Set Of Cut Points Research Articles

Wrist Acceleration Cut Points for Moderate-to-Vigorous Physical Activity in Youth.

This study aimed to examine the validity of wrist acceleration cut points for classifying moderate (MPA), vigorous (VPA), and moderate-to-vigorous (MVPA) physical activity. Fifty-seven children (5-12 yr) completed 15 semistructured activities. Three sets of wrist cut points (>192 mg, >250 mg, and >314 mg), previously developed using Euclidian norm minus one (ENMO192+), GENEActiv software (GENEA250+), and band-pass filter followed by Euclidian norm (BFEN314+), were evaluated against indirect calorimetry. Analyses included classification accuracy, equivalence testing, and Bland-Altman procedures. All cut points classified MPA, VPA, and MVPA with substantial accuracy (ENMO192+: κ = 0.72 [95% confidence interval = 0.72-0.73], MVPA: area under the receiver operating characteristic curve (ROC-AUC) = 0.85 [0.85-0.86]; GENEA250+: κ = 0.75 [0.74-0.76], MVPA: ROC-AUC = 0.85 [0.85-0.86]; BFEN314+: κ = 0.73 [0.72-0.74], MVPA: ROC-AUC = 0.86 [0.86-0.87]). BFEN314+ misclassified 19.7% non-MVPA epochs as MPA, whereas ENMO192+ and GENEA250+ misclassified 32.6% and 26.5% of MPA epochs as non-MVPA, respectively. Group estimates of MPA time were equivalent (P < 0.01) to indirect calorimetry for the BFEN314+ MPA cut point (mean bias = -1.5%, limits of agreement [LoA] = -57.5% to 60.6%), whereas estimates of MVPA time were equivalent (P < 0.01) to indirect calorimetry for the ENMO192+ (mean bias = -1.1%, LoA = -53.7% to 55.9%) and GENEA250+ (mean bias = 2.2%, LoA = -56.5% to 52.2%) cut points. Individual variability (LoA) was large for MPA (min: BFEN314+, -60.6% to 57.5%; max: GENEA250+, -42.0% to 104.1%), VPA (min: BFEN314+, -238.9% to 54.6%; max: ENMO192+, -244.5% to 127.4%), and MVPA (min: ENMO192+, -53.7% to 55.0%; max: BFEN314+, -83.9% to 25.3%). Wrist acceleration cut points misclassified a considerable proportion of non-MVPA and MVPA. Group-level estimates of MVPA were acceptable; however, error for individual-level prediction was larger.

Accelerometric estimates of physical activity vary unstably with data handling.

BackgroundBecause of unreliable self-report, accelerometry is increasingly used to objectively monitor physical activity (PA). However, results of accelerometric studies vary depending on the chosen cutpoints between activity intensities. Population-specific activity patterns likely affect the size of these differences. To establish their size and stability we apply three sets of cutpoints, including two calibrated to a single reference, to our accelerometric data and compare PA estimates.Methods1402 German adolescents from the GINIplus and LISAplus cohorts wore triaxial accelerometers (Actigraph GT3x) for one week (mean 6.23 days, 14.7 hours per day) at the hip. After validation of wear, we applied three sets of cutpoints for youth, including the most common standard (Freedson, 2005) and two calibrated to a single reference, (Romanzini uni- and triaxial, from Romanzini, 2014) to these data, estimating daily sedentary, light, moderate, vigorous and moderate-to-vigorous PA (MPA, VPA, MVPA). Stability of differences was assessed by comparing Romanzini’s two sets of cutpoints.ResultsRelative agreement between cutpoints was closer for activity of lower intensities (largest difference for sedentary behaviour 9%) but increased for higher intensities (largest difference for light activity 40%, MPA 102%, VPA 88%; all p<0.01). Romanzini’s uniaxial and triaxial cutpoints agreed no more closely with each other than with Freedson’s.ConclusionsEstimated PA differed significantly between different sets of cutpoints, even when those cutpoints agreed perfectly on another dataset (i.e. Romanzini’s.) This suggests that the detected differences in estimated PA depend on population-specific activity patterns, which cannot be easily corrected for: converting activity estimates from one set of cutpoints to another may require access to raw data. This limits the utility of accelerometry for comparing populations in place and time. We suggest that accelerometric research adopt a standard for data processing, and apply and present the results of this standard in addition to those from any other method.

