Evidence map›Paper›PMID 30105257›Full record

ArticleBioMed research international2018

The Incidence and Risk Factors of Acute Kidney Disease after Total Knee Arthroplasty with Early Postoperative Volume Supplement.

Kuan-Ting Wu, Chung-Yang Chen, Bradley Chen, Jun-Wen Wang, Po-Chun Lin, Shih-Hsiang Yen

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.4field-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

5 citing papers in PubMed, 18 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 3 institutions in 1 country.

Kuan-Ting WuDepartment of Orthopaedic Surgery, Kaohsiung Chang Gung Memorial Hospital, Taiwan.ORCID 0000-0003-3953-7860
Chung-Yang ChenDepartment of Orthopaedic Surgery, Kaohsiung Chang Gung Memorial Hospital, Taiwan.
Bradley ChenInstitute of Public Health, National Yang Ming University, Taipei, Taiwan.
Jun-Wen WangDepartment of Orthopaedic Surgery, Kaohsiung Chang Gung Memorial Hospital, Taiwan.ORCID 0000-0001-9879-8521
Po-Chun LinDepartment of Orthopaedic Surgery, Kaohsiung Chang Gung Memorial Hospital, Taiwan.
Shih-Hsiang YenDepartment of Orthopaedic Surgery, Kaohsiung Chang Gung Memorial Hospital, Taiwan.
Kaohsiung Chang Gung Memorial Hospital · TWChang Gung University · TWNational Yang Ming Chiao Tung University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEtiology of acute kidney disease (AKD) after total knee arthroplasty (TKA) was considered as multifactorial. However, the role of early postoperative volume supplement in AKD rate has not been investigated. The purpose of this study was to evaluate the incidence and risk factors of AKD in patients with early volume supplement following TKA.

methodsThis was a retrospective study with 458 patients who underwent unilateral TKA. All the patients received 6% tetrastarch, 7.5ml/kg, early in the postoperative period. Postoperative AKD was defined as the postoperative creatinine level ≥ 1.5 times compared with preoperative data. Potential variables associated with AKD were analyzed by multivariate logistic regression model to identify the AKD risk factors in TKA patients after early postoperative volume supplement.

resultsThe AKD rate was 3.3% (15 patients) in all patients. Age (OR = 1.09; P = .031) and

conclusionOur study demonstrated that age and

Indexed as

Acute Kidney InjuryAgedArthroplasty, Replacement, KneeFemaleHumansIncidenceMalePostoperative ComplicationsRetrospective StudiesRisk Factors

Identifiers

PMID30105257
PMCPMC6076950
OpenAlexW2883585839

What OpenQuestion holds

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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.