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Record W2753351534 · doi:10.3171/2017.4.spine16923

Utility and costs of radiologist interpretation of perioperative imaging in patients with traumatic single-level thoracolumbar fractures

2017· article· en· W2753351534 on OpenAlexaffabout
Michael H. Weber, Lojan Sivakumaran, Maryse Fortin, Alisson Roberto Teles, Jeff D. Golan, Carlo Santaguida, Peter Jarzem, Thierry Pauyo

Bibliographic record

VenueJournal of Neurosurgery Spine · 2017
Typearticle
Languageen
FieldMedicine
TopicSpinal Fractures and Fixation Techniques
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicinePerioperativeRadiographyRadiologyContext (archaeology)Retrospective cohort studySurgery

Abstract

fetched live from OpenAlex

OBJECTIVE The cost of spine management is rising. As diagnostic imaging accounts for approximately 10% of total patient care spending, there is interest in determining if economies could be made with regard to the routine consultation of radiology for image interpretation. In the context of spine trauma, both the spine surgeon and the radiologist interpret perioperative imaging. Authors of the present study investigated the impact of radiologist interpretation of perioperative imaging from patients with traumatic single-level thoracolumbar fractures given that spine surgeons are expected to be comfortable interpreting pathologies of the musculoskeletal system. METHODS The authors conducted a retrospective review of all patients presenting with a single-level thoracolumbar fracture treated at the McGill University Health Centre in the period from January 2003 to December 2010. The time between image capture and radiologist interpretation as well as the number of extraskeletal and/or incidental findings was extracted from the radiology reports on all perioperative images including radiographic, fluoroscopic, and CT images. The cost of interpretation was obtained from the provincial health insurance entity of Quebec. RESULTS Eighty-two patients met the study inclusion criteria. Radiologists took a median of 1 day (IQR 0-5.5 days) to interpret preoperative radiographs. Intraoperative fluoroscopic images and postoperative radiographs were read by the radiologist a median of 19 days (IQR 4-56.75 days) and 34 days (IQR 1-137.5 days) after capture, respectively (p < 0.05). Preoperative radiologist dictations reported extraskeletal and/or incidental findings for 8.1% of radiographs; there were no intraoperative or postoperative extraskeletal findings beyond those previously reported on the preoperative radiographs. Radiologists took a median of 1 day (IQR 0-1 day) to read both preoperative and postoperative CT scans; extraskeletal and/or incidental findings were present in 46.2% of preoperative reports and 4.5% of postoperative reports. There were no intraoperative or postoperative radiological findings that provoked reoperation. A total of 66 intraoperative fluoroscopy images and 225 postoperative radiographs were read for a cost of $1399.20 and $1867.50 (Canadian dollars), respectively, for radiologist interpretation. This cost amounted to 40.3% of all perioperative image interpretation spending. CONCLUSIONS In the management of single-level thoracolumbar fractures, radiologists add information to the diagnostic picture when interpreting preoperative radiographs and perioperative CT scans; however, the interpretation of intraoperative fluoroscopic images and postoperative radiographs comes with significant delay, does not add additional information, and represents an area of potential cost and professional-resource reduction.

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 score0.059
Threshold uncertainty score0.284

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.000

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 head0.028
GPT teacher head0.314
Teacher spread0.285 · 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
Published2017
Admission routes2
Has abstractyes

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