Evidence map›Paper›PMID 35621494›Full record

ArticleBioengineering (Basel, Switzerland)2022

3D Cephalometric Normality Range: Auto Contractive Maps (ACM) Analysis in Selected Caucasian Skeletal Class I Age Groups.

Marco Farronato, Giuseppe Baselli, Benedetta Baldini, Gianfranco Favia, Gianluca Martino Tartaglia

Abstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 2 pooled it
–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

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

26 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Retrospective Descriptive Case Series on the Use of AMCOPBioengineering (Basel, Switzerland) · 2026
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  20. Arduino Automated Microwave Oven for Tissue Decalcification.Bioengineering (Basel, Switzerland) · 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

5 authors.

Marco FarronatoDepartment of Orthodontics, Faculty of Medicine, University of Milan, 20100 Milan, Italy.ORCID 0000-0002-6209-9873
Giuseppe BaselliDepartment of Electronics, Information and Bioengineering, Politecnico Di Milano, 20133 Milan, Italy.ORCID 0000-0003-2978-1704
Benedetta BaldiniDepartment of Orthodontics, Faculty of Medicine, University of Milan, 20100 Milan, Italy.
Gianfranco FaviaDepartment of Interdisciplinary Medicine, Odontostomatology Unit, University of Bari "Aldo Moro", 70121 Bari, Italy.
Gianluca Martino TartagliaDepartment of Orthodontics, Faculty of Medicine, University of Milan, 20100 Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The objective of this paper is to define normal values of a novel 3D cephalometric analysis and to define the links through an artificial neural network (ANN).

methodsOne hundred and fifteen CBCTs of Class I young patients, distributed among gender-adjusted developmental groups, were selected. Three operators identified 18 cephalometric landmarks from which 36 measurements were obtained. The repeatability was assessed through the ICC. Two-dimensional values were extracted by an automatic function, and the mean value and standard deviation were compared by paired Student's

resultsThe ICC assessed an excellent (≥0.9) repeatability. Normal values were extracted, and compared with 2D measurements, they showed a high correlation on the mid-sagittal plane, reaching 1.00, with the lowest 0.71 on the lateral plane. The ANN showed strong links between the values with the centrality of the go-sagittal plane compared to the rest.

conclusionsThe study provides a set of 3D cephalometric values obtained by the upper and lower 95% CI for the mean divided into the developmental stage subgroups. The two-dimensional measurements showed variable concordance, while the ANN showed a centrality between the parameters.

Indexed as

anatomycephalometrydigital dentistryhead and skullneural networksorthodontics

Identifiers

PMID35621494
PMCPMC9137702

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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.