ArticleRenal failure2024
Development and validation of a prediction model for all-cause mortality in maintenance dialysis patients: a multicenter retrospective cohort study.
Article in Renal failure, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled 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.
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
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review of Proteomics in Obesity: Unpacking the Molecular Puzzle.Current obesity reports · 2024Pooled it
- Development and External Validation of a Nomogram for Individualized Risk Prediction of Hyperprolactinemia in Chronic Kidney Disease: A Retrospective Multicenter Study.International journal of general medicine · 2026Article
- Explainable machine learning algorithm to predict cardiovascular event in patients undergoing peritoneal dialysis.BMC medical informatics and decision making · 2025Article
- Inflammatory index is a promising biomarker for maintenance hemodialysis patients with cardiovascular disease.European journal of medical research · 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
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe mortality risk varies considerably among individual dialysis patients. This study aimed to develop a user-friendly predictive model for predicting all-cause mortality among dialysis patients.
methodsRetrospective data regarding dialysis patients were obtained from two hospitals. Patients in training cohort (
resultsThe best predictors of 1-, 3-, and 5-year all-cause mortality contained nine independent factors, including age, body mass index (BMI), diabetes mellitus (DM), cardiovascular disease (CVD), cancer, urine volume, hemoglobin (HGB), albumin (ALB), and pleural effusion (PE). The 1-, 3-, and 5-year
conclusionsThe effective and convenient nomogram may help clinicians quantify the risk of mortality in maintenance dialysis patients.
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.