Evidence map›Paper›PMID 42474571›Full record

ArticleJournal of robotic surgery2026

Preoperative gap phenotypes in functionally aligned robotic total knee arthroplasty: derivation and internal coherence of a driver-based classification.

Eduardo Frois Temponi, Jared Philip Sachs, Matheus Braga Jacques Gonçalves, Luiz Fernando Machado Soares, Lúcio Honório de Carvalho Júnior

Abstract read
In one paragraph

Article in Journal of robotic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Eduardo Frois TemponiHospital Madre Teresa, Av. Raja Gabaglia 1002Gutierrez, Belo Horizonte, 30441-070, MG, Brazil. dufrois@gmail.com.ORCID http://orcid.org/0000-0003-0612-7275
Jared Philip SachsDepartment of Orthopaedic Surgery, Westchester Medical Center, New York, Valhalla, USA.ORCID http://orcid.org/0009-0000-5919-0193
Matheus Braga Jacques GonçalvesHospital Madre Teresa, Av. Raja Gabaglia 1002Gutierrez, Belo Horizonte, 30441-070, MG, Brazil.ORCID http://orcid.org/0009-0008-3705-958X
Luiz Fernando Machado SoaresHospital Madre Teresa, Av. Raja Gabaglia 1002Gutierrez, Belo Horizonte, 30441-070, MG, Brazil.ORCID http://orcid.org/0009-0007-3434-2999
Lúcio Honório de Carvalho JúniorHospital Madre Teresa, Av. Raja Gabaglia 1002Gutierrez, Belo Horizonte, 30441-070, MG, Brazil.ORCID http://orcid.org/0000-0003-2683-6386

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Robotic total knee arthroplasty (TKA) enables repeated intraoperative quantification of preoperative alignment, flexion deformity, and medial and lateral compartment gaps in extension and at 90° flexion before component positioning, but the preoperative patterns guiding functional-alignment planning remain incompletely characterized. This study aimed to derive a pragmatic driver-based classification from preoperative robotic data and evaluate its internal coherence across the surgical workflow. We analyzed 68 consecutive primary functionally aligned robotic TKAs performed by a single surgeon using a CT-based robotic-arm platform. Preoperative variables included hip-knee-ankle angle (HKA), flexion deformity, and independent medial and lateral gaps in extension and at 90° flexion. A 10-case formative series informed concept generation; the finalized hierarchy was then applied to all cases using preoperative variables only. Four phenotypes were derived: bone-driven, ligament-driven, flexion-dominant, and mixed/complex (defined as the co-occurrence of two or more severe deformity drivers). Internal coherence was assessed through release escalation, corrected-state behavior, plan-to-final HKA fidelity, and mechanical and functional-alignment balance. Inter-observer reliability was tested by having five independent surgeons classify all cases blinded, with agreement quantified by Fleiss' and Cohen's kappa. All knees were classified: bone-driven, 40/68 (58.8%); ligament-driven, 6/68 (8.8%); flexion-dominant, 10/68 (14.7%); and mixed/complex, 12/68 (17.6%). Release escalation occurred in 1/68 (1.5%), with no posterior capsulotomy. Overall, 58/63 (92.1%) finished within ± 2° of planned HKA; strict mechanical balance was achieved in 58/62 (93.5%) and functional-alignment balance in 61/62 (98.4%). Flexion-dominant knees showed lower coronal fidelity but complete final balance, suggesting a coronal-sagittal trade-off during functional planning. Inter-observer agreement among the five surgeons was almost perfect (Fleiss' kappa 0.88, 95% CI 0.81-0.93; 92.4% overall agreement). Preoperative HKA, sagittal deformity, and medial-lateral gap asymmetry revealed recurring patterns organized into a four-phenotype driver framework. This classification is best interpreted as an internally coherent derivation framework that showed almost perfect inter-observer reliability (Fleiss' kappa 0.88) but still requires external, multicenter validation and threshold-sensitivity analysis before its clinical utility can be established.

Indexed as

Arthroplasty, Replacement, KneeRobotic Surgical ProceduresAgedFemaleHumansKnee JointMaleMiddle AgedPhenotypeRange of Motion, ArticularReproducibility of ResultsClassificationFunctional alignmentGap balancingKnee phenotypeRobotic-assisted surgeryTotal knee arthroplasty

Identifiers

PMID42474571
PMCPMC13385008

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.