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Record W2416730489 · doi:10.3748/wjg.v21.i23.7218

Impact of body mass index on complications following pancreatectomy: Ten-year experience at National Cancer Center in China

2015· article· en· W2416730489 on OpenAlexfundno aff
Yingtai Chen, Qian Deng, Xu Che, Jianwei Zhang, Yuheng Chen, Dongbin Zhao, Yantao Tian, Yawei Zhang, Chengfeng Wang

Bibliographic record

VenueWorld Journal of Gastroenterology · 2015
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsnot available
FundersBeijing Nova ProgramSpecialized Research Fund for the Doctoral Program of Higher Education of ChinaChinese Academy of Medical SciencesNational Natural Science Foundation of ChinaMcGill UniversityYale University
KeywordsMedicineOverweightBody mass indexPancreatic cancerPopulationRetrospective cohort studyCancerObesityPancreatectomySurgeryInternal medicineResection

Abstract

fetched live from OpenAlex

AIM: To examine the impact of body mass index (BMI) on outcomes following pancreatic resection in the Chinese population. METHODS: A retrospective cohort study using prospectively collected data was conducted at the Cancer Hospital of the Chinese Academy of Medical Sciences, China National Cancer Center. Individuals who underwent pancreatic resection between January 2004 and December 2013 were identified and included in the study. Persons were classified as having a normal weight if their BMI was < 24 kg/m(2) and overweight/obese if their BMI was ≥ 24 kg/m(2) as defined by the International Life Sciences Institute Focal Point in China. A χ(2) test (for categorical variables) or a t test (for continuous variables) was used to examine the differences in patients' characteristics between normal weight and overweight/obese groups. Multiple logistic regression models were used to assess the associations of postoperative complications, operative difficulty, length of hospital stay, and cost with BMI, adjusting for age, sex, and type of surgery procedures. RESULTS: A total of 362 consecutive patients with data available for BMI calculation underwent pancreatic resection for benign or malignant disease from January 1, 2004 to December 31, 2013. Of the 362 patients, 156 were overweight or obese and 206 were of normal weight. One or more postoperative complications occurred in 35.4% of the patients following pancreatic resection. Among patients who were overweight or obese, 42.9% experienced one or more complications, significantly higher than normal weight (29.6%) individuals (P = 0.0086). Compared with individuals who had normal weight, those with a BMI ≥ 24.0 kg/m(2) had higher delayed gastric emptying (19.9% vs 5.8%, P < 0.0001) and bile leak (7.7% vs 1.9%, P = 0.0068). There were no significant differences seen in pancreatic fistula, gastrointestinal hemorrhage, reoperation, readmission, or other complications. BMI did not show a significant association with intraoperative blood loss, operative time, length of hospital stay, or cost. CONCLUSION: Higher BMI increases the risk for postoperative complications after pancreatectomy in the Chinese population. The findings require replication in future studies with larger sample sizes.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.388
Teacher spread0.349 · 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".

Quick stats

Citations18
Published2015
Admission routes1
Has abstractyes

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