Evidence map›Paper›PMID 33853434›Full record

ArticleThe Journal of international medical research2021

Establishment of a prediction model for early and mid-term complications for patients undergoing catheter insertion for peritoneal dialysis.

Yibo Ma, Shuiqing Liu, Min Yang, Yun Zou, Dong Xue, Yufeng Wang, Xiao Xie, Hui Chen, Yanping Liu

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The Journal of international medical research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

9 authors at 1 institution in 1 country.

Yibo MaDepartment of Ultrasound, the Third Affiliated Hospital of Soochow University, Changzhou, China.ORCID https://orcid.org/0000-0001-7919-7413
Shuiqing LiuDepartment of Ultrasound, the Third Affiliated Hospital of Soochow University, Changzhou, China.
Min YangDepartment of Nephrology, the Third Affiliated Hospital of Soochow University, Changzhou, China.
Yun ZouDepartment of Nephrology, the Third Affiliated Hospital of Soochow University, Changzhou, China.
Dong XueDepartment of Urology, the Third Affiliated Hospital of Soochow University, Changzhou, China.
Yufeng WangDepartment of Ultrasound, the Third Affiliated Hospital of Soochow University, Changzhou, China.
Xiao XieDepartment of Ultrasound, the Third Affiliated Hospital of Soochow University, Changzhou, China.
Hui ChenDepartment of Ultrasound, the Third Affiliated Hospital of Soochow University, Changzhou, China.
Yanping LiuDepartment of Ultrasound, the Third Affiliated Hospital of Soochow University, Changzhou, China.
Soochow University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo investigate the factors involved in early and mid-term complications after catheter insertion for peritoneal dialysis and to establish prediction models.

methodsA total of 158 patients with peritoneal dialysis in the Department of Nephrology of our hospital were retrospectively analyzed. General information, laboratory indices, early complications (within 1 month after the operation), mid-term complications (1-6 months after the operation), and other relevant data were recorded. Multivariate logistic regression analysis was performed to establish a prediction model of complications and generate a nomogram. Receiver operating characteristic (ROC) curve analysis was used to evaluate the efficacy of the model.

resultsAmong the patients, 48 (30.8%) had early complications, which were mainly catheter-related complications, and 29 (18.4%) had mid-term complications, which were mainly abdominal infection and catheter migration. We constructed a prediction model for early complications (area under the curve = 0.697, 95% confidence interval: 0.609-0.785) and mid-term complications (area under the curve = 0.730, 95% confidence interval: 0.622-0.839). The sensitivity was 0.750 and 0.607, and the specificity was 0.589 and 0.765, respectively.

conclusionsOur prediction model has clinical significance for risk assessment of early and mid-term complications and prevention of complications after catheterization for peritoneal dialysis.

Indexed as

Catheters, IndwellingPeritoneal DialysisCatheterizationHumansRetrospective StudiesRisk Assessmentabdominal infectioncatheterizationcatheter migrationearly complicationmid-term complicationPeritoneal dialysisprediction model

Identifiers

PMID33853434
PMCPMC8059045
OpenAlexW3155284840

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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.