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Record W4390350295 · doi:10.14740/gr1670

Marital Status Is a Prognostic Factor for Cardiovascular Mortality but Not a Prognostic Factor for Cancer Mortality in Siewert Type II Adenocarcinoma of the Esophagogastric Junction

2023· article· en· W4390350295 on OpenAlexvenueno aff
Zhongqiang Zheng, Xuan Zi Sun

Bibliographic record

VenueGastroenterology Research · 2023
Typearticle
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHazard ratioInternal medicineProportional hazards modelMarital statusRisk factorAdenocarcinomaCancerConfidence intervalOncologyPopulation

Abstract

fetched live from OpenAlex

Background: The impact of marital status on the prognosis of patients with Siewert type II adenocarcinoma of the esophagogatric junction (AEG) remained unclear. This study aimed to investigate the associations of marital status with cancer-specific death risk and cardiovascular death risk in Siewert type II AEG patients. Methods: Data for Siewert type II AEG patients were obtained from the Surveillance, Epidemiology, and End Results database from 2010 to 2015. A 1:1 propensity score matching (PSM) was applied to reduce inter-group bias between the married and unmarried groups. Kaplan-Meier analysis, a competing risk model and the Fine-Gray multivariable regression model were used to identify the prognostic value of marital status. Results: In total, 1,623 subjects were included. After PSM, according to Fine-Gray multivariable regression analysis, there was no significant difference in the cumulative cancer-specific death rate between the married and the unmarried groups (hazard ratio (HR): 1.160, 95% confidence interval (CI): 0.994 - 1.354, P = 0.060). Patients in unmarried group had a higher cardiovascular death rate than patients in married group (HR: 3.066, 95% CI: 1.372 - 6.850, P = 0.006). Conclusions: Our study demonstrates that unmarried Siewert type II AEG patients are associated with higher cardiovascular death risk but not cancer-specific death risk compared with married patients.

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)0.002
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 score0.008
Threshold uncertainty score0.859

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.151
GPT teacher head0.411
Teacher spread0.260 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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