Evidence map›Paper›PMID 26222774›Full record

Trial reportPloS one2015

Elevated Circulating Osteoprotegerin and Renal Dysfunction Predict 15-Year Cardiovascular and All-Cause Mortality: A Prospective Study of Elderly Women.

Joshua R Lewis, Wai H Lim, Thor Ueland, Germaine Wong, Kun Zhu, Ee M Lim, Jens Bollerslev, Richard L Prince

Open access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 20% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Observational
  4. Evolving spectrum of diabetic nephropathy.World journal of diabetes · 2019
    Review
  5. Article
  6. Article
  7. 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

8 authors at 4 institutions in 2 countries.

Joshua R LewisUniversity of Western Australia School of Medicine and Pharmacology, Sir Charles Gairdner Hospital Unit, Perth, Australia; Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Perth, Australia.
Wai H LimUniversity of Western Australia School of Medicine and Pharmacology, Sir Charles Gairdner Hospital Unit, Perth, Australia; Department of Renal Medicine, Sir Charles Gairdner Hospital, Perth, Australia.
Thor UelandResearch Institute of Internal Medicine, Oslo University Hospital Rikshospitalet, Oslo, Norway.
Germaine WongCentre for Kidney Research, Children's Hospital at Westmead School of Public Health, Sydney Medical School, The University of Sydney, Sydney, Australia.
Kun ZhuUniversity of Western Australia School of Medicine and Pharmacology, Sir Charles Gairdner Hospital Unit, Perth, Australia; Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Perth, Australia.
Ee M LimDepartment of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Perth, Australia; PathWest, Sir Charles Gairdner Hospital, Perth, Australia.
Jens BollerslevSection of Specialised Endocrinology, Department of Endocrinology, Oslo University Hospital, Rikshospitalet, and University of Oslo, Oslo, Norway.
Richard L PrinceUniversity of Western Australia School of Medicine and Pharmacology, Sir Charles Gairdner Hospital Unit, Perth, Australia; Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Perth, Australia.
Sir Charles Gairdner Hospital · AUOslo University Hospital · NOUniversity of Western Australia · AUChildren's Hospital at Westmead · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundData on the predictive role of estimated glomerular filtration rate (eGFR) and osteoprotegerin (OPG) for cardiovascular (CVD) and all-cause mortality risk have been presented by our group and others. We now present data on the interactions between OPG with stage I to III chronic kidney disease (CKD) for all-cause and CVD mortality. METHODS AND

resultsThe setting was a 15-year study of 1,292 women over 70 years of age initially randomized to a 5-year controlled trial of 1.2 g of calcium daily. Serum OPG and creatinine levels with complete mortality records obtained from the Western Australian Data Linkage System were available. Interactions were detected between OPG levels and eGFR for both CVD and all-cause mortality (P < 0.05). Compared to participants with eGFR ≥60 ml/min/1.73 m2 and low OPG, participants with eGFR of <60 ml/min/1.73 m2 and elevated OPG had a 61% and 75% increased risk of all-cause and CVD mortality respectively (multivariate-adjusted HR, 1.61; 95% CI, 1.27-2.05; P < 0.001 and HR, 1.75; 95% CI, 1.22-2.55; P = 0.003). This relationship with mortality was independent of decline in renal function (P<0.05). Specific causes of death in individuals with elevated OPG and stage III CKD highlighted an excess of coronary heart disease, renal failure and chronic obstructive pulmonary disease deaths (P < 0.05).

conclusionThe association between elevated OPG levels with CVD and all-cause mortality was more evident in elderly women with poorer renal function. Assessment of OPG in the context of renal function may be important in studies investigating its relationship with all-cause and CVD mortality.

Indexed as

AgedAustraliaBiomarkersCardiovascular DiseasesCardiovascular SystemCreatinineFemaleGlomerular Filtration RateHumansOsteoprotegerinProspective StudiesRenal InsufficiencyRenal Insufficiency, ChronicRisk FactorsBiomarkersCreatinineOsteoprotegerin

Identifiers

PMID26222774
PMCPMC4519299
OpenAlexW947772477

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.