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Record W4207009029 · doi:10.1093/dote/doab100

Impact of preoperative sarcopenia on postoperative complications and survival outcomes of patients with esophageal cancer: a meta-analysis of cohort studies

2022· review· en· W4207009029 on OpenAlexaboutno aff
Fei Chen, Junting Chi, Bing Zhao, Fan Mei, Qianqian Gao, Li Zhao, Bin Ma

Bibliographic record

VenueDiseases of the Esophagus · 2022
Typereview
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsMedicineSarcopeniaEsophageal cancerCohortCancerCohort studyMeta-analysisEsophagectomyGeneral surgeryOncologyInternal medicine

Abstract

fetched live from OpenAlex

The effects of preoperative sarcopenia on postoperative complications and survival outcomes of patients undergoing esophageal cancer resection are controversial. From database establishment to 16 May 2021, we systematically searched PubMed, Embase, the Cochrane Library, Web of Science, and Chinese Biomedical Literature Database to collect relevant studies investigating the effects of preoperative sarcopenia on postoperative complications, survival outcomes, and the risk of a poor prognosis of patients undergoing esophagectomy. The Newcastle-Ottawa scale was used to evaluate the quality of the included literature, and RevMan 5.3 software was used for the meta-analysis. A total of 26 studies (3 prospective cohort studies and 23 retrospective cohort studies), involving 4,515 patients, were included. The meta-analysis showed that preoperative sarcopenia significantly increased the risk of overall complications (risk ratio [RR]: 1.15; 95% confidence interval [CI]: 1.08-1.22), pulmonary complications (RR: 1.78; 95% CI: 1.48-2.14), and anastomotic leakage (RR: 1.29; 95% CI: 1.04-1.59) and reduced the overall survival rate (hazard ratio: 1.12; 95% CI: 1.04-1.20) following esophageal cancer resection. Preoperative sarcopenia increased the risks of overall postoperative and pulmonary complications in patients undergoing esophageal cancer resection. For patients with esophageal cancer, assessing the preoperative risk of preoperative sarcopenia is necessary.

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)0.000
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: Review · Consensus signal: Review
Teacher disagreement score0.205
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0000.001
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 head0.152
GPT teacher head0.459
Teacher spread0.307 · 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
GenreReview

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

Citations23
Published2022
Admission routes1
Has abstractyes

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