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Record W2046648520 · doi:10.1007/s11999-013-3402-z

CORR Insights®: Long-term Results and Bone Remodeling After THA With a Short, Metaphyseal-fitting Anatomic Cementless Stem

2013· letter· en· W2046648520 on OpenAlexaff
Michael G. Zywiel

Bibliographic record

VenueClinical Orthopaedics and Related Research · 2013
Typeletter
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineSurvivorship curveImplantSurgeryFixation (population genetics)Orthopedic surgeryPopulation

Abstract

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Where Are We Now? The use of cementless femoral fixation in primary THA has steadily increased since the first results were described more than 30 years ago [7]. Although there is considerable worldwide variation in fixation preference, close to 90% of contemporary primary THA procedures in the United States are performed using cementless implants [4]. As successive designs addressed early failure modes, and indications expanded to include younger patients, device manufacturers began increasing their focus on improving the longer-term outcomes with THA. Regarding cementless femoral stems, these innovations have included the development of shorter bone preserving implants that rely solely on metaphyseal fit. Kim and colleagues reported the mid- to long-term outcomes (mean of 15.8 years, range 11 years to 18 years) of 641 patients younger than 65 years of age who underwent primary THA performed by a single surgeon using one such stem design. The authors reported excellent implant longevity (18-year all-cause survivorship of 99.4%, and 100% survivorship for aseptic loosening). Taking into account the 1.4% loss to followup, even in the most pessimistic scenario, this case series demonstrates excellent survivorship with this particular implant design in the hands of an experienced hip surgeon. Where Do We Need To Go? This report also alludes to a potential issue in the orthopaedic device market. Despite the excellent reported results, the Immediate Postoperative Stability (IPS) stem (DePuy, Warsaw, IN) used by the authors, is no longer available, having been replaced by the Proxima (DePuy, Warsaw, IN) component, a newer generation design. The new implant has been described as incorporating the design philosophy of the previous device, while enhancing the fixation surface and removing the superfluous distal stem [11]. The potential benefits of these modifications are welcome, and other authors have presented sound rationale and in vitro evidence for the new generation implant [11, 13, 14]. However, even theoretically sound design changes that received regulatory approval may occasionally be prone to unexpected adverse events that become apparent only after unrestricted clinical use, as illustrated by a number of recent examples including symptomatic taper corrosion and catastrophic modular neck failures [1, 10]. The reported early outcomes with the newer generation of the metaphyseal-fitting stem studied by Kim et al. have been positive to date [2, 6, 12], and the currently available design may indeed provide additional benefits in terms of bone conservation, patient-reported outcomes, and/or superior ease of use for the surgeon. Nevertheless, there is no way to confirm definitively the comparative long-term survivorship of these stems at present, and all too often, by the time long-term data are available for a specific design, it has been removed from the market, and replaced by a newer and purportedly better product. How Do We Get There? Several strategies for improving the approval and monitoring of new and existing orthopaedic implant designs have been proposed. Authors have advocated strengthening postmarketing surveillance requirements [8], and increasing adoption of implant registries [5]. Both of these strategies would increase the availability of data to compare outcomes between implants, but they would not necessarily impact the approval of new designs or withdrawal of otherwise well-functioning older ones. Other authors have advocated for a stepwise approval process similar to that used for pharmaceuticals [9], or a system of graduated introduction [15]. While these strategies might increase the barrier to entry of new implant designs, or help identify early failure modes before widespread release, they do not directly address the issue of withdrawal of older designs in favor of newly approved modifications. Orthopaedic practice, and medicine in general, is predicated on helping patients achieve the best possible future outcomes, and to maintain them for as long as possible. The fact that contemporary implant selection decisions can be informed by favorable survivorship data at followup times approaching 20 years is a testament to the effectiveness of these procedures. It is clear that despite the advances in adult reconstruction in the past 60 years, even successful contemporary hip and knee arthroplasty does not fully replicate the function and longevity of the native joint, and a small but notable proportion of patients remain dissatisfied with the results of surgery. Therefore, we must continue to innovate and improve on the successes to date, keeping in mind that innovation cannot occur without some risk of unforeseen complications [3]. Nevertheless, the question remains whether the orthopaedic community needs to make a greater effort to ensure that implant designs that have demonstrated good mid- and long-term outcomes remain available to those surgeons who believe they will best meet their patients’ needs. Acknowledgments The author would like to thank Dr. David Backstein for his insights and assistance during the preparation of this manuscript.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.098
GPT teacher head0.379
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2013
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