ArticleKidney international2013
The dynamics of prognostic indicators: toward earlier identification of dialysis patients with a high risk of dying.
Article in Kidney international, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Designing an Implementable Clinical Prediction Model for Near-Term Mortality and Long-Term Survival in Patients on Maintenance Hemodialysis.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2024Article
- Machine Learning Case Study: Patterns of Kidney Function Decline and Their Association With Clinical Outcomes Within 90 Days After the Initiation of Renal Dialysis.Advances in kidney disease and health · 2023Review
- Serum albumin at 1 year after peritoneal dialysis predicts long-term outcomes on continuous ambulatory peritoneal dialysis.Renal failure · 2022Article
- Prediction models for the mortality risk in chronic dialysis patients: a systematic review and independent external validation study.Clinical epidemiology · 2017Article
- Early changes in body weight and blood pressure are associated with mortality in incident dialysis patients.Clinical kidney journal · 2016Article
Corrections and comments
- Comment on
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mortality remains stubbornly high in patients receiving chronic dialysis treatment. Identifying at-risk patients is essential for implementation of supportive therapies. The Monitoring Dialysis Outcomes (MONDO) database shows that in 40,000 dialysis patients worldwide who died, systolic blood pressure, interdialytic weight gain, and serum albumin declined progressively, and C-reactive protein increased more than 12 months before death, indicating that predictive models may be developed to enable nephrologists to improve the clinical outcome of dialysis patients.
Indexed as
Identifiers
23812362What 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.