Evidence map›Paper›PMID 34779699›Full record

ArticleRenal failure2021

Nomogram for predicting 1-, 5-, and 10-year survival in hemodialysis (HD) patients: a single center retrospective study.

Han Ouyang, Qiuhong Shi, Jing Zhu, Huaying Shen, Shan Jiang, Kai Song

Open access · goldAbstract read
In one paragraph

Article in Renal failure, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.8field-weighted citation impact, top 9% 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

11 citing papers in PubMed, 15 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

6 authors at 2 institutions in 1 country.

Han OuyangDepartment of Nephrology, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Qiuhong ShiDepartment of Nephrology, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Jing ZhuDepartment of Cardiology, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Huaying ShenDepartment of Nephrology, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Shan JiangDepartment of Nephrology, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Kai SongDepartment of Nephrology, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Soochow University · CNSecond Affiliated Hospital of Soochow University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesRisk of death is high for hemodialysis (HD) patients but it varies considerably among individuals. There is few clinical tool to predict long-term survival rates for HD patients yet. The aim of this study was to develop and validate a easy-to-use nomogram for prediction of 1-, 5-, and 10-year survival among HD patients.

methodsThis study retrospectively enrolled 643 adult HD patients who was randomly assigned to two cohorts: the training cohort (

resultsThe score included seven commonly available predictors: age, diabetes, use of arteriovenous fistula (AVF), history of emergency temporary dialysis catheter placement, cardiovascular disease (CVD), hemoglobin (Hgl), and no caregiver. The score revealed good discrimination in the training and validation cohort (AUC 0.779 and 0.758, respectively) and the calibration plots showed well calibration, indicating suitable performance of the nomogram model. Decision curve analysis showed that the nomogram added more net benefit compared with the treat-all strategy or treat-none strategy with a threshold probability of 10% or greater.

conclusionsThis easy-to-use nomogram can accurately predict 1-, 5-, and 10-year survival for HD patients, which could be used in clinical decision-making and clinical care.

Indexed as

NomogramsAdultAgedArea Under CurveChinaCohort StudiesFemaleHumansMaleMiddle AgedRenal DialysisRetrospective StudiesRisk FactorsSurvival AnalysisTime Factorsall-cause mortalityHemodialysisnomogramprediction modelsurvival

Identifiers

PMID34779699
PMCPMC8604490
OpenAlexW3213304481

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.