Evidence map›Paper›PMID 35571982›Full record

ReviewThe Indian journal of surgery2023

Nursing Effect Analysis of Urinary Tract Infections in Urology Surgery Patients: a Systematic Review and Meta-analysis.

Ailin Shan, Muhammad Hasnain, Ping Liu

Open access · bronzeAbstract readReview
In one paragraph

Review in The Indian journal of surgery, 2023. 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
0.6field-weighted citation impact, top 33% 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, 4 citations in OpenAlex.

  1. 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

3 authors at 2 institutions in 2 countries.

Ailin ShanDepartment of Urology, Taizhou Jiangyan Hospital of Chinese Medicine, Taizhou, Jiangsu Province 225500 China.
Muhammad HasnainLahore Leads University, Lahore, Punjab, 42000 Pakistan.
Ping LiuDepartment of Urology, The First Affiliated Hospital of Harbin Medical University Qunli Hospital, Heilongjiang Province, Harbin, 150000 China.
First Affiliated Hospital of Harbin Medical University · CNLahore Leads University · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This meta-analysis aims to identify urinary tract infections (UTIs) in patients with different levels of age groups. For both diagnosis and treatment of UTIs, antibiotics have been widely used in nursing home settings. We also aimed to evaluate the duration of catheterization in UTI patients to reduce catheter-associated complications. We conducted a systematic review that was performed following the "Preferred Reporting Items for Systematic Reviews and Meta-Analyses" (PRISMA) guidelines and recommendations from Cochrane Collaboration. We performed a comprehensive search for published literature in PubMed, ScienceDirect, Taylor & Francis Online, Springer, and Wiley Online databases from 2010 to June 25, 2021. We performed two meta-analysis: the first meta-analysis (meta-analysis I) was performed on data obtained from included studies that compared patients with UTIs (experimental group) and without UTIs (control group); the second meta-analysis (meta-analysis II) was performed to assess the appropriate use of a catheter in UTI patients. All statistical analyses were conducted using the Review Manager 5.4 tool. A total of 15 research articles were included in this systematic review and meta-analysis. Of these, results showed the identification of critical patients with UTIs and without UTIs from nursing resident homes (risk ratio [RR] = 0.80 95% confidence interval CI = 0.69-0.93

Indexed as

AgentsAntibioticsCatheterDiagnostic and treatment techniqueNursing home residents

Identifiers

PMID35571982
PMCPMC9088134
OpenAlexW4229460174

What OpenQuestion holds

Textmetadata
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.