Evidence map›Paper›PMID 28893000›Full record

ArticleJournal of clinical and diagnostic research : JCDR2017

Detection of Dental Pathologies in Routine Paranasal CT Scans: A Retrospective Study.

Erdogan Bulbul, Bahar Yanik, Gulen Demirpolat

Abstract read
In one paragraph

Article in Journal of clinical and diagnostic research : JCDR, 2017. 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
–field-weighted citation impact
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

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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.

  1. Article
  2. Article
  3. Dental Trauma on whole Body Trauma CT-An underreported finding.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2022
    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.

Erdogan BulbulAssistant Professor, Department of Radiology, Faculty of Medicine, Balikesir University, Turkey.
Bahar YanikProfessor, Department of Radiology, Faculty of Medicine, Balikesir University, Turkey.
Gulen DemirpolatAssociate Professor, Department of Radiology, Faculty of Medicine, Balikesir University, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionMultidetector Computed Tomography (MDCT) is a widespread method for evaluating paranasal sinuses and nasal cavity in daily practice. The maxillary teeth are in field of view in a paranasal sinus CT scan and it is possible to detect dental pathologies with CT.

aimTo determine the incidence of maxillary teeth pathologies in routine paranasal sinus CT scans. MATERIALS AND

methodsA retrospective study was conducted. Consecutive 395 paranasal sinus CT scans were evaluated. All CT images were obtained with a 64 detector-CT. Patients with previous facial trauma, operation, invasive tumors and repeated exams were excluded. Detected findings were classified as "tooth loss, dental restorations or procedures and dental pathologies (carious lesions, dental developmental anomalies, periapical lesions and periodontal diseases). The proportion of findings was reported as simple percentiles.

resultsThree hundred and eighty-four CT scans were included in the study. Dental restorations or procedures were determined in 129 (33.5%) patients. A total of 34 (8.8%) patients had normal teeth count and morphology. A total of 264 (64.3%) patients had at least one tooth loss. A total of 195 (51%) patients had at least one or more dental pathology. Number of dental carious lesions, dental developmental anomalies, periapical lesions and periodontal disease were 104 (27.0%), 78 (14.3%), 46 (11.9%), 44 (11.4%), respectively.

conclusionDental pathologies were encountered in more than half of the patients. Detecting dental pathologies may prevent tooth loss and improve oral health. The radiologist should keep in mind dental pathologies while evaluating paranasal sinus CT in daily practice.

Indexed as

MaxillaryOral healthPeriodontal diseaseRadiologyTooth decay

Identifiers

PMID28893000
PMCPMC5583835

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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.