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Record W3214837274 · doi:10.1503/cjs.016820

Preoperative malnutrition in patients with colorectal cancer

2021· review· en· W3214837274 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Journal of Surgery · 2021
Typereview
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineMalnutritionColorectal cancerPrehabilitationBody mass indexCancerSurgeryIntensive care medicineInternal medicinePhysical therapy

Abstract

fetched live from OpenAlex

Preoperative malnutrition in patients with colorectal cancer is associated with several postoperative consequences and poorer prognosis. Currently, there is a lack of a universal screening tool to assess nutritional status, and intervention to treat preoperative malnutrition is often neglected. This review summarizes and compares preoperative screening and interventional tools to help providers optimize malnourished patients with colorectal cancer for surgery. We found that nutritional screenings, such as the Subjectibe Global Assessment, Patient-Generated Subjective Global Assessment, Prognostic Nutritional Index, Nutrition Risk Index, Malnutrition Universal Screening Tool, Nutrition Risk Screening 2002, Nutrition Risk Score, serum albumin, and prealbumin, have all effectively predicted postoperative outcome. Physicians should consider which of these tools best fits their needs based on the their mode of assessment, efficiency, and specified parameters. Additionally, preoperative nutritional support, such as trimodal prehabilitation, modified peripheral parenteral nutrition, and N-3 fatty acid and arginine supplementation, which have also benefited patients postoperatively, ought to be implemented appropriately according to their ease of execution. Given the high prevalence of preoperative malnutrition in patients undergoing surgery for colorectal cancer, it is essential that health care providers assess and treat this malnutrition to reduce postoperative complications and length of hospital stay, and to improve prognosis to augment a patient's quality of care.La malnutrition préopératoire chez les patients atteints d'un cancer colorectal est associée à plusieurs complications postopératoires et à un pronostic plus sombre. Il n'existe actuellement aucun outil universel d'évaluation du statut nutritionnel, et les mesures visant à corriger la malnutrition préopératoire font souvent défaut. La présente revue résume et compare les outils de dépistage et d'intervention préopératoires pour aider les professionnels à améliorer l'état des patients dénutris qui doivent subir une chirurgie pour le cancer colorectal. Nous avons constaté que le dépistage nutritionnel à l'aide de questionnaires tels que l'Évaluation globale subjective, l'Index nutritionnel pronostique, l'Outil universel de dépistage de la malnutrition, NRS 2002 (Nutrition Risk Screening 2002), l'évaluation du risque nutritionnel, et le dosage de l'albumine et de la préalbumine sériques, a permis de prédire avec justesse l'issue de la chirurgie. Les médecins devraient vérifier lequel de ces outils est le mieux adapté à leurs besoins selon leur modalité d'évaluation, leur efficience et autres paramètres spécifiques. Également, un soutien nutritionnel préopératoire, comme la préadaptation trimodale, la nutrition parentérale périphérique modifiée et les suppléments d'acides gras N-3 et d'arginine, qui ont aussi donné des résultats postopératoires favorables, devrait être appliqué selon sa facilité d'administration. Étant donné la forte prévalence de la malnutrition préopératoire chez les patients soumis à une chirurgie pour cancer colorectal, les professionnels de la santé se doivent d'évaluer et de corriger la malnutrition afin de prévenir les complications postopératoires, d'abréger la durée du séjour hospitalier, et d'améliorer ainsi le pronostic et la qualité des soins.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.809
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
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 head0.091
GPT teacher head0.350
Teacher spread0.259 · 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