Individual calibration of accelerometers in children and their health-related implications

ABSTRACTThis study compared children’s physical activity (PA) levels, the prevalence of children meeting current guidelines of ≥60 minutes of daily moderate to vigorous PA (MVPA), and PA-health associations using individually calibrated (IC) and empirical accelerometer cutpoints. Data from 75 (n = 32 boys) 10–12 year old children were included in this study. Clustered cardiometabolic (CM) risk, directly measured cardiorespiratory fitness (CRF), anthropometric and 7 day accelerometer data were included within analysis. PA data were classified using Froude anchored IC, Evenson et al. (Evenson, K. R., Catellier, D. J., Gill, K., Ondrak, K. S., & McMurray, R. G. (2008). Calibration of two objective measures of physical activity for children. Journal of Sports Sciences, 26(14), 1557–1565. doi:10.1080/02640410802334196) (Ev) and Mackintosh et al. (Mackintosh, K. A., Fairclough, S. J., Stratton, G., & Ridgers, N. D. (2012). A calibration protocol for population-specific accelerometer cutpoints in children. PLoS One, 7(5), e36919. doi:10.1371/journal.pone.0036919) (Mack) cutpoints. The proportion of the cohort meeting ≥60mins MVPA/day ranged from 37%-56% depending on the cutpoints used. Reported PA differed significantly across the cutpoint sets. IC LPA and MPA were predictors of CRF (LPA: standardised β = 0.32, p = 0.002, MPA: standardised β = 0.27 p = 0.013). IC MPA also predicted BMI Z-score (standardised β = −0.35, p = 0.004). Ev VPA was a predictor of BMI Z-score (standardised β = −0.33, p = 0.012). Cutpoint choice has a substantial impact on reported PA levels though no significant associations with CM risk were observed. Froude IC cutpoints represent a promising approach towards classifying children’s PA data.

Associations of Vigorous-Intensity Physical Activity with Biomarkers in Youth.

Physical activity (PA) conveys known cardiometabolic benefits to youth, but the contribution of vigorous-intensity PA (VPA) to these benefits is unknown. Therefore, we sought to determine (a) the associations between VPA and cardiometabolic biomarkers independent of moderate-intensity PA (MPA) and time sedentary and (b) the accelerometer cut point that best represents the threshold for health-promoting VPA in youth. Data from the International Children's Accelerometry Database (ICAD) were analyzed in 2015. The relationship between cardiometabolic biomarkers and four categories of VPA estimated via three sets of cut points were examined using isotemporal substitution quantile regression modeling at the 10th, 25th, 50th, 75th, and 90th percentile of the distribution of each biomarker, separately. Age, sex, accelerometer wear time, sedentary time, and MPA were controlled for while allowing substitution for light-intensity PA. Data from 11,588 youth (4-18 yr) from 11 ICAD studies (collected 1998-2009) were analyzed. Only 32 of 360 significant associations were observed. Significant, negative relationships were observed for VPA with waist circumference and insulin. Replacing light-intensity PA with VPA (corresponding to at the 25th to 90th percentiles of VPA) was associated with 0.67 (-1.33 to -0.01; P = 0.048) to 7.30 cm (-11.01 to -3.58; P < 0.001) lower waist circumference using Evenson and ICAD cut points (i.e., higher counts per minute). VPA levels were associated with 12.60 (-21.28 to -3.92; P = 0.004) to 27.03 pmol·L (-45.03 to -9.03; P = 0.003) lower insulin levels at the 75th to 90th percentiles using Evenson and ICAD cut points when substituted for light PA. Substituting light PA with VPA was inversely associated with waist circumference and insulin. However, VPA was inconsistently related to the remaining biomarkers after controlling for time sedentary and MPA.

