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Record W3133720746 · doi:10.7759/cureus.13788

Intramedullary Nailing Versus Plate Osteosynthesis for Humeral Shaft Metastatic Lesions

2021· article· en· W3133720746 on OpenAlexafffundabout
Marc-Antoine Ricard, Nikolaos A. Stavropoulos, Anas Nooh, Nathalie Ste-Marie, Krista Goulding, Robert Turcotte

Bibliographic record

VenueCureus · 2021
Typearticle
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsMcGill University Health CentreOttawa Hospital
FundersFondation du cancer des CèdresFondation de l'Hôpital Général de MontréalMcGill University
KeywordsMedicineIntramedullary rodOsteosynthesisSurgeryQuality of life (healthcare)Fixation (population genetics)

Abstract

fetched live from OpenAlex

In the event of surgical management of metastases to the humeral shaft, intramedullary nailing (IMN) is often preferred to plate osteosynthesis (PO) fixation despite a lack of consensus. In this study, we hypothesized that plate osteosynthesis will be associated with better functional and pain outcomes, thus better quality of life. Eighteen patients with the diagnosis of humeral shaft metastatic fracture or impending fracture were extracted from a prospective database of 140 metastatic patients collected across three hospitals over a five-year period. Musculoskeletal Tumor Society (MSTS) score, Toronto Extremity Salvage Score (TESS), Quality of Life (QOL) and Brief Pain Inventory (BPI) score were gathered during the year following the surgery. Statistical analysis was performed to compare the mean score differences between the two surgical options at baseline and five follow-up visits. Both treatment options were associated with an increase in functional outcomes based on both MSTS and TESS, and a decrease in pain level. However, no significant difference was found in quality of life and between the two treatment modalities. Thus, based on our results, a similar improvement in functional status and pain level can be achieved surgically by either intramedullary nailing or plating osteosynthesis.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.563
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.080
GPT teacher head0.355
Teacher spread0.275 · 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.

Study designNot applicable
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

Citations11
Published2021
Admission routes3
Has abstractyes

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