ArticlePloS one2017
Predictive features of chronic kidney disease in atypical haemolytic uremic syndrome.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed, 18 citations in OpenAlex.
- Characteristics and clinical courses of patients with atypical haemolytic uraemic syndrome on dialysis withdrawal after eculizumab treatment: sub-analysis of post-marketing surveillance in Japan.Journal of nephrology · 2025Article
- Underlying Mechanisms and Treatment of Hypertension in Glomerular Diseases.Current hypertension reports · 2024Review
- HELLP Syndrome and Differential Diagnosis with Other Thrombotic Microangiopathies in Pregnancy.Diagnostics (Basel, Switzerland) · 2024Review
- Clinical characteristics of anti-GBM disease with thrombotic microangiopathy: a case report and literature review.CEN case reports · 2024Review
- Atypical Hemolytic-Uremic Syndrome: Genetic Basis, Clinical Manifestations, and a Multidisciplinary Approach to Management.Journal of multidisciplinary healthcare · 2023Review
- Immune-mediated thrombotic thrombocytopenic purpura prognosis is affected by blood pressure.Research and practice in thrombosis and haemostasis · 2022Article
- IgA nephropathy and atypical hemolytic uremic syndrome: a case series and a literature review.Journal of nephrology · 2022Review
- Article
- Review
- Atypical hemolytic and uremic syndrome due to C3 mutation in pancreatic islet transplantation: a case report.BMC nephrology · 2020Article
- Eculizumab in atypical hemolytic uremic syndrome: strategies toward restrictive use.Pediatric nephrology (Berlin, Germany) · 2019Review
- Thrombotic thrombocytopenic purpura: Toward targeted therapy and precision medicine.Research and practice in thrombosis and haemostasis · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 9 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chronic kidney disease (CKD) is a frequent and serious complication of atypical haemolytic uremic syndrome (aHUS). We aimed to develop a simple accurate model to predict the risk of renal dysfunction in aHUS based on clinical and biological features available at hospital admission. Renal function at 1-year follow-up, based on an estimated glomerular filtration rate < 60mL/min/1.73m2 as assessed by the Modification of Diet in Renal Disease equation, was used as an indicator of significant CKD. Prospectively collected data from a cohort of 156 aHUS patients who did not receive eculizumab were used to identify predictors of CKD. Covariates associated with renal impairment were identified by multivariate analysis. The model performance was assessed and a scoring system for clinical practice was constructed from the regression coefficient. Multivariate analyses identified three predictors of CKD: a high serum creatinine level, a high mean arterial pressure and a mildly decreased platelet count. The prognostic model had a good discriminative ability (area under the curve = .84). The scoring system ranged from 0 to 5, with corresponding risks of CKD ranging from 18% to 100%. This model accurately predicts development of 1-year CKD in patients with aHUS using clinical and biological features available on admission. After further validation, this model may assist in clinical decision making.
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.