Computer‐Based Malnutrition Risk Calculation May Enhance the Ability to Identify Pediatric Patients at Malnutrition‐Related Risk for Unfavorable Outcome

Karagiozoglou–Lampoudi, Thomais; Daskalou, Efstratia; Lampoudis, Dimitrios; Apostolou, Aggeliki; Agakidis, Charalampos

doi:10.1177/0148607114529161

Cited by 35 publications

(33 citation statements)

References 21 publications

(53 reference statements)

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“…This tool has high sensitivity and specificity for predicting weight loss and the need of nutritional support during hospital stay, but it has moderate inter-interviewer agreement (κ = 0.474) [41].…”

Section: Nutritional Screening Tools For Pediatric Patientsmentioning

confidence: 99%

Hospital Malnutrition in Pediatric Patients: A Review

Mac¹

2017

Ann Nutr Disord Ther

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Malnutrition is common in pediatric inpatients, and nutritional status often deteriorates in the hospital. Although the prevalence of hospital malnutrition is high, this condition is ignored and consequently, not treated. The first step to fight malnutrition knows how to identify patients at greater risk of this condition. One way to identify them is by using risk screening tools, which should be used in all inpatients. Six screening tools have been created for pediatric patients, but none of these tools stood out. Nevertheless, the STRONGKids has been the most studied tool in many countries because of its ease and speed of use. In Brazil only STRONGKids has been translated and adapted, but just one study assessed its accuracy in our population, obtaining modest results. Hence, STRONGKids should be considered a preliminary tool, and its correlation with clinical data requires investigation.

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Section: Nutritional Screening Tools For Pediatric Patientsmentioning

confidence: 99%

Hospital Malnutrition in Pediatric Patients: A Review

Mac¹

2017

Ann Nutr Disord Ther

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“…Table 2 compiles and integrates the information from the 15 studies included in the literature review according to the PICO characteristics of the research. [26][27][28][29][30][31][32][33][34][35][36][37][38][39][40] It should be noted that, although the search included original studies published between 2002 and 2017, the selected articles were released between 2010 and 2017 (67% of them were published between 2012 and 2017), thus indicating that the results are up-to-date. All studies were developed in European countries.…”

Section: Search Resultsmentioning

confidence: 99%

“…The remaining 8 studies were classified at a moderate level since they were multicenter studies, with randomized, systematized or consecutive sampling and generally consistent results that allow, to some extent, the generalization of findings to clinical practice. [28][29][30][31]33,35,38,40 Recommendations for the use of nutritional screening tools in pediatrics Of the seven tools identified in this systematic review, quality assessment was only possible in six of them, namely, PYMS, iPYMS, STAMP, PMST, STRONGkids and PEDISMART. A complete quality analysis -i.e.…”

Section: Levels Of Certainty Of the Studiesmentioning

confidence: 99%

Revisión sistemática y análisis comparativo de las herramientas de tamizaje nutricional en pediatría validadas en Europa y Canadá

Vásquez-Cárdenas

Pinzón-Espitia

2020

Rev. Fac. Med.

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Introducción. El tamizaje nutricional es una herramienta efectiva que permite establecer el riesgo de desnutrición hospitalaria, por consiguiente es importante revisar las directrices respecto a su uso en pediatría.Objetivo. Ofrecer recomendaciones sobre el uso de las herramientas de tamizaje nutricional validadas en Canadá y Europa en población colombiana. Materiales y métodos. Se realizó una revisión sistemática siguiendo la metodología PRISMA. Para la evaluación de la calidad de la evidencia se utilizó la herramienta U.S Preventive Services Task Force, formulada para medir acciones preventivas por la Canadian Task Force on the Periodic Health Examination.Resultados. Se incluyeron 15 estudios que cumplían los criterios de selección y se identificaron 7 herramientas (PYMS, iPYMS, PeDiSMART, PNR, STAMP, PMST y STRONGkids). Según los lineamientos de la Sociedad Europea de Nutrición Clínica y Metabolismo, la PYMS, la iPYMS y la STRONGkids evalúan simultáneamente variables pronósticas como estado nutricional actual, estabilidad, progresión esperada e influencia de la enfermedad. En cuanto a validez concurrente, el análisis de datos muestra que la PYMS, la iPYMS y la PMST tienen sensibilidades >85% y que la PYMS tiene especificidad >85%. Respecto a reproducibilidad, la PEDISMART, la STRONGkids, la STAMP y la PYMS tienen una concordancia inter-observadores aceptable (k>0.41).Conclusión. Según la evidencia analizada en términos de variables pronósticas, validez concurrente y reproducibilidad, se sugiere el empleo en la práctica clínica de la herramienta PYMS, mientras que para el uso de la STAMP y la iPYMS las instituciones deben evaluar su aplicabilidad.

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“…Moreover, adverse impacts of malnutrition and the influence of an underlying disease on nutritional status interact and both affect LOS. When LOS as an outcome measure was controlled for confounders in the Paediatric Digital Scaled MAlnutrition Risk Screening Tool (PeDiSMART) validation study, 18 it was found not to be significantly associated with nutritional risks.…”

Section: Discussionmentioning

confidence: 98%

Validation and impact of paediatric malnutrition screening tool in hospitalised children on awareness of medical staff and health‐related outcomes

Marderfeld

Rub

Hodik

et al. 2019

Nutrition & Dietetics

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Aims This study aimed to evaluate the use of the Screening Tool for the Assessment of Malnutrition in Paediatrics (STAMP) among children admitted in a paediatric hospital, and assess its impact on the nutritional status awareness among the medical staff and on health outcomes at discharge. Methods STAMP performed by nurses on admission was compared with full nutritional assessment performed by a dietitian. Area under the receiving operating characteristic (AUROC) curve was used to evaluate validity of the tool. To assess how the tool affected awareness among the staff, information on nutritional status was compared prior to and following the intervention period. Therewith, health outcomes at discharge were compared for the children who had been screened by STAMP and the children who had not. Results The analysis was performed for a total of 60 children (38 boys, 63%). The mean age was 7.8 ± 4.7 years. Malnutrition was found in 16% of patients, segregating equally between acute and chronic malnutrition. Sensitivity, specificity, positive predictive value and negative predictive value were 95.7% (95% confidence interval, CI = 85.75–98.83%), 76.9% (95% CI = 49.74–91.82%), 93.7 and 83.3, respectively. AUROC was 0.863 (95% CI = 0.72–1). There was no difference either in malnutrition awareness among the medical staff before and after the intervention period or in health outcomes at discharge. Conclusions STAMP is a valid tool for malnutrition screening in hospitalised children; however, its use does not influence admitted patients’ nutritional status awareness among the medical staff nor their outcomes at discharge.

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Computer‐Based Malnutrition Risk Calculation May Enhance the Ability to Identify Pediatric Patients at Malnutrition‐Related Risk for Unfavorable Outcome

Cited by 35 publications

References 21 publications

Hospital Malnutrition in Pediatric Patients: A Review

Hospital Malnutrition in Pediatric Patients: A Review

Revisión sistemática y análisis comparativo de las herramientas de tamizaje nutricional en pediatría validadas en Europa y Canadá

Validation and impact of paediatric malnutrition screening tool in hospitalised children on awareness of medical staff and health‐related outcomes

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