Ability of commonly used prediction equations to predict resting energy expenditure in children with inflammatory bowel disease

Background: Paediatric onset inflammatory bowel disease (IBD) may cause alterations in energy requirements and invalidate the use of standard prediction equations. Our aim was to evaluate four commonly used prediction equations for resting energy expenditure (REE) in children with IBD. Methods: Sixty-three children had repeated measurements of REE as part of a longitudinal research study yielding a total of 243 measurements. These were compared with predicted REE from Schofield, Oxford, FAO/WHO/UNU, and Harris-Benedict equations using the Bland-Altman method. Results: Mean (±SD) age of the patients was 14.2 (2.4) years. Mean measured REE was 1566 (336) kcal per day compared with 1491 (236), 1441 (255), 1481 (232), and 1435 (212) kcal per day calculated from Schofield, Oxford, FAO/WHO/UNU, and Harris-Benedict, respectively. While the Schofield equation demonstrated the least difference between measured and predicted REE, it, along with the other equations tested, did not perform uniformly across all subjects, indicating greater errors at either end of the spectrum of energy expenditure. Smaller differences were found for all prediction equations for Crohn's disease compared with ulcerative colitis. Conclusions: Of the commonly used equations, the equation of Schofield should be used in pediatric patients with IBD when measured values are not able to be obtained. (Inflamm Bowel Dis 2010;) Copyright © 2010 Crohn's & Colitis Foundation of America, Inc.

Validity of currently used cutoff values of body mass index as a measure of obesity in Sri Lankan children

The aim of the study was to determine the reliability of body mass index based (BMI) cutoff values in diagnosing obesity among Sri Lankan children. Height, weight, waist circumference (WC) and hip circumference (HC) in 282 children were measured. Total body water was determined by deuterium dilution and fat mass (FM) derived using age and gender specific constants. A percentage FM of 30% for girls and 25% for boys were considered as cutoff levels for obesity. Two hundred and eighty two children (M/F: 158/124) were studied and 99 (80%) girls and 72 (45.5%) boys were obese based on % body fat. Eight (6.4%) girls and nine (5.7%) boys were obese based on International Obesity Task Force (IOTF) cutoff values. Percentage FM and WC centile charts were able to diagnose a significant proportion of children as true obese children. The FM and BMI were closely associated in both girls (r = 0.82, p < 0.001) and boys (r = 0.87, p < 0.001). Percentage FM and BMI had a very low but significant association; girls (r = 0.32, p < 0.001) and boys (r = 0.68, p < 0.001). FM had a significant association with WC and HC. BMI based cutoff values had a specificity of 100% but a very low sensitivity, varying between 8% and 23.6%. BMI is a poor indicator of the percentage fat and the commonly used cutoff values were not sensitive to detect cases of childhood obesity in Sri Lankan children.

Assessment of body composition in Sri Lankan children: Validation of a bioelectrical impedance prediction equation

Objective: To develop bioelectrical impedance analysis (BIA) equations to predict total body water (TBW) and fat-free mass (FFM) of Sri Lankan children. Subjects/Methods: Data were collected from 5- to 15-year-old healthy children. They were randomly assigned to validation (M/F: 105/83) and cross-validation (M/F: 53/41) groups. Height, weight and BIA were measured. TBW was assessed using isotope dilution method (D2 O). Multiple regression analysis was used to develop preliminary equations and cross-validated on an independent group. Final prediction equation was constructed combining the two groups and validated by PRESS (prediction of sum of squares) statistics. Impedance index (height2/impedance; cm2/Ω), weight and sex code (male = 1; female = 0) were used as variables. Results: Independent variables of the final prediction equation for TBW were able to predict 86.3% of variance with root means-squared error (RMSE) of 2.1l. PRESS statistics was 2.1l with press residuals of 1.2l. Independent variables were able to predict 86.9% of variance of FFM with RMSE of 2.7 kg. PRESS statistics was 2.8 kg with press residuals of 1.4 kg. Bland Altman technique showed that the majority of the residuals were within mean bias±1.96 s.d. Conclusions: Results of this study provide BIA equation for the prediction of TBW and FFM in Sri Lankan children. To the best of our knowledge there are no published BIA prediction equations validated on South Asian populations. Results of this study need to be affirmed by more studies on other closely related populations by using multi-component body composition assessment.

