Evidence map›Paper›PMID 35539015›Full record

ArticlePeerJ2022

Early warning model construction and validation for urinary tract infection in patients with neurogenic lower urinary tract dysfunction (NLUTD): a retrospective study.

Liqiong Zhou, Surui Liang, Qin Shuai, Chunhua Fan, Linghong Gao, Wenzhi Cai

Abstract read
In one paragraph

Article in PeerJ, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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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.

Liqiong Zhou *Nursing Department, Southern Medical University, Shenzhen Hospital, Shenzhen, Guangdong, China.
Surui Liang *Nursing Department, Southern Medical University, Shenzhen Hospital, Shenzhen, Guangdong, China.
Qin ShuaiNursing Department, Shenzhen Longcheng Hospital, Shenzhen, Guangdong, China.
Chunhua FanNursing Department, Shenzhen Longcheng Hospital, Shenzhen, Guangdong, China.
Linghong GaoNursing Department, Shenzhen Longcheng Hospital, Shenzhen, Guangdong, China.
Wenzhi CaiNursing Department, Southern Medical University, Shenzhen Hospital, Shenzhen, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study was performed to construct and validate an early risk warning model of urinary tract infection in patients with neurogenic lower urinary tract dysfunction (NLUTD). Methods: Eligible patients with NLUTD admitted to Shenzhen Longcheng hospital from January 2017 to June 2021 were recruited for model construction, internal validation and external validation. The first time point of data collection was within half a month of patients first diagnosed with NLUTD. The second time point was at the 6-month follow-up. The early warning model was constructed by logistic regression. The model prediction effects were validated using the area under the Receiver Operating Characteristic curve, the Boostrap experiment and the calibration plot of the combined data. The model was externally validated using sensitivity, specificity and accuracy. Results: Six predictors were identified in the model, namely patients ≥65 years old (OR = 2.478, 95%CI [1.215- 5.050]), female (OR = 2.552, 95%CI [1.286-5.065]), diabetes (OR = 2.364, 95%CI) [1.182-4.731]), combined with urinary calculi (OR = 2.948, 95%CI [1.387-6.265]), indwelling catheterization (OR = 1.988, 95%CI [1.003 -3.940]) and bladder behavior training intervention time ≥2 weeks (OR = 2.489, 95%CI [1.233-5.022]); and the early warning model formula was Conclusion: The early warning model for urinary tract infection in patients with NLUTD is suitable for clinical practice, which can provide targeted guidance for the evaluation of urinary tract infection in patients with NLUTD.

Indexed as

Urinary Bladder, NeurogenicUrinary CalculiUrinary Tract InfectionsAgedFemaleHumansInfantRetrospective StudiesUrinary BladderEarly waring modelNeurogenic bladderNeurogenic lower urinary tract dysfunctionRisk factorsUrinary tract infection

Identifiers

PMID35539015
PMCPMC9080428

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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.