Evidence map›Paper›PMID 38289424›Full record

ArticleWorld journal of urology2024

Predictive markers for infections after extracorporeal shockwave lithotripsy in patients with kidney stone based on a large prospective cohort.

Bitian Liu, Shen Pan, Lu Wang, Song Bai, Dongmei Liu

Abstract read
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In one paragraph

Article in World journal of urology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 40% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Predictive value of circulating PD-1Frontiers in medicine · 2025
    Article
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

5 authors at 1 institution in 1 country.

Bitian Liu *Department of Urology, Shengjing Hospital of China Medical University, 36 Sanhao Street, Shenyang, Liaoning, 110004, People's Republic of China.
Shen Pan *Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, People's Republic of China.
Lu Wang *Department of Urology, Shengjing Hospital of China Medical University, 36 Sanhao Street, Shenyang, Liaoning, 110004, People's Republic of China.
Song BaiDepartment of Urology, Shengjing Hospital of China Medical University, 36 Sanhao Street, Shenyang, Liaoning, 110004, People's Republic of China. baisongcmu81@163.com.ORCID http://orcid.org/0000-0002-6073-145X
Dongmei LiuDepartment of Urology, Shengjing Hospital of China Medical University, 36 Sanhao Street, Shenyang, Liaoning, 110004, People's Republic of China. liudongmeicmu@163.com.ORCID http://orcid.org/0000-0003-1822-7580
China Medical University · CN

Funding

Natural Science Foundation of Liaoning Education Department QN2019013Natural Science Foundation of Liaoning Science and Technology Department 2020-BS-093
6 · The paper itself

Abstract

objectiveInfections in patients with kidney stones after extracorporeal shockwave lithotripsy (SWL) is a common clinical issue. However, the associated factors are unclear. Therefore, we aim to develop and validate a predictive model for infections after SWL in patients with kidney stone.

methodsBetween June 2020 and May 2022, consecutive kidney stone patients were enrolled. Of them, 553 patients comprised the development cohort. One hundred sixty-five patients comprised the validation cohort. The data were prospectively collected. The stepwise selection was applied using the likelihood ratio test with Akaike's information criterion as the stopping rule; A predictive model was constructed through multivariate logistic regression. The performance was evaluated regarding discrimination, calibration, and clinical usefulness.

resultsPredictors of infections after SWL in treating kidney stones included older age (OR = 1.026, p = 0.041), female (OR = 2.066, p = 0.039), higher BMI (OR = 1.072, p = 0.039), lower stone density (OR = 0.995, p < 0.001), and higher grade of hydronephrosis (OR = 5.148, p < 0.001). For the validation cohort, the model showed good discrimination with an area under the receiver operating characteristic curve of 0.839 (95% CI 0.736, 0.941) and good calibration. Decision curve analysis demonstrated that the model was also clinically useful.

conclusionThis study indicated that age, gender, BMI, stone density, and hydronephrosis grade were significant predictors of infections after SWL in treating kidney stones. It provided evidence in optimizing prevention and perioperative treatment strategies to reduce the risk of infection after SWL.

Indexed as

HydronephrosisKidney CalculiLithotripsyFemaleHumansPatientsProspective StudiesExtracorporeal shock wave lithotripsyInfectionsKidney stonePredictive model

Identifiers

PMID38289424
OpenAlexW4391347100

What OpenQuestion holds

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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.