Measured and predicted total body water in children with myelomeningocele

Objective: Children with myelomeningocele (MMC) have an altered body composition and an atypical distribution of total body water (TBW). The aim of the present study was to determine the accuracy of current predictive equations, based on bioelectrical impedance analysis (BIA), in determining TBW when compared with measured TBW using deuterium dilution. Methods: Fourteen children with MMC were measured for whole body BIA and TBW (using deuterium dilution and the Plateau method). Total body water was predicted using equations based on the resistance and characteristic frequency from BIA measurements and heights of subjects. Results: The mean measured TBW was 15.46 ± 8.28 L and the mean predictions for TBW using equations based on the resistance and characteristic frequency from BIA measurements and heights of subjects were 18.29 ± 8.41 L, 17.72 ± 11.42 L and 12.51 ± 7.59 L, respectively. The best correlation was found using characteristic frequency. The limits of agreement between measured and predicted TBW values using Bland-Altman analysis were large. Conclusions: The present study suggests that the prediction of TBW in children with MMC can be made accurately using the equation of Cornish et al. based on BIA measurements of characteristic frequency.

Comparison of measured sleeping metabolic rate and predicted basal metabolic rate during the first year of life : evidence of a bias changing with increasing metabolic rate

Objective: To compare measurements of sleeping metabolic rate (SMR) in infancy with predicted basal metabolic rate (BMR) estimated by the equations of Schofield. Methods: Some 104 serial measurements of SMR by indirect calorimetry were performed in 43 healthy infants at 1.5, 3, 6, 9 and 12 months of age. Predicted BMR was calculated using the weight only (BMR-wo) and weight and height (BMR-wh) equations of Schofield for 0-3-y-olds. Measured SMR values were compared with both predictive values by means of the Bland-Altman statistical test. Results: The mean measured SMR was 1.48 MJ/day. The mean predicted BMR values were 1.66 and 1.47 MJ/day for the weight only and weight and height equations, respectively. The Bland-Altman analysis showed that BMR-wo equation on average overestimated SMR by 0.18 MJ/day (11%) and the BMR-wh equation underestimated SMR by 0.01 MJ/day (1%). However the 95% limits of agreement were wide: -0.64 to + 0.28 MJ/day (28%) for the former equation and -0.39 to + 0.41 MJ/day (27%) for the latter equation. Moreover there was a significant correlation between the mean of the measured and predicted metabolic rate and the difference between them. Conclusions: The wide variation seen in the difference between measured and predicted metabolic rate and the bias probably with age indicates there is a need to measure actual metabolic rate for individual clinical care in this age group.

Comparison of the Cosmed K4 b2 and the Deltatrac II™ metabolic cart in measuring resting energy expenditure in adults

Background and Aims: The objective of the study was to compare data obtained from the Cosmed K4 b2 and the Deltatrac II™ metabolic cart for the purpose of determining the validity of the Cosmed K4 b2 in measuring resting energy expenditure. Methods: Nine adult subjects (four male, five female) were measured. Resting energy expenditure was measured in consecutive sessions using the Cosmed K4 b2, the Deltatrac II™ metabolic cart separately and the Cosmed K4 b2 and Deltatrac II™ metabolic cart simultaneously, performed in random order. Resting energy expenditure (REE) data from both devices were then compared with values obtained from predictive equations. Results: Bland and Altman analysis revealed a mean bias for the four variables, REE, respiratory quotient (RQ), VCO2, VO2 between data obtained from Cosmed K4 b2 and Deltatrac II™ metabolic cart of 268 ± 702 kcal/day, -0.0±0.2, 26.4±118.2 and 51.6±126.5 ml/min, respectively. Corresponding limits of agreement for the same four variables were all large. Also, Bland and Altman analysis revealed a larger mean bias between predicted REE and measured REE using Cosmed K4 b2 data (-194±603 kcal/day) than using Deltatrac™ metabolic cart data (73±197 kcal/day). Conclusions: Variability between the two devices was very high and a degree of measurement error was detected. Data from the Cosmed K4 b2 provided variable results on comparison with predicted values, thus, would seem an invalid device for measuring adults. © 2002 Elsevier Science Ltd. All rights reserved.

Risk analysis of prostate cancer in PRACTICAL, a multinational consortium, using 25 known prostate cancer susceptibility loci

Background Genome-wide association studies have identified multiple genetic variants associated with prostate cancer risk which explain a substantial proportion of familial relative risk. These variants can be used to stratify individuals by their risk of prostate cancer. Methods We genotyped 25 prostate cancer susceptibility loci in 40,414 individuals and derived a polygenic risk score (PRS).We estimated empirical odds ratios (OR) for prostate cancer associated with different risk strata defined by PRS and derived agespecific absolute risks of developing prostate cancer by PRS stratum and family history. Results The prostate cancer risk for men in the top 1% of the PRS distribution was 30.6 (95% CI, 16.4-57.3) fold compared with men in the bottom 1%, and 4.2 (95% CI, 3.2-5.5) fold compared with the median risk. The absolute risk of prostate cancer by age of 85 years was 65.8% for a man with family history in the top 1% of the PRS distribution, compared with 3.7% for a man in the bottom 1%. The PRS was only weakly correlated with serum PSA level (correlation = 0.09). Conclusions Risk profiling can identify men at substantially increased or reduced risk of prostate cancer. The effect size, measured by OR per unit PRS, was higher in men at younger ages and in men with family history of prostate cancer. Incorporating additional newly identified loci into a PRS should improve the predictive value of risk profiles. Impact:We demonstrate that the risk profiling based on SNPs can identify men at substantially increased or reduced risk that could have useful implications for targeted prevention and screening programs.

