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Record W4376613505 · doi:10.1016/j.esmoop.2023.101505

165P Introduction of Magseed in the DGH setting: No inferiority to wire localisation

2023· article· en· W4376613505 on OpenAlexfundno aff
Humayun Irshad, Vanessa Pope, David Archampong, S.S. Hignett

Bibliographic record

VenueESMO Open · 2023
Typearticle
Languageen
FieldMedicine
TopicBreast Implant and Reconstruction
Canadian institutionsnot available
FundersMcMaster University
KeywordsMedicineDuctal carcinomaBreast cancerSurgeryRadiologyCancerInternal medicine

Abstract

fetched live from OpenAlex

Wire guided localization is the gold standard technique for pre-operative localization of non-palpable breast cancers in patients undergoing wide local excision (WLE). It has logistical challenges as it needs to be performed on the day of surgery, requiring coordination of Breast, Radiology and Theatre teams. Reported complications include wire displacement, intra-operative difficulty localizing the tip, pneumothorax, and cardiac injuries. Magseed is an alternative localization technique using a magnetic seed, which can be placed up to 30 days pre-operatively. This is localized intraoperatively with a ‘Sentimag probe’. The iBRA-NET Localisation Study performed in UK demonstrated magseed localization as an effective technique in terms of patient convenience and satisfaction, accurate localisation and avoiding unnecessary scheduling delays/cancellations. Our breast unit changed from using wires to predominantly Magseed localisations in early 2020. Data was retrospectively collected for all patients undergoing wire or Magseed localised WLE for non-palpable invasive breast cancer or ductal carcinoma-in-situ from 01/10/2019 to 01/10/2020. Accuracy was determined by the presence of cancer and wire/Magseed in the specimen or cavity shave, presence of clear margins, and need for re-excision. Complications within 30 days of surgery were also recorded. Statistical analysis was performed using IBM SPSS statistics version 24 (Univariate analysis). P values under 0.05 were considered significant. Table: 165PMagnetic seed (n=43)Wire (n=49)p-valuep-value in national auditAccurate localization42 (97.7%)48 (97.9%)0.7300.048*Re-operation rate8 (18.6%)13 (26.5%)0.4580.574Positive/Close margins9 (20.9%)9 (18.4%)0.7970.342Specimen weight34g (7.70-378.3g)29g (5.5-201.4g)0.3620.362Minor wound infection320.1470.170Major wound infection (needing IV antibiotics)100.3520.527Unexpected re-admission to hospital within 30 days100.7210.676Peri-operative problemMagseed/wire dislodged from lesion100.4670.039*Index lesion/clip not visible on specimen X-ray310.2610.406Type of surgeryWide local excision37480.032*0.002*Therapeutic mammoplasty51Other (LICAP)10 Open table in a new tab Results are shown in the table below. Magseed can be introduced safely into the DGH setting, with non-inferior results compared to wire localisations. The technique has advantages for both patients and scheduling teams. Our findings support those of the National Localization Audit.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.705
Threshold uncertainty score0.238

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.026
GPT teacher head0.312
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

Citations0
Published2023
Admission routes1
Has abstractyes

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