StrongKids for pediatric nutritional risk screening in Brazil: a validation study

The Low Sensitivity and Specificity of a Nutrition Screening Tool in Real Circumstances in a Tertiary Care Hospital Setting

Nutrition screening is an essential process to detect children at risk of malnutrition during hospitalization and provide appropriate nutrition management. STRONGkids is a nutrition screening tool which has been implemented in a tertiary-care hospital service in Bangkok, Thailand. This study aimed to evaluate the performance of STRONGkids in the real-situation setting. Electronic Medical Records (EMR) of hospitalized pediatric patients aged 1 month to 18 years from January to December 2019 were reviewed. Those with incomplete medical records and re-admission within 30 days were excluded. Nutrition risk scores and clinical data were collected. Anthropometric data were calculated to Z-score based on the WHO growth standard. The sensitivity (SEN) and specificity (SPE) of STRONGkids were determined against malnutrition status and clinical outcomes. In total, 3914 EMRs (2130 boys, mean age 6.22 ± 4.72 years) were reviewed. The prevalence of acute malnutrition (BMI-for-age Z-score < -2) and stunting (height-for-age Z-score < -2) were 12.9 and 20.5%. SEN and SPE of STRONGkids against acute malnutrition were 63.2 and 55.6%, stunting values were 60.6 and 56.7%, and overall malnutrition values were 59.8 and 58.6%. STRONGkids had low SEN and SPE to detect nutrition risks among hospitalized children in a tertiary-care setting. Further actions are required to improve the quality of nutrition screening in hospital services.

Evaluation of a new digital pediatric malnutrition risk screening tool for hospitalized children with congenital heart disease

BACKGROUND

In a cohort of hospitalized children with congenital heart disease (CHD), a new digital pediatric malnutrition screening tool as a mobile application was validated, and its effectiveness and clinical value were determined as a prospective study.

METHODS AND RESULTS

Children with CHD (n = 1125) were screened for malnutrition risk. The incidence of risk and the differences among various age groups and types of CHD were characterized. The optimal threshold for the tool to determine if there is a risk of malnutrition is score 2, while the Youden index was 79.1%, and the sensitivity and specificity were 91.2% and 87.9%, respectively. Based on such criterion, 351 children were at risk of malnutrition accounting for 31.20% of the total. Compared with the non-malnutritional risk group, the median age for the group at risk for malnutrition was younger (8.641 months [4.8, 23.1] vs. 31.589 months [12.4, 54.3], P < 0.01), and the length of stay was longer (12.000 [8.0, 17.0] vs. (8.420 [5.0, 12.0], P < 0.01]. There were significant differences in malnutrition risk among different age groups (χ² = 144.933, P < 0.01), and children under one year of age exhibited the highest risk for malnutrition and more extended hospital stay (H = 78.085, P < 0.01). The risk of malnutrition among children with cyanotic CHD was higher than in those with non-cyanotic CHD (χ² = 104.384, P < 0.01).

CONCLUSIONS

The new digital pediatric malnutrition screening tool showed high sensitivity and specificity in children with CHD. The tool indicated that the malnutrition risk for young children and children with cyanotic or Bethesda moderate and complex CHD was higher, and the hospitalization time was longer than in the non-risk group. The tool provides a rational approach to targeted nutrition intervention and support and may improve clinical outcomes.

Performance of subjective global nutritional assessment in predicting clinical outcomes: Data from the Brazilian survey of pediatric oncology nutrition

BACKGROUND

Methods for assessing nutritional status in children and adolescents with cancer is a difficult in clinical practice. The study aimed to evaluate the performance of Subjective Global Nutritional Assessment (SGNA) in predicting clinical outcomes in children and adolescents with cancer in Brazil.

METHODS

This was a prospective cohort multicenter study. It was included 723 children and adolescents with cancer aged 2-18 years between March 2018 and August 2019. Nutritional assessment was performed according to World Health Organization recommendations and using SGNA within 48h of hospitalization. Unplanned readmission, length of hospital stay, and post-discharge death were analyzed. Cohen's kappa coefficient was used to ascertain the agreement between body mass index for age (BMI/A) and SGNA. The sensitivity, specificity, positive and negative predictive values, and accuracy of SGNA were estimated. Odds ratios (ORs) with 95% confidence intervals (CIs) were evaluated using multiple logistic regression.

RESULTS

The mean patient age was 9.4 ± 4.9 years. SGNA showed that 29.7% (n = 215) and 6.5% (n = 47) patients had moderate and severe malnutrition, respectively. Considering the concurrent validity criterion, SGNA had an OR (95% CI) of 6.8 (3.1-14.9) for predicting low and very low weight for age at admission, with a sensitivity and specificity of 72.4% (59%-82.1%) and 72% (64.2%-78.9%), respectively. SGNA could predict death in children with severe/moderate malnutrition, with an accuracy of 63.8% (63%-65.1%). Logistic multivariate analysis showed that the adjusted effect of death; hematological tumor; living in the northeast, southeast, and midwest regions of Brazil; and older age was associated with malnutrition according to SGNA.

CONCLUSION

Based on concurrent validity between SGNA and anthropometry, SGNA performed well and had a good ability to predict death in Brazilian children with cancer.