Antithrombin III associated with fibrinogen predicts the risk of cerebral ischemic stroke

Background and purpose: The purpose of this study is to examine the feasibility of developing plasma predictive value biomarkers of cerebral ischemic stroke before imaging evidence is acquired. Methods: Blood samples were obtained from 198 patients who attended our neurology department as emergencies - with symptoms of vertigo, numbness, limb weakness, etc. - within 4.5 h of symptom onset, and before imaging evidence was obtained and medical treatment. After the final diagnosis was made by MRI/DWI/MRA or CTA in the following 24-72 h, the above cases were divided into two groups: stroke group and non-stroke group according to the imaging results. The levels of baseline plasma antithrombin III (AT-III), thrombin-antithrombin III (TAT), fibrinogen, D-dimer and high-sensitivity C-reactive protein (hsCRP) in the two groups were assayed. Results: The level of the baseline AT-III in the stroke group was 118.07 ± 26.22%, which was lower than that of the non-stroke group (283.83 ± 38.39%). The levels of TAT, fibrinogen, hsCRP were 7.24 ± 2.28 μg/L, 5.49 ± 0.98 g/L, and 2.17 ± 1.07 mg/L, respectively, which were higher than those of the non-stroke group (2.53 ± 1.23 μg/L, 3.35 ± 0.50 g/L, 1.82 ± 0.67 mg/L). All the P-values were less than 0.001. The D-dimer level was 322.57 ± 60.34 μg/L, which was slightly higher than that of the non-stroke group (305.76 ± 49.52 μg/L), but the P-value was 0.667. The sensitivities of AT-III, TAT, fibrinogen, D-dimer and hsCRP for predicting ischemic stroke tendency were 97.37%, 96.05%, 3.29%, 7.89%, but the specificity was 93.62%, 82.61%, 100% and 100%, respectively, and all the P-values were less than 0.001. High levels of D-dimer and hsCRP were mainly seen in the few cases with severe large-vessel infarction. Conclusions: Clinical manifestations of acute focal neurological deficits were associated with plasma AT-III and fibrinogen. These tests might help the risk assessment of acute cerebral ischemic stroke and/or TIA with infarction tendency in the superacute stage before positive imaging evidence is obtained.

Infant product-related injuries: comparing specialised injury surveillance and routine emergency department data

- Objective To explore the potential for using a basic text search of routine emergency department data to identify product-related injury in infants and to compare the patterns from routine ED data and specialised injury surveillance data. - Methods Data was sourced from the Emergency Department Information System (EDIS) and the Queensland Injury Surveillance Unit (QISU) for all injured infants between 2009 and 2011. A basic text search was developed to identify the top five infant products in QISU. Sensitivity, specificity, and positive predictive value were calculated and a refined search was used with EDIS. Results were manually reviewed to assess validity. Descriptive analysis was conducted to examine patterns between datasets. - Results The basic text search for all products showed high sensitivity and specificity, and most searches showed high positive predictive value. EDIS patterns were similar to QISU patterns with strikingly similar month-of-age injury peaks, admission proportions and types of injuries. - Conclusions This study demonstrated a capacity to identify a sample of valid cases of product-related injuries for specified products using simple text searching of routine ED data. - Implications As the capacity for large datasets grows and the capability to reliably mine text improves, opportunities for expanded sources of injury surveillance data increase. This will ultimately assist stakeholders such as consumer product safety regulators and child safety advocates to appropriately target prevention initiatives.

Harnessing information from injury narrative in the 'big data' era: Understanding and applying machine learning for injury surveillance

Objective Vast amounts of injury narratives are collected daily and are available electronically in real time and have great potential for use in injury surveillance and evaluation. Machine learning algorithms have been developed to assist in identifying cases and classifying mechanisms leading to injury in a much timelier manner than is possible when relying on manual coding of narratives. The aim of this paper is to describe the background, growth, value, challenges and future directions of machine learning as applied to injury surveillance. Methods This paper reviews key aspects of machine learning using injury narratives, providing a case study to demonstrate an application to an established human-machine learning approach. Results The range of applications and utility of narrative text has increased greatly with advancements in computing techniques over time. Practical and feasible methods exist for semi-automatic classification of injury narratives which are accurate, efficient and meaningful. The human-machine learning approach described in the case study achieved high sensitivity and positive predictive value and reduced the need for human coding to less than one-third of cases in one large occupational injury database. Conclusion The last 20 years have seen a dramatic change in the potential for technological advancements in injury surveillance. Machine learning of ‘big injury narrative data’ opens up many possibilities for expanded sources of data which can provide more comprehensive, ongoing and timely surveillance to inform future injury prevention policy and practice.

