Development and Validation of a New Screening Tool with Non-Invasive Indicators for Assessment of Malnutrition Risk in Hospitalised Children.

There is no evidence of the most effective nutritional screening tool for hospitalized children. The present study aimed to develop a quick, simple, and valid screening tool for identifying malnutrition risk of hospital admission with non-invasive indicators. A cross-sectional study was conducted. Children`s nutritional baseline using a questionnaire, subjective malnutritional risk, and Subjective Global Nutritional Assessment were assessed on admission. Concurrent validity was assessed using American Society for Parenteral and Enteral Nutrition (ASPEN)and Academy of Nutrition and Dietetics assessment and Subjective Global Nutritional Assessment tool. A new screening tool Simple Pediatric Nutritional risk Screening tool (SPENS) was developed, and sensitivity, specificity and reliability were evaluated. A total of 180 children aged from 1 month to 18 years were included (142 in the development phase and 38 in the validation phase). SPENS consist of four variables and shows almost perfect agreement with subjective malnutritional risk assessment (κ = 0.837) with high sensitivity and specificity (93.3% and 91.3% respectively). Compared with Subjective Global Nutritional Assessment and ASPEN and Academy of Nutrition and Dietetics assessment, SPENS had sensitivity 92.9% and 86.7%, a specificity of 87.5% and 87.0%, and an overall agreement of 0.78 and 0.728, respectively. Due to the fast, simple, easy, and practical to use, screening the SPENS can be performed by nurses, physicians, and dieticians.

Screening and assessment tools for early detection of malnutrition in hospitalised children: a systematic review of validation studies.

OBJECTIVE: The aim of the present study was to identify all currently available screening and assessment tools for detection of malnutrition in hospitalised children, and to identify the most useful tools on the basis of published validation studies. DESIGN: Systematic review. DATA SOURCES: PubMed, CINAHL and MEDLINE were searched up to October 2017. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Studies in English that reported sensitivity, specificity and positive/negative predictive values (PPVs/NPVs) in the paediatric population were eligible for inclusion. DATA EXTRACTION AND SYNTHESIS: Two authors independently screened all of the studies identified, and extracted the data. The methodological qualities of the studies included were assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. RESULTS: The 26 validation studies that met the inclusion criteria for this systematic review used eight screening and three assessment tools. The number of participants varied from 32 to 14 477. There was considerable variability in the chosen reference standards, which prevented direct comparisons of the predictive performances of the tools. Anthropometric measurements were used as reference standards in 16 of the identified studies, and full nutritional assessment in 5. The Pediatric Yorkhill Malnutrition Score (PYMS) screening tool performed better than Screening Tool for the Assessment of Malnutrition and Screening Tool for Risk On Nutritional status and Growth when compared in terms of anthropometric measurements, especially for body mass index (Se=90.9, Sp=81.9) and triceps skinfold thickness (Se=80.0, Sp=75.0). However, low PPVs indicated the problem of overprediction of positive cases, which was typical for all of the studies that used anthropometric measurements as the reference standard. CONCLUSIONS: This systematic review identifies the need for definition of the gold standard for validation of screening tools. Anthropometry measurements using WHO or Centers for Disease Control and Prevention growth charts should be considered as the possible reference standard in future validation studies. We would recommend the use of PYMS for hospitalised paediatric patients without chronic conditions, in combination with full nutritional assessment. PROSPERO REGISTRATION NUMBER: CRD42017077477.

Maximizing Interpretability and Cost-Effectiveness of Surgical Site Infection (SSI) Predictive Models Using Feature-Specific Regularized Logistic Regression on Preoperative Temporal Data.

This study describes a novel approach to solve the surgical site infection (SSI) classification problem. Feature engineering has traditionally been one of the most important steps in solving complex classification problems, especially in cases with temporal data. The described novel approach is based on abstraction of temporal data recorded in three temporal windows. Maximum likelihood L1-norm (lasso) regularization was used in penalized logistic regression to predict the onset of surgical site infection occurrence based on available patient blood testing results up to the day of surgery. Prior knowledge of predictors (blood tests) was integrated in the modelling by introduction of penalty factors depending on blood test prices and an early stopping parameter limiting the maximum number of selected features used in predictive modelling. Finally, solutions resulting in higher interpretability and cost-effectiveness were demonstrated. Using repeated holdout cross-validation, the baseline C-reactive protein (CRP) classifier achieved a mean AUC of 0.801, whereas our best full lasso model achieved a mean AUC of 0.956. Best model testing results were achieved for full lasso model with maximum number of features limited at 20 features with an AUC of 0.967. Presented models showed the potential to not only support domain experts in their decision making but could also prove invaluable for improvement in prediction of SSI occurrence, which may even help setting new guidelines in the field of preoperative SSI prevention and surveillance.

Defining the incremental value of 3D T2-weighted imaging in the assessment of prostate cancer extracapsular extension.

OBJECTIVES: To assess the added value of 3D T2-weighted imaging (T2WI) over conventional 2D T2WI in diagnosing extracapsular extension (ECE). METHODS: Seventy-five patients undergoing 3-T MRI before radical prostatectomy were included. PI-RADS ≥ 4 lesions were assessed for ECE on 2D T2W images using a 5-point Likert scale (1 = no ECE, 5 = definite ECE) and the length of tumour prostatic capsular contact. A second read using 3D T2W images and reformats evaluated ECE and the maximal 3D capsular contact length and surface. RESULTS: One hundred six lesions were identified at MRI. ECE was confirmed by histology in 54% (57/106) of lesions and 64% (48/75) of patients. Sensitivity and specificity for 3D T2 reads were 75.4% versus 64.9% (p = 0.058), respectively, and 83.7% versus 85.7% (p = 0.705) for 2D T2 reads, respectively. 3D T2W reads showed significantly higher mean subjective Likert scores of 3.7 ± 1.4 versus 3.3 ± 1.4 (p = 0.001) in ECE-positive lesions and lower mean Likert score of 1.5 ± 1 versus 1.6 ± 0.9 (p = 0.27) in ECE-negative lesions compared with 2D T2W reads. 3D contact significantly increased sensitivity from 59.6 to 73.7% (p = 0.03), whilst maintaining the same specificity of 87.8% (p = 1). High-grade group tumours (≥ Gleason 4 + 3) showed significantly higher ECE prevalence than low-grade tumours (88% versus 44%, p < 0.001) and a positive predictive value (PPV) for ECE of 90.9% with ≥ 5 mm of contact versus PPV of 90.4% at ≥ 12.5 mm for lower grade tumours. CONCLUSIONS: 3D T2WI significantly increases sensitivity and confidence in calling ECE. The capsular contact length threshold differed between low- and high-grade cancers. KEY POINTS: • 3D capsular contact length and 3D surface contact significantly increased sensitivity in diagnosing ECE. • 3D T2W reads significantly increased reader confidence in calling ECE. • Thresholds for capsular contact length differed between low-grade and high-grade cancers.