The Effect of Malnutrition on the Risk of Unplanned 7-Day Readmission in Pediatrics

Ehwerhemuepha, Louis; Bendig, Donald W.; Steele, Caroline; Rakovski, Cyril; Feaster, William

doi:10.1542/hpeds.2017-0195

Cited by 25 publications

(29 citation statements)

References 30 publications

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“…The pRI, as a continuous measure of general patient condition, considers the vital signs, laboratory results, and nursing assessment results that may be direct or proxy risk factors of readmission. For example, previous research has revealed that there is an association between malnutrition and risk of readmission, 23,24 and the pRI considers a nursing assessment for food sufficiency. Consequently, in addition to being a measure of general patient condition, the pRI encapsulates a range of clinical data that may modify a patient' s risk of readmission.…”

mentioning

confidence: 99%

A Novel Model for Enhanced Prediction and Understanding of Unplanned 30-Day Pediatric Readmission

Ehwerhemuepha

Finn²,

Rothman

et al. 2018

Hospital Pediatrics

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Our model provides significant performance improvements in the prediction of unplanned 30-day pediatric readmissions with AUC higher than the LACE readmission model and other general unplanned 30-day pediatric readmission models. The model is expected to provide an opportunity to capture 39% of readmissions (at a selected operating point) and may therefore assist clinicians in reducing avoidable readmissions.

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confidence: 99%

A Novel Model for Enhanced Prediction and Understanding of Unplanned 30-Day Pediatric Readmission

Ehwerhemuepha

Finn²,

Rothman

et al. 2018

Hospital Pediatrics

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“…True validity of the AMC against a “gold standard,” such as SGA, has not yet been published and is clearly needed. Notwithstanding the need for further validation work, the use of the AMC and the PMI tools has been useful in measuring malnutrition in hospitalized adult and pediatric patients and linking that condition with important clinical outcomes, including mortality, hospital length of stay (adults), complications (pediatrics), and readmissions . .…”

Section: Discussionmentioning

confidence: 99%

“…In the pediatric population, similar results have been observed with 3 published studies to date evaluating malnutrition as identified by the PMI and outcomes (see Table 6). [46][47][48] Increased odds of 30-day complications following surgery in children with Crohn's disease was demonstrated in those identified as mildly, moderately, or severely malnourished using the z-score BMI single indicator. 46 This was observed only in mild (OR = 2.1 [P = 0.04]) and severely (OR 3.3 [P = 0.03]) malnourished patients.…”

Section: Malnutrition Characteristics and Outcomesmentioning

confidence: 99%

“…This was observed only in mild (OR = 2.1 [ P = 0.04]) and severely (OR 3.3 [ P = 0.03]) malnourished patients. In a tertiary children's hospital, odds of unplanned readmissions within 7 days of a previous discharge were higher in those malnourished and younger ( P = 0.002) . Higher all‐cause ICU mortality (adjusted OR 3.0, 95% CI 1.2–7.7, P = 0.02) was demonstrated in those severely malnourished defined with the single z ‐score BMI indicator in an international pediatric severely septic cohort …”

Section: Introductionmentioning

confidence: 95%

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Academy of Nutrition and Dietetics/American Society for Parenteral and Enteral Nutrition Consensus Malnutrition Characteristics: Usability and Association With Outcomes

et al. 2019

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Malnutrition has been documented in approximately one‐third of patients in developed countries on hospital admission and is associated with negative clinical outcomes. The need to identify and intervene in at‐risk patients is critical to minimize these negative outcomes. A consensus approach for diagnosing and documenting malnutrition in hospitalized adult and pediatric patients was published jointly by the Academy of Nutrition and Dietetics (Academy) and the American Society for Parenteral and Enteral Nutrition (ASPEN) in 2012 and 2014, respectively. The purpose of this paper is to review the available literature on the usability, feasibility, validity, and reliability of both the adult and pediatric consensus malnutrition diagnostic approaches, as well as to evaluate their use in studying clinical outcomes. In adults, abstracts and published studies have shown the diagnostic tool is a usable, feasible, and reliable method for the identification of severe and non‐severe or moderate malnutrition. In pediatrics, only 1 published study to date used the pediatric malnutrition indicators, indicating the need to demonstrate that the tool is feasible, valid, and reliable. Both the adult and pediatric tools have shown significant correlation with negative clinical outcomes in malnourished patients, including increased mortality, increased hospital length of stay (adults), increased complications (pediatrics), and increased hospital readmissions. Further large‐scale studies are needed to evaluate the feasibility, usability, validity, and reliability of both the adult and pediatric malnutrition diagnostic approaches.

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“…Logistic regression is an integral part of data analysis focused on exploring the strength and direction of associations between a dichotomous response variable and a set of potential predictors, and is widely used by researchers [1], [2], [3], [4], [5], [6]. In general, the goal of these research studies is to identify the set of true predictors that are incorporated in the final model which is used for classification, prediction or interpretation.…”

Section: Introductionmentioning

confidence: 99%

A comprehensive assessment of automatic logistic regression model selection methods

Ehwerhemuepha

Rakovski

2019

Preprint

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Background: Current studies of variable selection methods are based on small datasets for which the true underlying predictors and corresponding effect sizes may not be known precisely. We designed and implemented a large-scale simulation study to assess the ability of stepwise logistic regression variable selection and lasso regression methods to identify the correct underlying model. Methods: We simulated data based on a random multivariate distribution over an extensive range of covariate correlation structures, sample sizes, number of covariates, number of true predictors, and effect sizes. We considered correlation structures reflecting the scenarios of independence across all covariates; two low correlation blocks and a block of zero correlation; three blocks of high correlation, low correlation and zero correlation; and two blocks of high correlation with low cross block correlation and a block of zero correlation respectively. Results: Our results show that the performances of stepwise regression, lasso regression, and random forest algorithm (as measured by the AUC, detection of true predictors, selection of noise variables, and effect size estimation) are affected by the number of true predictor variables, the correlation between the variables in the dataset, and the sample size. The number of noise variables in the dataset, although significant in some cases, has only a marginal effect on a variety of model performance statistic. Our results show that stepwise regression procedures are more likely to capture a true predictor, more likely to correctly estimate the true effect sizes, and more likely to have lower false discovery rates. Moreover, stepwise model selection based on the BIC criteria obtained the highest average AUC (0.7515) closely followed by lasso regression, stepwise model selection based on the AIC criteria, ridge regression, and random forest algorithm. Conclusions: Stepwise procedures for variable selection are robust in the selection of the true underly predictor variables, estimation of corresponding effect sizes, and predictive model performance. Recommendations suggesting that stepwise procedures should be abandoned may be misguided.

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The Effect of Malnutrition on the Risk of Unplanned 7-Day Readmission in Pediatrics

Abstract: The statistical interaction effect revealed that a patient's risk of readmission is jointly modified by the patient's age and malnutrition status. This finding advances our understanding of the complex picture of the simultaneous risk factor of unplanned 7-day readmissions in pediatrics.

Cited by 25 publications

References 30 publications

A Novel Model for Enhanced Prediction and Understanding of Unplanned 30-Day Pediatric Readmission

A Novel Model for Enhanced Prediction and Understanding of Unplanned 30-Day Pediatric Readmission

Academy of Nutrition and Dietetics/American Society for Parenteral and Enteral Nutrition Consensus Malnutrition Characteristics: Usability and Association With Outcomes

A comprehensive assessment of automatic logistic regression model selection methods

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