Sonography of paediatric appendicitis and its secondary signs

Sonographic diagnosis of appendicitis in children is an important clinical tool, often obviating the need for potentially harmful ionising radiation from computed tomography (CT) scans and unnecessary appendectomies. Established criteria do not commonly account for the sonographic secondary signs of acute appendicitis as an adjunct or corollary to an identifiably inflamed appendix. If one of, or combinations of these secondary signs are a reliable positive and/or negative indicator of the condition, diagnostic accuracy may be improved. This will be of particular importance in cases where the appendix cannot be easily identified, possibly providing referring clinicians with a less equivocal diagnosis. Acute appendicitis (AA) is the most common emergency presentation requiring surgical intervention among both adults and children. During 2010-11 in Australia 25000 appendicectomies were performed on adults and children, more than double the number of the next most common surgical procedure [1]. Ultrasound has been commonly used to diagnose AA since the 1980s, however the best imaging modality or combination of modalities to accurately and cost-effectively diagnose the condition is still debated. A study by Puylaert advocated ultrasound in all presentations [2], whereas others suggested it only as a first line modality [3–5]. Conversely, York et al state that it is not appropriate as it delays treatment [6]. CT has been shown to more accurately diagnose AA than ultrasound, however its inherent radiation risks warrant cautionary use in children [7]. Improved accuracy in the diagnosis of suspected AA using ultrasound would enable surgeons to make a decision without the need to expose children to the potentially harmful effects of CT. Secondary signs of appendicitis are well established [8], although research into their predictive values has only recently been undertaken [9,10] indicating their potential diagnostic benefit in the absence of an identifiable appendix. The purpose of this review is to examine the history of appendiceal sonography, established sonographic criteria, paediatric specific techniques and the predictive value of secondary signs.

The association between student characteristics and the development of clinical reasoning in a graduate-entry, PBL medical programme

This study sought to assess the extent to which the entry characteristics of students in a graduate-entry medical programme predict the subsequent development of clinical reasoning ability. Subjects comprised 290 students voluntarily recruited from three successive cohorts of the University of Queensland's MBBS Programme. Clinical reasoning was measured once a year over a period of three years using two methods, a set of 10 Clinical Reasoning Problems (CRPs) and the Diagnostic Thinking Inventory (DTI). Data on gender, age at entry into the programme, nature of primary degree, scores on selection criteria (written examination plus interview) and academic performance in the first two years of the programme were recorded for each student, and their association with clinical reasoning skill analysed using univariate and multivariate analysis. Univariate analysis indicated significant associations between CRP score, gender and primary degree with a significant but small association between DTI and interview score. Stage of progression through the programme was also an important predictor of performance on both indicators. Subsequent multivariate analysis suggested that female gender is a positive predictor of CRP score independently of the nature of a subject's primary degree and stage of progression through the programme, although these latter two variables are interdependent. Positive predictors of clinical reasoning skill are stage of progression through the MBBS programme, female gender and interview score. Although the nature of a student's primary degree is important in the early years of the programme, evidence suggests that by graduation differences between students' clinical reasoning skill due to this factor have been resolved.

Appendiceal sonography in children: A retrospective analysis as a platform for potential implementation of diagnostic categories

- Background Sonography is an important diagnostic tool in children with suspected appendicitis. Reported accuracy and appendiceal visualisation rates vary significantly, as does the management of equivocal ultrasound findings. The aim of this study was to audit appendiceal sonography at a tertiary children's hospital, and provide baseline data for a future prospective study. - Summary of work Records of children who underwent ultrasound studies for possible appendicitis between January 2008 and December 2010 were reviewed. Variables included patient demographics, sonographic appendix characteristics, and secondary signs. Descriptive statistics and analysis using ANOVA, Mann-Whitney U test, and ROC curves were performed. Mater Human Research Ethic Committee approval was granted. - Summary of results There were 457 eligible children. Using a dichotomous diagnostic model (including equivocal results), sensitivity was 89.6%, specificity 91.6%, and diagnostic yield of 40.7%. ROC curve analysis of a 6mm diameter cut-off was 0.88 AUC (95% CI 0.80 to 0.95). - Discussion and conclusions Sonography is an accurate test for acute appendicitis in children, with a high sensitivity and negative predictive value. A diameter of 6mm as an absolute cut-off in a binary model can lead to false findings. Results were compared with available literature. Recent publications propose categorising diameter1 and integrating secondary signs2 to improve accuracy and provide more meaningful results to clinicians. This study will be a benchmark for future studies with multiple diagnostic categorisation.