Evidence map›Paper›PMID 29578399›Full record

ReviewClinical nephrology2018

Mini-review of kidney disease following hematopoietic stem cell transplant
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Ramy Sedhom, Daniel Sedhom, Edgar Jaimes

Open access · greenAbstract readReview
In one paragraph

Review in Clinical nephrology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 35% of its field
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

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 1 country.

Ramy Sedhom
Daniel Sedhom
Edgar Jaimes
Cornell University · USJohnson University · USRutgers, The State University of New Jersey · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

Advancements in hematopoietic cell transplantation (HCT) have broadened indications for its use and resulted in more long-term survivors. Stem cell transplantation is associated with several well-known toxicities, although renal complications are not well defined. Acute and chronic kidney disease remains a common complication following transplantation itself. Incidence and risk factors for the development of chronic kidney disease (CKD) is less well understood. Recent estimates suggest that nearly 15% of subjects undergoing HCT will develop CKD, a complication that can progress to end-stage renal disease (ESRD), disrupts overall quality of life, and reduces overall survival. Several commonly-reported risk factors include acute kidney injury, graft-versus-host disease, and long-term calcineurin inhibitor use. This review highlights the incidence, timeline, etiology, risk factors, and prognosis of kidney disease in the setting of hematopoietic stem cell transplantation. Investigation of the causes of CKD is needed, as are ways to prevent, mitigate, and treat kidney injury. Renal disease importantly reflects prognosis, with dialysis-requiring patients carrying greater than 80% mortality after 3 years. Although CKD following HCT is common, prospective studies are needed to confirm risk factors and better define the underlying mechanisms in order to promote therapies that prevent this complication.
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Indexed as

Kidney DiseasesGraft vs Host DiseaseHematopoietic Stem Cell TransplantationHumansPostoperative Complications

Identifiers

PMID29578399
PMCPMC6727568
OpenAlexW2793732370

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.