Evidence map›Paper›PMID 35386911›Full record

ArticleFrontiers in medicine2022

Evaluation of the Predictive Value of Urine Leukocyte Esterase Test in

Xueying Yu, Peizhen Zhao, Zhida Mai, Qingqing Xu, Wentao Chen, Zhiqiao Wu, Xiaojuan Luo, Zhizhou Wu, Xiaofeng Liu, Qian Wu and 2 more

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

Article in Frontiers in medicine, 2022. 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, top 97% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

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

12 authors at 5 institutions in 1 country.

Xueying YuDepartment of Clinical Laboratory, Dermatology Hospital, Southern Medical University, Guangzhou, China.
Peizhen ZhaoDepartment of Clinical Laboratory, Dermatology Hospital, Southern Medical University, Guangzhou, China.
Zhida MaiDepartment of Clinical Laboratory, Dermatology Hospital, Southern Medical University, Guangzhou, China.
Qingqing XuDepartment of Clinical Laboratory, Dermatology Hospital, Southern Medical University, Guangzhou, China.
Wentao ChenDepartment of Clinical Laboratory, Dermatology Hospital, Southern Medical University, Guangzhou, China.
Zhiqiao WuDepartment of Clinical Laboratory, The Sixth People's Hospital of Dongguan, Dongguan, China.
Xiaojuan LuoDepartment of Clinical Laboratory, The First People's Hospital of Foshan, Foshan, China.
Zhizhou WuDepartment of Clinical Laboratory, Dermatology Hospital of Jiangmen, Jiangmen, China.
Xiaofeng LiuDepartment of Clinical Laboratory, The Third People's Hospital of Zhuhai, Zhuhai, China.
Qian WuDepartment of Clinical Laboratory, Dermatology Hospital, Southern Medical University, Guangzhou, China.
Heping ZhengDepartment of Clinical Laboratory, Dermatology Hospital, Southern Medical University, Guangzhou, China.
Yaohua XueDepartment of Clinical Laboratory, Dermatology Hospital, Southern Medical University, Guangzhou, China.
Southern Medical University · CNJiangmen Central Hospital · CNFirst People's Hospital of Foshan · CNTongji University · CNZhuhai People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Leukocyte esterase test (LET) detection is a simple and inexpensive test performed by urinalysis. This study investigated the predictive value of LET for

Indexed as

Chlamydia trachomatiscost-effectiveleukocyte esterase testNeisseria gonorrhoeaenucleic acid amplification testprevalence

Identifiers

PMID35386911
PMCPMC8978786
OpenAlexW4221038472

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.