MétaCan
Menu
Back to cohort
Record W2077860275 · doi:10.2106/jbjs.m.00563

Will My Clavicle Heal?

2013· letter· en· W2077860275 on OpenAlexaboutno aff
Andrew H. Schmidt

Bibliographic record

VenueJournal of Bone and Joint Surgery · 2013
Typeletter
Languageen
FieldMedicine
TopicShoulder and Clavicle Injuries
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineNonunionMalunionClavicleDashSurgeryRandomized controlled trialBone healing

Abstract

fetched live from OpenAlex

Commentary The management of clavicular fractures has changed substantially in the last fifteen years. In 1997, Hill et al. documented poor results and increased risk of nonunion in clavicular fractures with initial shortening of ≥20 mm1. McKee et al. confirmed this finding in a study involving more sophisticated outcome assessments including Constant and DASH (Disabilities of the Arm, Shoulder and Hand) scores as well as muscle strength testing2. However, the 2007 publication of the results of a randomized clinical trial conducted by the Canadian Orthopaedic Trauma Society3 showing improved outcomes with surgical management of displaced clavicular fractures appears to represent the “pivot point,” following which clinical practice began to be more commonly surgical. Despite the accumulating evidence of the potential for compromised functional outcome and the increased risk of nonunion in patients with a displaced clavicular fracture, the role of surgery remains uncertain. Even if the nonunion rate is as high as 20%, it remains true that four of five patients with a displaced clavicular fracture will have healing of the fracture, treatment of a nonunion is relatively straightforward, and functional outcomes remain acceptable in many patients despite malunion. For these reasons, many investigators have tried to better define surgical indications by investigating risk factors for poor outcomes. Nowak et al. reviewed 245 adult patients with a clavicular fracture and noted that lack of osseous contact and fracture comminution with a transverse fragment were strong predictors of adverse sequelae whereas fracture location and shortening alone were not4. In 2004, even before the Canadian trial was completed, a group from Edinburgh reported study data that could be used to estimate the likelihood of clavicular nonunion5. In a consecutive series of 868 patients, the nonunion rate of diaphyseal clavicular fractures was just 4.5%, and advancing age, female sex, fracture comminution, and lack of cortical apposition were independent predictors of nonunion5. Now that operative management of displaced clavicular fractures has become more common, it is even more important to be sure that surgery is appropriately utilized. Since displaced fractures are considered the fractures that are particularly at risk for adverse sequelae, the Edinburgh group has repeated their 2004 study but instead focused their attention solely on this group of injuries. Using much more sophisticated statistical analyses, the authors find that smoking status (yes/no), comminution (yes/no), and fracture displacement in millimeters can be used to predict the risk of nonunion. By calculating the absolute risk difference among different groups of patients and thereby defining the number needed to treat (NNT), the authors are able to provide clinicians with very clear indicators of the potential benefit of surgery in subsets of patients with various well-defined characteristics. Clinicians treating fractures of the clavicle should familiarize themselves with the findings of this paper and incorporate the authors’ predictive model into their preoperative discussions. Data such as those in the study by Murray et al. provide a strong evidence base that lends itself to a shared decision-making process by presenting risks in a manner that is more quantifiable and easily understood by patients.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.113
Threshold uncertainty score0.821

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.030
GPT teacher head0.310
Teacher spread0.280 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations3
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Bone and Joint SurgerySame topicShoulder and Clavicle InjuriesFrench-language works237,207