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Record W4366773248 · doi:10.3389/fsurg.2023.1161938

Association of hospital volume and long-term survival after esophagectomy: A systematic review and meta-analysis

2023· review· en· W4366773248 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFrontiers in Surgery · 2023
Typereview
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsnot available
FundersChina Scholarship Council
KeywordsEsophagectomyMedicineMeta-analysisSubgroup analysisEsophageal cancerCochrane LibraryFunnel plotMEDLINECancerInternal medicinePublication biasSurgeryGeneral surgery

Abstract

fetched live from OpenAlex

Background: It remains controversial whether esophageal cancer patients may benefit from esophagectomy in specialized high-volume hospitals. Here, the effect of hospital volume on overall survival (OS) of esophageal cancer patients post esophagectomy was assessed. Methods: PubMed, Embase, and Cochrane Library were systematically searched for relevant published articles between January 1990 and May 2022. The primary outcome was OS after esophagectomy in high- vs. low-volume hospitals. Random effect models were applied for all meta-analyses. Subgroup analysis were performed based on volume grouping, sample size, study country, year of publication, follow-up or study quality. Sensitivity analyses were conducted using the leave-one-out method. The Newcastle-Ottawa Scale was used to assess the study quality. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-analysis guidance, and was registered (identifier: INPLASY202270023). Results: < 0.01). Next, we conducted subgroup analysis based on volume grouping category, consistent results were found that high-volume hospitals significantly improved OS after esophagectomy than their low-volume counterparts. Subgroup analysis and sensitivity analyses further confirmed that all the results were robust. Conclusions: Esophageal cancer should be centralized in high-volume hospitals.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.758
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0120.002
Bibliometrics0.0010.001
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 head0.055
GPT teacher head0.345
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