Applicability of predictive models for 30-day unplanned hospital readmission risk in paediatrics: a systematic review

OBJECTIVES

To summarise multivariable predictive models for 30-day unplanned hospital readmissions (UHRs) in paediatrics, describe their performance and completeness in reporting, and determine their potential for application in practice.

DESIGN

Systematic review.

DATA SOURCE

CINAHL, Embase and PubMed up to 7 October 2021.

ELIGIBILITY CRITERIA

English or German language studies aiming to develop or validate a multivariable predictive model for 30-day paediatric UHRs related to all-cause, surgical conditions or general medical conditions were included.

DATA EXTRACTION AND SYNTHESIS

Study characteristics, risk factors significant for predicting readmissions and information about performance measures (eg, c-statistic) were extracted. Reporting quality was addressed by the 'Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis' (TRIPOD) adherence form. The study quality was assessed by applying six domains of potential biases. Due to expected heterogeneity among the studies, the data were qualitatively synthesised.

RESULTS

Based on 28 studies, 37 predictive models were identified, which could potentially be used for determining individual 30-day UHR risk in paediatrics. The number of study participants ranged from 190 children to 1.4 million encounters. The two most common significant risk factors were comorbidity and (postoperative) length of stay. 23 models showed a c-statistic above 0.7 and are primarily applicable at discharge. The median TRIPOD adherence of the models was 59% (P₂₅-P₇₅, 55%-69%), ranging from a minimum of 33% to a maximum of 81%. Overall, the quality of many studies was moderate to low in all six domains.

CONCLUSION

Predictive models may be useful in identifying paediatric patients at increased risk of readmission. To support the application of predictive models, more attention should be placed on completeness in reporting, particularly for those items that may be relevant for implementation in practice.

STRONGkids nutrition screening tool in pediatrics: An analysis of cutoff points in Brazil

BACKGROUND

Studies have indicated the Screening Tool for Risk on Nutritional Status and Growth (STRONGkids) as a method of pediatric nutrition screening with good validity in the hospital setting. However, we need to analyze whether the cutoff values originally proposed are suitable for use in Brazil.

METHODS

A cross-sectional study was performed in patients admitted to the pediatric ward of a public hospital. STRONGkids was used to assess nutrition risk (low risk, 0 points; moderate risk, 1-3 points; and high risk, 4-5 points). The indexes weight/height or body mass index/age were used to indicate acute malnutrition, and length or height/age was used to indicate chronic malnutrition. Receiver operating characteristic curves were constructed and the areas under the curve were calculated, with respective 95% confidence intervals, to assess the ability of STRONGkids to predict malnutrition and longer hospital stay.

RESULTS

The study included 599 patients, with a median age of 2.6 years. The frequency of nutrition risk (medium or high) was 83.6%. In comparison with anthropometric indexes, STRONGkids was the only scoring system with the discriminatory capacity to identify patients with longer hospital stays. The comparative analysis of the means of hospital stay according to STRONGkids showed that patients with a score equal to 3 behaved similarly to those classified as high nutrition risk (4-5 points).

CONCLUSIONS

Considering the best cutoff point to predict prolonged hospitalization, STRONGkids used in Brazil should consider patients with 3 points as having high nutrition risk, as well those scoring 4 and 5.

Nutritional screening tool for critically ill children: a systematic review

CONTEXT

Nutritional screening tools (NSTs) are used to identify patients who are at risk of nutritional status (NS) deterioration and associated clinical outcomes. Several NSTs have been developed for hospitalized children; however, none of these were specifically developed for Pediatric Intensive Care Unit (PICU) patients.

OBJECTIVE

A systematic review of studies describing the development, application, and validation of NSTs in hospitalized children was conducted to critically appraise their role in PICU patients.

DATA SOURCES

PubMed, Embase, Web of Science, Scopus, SciELO, LILACS, and Google Scholar were searched from inception to December 11, 2020.

DATA EXTRACTION

The review included 103 studies that applied NSTs at hospital admission. The NST characteristics collected included the aims, clinical setting, variables, and outcomes. The suitability of the NSTs in PICU patients was assessed based on a list of variables deemed relevant for this population.

DATA ANALYSIS

From 19 NSTs identified, 13 aimed to predict NS deterioration. Five NSTs were applied in PICU patients, but none was validated for this population. NSTs did not include clinical, NS, laboratory, or dietary variables that were deemed relevant for the PICU population.

CONCLUSION

None of the available NSTs were found to be suitable for critically ill children, so a new NST should be developed for this population. AQ6.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration no. CRD42020167898.

Anthropometric assessment in ambulatory nutrition amid the COVID-19 pandemic: Possibilities for the remote and in-person care

Background and aims

The COVID-19 pandemic has caused many changes in the nutritional care process as a result of the social distancing measures imposed, especially in the assessment of nutritional status, in which obtaining anthropometric measures is necessary.

Methods

Critical review of the international anthropometry literature, in the light of the recent scientific evidence of COVID-19.

Results

This paper presents recommendations for anthropometric assessment of the nutritional status of people in ambulatory settings for both remote and in-person assessment. The most appropriate measures to the current pandemic scenario are also discussed, in order to contribute to the monitoring of nutritional status and to minimize health impacts.results

Conclusion

When sanitary conditions cannot be guaranteed during in-person encounters or when the person cannot attend the office of the professional, the remote anthropometric assessment can be a useful strategy to nutritional surveillance.conclusions