MétaCan
Menu
Retour à la cohorte
Enregistrement W2573165657 · doi:10.1097/01.asw.0000511698.41409.4a

The Canadian Nutrition Screening Tool

2017· article· en· W2573165657 sur OpenAlexaffabout
Manon Laporte

Notice bibliographique

RevueAdvances in Skin & Wound Care · 2017
Typearticle
Langueen
DomaineMedicine
ThématiqueNutrition and Health in Aging
Établissements canadiensVitalité Health Network
Organismes subventionnairesnon disponible
Mots-clésMalnutritionMedicineHealth careMEDLINEPediatricsIntensive care medicineFamily medicineNursing

Résumé

récupéré en direct d'OpenAlex

Nutrition is an important component of a patient’s overall health, and cases of malnutrition may be more prevalent than realized. This commentary presents a brief overview of an easy-to-use nutrition screening tool created during a Canadian study. In the recent Nutrition Care in Canadian Hospitals (NCCH) Study conducted by the Canadian Malnutrition Task Force, a 45% prevalence of malnutrition on admission was found among 1015 patients admitted to medical and surgical wards of 18 Canadian hospitals. The study was conducted from July 2010 to February 2013 in patients 18 years or older who were admitted to the hospital for more than 2 days. Excluded were those admitted directly to the intensive care unit; obstetric, psychiatry, or palliative units; or medical day units. Malnutrition was independently associated with prolonged length of stay (LOS).1 It is known that malnutrition is also related to detrimental outcomes such as delayed wound healing. Moreover, very few malnourished patients are identified on admission in order to provide prompt nutrition care.2 Nutrition screening remains the process for early identification of patients who are malnourished or at risk for malnutrition. In the hospital setting, nutrition screening should be conducted on admission by the frontline nursing staff.3 The NCCH study included a nursing survey that showed 91% of nurses agreed that 2 or 3 nutrition screening questions could be integrated into patient admission histories.4 An efficient nutrition screening process relies on a simple, valid, and reliable tool. In the NCCH study, the Canadian Nutrition Screening Tool (CNST) was developed (Figure). It initially included 2 questions about weight loss and decreased food intake and the body mass index (BMI) calculation. The first criterion validity and the predictive validity of this tool have been tested in the NCCH study. The Subjective Global Assessment (SGA) was the criterion standard, and the screening tool was completed by the researchers. This first validity assessment of the tool showed promising results: (1) sensitivity, 91.7% (correctly identifies patients at nutrition risk or who are malnourished), and specificity, 74.8% (correctly identifies patients who are not at nutrition risk or malnourished), which indicated good potential of the tool to screen, and (2) the tool could significantly predict clinical outcomes: LOS (P < .001), 30-day readmission (P = .02, odds ratio [OR] = 1.56; 95% confidence interval [CI], 1.07–2.27), and mortality (in hospital or within 30 days of discharge) (P < .001, OR = 5.37; 95% CI, 2.36–12.79).3Figure.: The Canadian Nutrition Screening ToolThe reliability and the second criterion validity of the CNST were assessed in a second study with 150 patients admitted to medical and surgical wards of 3 Canadian hospitals. In this study, the CNST was completed by untrained nursing personnel (n = 160) and 1 nutrition technician to better reflect the real-world hospital setting. To test the interrater reliability of the tool, the CNST was completed by 2 blinded, independent raters for each patient. Reliability results showed a κ coefficient of 0.88 (95% CI, 0.80–0.97), which indicates an almost perfect agreement between the raters. The SGA conducted by the research associates was used to measure the criterion validity of the tool. While using 2 “yes” answers for classifying the patient at nutrition risk, the CNST showed a sensitivity of 73% and a specificity of 86% (rater 1), which is considered adequate performance for a clinical tool. Interestingly, validity results were very similar with or without the inclusion of BMI in the tool. As a result, BMI was removed from the tool to promote ease of use, because calculating the BMI is likely challenging to busy hospital staff.3 Tackling malnutrition in Canadian hospitals requires an interprofessional approach where the first step is nutrition screening. The CNST is the first valid and reliable tool tested by untrained nursing personnel, which represents the reality of a hospital setting. The CNST (Figure) is a simple tool that poses 2 questions, and when the answer is “yes” for both questions, a patient is classified at nutrition risk and will require an evaluation by the dietitian. It is recommended that hospitals include the CNST in the nursing admission questionnaire and the electronic medical record for early recognition of malnourished patients. These steps will help facilitate the appropriate screening and referral process.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,924
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0020,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,027
Tête enseignante GPT0,363
Écart entre enseignants0,336 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations6
Publié2017
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revueAdvances in Skin & Wound CareMême sujetNutrition and Health in AgingTravaux en français237 207