Evidence map›Paper›PMID 41476358›Full record

ArticleJournal of Indian Prosthodontic Society2026

Predictors of patient dissatisfaction with ceramic veneers: A matched case-control study.

Sagar J Abichandani, Aneendita Dutta

Abstract read
In one paragraph

Article in Journal of Indian Prosthodontic Society, 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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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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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

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Sagar J AbichandaniDepartment of Prosthodontics, Private Practice, Mumbai, Maharashtra, India.
Aneendita DuttaDepartment of General Dentistry, Private Practice, Mumbai, Maharashtra, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo assess the association between mock-up technique (chairside bis-acryl vs digitally fabricated 3D-printed) and shade-matching protocol (chairside visual vs laboratory-assisted/digital) with patient-initiated esthetic dissatisfaction resulting in refund or retreatment within 12 months of veneer delivery. SETTINGS AND

designSingle-center, 1:1 matched case-control study (23 pairs; n = 46) in a private prosthodontic practice. MATERIALS AND

methodsExposures were chairside bis-acryl versus digitally fabricated 3D-printed mock-ups and chairside visual versus laboratory-assisted/digital shade matching. The primary outcome was patient-initiated esthetic dissatisfaction within 12 months resulting in refund or retreatment; refund-only and retreatment-only outcomes were prespecified as exploratory. STATISTICAL ANALYSIS USED: Primary analysis used exact conditional methods for matched pairs (McNemar) with exact 95% confidence intervals; in the presence of separation, the exact lower confidence bound was reported without continuity corrections. A supportive multivariable unconditional logistic regression adjusted for age, sex, exact number of units, arch, and cost tier, and E-values were calculated to assess robustness to unmeasured confounding.

resultsChairside mock-ups and chairside-only shade selection were more frequent in cases than controls. The matched odds ratio (OR) for chairside versus digitally fabricated mock-ups was ∞ (exact lower 95% confidence interval ≥2.51; P = 0.0010), and for chairside versus laboratory-assisted/digital shade matching was 6.00 (95% confidence interval 1.34-55.20; P = 0.0129). In the supportive adjusted model, the ORs were 5.87 (95% confidence interval 1.59-21.66; P = 0.008) for mock-up technique and 4.41 (1.26-15.42; P = 0.021) for shade protocol; corresponding E-values were 11.48, 11.22, and 8.29, respectively.

conclusionWithin the limitations of a retrospective, single-center design and modest sample size, chairside bis-acryl mock-ups and chairside-only shade matching were associated with higher odds of early esthetic dissatisfaction leading to refund or retreatment. Adoption of standardized digital workflows with digitally designed/3D-printed mock-ups and calibrated shade protocols is recommended as a clinical quality-assurance measure to mitigate this risk.

Indexed as

CeramicsDental Prosthesis DesignDental VeneersEsthetics, DentalPatient SatisfactionAdultCase-Control StudiesFemaleHumansMaleMiddle AgedPrinting, Three-DimensionalCase–control studiescolor matchingcomputer-aided designdental estheticsdental veneerspatient satisfaction

Identifiers

PMID41476358
PMCPMC12912501

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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.