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Record W2901968171 · doi:10.4055/cios.2018.10.4.491

Analysis of Postural Stability and Daily Energy Expenditure to Manage Tumor Patients' Functional Expectation

2018· article· en· W2901968171 on OpenAlexaboutno aff
Emrah Çalışkan, Evrim Karadağ‐Saygı, Zeynep Kardelen Gencer, Hızır Kurtel, Bülent Erol

Bibliographic record

VenueClinics in Orthopedic Surgery · 2018
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRehabilitationRange of motionPhysical therapyQuality of life (healthcare)Activities of daily livingPhysical medicine and rehabilitationEnergy expenditureMuscle strengthImplantSurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Advances in surgical techniques, implant technology, radiotherapy, and chemotherapy have increased the recovery chances of patients with bone sarcomas. Accordingly, patients' expectations on life quality have also increased, highlighting the importance of objective evaluation of the functional results of reconstruction. METHODS: Thirteen patients with distal femoral endoprosthesis, who had been followed for an average of 2.9 years were evaluated. Postural stability, daily energy expenditure, muscle power, and range of motion were the four parameters analyzed in this study. The Musculoskeletal Tumor Society (MSTS) score and Toronto Extremity Salvage Score (TESS) were used to assess postoperative function and examine correlations with other parameters. RESULTS: = 0.005). MSTS scores were significantly correlated with the daily energy expenditure and walking speed. CONCLUSIONS: Objective functional results acquired from various clinics will provide significant data to compare reconstruction techniques, rehabilitation protocols, and surgical techniques. In this way, it will be possible to satisfy the expectations of patients that increase in relation to enhanced recovery.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.012
Threshold uncertainty score0.464

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.036
GPT teacher head0.300
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 teacher head, 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".

Quick stats

Citations5
Published2018
Admission routes1
Has abstractyes

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