On the cut locus of free, step two Carnot groups

In this note, we study the cut locus of the free, step two Carnot groups $\mathbb{G}_k$ with $k$ generators, equipped with their left-invariant Carnot-Carath\'eodory metric. In particular, we disprove the conjectures on the shape of the cut loci proposed in [Myasnichenko - 2002] and [Montanari, Morbidelli - 2016], by exhibiting sets of cut points $C_k \subset \mathbb{G}_k$ which, for $k \geq 4$, are strictly larger than conjectured ones. While the latter were, respectively, smooth semi-algebraic sets of codimension $\Theta(k^2)$ and semi-algebraic sets of codimension $\Theta(k)$, the sets $C_k$ are semi-algebraic and have codimension $2$, yielding the best possible lower bound valid for all $k$ on the size of the cut locus of $\mathbb{G}_k$. Furthermore, we study the relation of the cut locus with the so-called abnormal set. In the low dimensional cases, it is known that \[ \mathrm{Abn}_0(\mathbb{G}_k) = \overline{\mathrm{Cut}_0(\mathbb{G}_k)} \setminus \mathrm{Cut}_0(\mathbb{G}_k), \qquad k=2,3. \] For each $k \geq 4$, instead, we show that the cut locus always intersects the abnormal set, and there are plenty of abnormal geodesics with finite cut time. Finally, and as a straightforward consequence of our results, we derive an explicit lower bound for the small time heat kernel asymptotics at the points of $C_k$. The question whether $C_k$ coincides with the cut locus for $k\geq 4$ remains open.

Characterization of total line-cut graphs

The total line-cut graph of a graph G = (V,E), denoted by TLc(G), is the graph with point set E(G) ∪ W(G), where W(G) is the set of cutpoints of G, in which two points are adjacent if and only if they correspond to adjacent lines of G or correspond to adjacent or coadjacent cutpoints of G or one point corresponds to a line e of G and the other corresponds to a cutpoint c of G such that e is incident with c. In this paper, we offer a structural characterization of total line-cut graphs.

Application of the Rosetta Stone to understand how much MVPA preschoolers accumulate: A systematic review.

This study illustrates the utility of the Rosetta Stone equations for comparing estimates of preschool-age children's moderate-to-vigorous physical activity (MVPA) across studies utilizing different cutpoints. Systematic review. A search of online databases was conducted to identify studies that reported daily minutes of MVPA in preschoolers using the cutpoints from which Rosetta Stone equations have been developed. Mean MVPA minday-1 from each study and the transformed estimate using the Rosetta Stone equations were compared across 7 sets of cutpoints. The weighted mean was used to calculate absolute differences between the MVPA estimates of studies using the same cutpoints (e.g all studies that have used Pate cutpoint), and from all of the remaining studies using different cutpoints (e.g., all remaining studies that have not used Pate cutpoint), before and after the Rosetta Stone transformation. A total of 33 manuscripts met the eligibility criteria and reported MVPA for 12,178 preschoolers (50% girls). The mean MVPA for the total sample ranged from 21.1 (Puyau cutpoint) to 288.6 (Freedson cutpoints) minday-1. The difference between studies using the same cutpoint and estimates from remaining studies using different cutpoints was 82.4 and 80.0minday-1 for boys and girls, respectively. These differences were reduced to approximately 14minday-1 for boys and girls, after Rosetta Stone transformations. The Rosetta Stone equations substantially reduced the differences across studies that utilize different cutpoints and improved the ability to interpret findings across studies. Future equations should be developed for sedentary and total physical activity, as well as, comparisons across different devices and placements.

Childhood obesity classification systems and cardiometabolic risk factors: a comparison of the Italian, World Health Organization and International Obesity Task Force references

