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Record W4367280847 · doi:10.2106/jbjs.oa.22.00070

Predicting Pathological Fractures at Metastatic Humeral Lesions

2023· article· en· W4367280847 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJBJS Open Access · 2023
Typearticle
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsSunnybrook HospitalHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineConfidence intervalReceiver operating characteristicLogistic regressionOdds ratioMalignancyProportional hazards modelCutoffRetrospective cohort studyInternal medicineSurgeryHazard ratioRadiology

Abstract

fetched live from OpenAlex

The humerus is the second most common site of metastatic disease involving long bones, yet it is still unclear which patients are at high risk for a fracture and may require prophylactic surgical fixation. The goal of this study was to assess the validity of the Mirels score to predict fractures of metastatic lesions in the humerus. Methods: We performed a retrospective electronic chart review of patients with humeral metastases at our institution (2005 to 2021), with 188 patients meeting the inclusion criteria. Sixty-one of the patients developed a fracture during follow-up. The metastatic humeral lesions were scored according to the Mirels rating system and additional radiographic criteria (cortical breach, location within the humerus, number of lesions). The predictive value of each Mirels score cutoff for fracture was assessed using sensitivity, specificity, area under the receiver operating characteristic curve (AUC), and multivariate logistic regression. Survivorship until fracture was analyzed for each Mirels score cutoff using Kaplan-Meier curves and the log-rank test. Significance was set at p < 0.01. Results: There were no significant differences in age, sex, side of the lesion, type of malignancy, and radiation dose between the groups with and without fracture (all p > 0.01). A Mirels score of ≥8 points had the best predictive profile, with sensitivity of 83.6%, specificity of 79.5%, and AUC of 0.82 (95% confidence interval [CI], 0.75 to 0.88, p < 0.01). A logistic regression model also demonstrated that a Mirels score of ≥8 (odds ratio = 5.8, 95% CI = 1.9 to 18.2, p < 0.01) and a cortical breach (odds ratio = 21.0, 95% CI = 5.7 to 77.2, p < 0.01) were significant predictors of pathological fracture. No other radiographic characteristics were found to be significant predictors of fracture. Conclusions: This study indicated that a Mirels score of ≥8 points had the best predictive profile for anticipating fractures at a metastasis in the humerus. This is in contrast to the traditional Mirels definition of an impending pathological fracture that is used for the lower extremity, a score of ≥9. Additionally, the presence of a cortical breach was a significant predictor of fracture risk. Level of Evidence: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

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.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.543
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.178
GPT teacher head0.496
Teacher spread0.318 · 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