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Record W6920598927 · doi:10.60692/81y60-3k353

The outcomes of total hip replacement in osteonecrosis versus osteoarthritis: a systematic review and meta-analysis

2023· article· en· W6920598927 on OpenAlexaboutno aff

Bibliographic record

VenueGreater South Information System · 2023
Typearticle
Languageen
FieldMedicine
TopicBone and Joint Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsPeriprostheticOsteoarthritisContext (archaeology)ConfoundingFemoral headObservational studyTotal hip replacementArthroplastyTotal hip arthroplasty

Abstract

fetched live from OpenAlex

This systematic review and meta-analysis aimed to compare the outcomes of THA in patients with osteonecrosis (ON) and those with osteoarthritis (OA).Four databases were searched from inception till December 2022 for original studies that compared the outcomes of THA in ON and OA. The primary outcome was the revision rate; the secondary outcomes were dislocation and Harris hip score. This review was conducted in line with PRISMA guidelines, and the risk of bias was assessed using the Newcastle-Ottawa scale.A total of 14 observational studies with 2,111,102 hips were included, with a mean age of 50.83 ± 9.32 and 55.51 ± 8.95 for ON and OA groups, respectively. The average follow-up was 7.25 ± 4.6 years. There was a statistically significant difference in revision rate between ON and OA patients in favour of OA (OR: 1.576; 95%CI: 1.24-2.00; p-value: 0.0015). However, dislocation rate (OR: 1.5004; 95%CI: 0.92-2.43; p-value: 0.0916) and Haris hip score (HHS) (SMD: - 0.0486; 95%CI: - 0.35-0.25; p-value: 0.6987) were comparable across both groups. Further sub-analysis adjusting for registry data also showed similar results between both groups.A higher revision rate, periprosthetic fracture and periprosthetic joint infection following total hip arthroplasty were associated with osteonecrosis of the femoral head compared with osteoarthritis. However, both groups had similar dislocation rates and functional outcome measures. This finding should be applied in context due to potential confounding factors, including patient's age and activity level.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.682
Threshold uncertainty score0.338

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.066
GPT teacher head0.277
Teacher spread0.210 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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