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Record W3004714299

Incidental finding of Gastrointestinal Stromal Tumors (GISTs) during Laparoscopic Sleeve Gastrectomy

2019· article· en· W3004714299 on OpenAlexaboutno aff
Hatam Sawlmh, Maahroo Makhdoom, Ali Khammas, Alya Al Mazrouei, Faisal Badri

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal Tumor Research and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsInterstitial cell of CajalCD117GiSTLeiomyosarcomaSmooth Muscle TumorPathologyCD34MedicineLeiomyomaAsymptomaticStromal tumorEsophagusDesminStromal cellStomachImmunohistochemistryGastroenterologyInternal medicineBiologyVimentinStem cell
DOInot available

Abstract

fetched live from OpenAlex

Gastrointestinal stromal tumors (GISTs) are rare stromal tumors found throughout the GI tract, but most commonly located in the stomach (mainly fundus and cardia) (50%), small bowel (25%) and less common in the colon (10 %), omentum/mesentery (7%), and esophagus (5%). Although the true incidence of GISTs is unknown, some reports have stated it to be about 0.68/100,000. They arise from the interstitial cells of Cajal, an intestinal pacemaker cell with characteristics of both neural and smooth muscle differentiation and are distinct from leiomyoma and leiomyosarcoma, which arise from smooth muscle. Immunohistochemical analysis demonstrates that nearly all GISTs express c-KIT protein (CD117) (95%), protein kinase C theta (80%) and CD34 (60-70%), and smooth muscle actin (30-40%) ; almost all smooth muscle tumours express actin and desmin. These markers can often be detected by specimens obtained by fine needle aspiration. This differentiation is crucial given that GISTs have a more aggressive clinical course when compared with other GI mesenchymal tumors, Gross differentiation between benign and malignant GISTs can be difficult, but the subset of GISTs that have a high likelihood of malignant behavior are generally identified by increased mitotic activity and larger tumor size. However, the prediction of malignant behavior may be difficult because even small tumors with low mitotic activity may still metastasize. Nearly one-third of GISTs are asymptomatic, and even if symptomatic, symptoms are often vague and nonspecific. Asymptomatic GISTs are often found incidentally at the time of radiographic, endoscopic or surgical evaluation, but the true incidence may be higher, as incidental cases may go unreported. Surgery is the mainstay of therapy for primary GISTs with the goal of achieving negative microscopic margins. Lymphadenectomy is unnecessary because lymph node metastases are rare. Next to the National Comprehensive Cancer Network (NCCN) and European Society for Medical Oncology (ESMO) guidelines, GISTs 2 cm in size or greater should be resected. Management of incidentally encountered small GISTs less than 2 cm in size remains controversial in the literature, whereas the Canadian guidelines indicate that even small GISTs <1 cm should be resected because of the risk of metastasis. Due to the worldwide epidemic of obesity, bariatric procedures are increasing and are among the most commonly performed gastrointestinal operations today. In a study done in 2014, LSG was found to be the more common bariatric procedure, with very good results in short terms as compared to Laparoscopic RYGB. Increasing data is being published on Minigastirc Bypass (MGB) surgery and has been reported to be give equivalent results to RYGB in the long run as well as being a safe and effective procedure. The incidence of GIST has been suspected to be more in obese patients undergoing bariatric surgery (0.6-0.8 %) in comparison to the general population (0.0006 to 0.0015%). The bariatric surgeon has to inspect the stomach during laparoscopy for such tumors and manage the incidentally encountered during a laparoscopic bariatric operation.

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: Observational · Consensus signal: none
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)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.001
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 head0.015
GPT teacher head0.284
Teacher spread0.269 · 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 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".

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Citations1
Published2019
Admission routes1
Has abstractyes

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