BackgroundBody Mass Index Italian reference data are available for clinical and/or epidemiological use, but no study compared the ability of this system to classify overweight and obesity and detect subjects with clustered cardiometabolic risk factors with international standards. Therefore our aim was to assess 1) the agreement among the Italian Society for Pediatric Endocrinology and Diabetology (ISPED), the World Health Organisation (WHO) and the International Obesity Task Force (IOTF) Body Mass Index cut-offs in estimating overweight or obesity in children and adolescents; 2) the ability of each above-mentioned set of cut-points to detect subjects with cardiometabolic risk factors.MethodsData of 6070 Italian subjects aged 5–17 years were collected. Prevalence of normal-weight, overweight and obesity was determined using three classification systems: ISPED, WHO and IOTF. High blood pressure, hypertriglyceridemia, low high density lipoprotein-cholesterol and impaired fasting glucose were considered as cardiometabolic risk factors.ResultsISPED and IOTF classified more subjects as normal-weight or overweight and less subjects as obese as compared to WHO (p <0.0001) in the whole sample and in groups divided by gender and age. The strength of agreement between the three methods compared to each other was excellent for overweight (including obesity) definition (k > 0.900), while it differed for obesity definition, ranging from the highest agreement between ISPED and IOTF (k 0.875) to the lowest between ISPED and WHO (k 0.664). WHO had the highest sensitivity, while ISPED and IOTF systems had the highest specificity, in identifying obese subjects with clustered cardiometabolic risk factors. Analogous results were found in subjects stratified by gender or age.ConclusionsISPED and IOTF systems performed similarly in assessing overweight and obesity, and were more specific in identifying obese children/adolescents with clustered cardiometabolic risk factors; on the contrary, the WHO system was more sensitive. Given the seriousness of the obesity epidemic, we wonder whether the WHO system should be preferable to the national standards for clinical practice and/or obesity screening.

Effects of Varying Epoch Lengths, Wear Time Algorithms, and Activity Cut-Points on Estimates of Child Sedentary Behavior and Physical Activity from Accelerometer Data.

ObjectiveTo examine the effects of accelerometer epoch lengths, wear time (WT) algorithms, and activity cut-points on estimates of WT, sedentary behavior (SB), and physical activity (PA).Methods268 7–11 year-olds with BMI ≥ 85th percentile for age and sex wore accelerometers on their right hips for 4–7 days. Data were processed and analyzed at epoch lengths of 1-, 5-, 10-, 15-, 30-, and 60-seconds. For each epoch length, WT minutes/day was determined using three common WT algorithms, and minutes/day and percent time spent in SB, light (LPA), moderate (MPA), and vigorous (VPA) PA were determined using five common activity cut-points. ANOVA tested differences in WT, SB, LPA, MPA, VPA, and MVPA when using the different epoch lengths, WT algorithms, and activity cut-points.ResultsWT minutes/day varied significantly by epoch length when using the NHANES WT algorithm (p < .0001), but did not vary significantly by epoch length when using the ≥ 20 minute consecutive zero or Choi WT algorithms. Minutes/day and percent time spent in SB, LPA, MPA, VPA, and MVPA varied significantly by epoch length for all sets of activity cut-points tested with all three WT algorithms (all p < .0001). Across all epoch lengths, minutes/day and percent time spent in SB, LPA, MPA, VPA, and MVPA also varied significantly across all sets of activity cut-points with all three WT algorithms (all p < .0001).ConclusionsThe common practice of converting WT algorithms and activity cut-point definitions to match different epoch lengths may introduce significant errors. Estimates of SB and PA from studies that process and analyze data using different epoch lengths, WT algorithms, and/or activity cut-points are not comparable, potentially leading to very different results, interpretations, and conclusions, misleading research and public policy.

143 Vital Signs as Predictors of Rapid Response Team Activations Within Twelve Hours of Admission From the Emergency Department

Rapid-response teams (RRTs) are interdisciplinary groups created to rapidly assess and treat patients with unexpected clinical deterioration in non-intensive care unit (ICU) beds. It has been suggested that emergency department (ED) disposition should take into consideration vital signs (VS) at the time of hospital admission. We aimed to predict which patients will have RRT activation within 12 hours of admission based on their ED VS. We conducted a case-control study of patients presenting from January 2009 to December 2013 to a tertiary ED who subsequently had RRT activation within 12 hours of admission. The records of patients 18 years and older admitted to a non-ICU setting were reviewed to obtain VS at the time of ED departure. Each of the 474 RRT activation cases was matched to a control by age, sex, and ED diagnosis. Controls presented to the ED during the same time period, were admitted, but did not have RRT activation. VS were evaluated using cut points (lowest 10%, middle 80% and highest 10%) based on the distribution of VS for all 948 patients and were compared between cases and controls using conditional logistic regression. Vital signs have a bimodal distribution, where the lowest and the highest extremes are concerning. Cutoff comparison between cases and controls is shown in Table 1. Patients with RRT activations were more likely to have a heart rate > 111 bpm (OR 2.76; CI 1.65-4.60), have a sBP 157 mmHg (OR 1.82; 1.19-2.80), have a respiratory rate >24 (OR 4.15; CI 2.44-7.07) and have an oxygen saturation <93% (OR 2.29; CI 1.43-3.67) at the time of ED departure. After matching for age, sex, and ED diagnosis, abnormal VS at the time of ED departure are predictive of RRT activation within 12 hours of admission. However, an ideal set of VS cut points to trigger a change in ED disposition remain unclear.

