Fifth Medical Center of PLA General Hospital, Beijing, China.
Min YiInstitute of Medical Information and Library, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Xiaobo PengDepartment of Chemical Poisoning Treatment, Senior Department of Hematology, The Fifth Medical Center of PLA General Hospital, Beijing, China.
Chunzi LiuSenior Department of Oncology, The Fifth Medical Center of PLA General Hospital, Beijing, China.
Chinese PLA General Hospital · CNChinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Suicide is a global concern, especially among young people. Suicide prediction models have the potential to make it easier to identify patients who are at a high risk of suicide, but they have very little predictive power when there is a positive value for suicide mortality. Therefore, the aim of the study is to uncover potential risk factors associated with suicide by self-poisoning and further to provide a trustworthy nomogram to predict self-poisoning suicide among poisoned patients. Methods: This study prospectively enrolled 237 patients who were treated for poisoning at the Fifth Medical Center of PLA General Hospital (Beijing) between May 2021 and May 2022. Patient's basic characteristics, daily activities, mental health status, and history of psychological illnesses were gathered to examine their predictive power for self-poisoning suicide. On developing a prediction model, patients were split 8:2 into a training ( Results: Of all poisoned patients, 64.6% committed suicide by self-poisoning. With regard to self-poisoning attempted suicide, multivariate analysis demonstrated that female gender, smoking, generalized anxiety disorder-7 (GAD-7), and beck hopelessness scale-20 (BHS-20) were significant risk factors, whereas married status, relatively higher education level, a sedentary time of 1-3 h per day, higher sport frequency per week, higher monthly income were significant protective features. The nomogram contained each of the aforementioned nine features. In the training group, the area under curve (AUC) of the nomogram was up to 0.938 (0.904-0.972), whereas in the validation group, it reached a maximum of 0.974 (0.937-1.000). Corresponding accuracy rates were up to 0.883 and 0.927, respectively, and the Conclusions: This study proposes a prediction model to stratify patients at a high risk of suicide by self-poisoning and to guide individual preventive strategies. Patients in the high-risk group require further mental health counseling to alleviate anxiety and hopelessness, healthy lifestyle like quitting smoking and exercising more, and restriction of access to poison and psychiatric drugs.

Indexed as

NomogramsSuicide, AttemptedAdolescentFemaleHumansRisk Factorsmental healthnomogramprediction modelself-poisoningsuicide

Identifiers

PMID36969682
PMCPMC10031109
OpenAlexW4323567821

What Socratic holds

Textfull text, public
LicenceCC BY
measurements read49
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 Socratic graph.