Evidence map›Paper›PMID 35002261›Full record

ArticleInfection and drug resistance2021

Predictive Value of Urinalysis and Recent Antibiotic Exposure to Distinguish Between Bacteriuria, Candiduria, and No-Growth Urine.

Darunee Chotiprasitsakul, Akara Kijnithikul, Anuchat Uamkhayan, Pitak Santanirand

Open access · goldAbstract read
In one paragraph

Article in Infection and drug resistance, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.8field-weighted citation impact, top 27% 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

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. High prevalence of fluconazole resistantFrontiers in microbiology · 2023
    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

4 authors at 1 institution in 1 country.

Darunee ChotiprasitsakulDepartment of Medicine, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.ORCID 0000-0003-2669-0372
Akara KijnithikulDepartment of Medicine, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
Anuchat UamkhayanDepartment of Pathology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
Pitak SantanirandDepartment of Pathology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.ORCID 0000-0002-3914-1367
Mahidol University · TH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeUrinary tract infections are diagnosed by clinical symptoms and detection of causative uropathogen. Antibiotics are usually not indicated in candiduria and no-growth urine. We aimed to develop a predictive score to distinguish bacteriuria, candiduria, and no-growth urine, and to describe the distribution of microorganisms in urine. PATIENTS AND

methodsA single-center, retrospective cohort study was conducted between January 2017 and November 2017. Patients with concomitant urinalysis and urine culture were randomly sorted for a clinical prediction model. Multivariable regression analysis was performed to determine factors associated with bacteriuria, candiduria, and no-growth urine. A scoring system was constructed by rounding the regression coefficient for each predictor to integers. Accuracy of the score was measured by the concordance index (c-index).

resultsThere were 8091 positive urine cultures: bacteria 85.6%,

conclusionNumerous yeast on urinalysis and the NABY score may help identify patients with a low risk of bacteriuria in whom empiric antibiotics for UTIs can be avoided.

Indexed as

antibioticsCandidamicroscopyNABY scoreurinary tract infectionurine culture

Identifiers

PMID35002261
PMCPMC8722576
OpenAlexW4200509671

What OpenQuestion holds

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LicenceCC BY-NC
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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.