Evidence map›Paper›PMID 32335620›Full record

ArticleJNMA; journal of the Nepal Medical Association2020

Study of Missing Clinical Details in Computed Tomography Radiology Request Forms: A Descriptive Cross-sectional Study.

Muna Badu

Open access · diamondAbstract read
In one paragraph

Article in JNMA; journal of the Nepal Medical Association, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 38% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Review
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

1 author at 1 institution in 1 country.

Muna BaduDepartment of Radiology, Kathmandu Medical College and Teaching Hospital, Sinamangal, Kathmandu, Nepal.
Kathmandu Medical College Teaching Hospital · NP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionDetailed clinical history through a properly filled requisition form can help a radiologist in making a diagnosis. The objective of this study was to observe the missing clinical details of Computed Tomography requisition forms at radiology department in tertiary care hospital.

methodsThis descriptive cross-sectional study was done in 196 Computed Tomography requisition forms in the department of radiology from September 2019 to October 2019. Ethical clearance from the Institutional Review Committee - Reference No. 120720194 was obtained. An informed consent from the participants was taken prior to the procedure. Convenient sampling was done. The data obtained were computed and analyzed using Statistical Package for Social Sciences to tabulate the results. The results were displayed in frequency and proportion of binary data.

resultsAll the request forms had name filled, however date was filled in 183 (93.4%), age was filled in 195 (99.5%), sex was filled in 193 (98.5%) and address was only in 30 (15.3%) of the forms. Clinical history and provisional diagnosis were written in 179 (91.3%) forms. Signature was found in more than half of forms 135 (68.9%) whereas the department referring the patient was filled in 92 (46.9%) of forms and the name of doctor referring the patient was not filled mostly. The handwriting was clear in 191 (97.4%) of cases and standard words were used. Use of non-standard abbreviation was found in only 2 (1%) forms.

conclusionsClinical details were filled in most of the requisition forms however other parameters were still incompletely and inadequately filled.

Indexed as

Forms and Records ControlInformed ConsentRadiologyTomography, X-Ray ComputedCross-Sectional StudiesHumansPhysiciansdata; forms; missing; Tomography; radiology.

Identifiers

PMID32335620
PMCPMC7654455
OpenAlexW3027861171

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Registered trials

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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.