Evidence map›Paper›PMID 40452927›Full record

ArticlePeerJ2025

Traumatic spinal cord injury: identifying independent risk factors and predictive model development for symptomatic urinary tract infections.

Huayong Du, Zehui Li, Jinming Zhang, Xiaoxin Wang, Yingli Jing, Degang Yang, Jianjun Li

Abstract read
In one paragraph

Article in PeerJ, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Huayong DuSchool of Rehabilitation Medicine, Capital Medical University, Beijing, Fengtai, China.
Zehui LiSchool of Rehabilitation Medicine, Capital Medical University, Beijing, Fengtai, China.
Jinming ZhangSchool of Rehabilitation Medicine, Capital Medical University, Beijing, Fengtai, China.
Xiaoxin WangSchool of Rehabilitation Medicine, Capital Medical University, Beijing, Fengtai, China.
Yingli JingSchool of Rehabilitation Medicine, Capital Medical University, Beijing, Fengtai, China.
Degang YangSchool of Rehabilitation Medicine, Capital Medical University, Beijing, Fengtai, China.
Jianjun LiSchool of Rehabilitation Medicine, Capital Medical University, Beijing, Fengtai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Traumatic spinal cord injury (TSCI) is commonly associated with urinary tract infections (UTIs), with a reported prevalence ranging from 31.7% to 68%. Symptomatic UTIs can result in serious complications, including chronic kidney damage and recurrent infections. The objective of this study was to identify independent risk factors and develop a predictive model for symptomatic UTIs in TSCI patients, thereby providing valuable insights for prevention and management strategies. Methods: A retrospective study was conducted at the China Rehabilitation Research Center, involving 168 TSCI patients admitted between January 1, 2020, and August 1, 2024. Symptomatic UTIs were diagnosed using Delphi consensus criteria, which integrated clinical symptoms, urinalysis, and culture confirmation. Comprehensive clinical data, including demographic characteristics, injury profiles, and laboratory parameters, were systematically extracted from the hospital information system. Potential risk factors were initially screened using univariable logistic regression, with statistically significant variables subsequently analyzed in a multivariable logistic regression model to identify independent predictors. A predictive model for symptomatic UTIs was constructed using the regression coefficients. The model's performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration with the Hosmer-Lemeshow test, and internal validation through bootstrap resampling. Results: The incidence of symptomatic UTIs was 57.14%, with the majority presenting with fever (65.07%) and Escherichia coli infections (44.52%). Prolonged hospitalization (OR = 1.005, 95% CI [1.001-1.010]) and cumulative antibiotic exposure (OR = 1.011, 95% CI [1.000-1.022]) were identified as independent risk factors. The predictive model, which incorporated these factors, demonstrated strong discrimination (AUC = 0.81, 95% CI [0.746-0.879]) and good calibration ( Conclusions: This study presents the incidence of symptomatic UTIs in TSCI patients and identifies two critical predictive factors along with a risk score for early prediction of symptomatic UTIs. The findings provide a foundation for improved clinical practices aimed at preventing and managing symptomatic UTIs in this patient population, potentially reducing healthcare costs and improving patient outcomes.

Indexed as

Spinal Cord InjuriesUrinary Tract InfectionsAdultAgedChinaFemaleHumansIncidenceLogistic ModelsMaleMiddle AgedRetrospective StudiesRisk FactorsYoung AdultLogistic regressionReceiver operator characteristicRisk factorsSymptomatic urinary tract infectionsTraumatic spinal cord injury

Identifiers

PMID40452927
PMCPMC12126090

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.