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Enregistrement W3011851789 · doi:10.2106/jbjs.19.01510

Potentially Appropriate Might Not Be the Most Appropriate

2020· letter· en· W3011851789 sur OpenAlexaff
Michael G. Zywiel

Notice bibliographique

RevueJournal of Bone and Joint Surgery · 2020
Typeletter
Langueen
DomaineMedicine
ThématiqueOrthopaedic implants and arthroplasty
Établissements canadiensToronto Western HospitalUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésMedicineSurvivorship curveOsteoarthritisTotal knee arthroplastyPhysical therapyIncidence (geometry)ArthroplastyHealth careSurgeryAlternative medicineInternal medicine

Résumé

récupéré en direct d'OpenAlex

Commentary Over the past half century, total knee arthroplasty (TKA) has evolved into a reliable, cost-effective procedure that provides predictable long-term implant survivorship and meaningful improvements in pain and function in the majority of patients. Additionally, as care pathways have evolved, the health economic burden of individual procedures has decreased1. Given these successes, as well as the marked increases in the prevalence of symptomatic knee osteoarthritis in the United States and elsewhere, it is perhaps not surprising that the incidence of knee arthroplasty is approaching 1 million cases per year in the U.S. alone2. Despite these accomplishments, the outcomes of TKA remain variable. While the majority of patients have a successful outcome, data suggest that as many as 20% of patients have unsatisfactory results with surgery3. At the same time, other patients who are likely to benefit from this procedure may have difficulty accessing it. For example, certain racial groups remain consistently underrepresented among patients undergoing TKA4. With these considerations in mind, Ghomrawi et al. sought to gain a better understanding of the appropriateness of utilization of TKA in the United States with use of data from 2 longitudinal cohorts of patients with risk factors for knee osteoarthritis. Using the Escobar criteria for appropriateness, they found that of 3,123 knees deemed potentially appropriate for TKA, only 9% had undergone TKA within 2 years. Conversely, of all of the patients who had undergone TKA during the study period, 26% did not meet appropriateness criteria and were deemed premature. The authors additionally reported associations between black race and decreased likelihood of having undergone TKA despite meeting appropriateness criteria, as well as associations between elevated body mass index and depression and an increased likelihood of premature TKA. With 91% of potentially appropriate knees in the cohort having not undergone TKA, this study highlights the large societal burden of symptomatic knee osteoarthritis, and suggests that the large number of TKAs performed every year represent only a small proportion of patients living with symptomatic knee osteoarthritis. With this in mind, one wonders how osteoarthritis is affecting the lives of the 91% of “potentially appropriate” patients who did not undergo TKA in this study. Is this silent majority of “potentially appropriate” patients successfully managing their symptoms and maintaining acceptable quality of life through less-invasive treatments such as neuromuscular exercise, activity modification, and non-narcotic oral analgesia? Or do these findings indicate that many individuals are suffering but are either unable or unwilling to undergo arthroplasty surgery? I imagine that both of these possibilities are true and hope that this study will motivate additional work that will lead to a better understanding of these findings. An important limitation of this study rests with the appropriateness criteria used. The Escobar criterwia were developed with use of Delphi methodology by a panel of exclusively musculoskeletal physicians (dominated by orthopaedic surgeons). Perhaps for this reason, the criteria rely largely on physician-assessed factors such as age, radiographic grading, and objective knee stability. However, many adult reconstruction surgeons have learned through experience the limited ability of these objective measures alone to reliably predict a satisfied patient. The literature is increasingly recognizing the importance of factors such as medical comorbidities, patient preferences and values, functional impact, behavioral factors (including patient engagement in the management of their own health), and patient experience with other treatment options in informing the appropriateness of TKA surgery as well as in predicting surgical outcomes from a patient perspective. With this in mind, the criteria used may not accurately reflect contemporary decision-making around TKA. We also should consider the fact that appropriateness for a particular intervention is not a binary measure. For knee osteoarthritis in particular, there are a range of invasive and noninvasive treatment options available, many of which could be potentially appropriate for a given patient. Helping patients to identify the best option for them at a given point in time requires a condition-centered approach that considers the full range of other treatment options available, including the expected risks and benefits of each for that particular patient. Thus, even though a particular treatment may be “potentially appropriate,” it might not be the most appropriate at that time. Notwithstanding the limitations of the study, the authors should be commended for exploring the question of appropriateness of contemporary total knee arthroplasty, specifically, the extent to which this procedure might be both underused and overused. While the answers supplied by the study are limited, they provide an opportunity to reflect on how our understanding of the appropriateness of TKA has evolved over time from a largely surgeon-centered perspective. They also highlight the work that must still be done to better inform ongoing transitions toward integrated, high-value, condition-centered care, and to ensure that every patient with symptomatic knee osteoarthritis receives advice and treatment that is most appropriate for their individual circumstances, preferences, and goals.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,013
score de la tête « metaresearch » (Gemma)0,147
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,034
Score d'incertitude au seuil0,096

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0130,147
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,002
Bibliométrie0,0020,002
Études des sciences et des technologies0,0050,009
Communication savante0,0060,009
Science ouverte0,0070,003
Intégrité de la recherche0,0340,038
Charge utile insuffisante (le modèle a refusé de juger)0,0290,012

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.

Tête enseignante Opus0,033
Tête enseignante GPT0,229
Écart entre enseignants0,196 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

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