Evidence map›Paper›PMID 28900872›Full record

ReviewJournal of nephrology2017

The use of bone mineral density measured by dual energy X-ray absorptiometry (DXA) and peripheral quantitative computed microtomography in chronic kidney disease.

Martin Jannot, Fabrice Mac-Way, Vanessa Lapierre, Marie-Helene Lafage-Proust

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of nephrology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.5field-weighted citation impact, top 19% 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

8 citing papers in PubMed, 14 citations in OpenAlex.

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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

4 authors at 3 institutions in 2 countries.

Martin JannotINSERM 1059, SAINBIOSE, Université de Lyon, CHU 42023-42055, Saint-Etienne Cedex 2, France.
Fabrice Mac-WayCentre de Recherche du CHU de Québec, Hôpital Hôtel-Dieu de Québec, Division of Nephrology and Endocrinology, Laval University, 0877, 10 McMahon, Québec City, Québec, G1R 2J6, Canada.
Vanessa LapierreINSERM 1059, SAINBIOSE, Université de Lyon, CHU 42023-42055, Saint-Etienne Cedex 2, France.
Marie-Helene Lafage-ProustINSERM 1059, SAINBIOSE, Université de Lyon, CHU 42023-42055, Saint-Etienne Cedex 2, France. lafagemh@univ-st-etienne.fr.
Inserm · FRHôtel-Dieu de Québec · CAUniversité Claude Bernard Lyon 1 · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic kidney disease (CKD) is a risk factor for fractures. The current evaluation of fracture risk is based upon the combination of various clinical factors and quantitative imaging of bone. X-ray-based tools were developed to evaluate bone status and predict fracture risk. Dual energy X-ray absorptiometry (DXA) is available worldwide. Longitudinal studies showed that low areal Bone Mineral Density (BMD) measured by DXA predicts fractures in the CKD population as it does in non uremic populations, with good specificity and moderate sensitivity. Peripheral quantitative computed tomography (pQCT) and high resolution pQCT are research tools which measure volumetric BMD at the tibia and radius. They are able to discriminate between the cortical and trabecular envelopes which are differentially affected by renal osteodystrophy. In CKD, a rapid thinning and increased porosity at the cortex is observed which is associated with increased the risk for fracture.

Indexed as

Absorptiometry, PhotonBone DensityX-Ray MicrotomographyBone and BonesFractures, BoneHumansRenal Insufficiency, ChronicRisk AssessmentBoneChronic kidney diseaseDXAFracturesHRpQCTpQCT

Identifiers

PMID28900872
OpenAlexW2755564027

What OpenQuestion holds

Textmetadata
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.