Evidence map›Paper›PMID 29725646›Full record

ArticleKidney international reports2018

Prediction Model and Risk Stratification Tool for Survival in Patients With CKD.

Alexander S Goldfarb-Rumyantzev, Shiva Gautam, Ning Dong, Robert S Brown

Abstract read
In one paragraph

Article in Kidney international reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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

9 citing papers in PubMed.

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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.

Alexander S Goldfarb-RumyantzevDivision of Nephrology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
Shiva GautamDepartment of Biostatistics, University of Florida, Gainesville, Florida, USA.
Ning DongDepartment of Medicine, Rutgers New Jersey Medical School, Newark, New Jersey, USA.
Robert S BrownDivision of Nephrology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionBecause chronic kidney disease (CKD) adversely affects survival, prediction of mortality risk should help to identify individuals requiring therapeutic intervention. The goal of this project was to construct and to validate a risk scoring system and prediction model of the probability of 2-year mortality in a CKD population.

methodsWe applied the Woodpecker approach to develop prediction equations using linear, exponential, and combined models. A risk indicator

resultsUsing

conclusionThe risk stratification tool and prediction model of 2-year mortality demonstrated good performance and may be used in clinical practice to quantify the risk of death for individual patients with CKD.

Indexed as

CKDepidemiologymortalityoutcomepredictionsurvival

Identifiers

PMID29725646
PMCPMC5932311

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.