Equating accelerometer estimates among youth: The Rosetta Stone 2.

Different accelerometer cutpoints used by different researchers often yields vastly different estimates of moderate-to-vigorous intensity physical activity (MVPA). This is recognized as cutpoint non-equivalence (CNE), which reduces the ability to accurately compare youth MVPA across studies. The objective of this research is to develop a cutpoint conversion system that standardizes minutes of MVPA for six different sets of published cutpoints. Secondary data analysis. Data from the International Children's Accelerometer Database (ICAD; Spring 2014) consisting of 43,112 Actigraph accelerometer data files from 21 worldwide studies (children 3-18 years, 61.5% female) were used to develop prediction equations for six sets of published cutpoints. Linear and non-linear modeling, using a leave one out cross-validation technique, was employed to develop equations to convert MVPA from one set of cutpoints into another. Bland Altman plots illustrate the agreement between actual MVPA and predicted MVPA values. Across the total sample, mean MVPA ranged from 29.7MVPAmind(-1) (Puyau) to 126.1MVPAmind(-1) (Freedson 3 METs). Across conversion equations, median absolute percent error was 12.6% (range: 1.3 to 30.1) and the proportion of variance explained ranged from 66.7% to 99.8%. Mean difference for the best performing prediction equation (VC from EV) was -0.110mind(-1) (limits of agreement (LOA), -2.623 to 2.402). The mean difference for the worst performing prediction equation (FR3 from PY) was 34.76mind(-1) (LOA, -60.392 to 129.910). For six different sets of published cutpoints, the use of this equating system can assist individuals attempting to synthesize the growing body of literature on Actigraph, accelerometry-derived MVPA.

Severe Obesity and Cardiometabolic Risk in Children: Comparison from Two International Classification Systems

ObjectivesThere is no agreed-upon definition for severe obesity (Sev-OB) in children. We compared estimates of Sev-OB as defined by different cut-points of body mass index (BMI) from the Centers for Disease Control and Prevention (CDC) or the World Health Organization (WHO) curves and the ability of each set of cut-points to screen for the presence of cardiometabolic risk factors.Research Design and MethodsCross-sectional, multicenter study involving 3,340 overweight/obese young subjects. Sev-OB was defined as BMI ≥99th percentile or ≥1.2 times the 95th percentile of the CDC or the WHO curves. High blood pressure, hypertriglyceridemia, low High Density Lipoprotein -cholesterol and impaired fasting glucose were considered as cardiometabolic risk factors.ResultsThe estimated prevalence of Sev-OB varied widely between the two reference systems. Either using the cut-point ≥99th percentile or ≥1.2 times the 95th percentile, less children were defined as Sev-OB by CDC than WHO (46.8 vs. 89.5%, and 63.3 vs. 80.4%, respectively p<0.001). The CDC 99th percentile had lower sensitivity (58.5 vs 94.2), higher specificity (57.6 vs 12.3) and higher positive predictive value (34.4 vs 28.9) than WHO in identifying obese children with ≥2 cardiometabolic risk factors. These differences were mitigated using the 1.2 times the 95th percentile (sensitivity 73.9 vs. 88.1; specificity 40.7 vs. 22.5; positive predictive value 32.1 vs. 30.1). Substantial agreement between growth curves was found using the 1.2 times the 95th percentile, in particular in children ≤10 years.ConclusionsEstimates of Sev-OB and cardiometabolic risk as defined by different cut-points of BMI are influenced from the reference systems used. The 1.2 times the 95th percentile of BMI of either CDC or WHO standard has a discriminatory advantage over the 99th percentile for identifying severely obese children at increased cardiometabolic risk, particularly under 10 years of age.

