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Record W2793025343 · doi:10.1093/jcag/gwy008.077

A76 SINGLE OPERATOR PANCREATOSCOPY IN THE EVALUATION OF PANCREATIC NEOPLASMS: A CASE SERIES

2018· article· en· W2793025343 on OpenAlexaff
Dana C. Moffatt

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2018
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineMagnetic resonance cholangiopancreatographyPancreatic ductIntraductal papillary mucinous neoplasmRadiologySingle CenterPancreatic massEndoscopic ultrasoundTransabdominal ultrasoundRetrospective cohort studyGastroenterologyPancreasInternal medicineEndoscopic retrograde cholangiopancreatographyUltrasonographyPancreatitis

Abstract

fetched live from OpenAlex

Pancreatic neoplasms are most commonly diagnosed by endoscopic ultrasound (EUS), computed tomography (CT) scan and magnetic resonance cholangiopancreatography (MRCP). However, all these imaging modalities have limitations in their ability to diagnose small main duct intraductal papillary mucinous neoplasm (MD-IPMN) or early pancreatic neoplasms. Single operator pancreatoscopy (SOP) is a new modality to diagnose pancreatic neoplasia that is gaining popularity as case series and a retrospective single-center study have been published showing favorable efficacy. This case-series was performed to evaluate our centre’s experience with SOP. Patients who underwent SOP using the SpyGlass Direct Visualization System (Boston Scientific, Natick, Mass) between June 2013 and July 2016 were identified. Main outcome measurements included efficacy and safety of pancreatoscopy. During the study period, 32 patients underwent SOP for evaluation of suspected IPMN or pancreatic duct neoplasia. Prior to SOP, all patients had either an EUS or MRCP. Twenty-two (68.8%) patients had an EUS while 29 (90.6%) had MRCPs with indeterminate features for MD-IPMN or pancreatic neoplasia. Twenty-one (65.6%) patients were female and the mean age was 64.9 ± 12.2 years at the time of procedure. Technical failure occurred in 6 (18.8%) patients. Samplings through biopsy or brushing, were performed in 8 (30.7%) of patients. Overall, 13 (40.6%) patients had a pancreatic duct neoplasia, MD-IPMN, side branch IPMN or combined IPMN. In one patient, the pancreatoscope could not be introduced into the pancreatic duct. High-risk patients (n=8) were considered to be individuals who were diagnosed with MD-IPMN with or without side branch involvement. One patient is currently awaiting surgery. Five patients (71.4%) were diagnosed with adenocarcinoma and 1 (14.2%) was diagnosed with a dysplastic cyst via surgical specimens. The last patient did not undergo surgery and is being followed with serial imaging that has yet to suggest malignancy. Of the 19 patients with a negative pancreatoscopy for IPMN, 0 have developed an IPMN or pancreatic neoplasm in mean follow up of 1.5 years (SD 0.67). In our series, if pancreatic duct cannulation is successful, SOP has a diagnostic accuracy, sensitivity and specificity of 92.3%, 100% and 90.4% respectively for determining high risk IPMN/pancreatic cancers at time of ERCP. Complications occurred in 2 (7.6%) patients, 1 (3.8%) mild post-ERCP pancreatitis and 1 (3.8%) contained perforation related to sphincterotomy. Prophylactic pancreatic stents were placed in 27 (84.4%) patients and rectal indomethacin was used in 27 (84.4%) patients. Our case-series suggests that SOP to evaluate for pancreatic neoplasia is safe and adds important information in the evaluation of pancreatic duct neoplasm that are not definitively diagnosed by EUS or MRCP. None

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.036
GPT teacher head0.326
Teacher spread0.290 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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
Published2018
Admission routes1
Has abstractyes

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