Evidence map›Paper›PMID 41404419›Full record

ArticleResearch and practice in thrombosis and haemostasis2025

The Patient-Reported Outcomes Measurement Information System perspective of adults with long-standing atypical hemolytic uremic syndrome.

Anne Hubben, Jenna Brown, Linda Burke, Len Woodward, Clare Martin, Keith McCrae, Shruti Chaturvedi

Abstract read
In one paragraph

Article in Research and practice in thrombosis and haemostasis, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from 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.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

7 authors.

Anne HubbenDepartment of Hematology and Medical Oncology, Cleveland Clinic Foundation, Cleveland, Ohio, USA.
Jenna BrownDepartment of Hematology and Medical Oncology, Johns Hopkins University, Baltimore, Maryland, USA.
Linda BurkeaHUS Alliance Global Action, Knutsford, England, United Kingdom.
Len WoodwardaHUS Alliance Global Action, Knutsford, England, United Kingdom.
Clare MartinThe United States Thrombotic Microangiopathy Alliance, Columbus, Ohio, USA.
Keith McCraeDepartment of Hematology and Medical Oncology, Cleveland Clinic Foundation, Cleveland, Ohio, USA.
Shruti ChaturvediDepartment of Hematology and Medical Oncology, Johns Hopkins University, Baltimore, Maryland, USA.

Funding

Targeting silent cerebral infarction to improve long-term neurologic outcomes in immune thrombotic thrombocytopenic purpura (iTTP)R00HL172303 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI Shruti Chaturvedi · 2024 to 2026
$1.3M
NHLBI NIH HHS R00 HL172303
6 · The paper itself

Abstract

Background: Atypical hemolytic uremic syndrome (aHUS) is a thrombotic microangiopathy driven by a dysregulation of the complement system, disproportionately affecting the kidneys. While terminal complement blockade has reduced the risk of death and progression to end stage renal disease, patients face significant chronic health challenges. The patient experience in the current treatment era has not been well-characterized. Objectives: To evaluate patient-reported health outcomes (PRO) across global health domains, including physical and cognitive function and social isolation. Methods: We performed a cross-sectional analysis of adults with aHUS using validated National Institute of Health Patient-Reported Outcomes Measurement Information System instruments. Results: Compared with a normative reference population, our aHUS cohort ( Conclusion: In this first study of PROs in patients with long-standing aHUS in the era of complement-directed therapies, patients reported a chronically impaired global health status with reduced physical and cognitive function and higher levels of fatigue, anxiety, depression, and sleep disturbances compared with the general population. Our data underscore that aHUS is a multisystem disease that may be associated with persistent symptoms even during periods of hematologic and renal quiescence.

Indexed as

atypical hemolytic uremic syndromehealth-related quality of lifemicroangiopathic hemolytic anemiapatient reported outcomesthrombosisthrombotic microangiopathies

Identifiers

PMID41404419
PMCPMC12703853

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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.