ArticleEBioMedicine2019
Derivation and external validation of a model to predict 2-year mortality risk of patients with advanced schistosomiasis after discharge.
Article in EBioMedicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Network Analysis and Nomogram in the Novel Classification and Prognosis Prediction of Advanced Schistosomiasis Japonica.The American journal of tropical medicine and hygiene · 2023Trial
- A prognostic model for elderly patients with squamous non-small cell lung cancer: a population-based study.Journal of translational medicine · 2020Trial
- Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study.Circulation · 2026Article
- Prediction of 6-year mortality in advanced splenomegaly-subtype schistosomiasis: a retrospective cohort study from Hubei, China.BMJ open · 2026Article
- Prognostic determinants and mortality risk of advanced schistosomiasis revealed by Lasso-Cox regression integrative approach.PLoS neglected tropical diseases · 2026Article
- CXCR6 recruits Th2 cells and promotes liver fibrosis in schistosomiasis japonica.Hepatology communications · 2025Article
- Spatial metabolomics to profile metabolic reprogramming of liver inParasitology · 2025Article
- A model predicting the 6-year all cause mortality of patients with advanced schistosomiasis after discharge: Derived from a large population-based cohort study.PLoS neglected tropical diseases · 2025Article
- Single-cell RNA sequencing reveals a peripheral landscape of immune cells in Schistosomiasis japonica.Parasites & vectors · 2023Article
- A Nomogram for Predicting Prognosis of AdvancedTropical medicine and infectious disease · 2023Article
- Development of New Technologies for Risk Identification of Schistosomiasis Transmission in China.Pathogens (Basel, Switzerland) · 2022Review
- Single-cell RNA sequencing to dissect the immunological network of liver fibrosis inFrontiers in immunology · 2022Article
- Potential application of nanotechnology in the treatment, diagnosis, and prevention of schistosomiasis.Frontiers in bioengineering and biotechnology · 2022Review
- Development and Validation of 3-Month Major Post-Stroke Depression Prediction Nomogram After Acute Ischemic Stroke Onset.Clinical interventions in aging · 2021Article
- In vivo assessment of the antischistosomal activity of curcumin loaded nanoparticles versus praziquantel in the treatment of Schistosoma mansoni.Scientific reports · 2020Article
- Nomograms to predict 2-year overall survival and advanced schistosomiasis-specific survival after discharge: a competing risk analysis.Journal of translational medicine · 2020Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To date, no risk prediction tools have been developed to identify high mortality risk of patients with advanced schistosomiasis within 2 years after discharge. We aim to derive and validate a risk prediction model to be applied in clinical practice. The risk prediction model was derived from 1487 patients from Jingzhou and externally validated by 723 patients of Huangshi, two prefecture-level cities in Hubei province, China (from September 2014 to January 2015, with follow-up to January 2017). The baseline variables were collected. The mean age [SD] was 62.89 [10.38] years for the derivation cohort and 62.95 [12.22] years for the external validation cohort. The females accounted for 36.3% and 43.7% of the derivation and validation cohorts, respectively. 8.27% patients (123/1487) in the derivation cohort and 7.75% patients (56/723) in the external validation cohort died within 2 years after discharge. We constructed 4 models based on the 7 selected variables: age, clinical classification, serum direct bilirubin (DBil), aspartate aminotransferase (AST), alkaline phosphatase (ALP), hepatitis B surface antigen (HBsAg), alpha fetoprotein (AFP) at admission. In the external validation cohort, the multivariate model including 7 variables had a C statistic of 0.717 (95% CI, 0.646-0.788) and improved integrated discrimination improvement (IDI) value and net reclassification improvement (NRI) value compared to the other reduced models. Therefore, a multivariate model was developed to predict the 2-year mortality risk for patients with advanced schistosomiasis after discharge. It could also help guide follow-up, aid prognostic assessment and inform resource allocation.
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