ArticleSocial psychiatry and psychiatric epidemiology2024
Development and validation of the risk score for estimating suicide attempt in patients with major depressive disorder.
Article in Social psychiatry and psychiatric epidemiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Article
- Nomogram for estimating the risk of suicide attempts in major depressive disorder: integrating demographic, clinical and biochemical markers - a cross-sectional study.Frontiers in psychiatry · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Early identification of high-risk patients with Major depressive disorder (MDD) having suicide attempts (SAs) is essential for timely targeted and tailored psychological interventions and medications. This study aimed to develop and validate a web-based dynamic nomogram as a personalized predictor of SA in MDD patients. A dynamic nomogram was developed using data collected from 1718 patients in China. The dynamic model was established based on a machine learning-based regression technique in the training cohort. We validated the nomogram internally using 1000 bootstrap replications. The nomogram performance was assessed using estimates of discrimination (via the concordance index) and calibration (calibration plots). The nomogram incorporated five predictors, including Hamilton anxiety rating scale (odds ratio [OR]: 1.255), marital status (OR: 0.618), clinical global impressions (OR: 2.242), anti-thyroid peroxidase antibodies (OR: 1.002), and systolic pressure levels (OR: 1.037). The model demonstrated good overall discrimination (Harrell's C-index = 0.823). Using decision curve analysis, this model also demonstrated good clinical applicability. An online web server was constructed ( https://odywong.shinyapps.io/PRSM/ ) to facilitate the use of the nomogram. Based on these results, our study developed a nomogram to predict SA in MDD patients. The application of this nomogram may help for patients and clinicians to make decisions.
Indexed as
Identifiers
37831079What OpenQuestion holds
Registered trials
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.