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Record W4401094857 · doi:10.21037/jtd-24-427

The relationship between the collagen score at the anastomotic site of esophageal squamous cell carcinoma and anastomotic leakage

2024· article· en· W4401094857 on OpenAlexaff
Xiaofeng Chen, Jun-Peng Lin, Hang Zhou, Bing-Zi Kang, Rahul Nayak, Lin Gao, Shui-Sen Jiang, Feng Wang

Bibliographic record

VenueJournal of Thoracic Disease · 2024
Typearticle
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsWestern University
FundersNatural Science Foundation of Fujian Province
KeywordsMedicineAnastomosisEsophagectomyExtracellular matrixBlood supplyEsophageal cancerSurgeryExtracellularBasal cellInternal medicineCancer

Abstract

fetched live from OpenAlex

Background: Anastomotic leakage (AL) has always been one of the most serious complications of esophagectomy with gastric conduit reconstruction. There are many strong risk factors for AL in clinical practice. Notably, the tension at the esophagogastric anastomosis and the blood supply to the gastric conduit directly affect the integrity of the anastomosis. However, there has been a lack of quantitative research on the tension and blood supply of the gastric conduit. Changes in extracellular matrix collagen reflect tension and blood supply, which affect the quality of the anastomosis. This study aimed to establish a quantitative collagen score to describe changes in the collagen structure in the extracellular matrix and to identify patients at high risk of postoperative AL. Methods: A retrospective study of 213 patients was conducted. Clinical and pathological data were collected at baseline. Optical imaging of the "donut" specimen at the anastomotic gastric end and collagen feature extraction were performed. Least absolute shrinkage and selection operator (LASSO) regression models were used to select the significant collagen features, compute collagen scores, and validate the predictive efficacy of the collagen scores for ALs. Results: LASSO regression analysis revealed three collagen-related parameters in the gastric donuts: histogram mean, histogram variance, and histogram energy. Based on this analysis, we established a formula to calculate the collagen score. The results of the univariate analysis revealed significant differences in the preoperative low albumin values (P=0.002) and collagen scores between the AL and non-AL groups (P=0.001), while the results of the multivariate analysis revealed significant differences in the collagen scores between the AL and non-AL groups (P=0.002). The areas under the curve (AUCs) of the experimental and validation cohorts were 0.978 [95% confidence interval (CI): 0.931-0.996] and 0.900 (95% CI: 0.824-0.951), respectively. Conclusions: The collagen score established herein was shown to be related to AL and can be used to predict AL in patients who underwent esophagectomy.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.346

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 head0.037
GPT teacher head0.346
Teacher spread0.308 · 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
Published2024
Admission routes1
Has abstractyes

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