Notice bibliographique
Résumé
This symposium arose from a discussion of papers presented at a radiostereometry (RSA) meeting in New Orleans, February 4, 2003. RSA has become the gold standard method to quantitatively assess in vivo displacements or motions of orthopaedic interventions and devices. Owing to its sensitivity, early failures of operations and implants may often be predicted. Research into the modern incarnation of RSA began in 1974 by Göran Selvik in Lund, Sweden.2 During the first 15 years, it was used almost exclusively in the Scandinavian countries as a research tool; thereafter it was adopted by several European centers. Today, routine RSA usage has extended worldwide including to the USA, Canada and Australia, as illustrated by a number of contributions to this symposium from research groups based in those countries. This clearly demonstrates a worldwide increase of interest in RSA. There is a growing awareness within the orthopaedic community that new joint replacement prostheses, cements, and surgical techniques should be thoroughly evaluated before general release to the market, an approach that has been common in the pharmaceutical industry for decades. Regulatory bodies have begun to demand direct scrutiny of premarket clinical data used to support performance claims. According to the EU Reclassification Directive, the upward classification of hip, knee and shoulder joint replacements renders them subject to a more burdensome set of regulatory requirements.1 Currently, a number of RSA research groups are collaborating with the International Standardization Organization Working Group 4 to establish a standard of premarket clinical evaluation using RSA (CEN/TC 285/WG4).3 In its 30-year history, RSA has proven an active and evolving technique that continues to be comprehensively updated to maximize current advances in computer technologies and increases in computational power. Kärrholm et al in their overview article demonstrate RSA can be used in a broad spectrum of applications. As described by Kärrholm et al and Kaptein et al, RSA today is a method that uses automated analysis of digital images. For several implants, the problem of attaching markers to them has been solved by a recently developed technique called model-based RSA, which uses three-dimensional computer models to overcome the need for implant modification. The advances exemplified by the various studies in the symposium demonstrate not only the increasing power of RSA but, equally importantly, its practicality in a wider range of situations. The symposium provides an overview of the state of the art through a number of experimental studies and a wide-ranging series of clinical studies. Radiostereometric analysis is not limited to the knee or the hip, but can be used for the evaluation of virtually any implant or surgical technique where motion or displacement might predict failure. This is amply illustrated by the inclusion of two shoulder studies (Hallström et al; Rahme et al), one ankle study (Nelissen et al), and an experimental study on biodegradable spinal cages (Krijnen et al). Another use of RSA is as a highly accurate ruler for validation and refinement of finite element models, as demonstrated in the paper of Gill et al. We hope this collection of papers will provide readers with an appreciation of the historical impact of this highly accurate clinical measurement tool, as well as its future influence on the evaluation of new developments in arthroplasty, spine surgery, and fracture fixation. Edward R. Valstar, PhD Biomechanics and Imaging Group, Department of Orthopaedics Leiden University Medical Center, Leiden, The Netherlands; and Department of Biomechanical Engineering, Delft University of Technology, Delft, The Netherlands Richie (H.S.) Gill, DPhil, OOEC Nuffield Department of Orthopaedic Surgery, Botnar Research Center University of Oxford, Nuffield Orthopaedic Centre, Oxford, UK
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,006 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,004 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,003 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».