Evidence map›Paper›PMID 36199957›Full record

ArticleComputational intelligence and neuroscience2022

Computational Analysis of Influencing Factors and Multiple Scoring Systems of Stone Clearance Rate after Flexible Ureteroscopic Lithotripsy.

Lei Xia, Hanqing Xuan, Yang Cao, Zhebin Du, Hai Zhong, Qi Chen

Abstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
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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

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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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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.

Lei XiaDepartment of Urology, Ren Ji Hospital, School of Medicine Shanghai Jiaotong University, Shanghai 200127, China.ORCID https://orcid.org/0000-0001-5631-1180
Hanqing XuanDepartment of Urology, Ren Ji Hospital, School of Medicine Shanghai Jiaotong University, Shanghai 200127, China.ORCID https://orcid.org/0000-0002-2021-0131
Yang CaoDepartment of Urology, Ren Ji Hospital, School of Medicine Shanghai Jiaotong University, Shanghai 200127, China.ORCID https://orcid.org/0000-0002-6302-1883
Zhebin DuDepartment of Urology, Ren Ji Hospital, School of Medicine Shanghai Jiaotong University, Shanghai 200127, China.ORCID https://orcid.org/0000-0001-7330-3035
Hai ZhongDepartment of Urology, Ren Ji Hospital, School of Medicine Shanghai Jiaotong University, Shanghai 200127, China.ORCID https://orcid.org/0000-0002-7014-7871
Qi ChenDepartment of Urology, Ren Ji Hospital, School of Medicine Shanghai Jiaotong University, Shanghai 200127, China.ORCID https://orcid.org/0000-0002-7085-7777

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Our research aims at the analysis of various stone scoring systems which are referred to as STONE scoring system (SSS) in this study. GUY's scoring system and RUSS scoring system (RSS) are utilized to predict stone-free status (SFS) after surgery and problems after percutaneous nephrolithotomy (PCNL) for harder stones. The data of 68 patients with renal calculi who received FURL in Ren Ji Hospital from Jan 2020 to Mar 2021 are collected as the study subjects. There were 44 male and 24 female patients, with an average age of 55.6 ± 11.4 years. Reliability analysis of related influencing factors (IF) of stone clearance rate (SCR) and multiple scoring systems after flexible ureteroscopic lithotripsy (FURL) was performed. Relevant factors with statistical significance for postoperative SCR were selected for logistic regression analysis (RA). According to the SSS score, GSS classification, and RUSS score, the SCR after FURL was statistically analyzed. The results showed that the

Indexed as

LithotripsyUreteroscopyAdultAgedFemaleHumansMaleMiddle AgedReproducibility of ResultsRetrospective StudiesTreatment Outcome

Identifiers

PMID36199957
PMCPMC9529465

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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.