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Changes In Muscle Mass, Strength, And Quality Of Life After Total Hip Replacement Surgery

2023· article· en· W4387052898 on OpenAlexaboutno aff
In Ho Woo, Dong Hyun Ye, Yoon Tae Jung, Won Kim

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2023
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsnot available
Fundersnot available
KeywordsWOMACMedicineBody mass indexBayesian multivariate linear regressionOsteoarthritisQuality of life (healthcare)Hip replacementSurgeryPhysical therapyLinear regressionOrthopedic surgeryInternal medicine

Abstract

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PURPOSE: To quantitatively measure the changes in muscle mass, strength, and quality of life evaluated before and 1 year after surgery in a group of patients who underwent total hip replacement for avascular necrosis or hip dysplasia. METHOD: This is prospective, observational study and 57 patients who underwent total hip replacement were enrolled. Demographic data were collected. Grip strength(GS), knee extension strength(KES) were measured and Dual-energy X-ray absorptiometry was performed before and 1-year after surgery. Appendicular skeletal muscle mass (ASM), and muscle mass of all extremities were quantitatively measured. In addition, gait speed, chair stand test, and patient-reported outcome measurements including modified Harris hip score (MHHS) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) were evaluated. The mean difference of variables was analyzed using the paired t-test. Patient-reported outcome measurements and variables evaluated before and one year after surgery were analyzed using multivariate linear regression. RESULTS: KES, both leg muscle mass, ASM, gait speed, MHSS, and WOMAC score have been significantly improved (Table 1). In multivariate linear regression, pre-surgery both leg muscle mass and ASM divided by weight and post-surgery GS, KES, both leg muscle mass, and ASM divided by weight and BMI were significantly associated with patient-reported outcomes(Table 2). CONCLUSION: Patients undergoing total hip replacement experience improvement in muscle strength, performance, and quality of life. Table 1. - Differences in variables before and after the surgery Pre op Post op 1 yr Variables Mean ± SD Mean ± SD P-value Body weight, kg 66.21 ± 13.46 65.09 ± 12.42 0.09 BMI, kg/m2 25.77 ± 4.22 25.36 ± 4.03 0.08 Grip strength, kg 27.57 ± 8.45 27.97 ± 8.92 0.31 Knee extension strength (affected), kg 22.97 ± 10.88 29.25 ± 11.47 0.00* Knee extension strength (sound), kg 30.11 ± 12.51 32.12 ± 13.19 0.01* Mass of both arms, kg 4.82 ± 1.3 4.9 ± 1.29 0.17 Mass of both legs, kg 13.1 ± 3.23 13.63 ± 3.35 0.00* Appendicular skeletal mass, kg 17.95 ± 4.4 18.53 ± 4.39 0.00* Leg mass of affected side, kg 6.31 ± 1.59 6.63 ± 1.67 0.00* Leg mass of sound side, kg 6.82 ± 1.73 7.0 ± 1.78 0.02* Gait speed, m/sec 1.11 ± 0.32 1.45 ± 0.27 0.00* Chair stand test, sec 8.15 ± 0.6 6.7 ± 5.37 0.16 MHHS score 53.25 ± 20.9 81.4 ± 8.95 0.00* Womac score 40.05 ± 21.43 14.68 ± 11.69 0.00* Table 2. - Linear regression analysis by multivariate variables Preoperative Postoperative 1 year MHHS WOMAC MHHS WOMAC Standardized Coefficients P Standardized Coefficients P Standardized Coefficients P Standardized Coefficients P Grip strength 0.178 0.456 -0.249 0.300 0.335 0.101 -0.295 0.116 Grip strength per HT2 0.156 0.446 -0.220 0.287 0.207 0.241 -0.231 0.153 Grip strength per WT 0.163 0.395 -0.107 0.581 0.242 0.180 -0.341 0.038* Grip strength per BMI 0.190 0.403 -0.131 0.569 0.385 0.071 -0.446 0.021* Knee extension 0.156 0.383 -0.211 0.244 0.241 0.178 -0.362 0.025* Knee extension per HT2 0.147 0.369 -0.195 0.235 0.207 0.201 -0.337 0.021* Knee extension per WT 0.144 0.395 -0.135 0.431 0.191 0.235 -0.384 0.008* Knee extension per BMI 0.157 0.404 -0.152 0.424 0.223 0.209 -0.423 0.008* Both arms mass -0.056 0.785 -0.052 0.803 0.019 0.926 0.227 0.218 Both arms mass per HT2 -0.068 0.687 -0.034 0.844 -0.099 0.536 0.233 0.110 Both arms mass per WT -0.053 0.819 0.020 0.934 -0.089 0.674 0.180 0.351 Both arms mass per BMI -0.047 0.891 0.024 0.945 0.184 0.551 0.116 0.682 Both legs mass 0.235 0.187 -0.245 0.172 0.248 0.144 -0.151 0.337 Both legs mass per HT2 0.269 0.076 -0.269 0.080 0.172 0.241 -0.136 0.317 Both legs mass per WT 0.591 0.002* -0.417 0.032* 0.283 0.067 -0.330 0.026* Both legs mass per BMI 0.536 0.025* -0.382 0.117 0.379 0.039* -0.368 0.029* ASM 0.182 0.339 -0.218 0.256 0.234 0.212 -0.081 0.640 ASM per HT2 0.200 0.215 -0.231 0.156 0.123 0.440 -0.044 0.762 ASM per WT 0.612 0.008* -0.439 0.063 0.307 0.095 -0.340 0.043* ASM per BMI 0.556 0.054 -0.399 0.175 0.465 0.037* -0.406 0.048*

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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.298
Teacher spread0.264 · 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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Citations0
Published2023
Admission routes1
Has abstractyes

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