Evidence map›Paper›PMID 29282123›Full record

ArticleEuropean journal of medical research2017

Impact of risk factors on functional status in maintenance hemodialysis patients.

Jin-Bor Chen, Wen-Chin Lee, Ben-Chung Cheng, Sin-Hua Moi, Cheng-Hong Yang, Yu-Da Lin

Open access · goldAbstract read
In one paragraph

Article in European journal of medical research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
0.8field-weighted citation impact, top 26% 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

13 citing papers in PubMed, 22 citations in OpenAlex.

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  7. Observational
  8. Decision-making around Commencing Dialysis.Indian journal of palliative care · 2021
    Review
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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 3 institutions in 1 country.

Jin-Bor ChenDivision of Nephrology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, 83301, Taiwan.
Wen-Chin LeeDivision of Nephrology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, 83301, Taiwan.
Ben-Chung ChengDivision of Nephrology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, 83301, Taiwan.
Sin-Hua MoiDepartment of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, 80778, Taiwan.
Cheng-Hong YangDepartment of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, 80778, Taiwan. chyang@cc.kuas.edu.tw.
Yu-Da LinDepartment of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, 80778, Taiwan. e0955767257@yahoo.com.tw.
National Kaohsiung University of Applied Sciences · TWChang Gung University · TWKaohsiung Chang Gung Memorial Hospital · TW

Funding

Ministry of Sciences and Techonlogy of Taiwan 103-2221-E-151-029-MY3Ministry of Sciences and Techonlogy of Taiwan 105-2221-E-151 -053 -MY2Ministry of Sciences and Techonlogy of Taiwan 105-2811-E-151-002-
6 · The paper itself

Abstract

objectivesTo survey by measuring patient's functional status which is crucial when end-stage renal disease patients begin a dialysis program. The influence of the disease on patients can be examined by the measurement of Karnofsky Performance Status (KPS) scores, together with a quality of life survey, and clinical variables.

methodsThe details for the dataset in the study were collected from patients receiving regular hemodialysis (HD) in one hospital, which were available retrospectively for 1166 patients during the 5-year study period. KPS scores were applied for quantifying functional status. To identify risk factors for functional status, clinical factors including demographics, laboratory data, and HD vintage were selected. This study applied a classification and regression tree approach (CART) and logistic regression to determine risk factors on functional impairment among HD patients.

resultsTen risk factors were identified by CART and regression model (age, primary kidney disease subclass, treatment years, hemoglobin, albumin, creatinine, phosphorus, intact parathyroid hormone, ferritin, and cardiothoracic ratio). The results of logistic regression with selected interaction models showed older age or higher hematocrit, blood urea nitrogen, and glucose levels could significantly increase the log-odds of obtaining low KPS scores at in-person visits.

conclusionsIn interaction results, the combination of older age with higher albumin level and higher creatinine level with longer HD treatment years could significantly decrease the log-odds of a low KPS score assessment during in-person visits. Age, hemoglobin, albumin, urea, creatinine levels, primary kidney disease subclass, and HD duration are the major determinants for functional status in HD patients.

Indexed as

Karnofsky Performance StatusQuality of LifeRenal DialysisAgedAlgorithmsFemaleHumansKidney Failure, ChronicMaleMiddle AgedRisk FactorsClassification and regression tree approachFunctional statusHemodialysisKarnofsky Performance Status

Identifiers

PMID29282123
PMCPMC5745856
OpenAlexW2776169741

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.