Pharmacological Profile Of Cytarabine and Idarubicin In Patient Samples (ex vivo) With Newly Diagnosed Acute Myeloid Leukemia Identifies Responders Vs Non Responders

▪ Background and objectivesComplete remission (CR) after induction therapy is the first treatment goal in acute myeloid leukemia (AML) patients. The aim of this study is to determine the ability of the Vivia's novel ex vivo drug sensitivity platform Exvitech analyzing leukemic cell death to predict the CR rates after induction chemotherapy with cytarabine (Ara-C) and idarubicin (Ida) in 1st line AML. Patients and MethodsThis non-interventional and prospective study included samples from adult patients over 18 years of age diagnosed with de novo AML in Spanish centers from the PETHEMA group. Marrow samples were collected at diagnosis, sent to the Vivia laboratories, and incubated for 48 hours in whole samples in well plates containing Ara-C, Ida, or the combination Ara-C+Ida, each at 8 different concentrations to calculate dose responses. Annexin V-FITC was used to quantify the drug-induced apoptosis. Pharmacological responses are calculated using pharmacokinetic population models. Induction response was assessed according to the Cheson criteria (2003). Patients attaining a CR/CRi were classified as responders. The remaining patients were considered as resistant. Patients dying during induction response assessment were non-evaluable. The correlation was modeled using a generalized additive model with a logit link and a binomial distribution for residuals. Kernel density estimates were then used to plot empirical probability density functions for both groups. Their separation was quantified as the area under the ROC curve and a cut point was selected using the Youden's criteria to optimize the classification probabilities (sensitivity, specificity). 95% confidence intervals for sampling errors were calculated for all these quantifiers. Results125 patient samples were used to calculate the dose response curves for Ara-C alone, Ida alone, and the synergism of the Ara-C plus Ida combination. For clinical correlation we used 64 patients with a median age of 55 years (range 31 to 72). Dose responses for Ara-C alone are shown in Figure 1.A; note that for many samples there is a significant number (>20%) of resistant cells to Ara-C (bracket). This is a strong clinical predictor of resistance because in the patient the drug will never be present at these high doses for 48 h. The second variable that is a good predictor of response is the synergism between these 2 drugs. The generalized additive model identified an algebraic combination of these 2 variables that yielded the best marker to separate both groups of patients. The probability density functions had minimal overlap. The area under the corresponding ROC curve was 0.965 (0.928, 1.000), and the classification probabilities for the optimal cut point (set at 0.414 for the marker), expressed as percentages, were 85% (62.1% to 96.8%) and 86.4% (72.6% to 94.8%) for sensitivity and specificity, respectively. Results are shown in Figure 1.B; Forty-four patients (68.8%) achieved CR after Ida+Ara-C, and the remaining 20 (31.3%) were resistant. Correlations of the PM test are shown in Figure 1.B. Seventeen of the 20 (85%) patients who fail to achieve CR were predicted as resistance in the ex vivo test. Thirty-eight of the 44 patients (86.4%) who achieved CR showed good ex vivo sensitivity to Ida+Ara-C predicting for CR. When the ex vivo test predicted a patient as sensitive it was correct in 38/39 cases (93%), and when it predicted resistant it was correct 17/23 cases (74%). Overall, 45 patients (86%) had an accurate prediction of their response to treatment. [Display omitted] ConclusionsThis study shows that this novel ex vivo pharmacological profile test is able to predict the clinical response to Ida+Ara-C induction. We are increasing the number of patients in this ongoing study, and we are planning a PM Test-adapted Clinical Trial. Disclosures:Martínez:Vivia Biotech: Employment. Ortega:Vivia Biotech: Employment. Primo:Vivia Biotech: Employment. Hernandez-Campo:Vivia Biotech: Employment. Rojas:Vivia Biotech: Employment. Bennett:Vivia Biotech: Employment. Liebana:Vivia Biotech: Employment. Lopez:Vivia Biotech: Employment. Ballesteros:Vivia Biotech: Equity Ownership.

Cut points for mild, moderate, and severe pain on the VAS for children and adolescents: What can be learned from 10 million ANOVAs?

