Evidence map›Paper›PMID 41618270›Full record

ArticleBMC oral health2026

Comparative effectiveness of cervical vertebral maturation and hand-wrist radiography in assessing bone age in patients with amelogenesis imperfecta: a retrospective analysis.

İpek Şavkan, Elis Dayan, Didem Öner Özdaş, Sevgi Erişmiş Zorlu, Sibel Biren, Elif Sepet, Gamze Aren

Abstract readComparative Study
In one paragraph

Article in BMC oral health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

İpek ŞavkanDepartment of Orthodontics, Istanbul Kent University, Cihangir Mah. Sıraselviler Caddesi No 71 Beyoğlu, Istanbul, Turkey. ipek.savkan@kent.edu.tr.
Elis DayanDepartment of Pediatric Dentistry, Istanbul Kent University, Istanbul, Turkey.
Didem Öner ÖzdaşDepartment of Pediatric Dentisrty, İstanbul Aydın University, Istanbul, Turkey.
Sevgi Erişmiş ZorluDepartment of Pediatric Dentisrty, İstanbul Aydın University, Istanbul, Turkey.
Sibel BirenDepartment of Orthodontics, Istanbul Kent University, Cihangir Mah. Sıraselviler Caddesi No 71 Beyoğlu, Istanbul, Turkey.
Elif SepetDepartment of Pediatric Dentistry, Istanbul Kent University, Istanbul, Turkey.
Gamze ArenDepartment of Peidatric Dentistry, Biruni University, Istanbul, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveAmelogenesis imperfecta (AI) is a hereditary enamel disorder whose potential impact on skeletal development remains unclear. Accurate assessment of skeletal maturation is essential for optimizing treatment timing in these individuals. This study aimed to investigate the agreement between cervical vertebral maturation (CVM) and hand-wrist radiography (HWR) in determining skeletal age in patients with AI.

methodsThis retrospective study included 28 AI patients (16 females, 12 males; mean age: 9.65 ± 2.92 years) and 30 age- and sex-matched healthy controls. This retrospective study analyzed 58 participants: 28 patients with AI (16 females, 12 males; mean age 9.65 ± 2.92 years) and 30 healthy controls matched for age and sex (15 females, mean age 10.4 ± 2.09 years and 15 males, mean age 10.93 ± 2.4 years). Skeletal maturation was assessed via CVM stages from lateral cephalometric radiographs and Björk’s hand-wrist maturation stages. For comparative analysis, Björk’s nine stages were condensed into five developmental categories. Agreement between methods was evaluated via weighted kappa statistics. Gender-based subgroup analyses and intermethod correlations were also performed. Statistical significance was set at p < 0.05.

resultsModerate agreement was observed between the CVM and HWM stages in both groups (AI group: κ = 0.440; control group: κ = 0.556; total: κ = 0.525;p < 0.05). The lowest agreement was found among males with AI (κ = 0.221; p < 0.05), whereas the highest agreement occurred among control group males (κ = 0.623; p < 0.05). Despite moderate overall agreement, the findings suggest possible discrepancies in skeletal maturation assessment among AI patients, particularly in male subgroups.

conclusionThe CVM and HWM methods demonstrated moderate overall agreement in assessing skeletal age. However, the reduced agreement in male AI patients indicates the need for careful interpretation of skeletal maturation in this subgroup. The results highlight the importance of using both methods complementarily to optimize growth assessment and treatment planning in AI patients.

Indexed as

Age Determination by SkeletonAmelogenesis ImperfectaCervical VertebraeHandHand BonesWristAdolescentCase-Control StudiesChildFemaleHumansMaleRadiographyRetrospective StudiesAmelogenesis imperfectaCVMMaturation

Identifiers

PMID41618270
PMCPMC12931047

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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.