MétaCan
Menu
Back to cohort
Record W4413288787 · doi:10.1186/s12888-025-07263-8

The associations of suicidal ideation with psychopathology and inflammatory cytokines in patients with chronic schizophrenia

2025· article· en· W4413288787 on OpenAlexaboutno aff
Lewei Liu, Lili Zhao, Liling Sun, Haojie Fan, Mingru Hao, Xin Zhao, Jiawei Wang, Yinghan Tian, Xianhu Yao, Wenzheng Li, Lei Xia, Huanzhong Liu

Bibliographic record

VenueBMC Psychiatry · 2025
Typearticle
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsnot available
Fundersnot available
KeywordsPsychopathologySuicidal ideationSchizophrenia (object-oriented programming)PsychiatryClinical psychologyPsychologyMedicinePoison controlHuman factors and ergonomicsMedical emergency

Abstract

fetched live from OpenAlex

BACKGROUND: Suicidal ideation (SI) is common in patients with chronic schizophrenia, but the exact mechanisms underlying its development are unclear. Therefore, this study aimed to initially assess the prevalence of SI and to thoroughly explore the potential associations between SI and general demographic factors, psychopathological characteristics, and inflammatory cytokines in patients with chronic schizophrenia. METHODS: From May to December 2018, 302 patients with chronic schizophrenia were included in this study. A self-administered questionnaire was used to collect general demographic data, and a series of scales were used to assess SI, psychotic symptoms, depression, insomnia, involuntary movements, extrapyramidal side effects, and akathisia symptoms, respectively. Additionally, plasma levels of inflammatory cytokines, including interleukin (IL)-1β, IL-6, IL-17 A and tumor necrosis factor-α (TNF-α) were measured. By logarithmic transformation with a base of 10, the values of Log IL-1β, Log IL-6, Log IL-17 A, and Log TNF-α were yielded. Among these, SI was designated as the dependent variable, with other psychopathological symptoms and inflammatory cytokines serving as independent variables, while general demographic factors were controlled for as potential confounders. Finally, multifactorial logistic stepwise regression analyses were performed to identify independent factors influencing SI in patients with chronic schizophrenia. Receiver operating characteristic (ROC) curve analyses were then used to assess the predictive value of each identified independent factor for SI. RESULTS: The prevalence of SI (lifetime) and SI (last week) in patients with chronic schizophrenia was 36.4% and 8.0%, respectively. After controlling for general demographic factors such as age, Body Mass Index (BMI), and years of education, regression analyses showed that being female, Calgary Depression Scale (CDSS) score and Log IL-1β were independent correlates of patients' SI (lifetime), while chlorpromazine equivalents, Positive and Negative Syndrome Scale (PANSS) score, CDSS score and Log IL-6 were independent correlates of SI (last week). Additionally, ROC curve analyses showed that the combination of both CDSS score and Log IL-1β items demonstrated better discriminative ability of SI (lifetime). And the four-item combination of chlorpromazine equivalents, PANSS score, CDSS score and Log IL-6 was a better predictor of SI (last week). CONCLUSION: There was higher overall risk of SI in patients with chronic schizophrenia. SI might be associated with psychotic symptoms, depression, insomnia, medication side effects, and increased levels of inflammatory cytokines. In clinical practice, doctors should take prompt preventive measures in patients combining suicidal risk factors.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.238
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueBMC PsychiatrySame topicTryptophan and brain disordersFrench-language works237,207