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Record W4320716282 · doi:10.1016/s2214-109x(22)00550-2

Impact of malnutrition on early outcomes after cancer surgery: an international, multicentre, prospective cohort study

2023· article· en· W4320716282 on OpenAlexaff
Aya Riad, Stephen R Knight, Dhruva Ghosh, Pamela Alice Kingsley, Marie Carmela Lapitan, Marie Dione Parreno‐Sacdalan, Sudha Sundar, Ahmad Uzair Qureshi, Apple P. Valparaiso, Riinu Pius, Catherine A. Shaw, Thomas M Drake, Lisa Norman, Adesoji Ademuyiwa, Adewale Adisa, María Lorena Aguilera, Sara W Al‐Saqqa, Ibrahim Al‐Slaibi, Aneel Bhangu, Bruce Biccard, Peter Brocklehurst, Sorrel Burden, Kathryn Chu, Ainhoa Costas‐Chavarri, Anna Dare, Muhammed Elhadi, Cameron J. Fairfield, J.E.F. Fitzgerald, James Glasbey, Mark I. van Berge Henegouwen, JC Allen Ingabire, T. Peter Kingham, Ismaïl Lawani, Bettina Lieske, Richard Lilford, Laura Magill, Mayaba Maimbo, Janet Martin, Sonia Mathai, Kenneth A McLean, Rachel Moore, Dion Morton, Dmitri Nepogodiev, John Norrie, Faustin Ntirenganya, Francesco Pata, Thomas Pinkney, Rajkumar Kottayasamy Seenivasagam, Antonio Ramos‐De la Medina, Tracey Roberts, Hosni Salem, Joana Simões, Richard J.E. Skipworth, Richard T. Spence, Neil Smart, Evropi Τheodoratou, Hannah S. Thomas, Thomas G. Weiser, Malcolm West, John Whitaker, Edwin Mwintiereh Ta-ang Yenli, Ewen M. Harrison

Bibliographic record

VenueThe Lancet Global Health · 2023
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsCentre for Global Health Research
FundersMedical Research CouncilNational Institute for Health and Care ResearchDepartment of Health and Social CareCancer Research UK
KeywordsMedicineMalnutritionProspective cohort studyOdds ratioCancerColorectal cancerCohortElective surgeryCohort studySurgeryPediatricsGeneral surgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Malnutrition represents a key priority for global health policy, yet the impact of nutritional state on cancer surgery worldwide remains poorly described. We aimed to analyse the effect of malnutrition on early postoperative outcomes following elective surgery for colorectal or gastric cancer. METHODS: We did an international, multicentre, prospective cohort study of patients undergoing elective surgery for colorectal or gastric cancer between April 1, 2018, and Jan 31, 2019. Patients were excluded if the primary pathology was benign, they presented with cancer recurrence, or if they underwent emergency surgery (within 72 h of hospital admission). Malnutrition was defined with the Global Leadership Initiative on Malnutrition criteria. The primary outcome was death or a major complication within 30 days of surgery. Multilevel logistic regression and a three-way mediation analysis were done to establish the relationship between country income group, nutritional status, and 30-day postoperative outcomes. FINDINGS: This study included 5709 patients (4593 with colorectal cancer and 1116 with gastric cancer) from 381 hospitals in 75 countries. The mean age was 64·8 years (SD 13·5) and 2432 (42·6%) patients were female . Severe malnutrition was present in 1899 (33·3%) of 5709 patients, with a disproportionate burden in upper-middle-income countries (504 [44·4%] of 1135) and low-income and lower-middle-income countries (601 [62·5%] of 962). After adjustment for patient and hospital risk factors, severe malnutrition was associated with an increased risk of 30-day mortality across all country income groups (high income: adjusted odds ratio [aOR] 1·96 [95% CI 1·14-3·37], p=0·015; upper-middle income: 3·05 [1·45-6·42], p=0·003; low income and lower-middle income: 11·57 [5·87-22·80], p<0·0001). Severe malnutrition mediated an estimated 32% of early deaths in low-income and lower-middle-income countries (aOR 1·41 [95% CI 1·22-1·64]) and an estimated 40% of early deaths in upper-middle-income countries (1·18 [1·08-1·30]). INTERPRETATION: Severe malnutrition is common in patients undergoing surgery for gastrointestinal cancers and is a risk factor for 30-day mortality following elective surgery for colorectal or gastric cancer. There is an urgent need to examine whether perioperative nutritional interventions can improve early outcomes following gastrointestinal cancer surgery worldwide. FUNDING: National Institute for Health Research Global Health Research Unit.

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 score0.012
Threshold uncertainty score0.756

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.078
GPT teacher head0.478
Teacher spread0.400 · 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

Citations144
Published2023
Admission routes1
Has abstractyes

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