Evidence map›Paper›PMID 36788830›Full record

ArticleCureus2023

Role of Multi-Detector Computed Tomography in the Diagnosis of Intestinal Obstruction.

Shaista Afzal, Furqan Ahmad, Fizza Farooq

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2023. 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
2.9field-weighted citation impact, top 10% 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, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. 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

3 authors at 1 institution in 1 country.

Shaista AfzalDiagnostic Radiology, Aga Khan University Hospital, Karachi, PAK.
Furqan AhmadDiagnostic Radiology, Aga Khan University Hospital, Karachi, PAK.
Fizza FarooqDiagnostic Radiology, Aga Khan University Hospital, Karachi, PAK.
Aga Khan University Hospital · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThere is a need to identify patients whose small bowel obstruction (SBO) can resolve spontaneously so that unnecessary surgical interventions are avoided. This study aimed to evaluate the diagnostic accuracy of multi-detector computed tomography (MDCT) in intestinal obstruction and find out the presence, level, causes, and degree of intestinal obstruction taking intraoperative findings as gold standard. METHODOLOGY: This cross-sectional study was conducted analyzing 147 patients that were referred from emergency with abdominal pain, abdominal distension, inability to pass flatus, and aged 18-70 years from both genders. Computed tomography (CT) examinations were done and findings like intestinal dilatation, evidence of mesenteric fat stranding, and area of transition between the dilated and collapsed loops were noted. The final report was made by the radiologist while the operative findings were reviewed from the operative notes written by operative surgeons of the same patient.

resultsIn a total of 147 patients, mean age was 52.38±16.01 years. There were 76 (51.70%) males and 71 (48.30%) females. Sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy of multi-detector computed tomography scan in diagnosing intestinal obstruction, taking operative findings as gold standard, were 98.39%, 65.22%, 93.85%, 88.24%, and 93.20%, respectively.

conclusionThe multi-detector CT can be used routinely as a prime modality for detecting intestinal obstruction which will result in proper and timely management for reducing the morbidity and mortality of these particular patients.

Indexed as

abdominal distensionintestinal obstructionmulti-detector computed tomographysensitivityspecificity

Identifiers

PMID36788830
PMCPMC9922381
OpenAlexW4316039786

What OpenQuestion holds

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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.