ArticleAging2023
Predicting the prognosis in patients with sepsis by an endoplasmic reticulum stress gene signature.
Article in Aging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 6 citations in OpenAlex.
- Evaluation of the clinical value of serum inflammatory mediators in assessing sepsis severity.Pakistan journal of medical sciences · 2026Article
- Transcriptomic Profiling Reveals Distinct Immune Dysregulation in Early-Stage Sepsis Patients.International journal of molecular sciences · 2025Article
- Screening and Identification of Neutrophil Extracellular Trap-related Diagnostic Biomarkers for Pediatric Sepsis by Machine Learning.Inflammation · 2025Article
- Machine learning-based identification of leptin-associated biomarkers and prognostic prediction models in sepsis.Frontiers in cellular and infection microbiology · 2025Article
- Article
- Identification of the key targets for sepsis-associated acute kidney injury by RNA sequencing combined with bioinformatics methods.BMC immunology · 2024Article
- Predictive Value of Combined Detection of Serum LGALS3BP and GDF-15 for the Prognosis of ICU Sepsis Patients.Infection and drug resistance · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPrognostic stratification of patients with sepsis is important for the development of individualized treatment strategies. Endoplasmic reticulum stress (ERS) plays a key role in sepsis. This study aimed to identify a set of genes related to ER stress to construct a predictive model for the prognosis of sepsis.
methodsThe transcriptomic and clinical data of 479 sepsis patients were obtained from GSE65682 and divided into a training set (n=288) and a validation set (n=191) at a ratio of 3:2. The external test set was GSE95233 (n=51). LASSO and Cox regression analyses were performed to establish a signature to predict the prognosis of patients with sepsis. Moreover, we developed a nomogram that included the risk signature and clinical features to predict survival probability.
resultsA prognostic signature was constructed with ten endoplasmic reticulum related genes (ADRB2, DHCR7, GABARAPL2, MAOA, MPO, PDZD8, QDPR, SCAP, TFRC, and TLR4) in the training set, which significantly divided patients with sepsis into high- and low-risk groups in terms of survival. This signature was validated using validation and external test sets. A nomogram based on the risk signature was constructed to quantitatively predict the prognosis of patients with sepsis.
conclusionsWe constructed an ERS signature as a novel prognostic marker for predicting survival in sepsis patients, which could be used to develop novel biomarkers for the diagnosis, treatment, and prognosis of sepsis and to provide new ideas and prospects for future clinical research.
Indexed as
Identifiers
What 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.