Cut points that classify pain intensity into mild, moderate, and severe levels are widely used in pain research and clinical practice. At present, there are no agreed-upon cut points for the visual analog scale (VAS) in pediatric samples. We applied a method based on Serlin and colleagues’ procedure (Serlin RC, Mendoza TR, Nakamura Y, Edwards KR, Cleeland CS. When is cancer pain mild, moderate or severe? Grading pain severity by its interference with function. PAIN® 1995;61:277–84) that was previously only used for the 0 to 10 numerical rating scale to empirically establish optimal cut points (OCs) for the VAS and used bootstrapping to estimate the variability of these thresholds. We analyzed data from the German Health Interview and Examination Survey for Children and Adolescents (KiGGS) study and defined OCs both for parental ratings of their children’s pain and adolescents’ self-ratings of pain intensity. Data from 2276 children (3 to 10years; 54% female) and 2982 adolescents (11 to 17years; 61% female) were analyzed. OCs were determined in a by-millimeter analysis that tested all possible 4851 OC combinations, and a truncated analysis were OCs were spaced 5mm apart, resulting in 171 OC combinations. The OC method identified 2 different OCs for parental ratings and self-report, both in the by-millimeter and truncated analyses. When we estimated the variability of the by-millimeter analysis, we found that the specific OCs were only found in 11% of the samples. The truncated analysis revealed, however, that cut points of 35:60 are identified as optimal in both samples and are a viable alternative to separate cut points. We found a set of cut points that can be used both parental ratings of their children’s pain and self-reports for adolescents. Adopting these cut points greatly enhances the comparability of trials. We call for more systematic assessment of diagnostic procedures in pain research.

The effect of reintegrating Actigraph accelerometer counts in preschool children: Comparison using different epoch lengths

ObjectivesThe purpose of this study was to determine whether ActiGraph accelerometer activity counts and estimates of moderate-to-vigorous physical activity collected at a single larger epoch are comparable to those collected at smaller epochs reintegrated into a larger epoch. DesignA cross-sectional study design. MethodsThirty-one preschoolers (3–5years) concurrently wore four accelerometers that were each initialized at four different epoch lengths (1s, 15s, 30s, and 60s) during a full preschool day. Counts collected at 1s, 15s, and 30s epoch were each reintegrated and compared to those collected at a larger epoch (e.g., counts from one 15s epoch vs. consecutive sum of counts from fifteen 1s epochs). Six sets of cut-points (Pate, Freedson, Sirard, Van Cauwenberghe, Evenson and Puyau) were applied to estimate moderate-to-vigorous physical activity minutes. Paired t-test and Cohen's d were used to compare group mean differences. Absolute percent errors Bland–Altman plots with limits of agreement were used to compare individual differences. ResultsMinimal group mean differences were found for counts and moderate-to-vigorous physical activity estimates between larger and reintegrated epochs. Relatively smaller absolute percent errors (6.2–9.2%) and limits of agreements (−15.52%, 18.00% to −28.27%, 28.02%) were observed for counts than absolute percent errors (10.1–50.3%) and limits of agreements (−27.3%, 33.3% to −156.9%, 137.9%) for moderate-to-vigorous physical activity estimates. ConclusionsSmaller individual differences in activity counts tended to yield larger individual variations in moderate-to-vigorous physical activity estimates, despite minimal group mean differences. Therefore, researchers reintegrating smaller epochs into a larger epoch should be conscious of possible differences in moderate-to-vigorous physical activity estimates obtained from a single larger epoch.

Revision of sediment quality triad indicators in Puget Sound (Washington, USA): I. a Sediment Chemistry Index and targets for mixtures of toxicants

The Washington State Department of Ecology annually conducts sediment quality monitoring in Puget Sound as a component of the Puget Sound Ecosystem Monitoring Program. Sediment samples are analyzed to determine the concentrations of about 170 chemical and physical variables. A Sediment Chemistry Index (SCI) was derived using the State of Washington Sediment Management Standards to account for the presence and concentrations of mixtures of toxicants. Mean Sediment Quality Standard quotients (mSQSq) were calculated as the basis for the SCI and compared to the incidence and degree of toxicity in laboratory tests and to metrics of the diversity and abundance of resident benthic assemblages in a database consisting of as many as 664 samples. These data were evaluated with co-occurrence analyses to identify "cut points" (i.e., thresholds) in the index below which the frequency and magnitude of biological effects were relatively low and above which they occurred with increasing frequency or magnitude. Iterative trials of different sets of cut points established the final cut points in mSQSq of 0.1, 0.3, and 0.5. They defined 4 ranges in chemical exposure: Minimum (<0.1), Low (0.1- < 0.3), Moderate (0.3- < 0.5), and Maximum (≥0.5). Across these 4 exposure ranges both the incidence and magnitude of toxicity in some laboratory tests increased, the abundance of most stress-sensitive benthic taxa decreased, and the abundance of most stress-tolerant taxa increased. The mSQSq cut point of 0.1 appears to be the target value for protection of benthic resources, the value below which the probability and magnitude of adverse effects either in the laboratory or the field are the lowest. The mSQSq values are rescaled from 0 to 100 to form the SCI, used by the Puget Sound Partnership and environmental managers as a Dashboard Indicator, with biologically relevant targets selected to monitor ecosystem recovery.

