Evidence map›Paper›PMID 34408932›Full record

ArticleCureus2021

The Use of Visual Analogue Scale Score as a Predicting Tool in Differentiating Renal Colic From Lumbar Back Pain.

Mehmet Caniklioğlu, Muharrem Özkaya

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 22% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. 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

2 authors at 2 institutions in 2 countries.

Mehmet CaniklioğluUrology, Bozok University Faculty of Medicine, Yozgat, TUR.
Muharrem ÖzkayaUrology, Sinop Atatürk State Hospital, Sinop, TUR.
Bozok Universitesi · TRState Hospital · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction Renal colic is often confused with low back pain (LBP) and other pathologies. Computed tomography (CT) is frequently used to reach a definitive diagnosis, but its use increases the exposure to radiation. Researchers have tried to predict urinary stones in patients presenting with flank pain. Several scoring systems have been introduced; however, none of them provide a prediction based on the physical examination of the patient upon initial presentation to the outpatient clinic. In this study, we aimed to investigate whether we can predict the presence of stone with visual analogue scale (VAS) questionnaire during the first admission. Materials and methods Patients with complaints of flank pain were started to be followed for three months in our urology clinic. After the definitive diagnosis was made the patients were classified into two groups: renal colic group (group 1; n=36) and the LBP group (group 2; n=30). Results In logistic regression analysis, the possibility of renal colic increased 5.4 times more per one-unit increase in the VAS score. In receiver operating characteristic (ROC) analyses, when the VAS was 4.5, the diagnosis of renal colic could be made with 88% sensitivity and 71% specificity. Conclusion If the VAS score is ≤ 4 in patients that have flank pain without limitation of movement, it is more likely to manage these patients with a simple medical treatment plan. In these patients, unnecessary ultrasonography (US) scans be reduced by 86.3% and unnecessary CT scans by 88.8%. A VAS score of ≥5 should warn the clinician about the necessity of routine urinary stone examinations.

Indexed as

differential diagnosisflank painlow back painrenal colicscoring systemsvas score

Identifiers

PMID34408932
PMCPMC8362862
OpenAlexW3179138866

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.