Covariance Decompositions for Accurate Computation in Bayesian Scale-Usage Models

Analyses of multivariate ordinal probit models typically use data augmentation to link the observed (discrete) data to latent (continuous) data via a censoring mechanism defined by a collection of “cutpoints.” Most standard models, for which effective Markov chain Monte Carlo (MCMC) sampling algorithms have been developed, use a separate (and independent) set of cutpoints for each element of the multivariate response. Motivated by the analysis of ratings data, we describe a particular class of multivariate ordinal probit models where it is desirable to use a common set of cutpoints. While this approach is attractive from a data-analytic perspective, we show that the existing efficient MCMC algorithms can no longer be accurately applied. Moreover, we show that attempts to implement these algorithms by numerically approximating required multivariate normal integrals over high-dimensional rectangular regions can result in severely degraded estimates of the posterior distribution. We propose a new data augmentation that is based on a covariance decomposition and that admits a simple and accurate MCMC algorithm. Our data augmentation requires only that univariate normal integrals be evaluated, which can be done quickly and with high accuracy. We provide theoretical results that suggest optimal decompositions within this class of data augmentations, and, based on the theory, recommend default decompositions that we demonstrate work well in practice. This article has supplementary material online.

Uso del ácido sulfosalicílico para la detección de proteinuria y su aplicación a problemas de hipertensión en el embarazo

Objetivo: determinar la confiabilidad de la prueba del ácido sulfosalicílico en la detección rápida y semicuantificación de la proteinuria. Métodos: estudio descriptivo, prospectivo llevado a cabo en el Hospital Universitario San Vicente de Paúl, Medellín, Colombia. Se incluyeron 98 mujeres gestantes con proteinuria y 129 sin proteinuria. La prueba de turbidez con ácido sulfosalicílico se comparó con la medición de proteinuria en 24 horas. Resultados: los coeficientes de probabilidad (likelihood ratio) para los resultados de la prueba fueron los siguientes: 1+ = 0,4; 2+: = 0,7; 3+ = 3,4; 4+ = 6,7 y 5+ = 39,1. La correlación entre los tres evaluadores de la turbidez fue 0,966. Con un punto de corte de 4+ la sensibilidad fue 41,1% (IC 95%: 30,6- 51,5), la especificidad fue 97,7% (IC 95%: 94,7-100). Cuando la prueba se aplicó solamente a las pacientes hipertensas el valor predictivo positivo fue 95% (IC 95%: 87-100) y el valor predictivo negativo fue 53,3% (IC 95%: 42,5-64). Conclusiones: la prueba de turbidez con ácido sulfosalicílico es fácil, rápida, económica y reproducible. Por su baja sensibilidad no es útil como método de tamización pero por su alta especificidad es ideal para la confirmación rápida de proteinuria en las gestantes hipertensas.

Correlation maximisation-based discretisation for supervised classification

This paper proposes a novel supervised discretisation algorithm based on Correlation Maximisation (CM) using Multiple Correspondence Analysis (MCA). MCA is an effective technique to capture the correlation between multiple variables. For each numeric feature, the proposed discretisation algorithm utilises MCA to measure the correlations between feature intervals/items and classes, and the set of cut-points yielding the maximum correlation is chosen as the discretisation scheme for that feature. Therefore, the discretised feature can not only produce a concise summarisation of the original numeric feature but also provide the maximum correlation information to predict class labels. Experiments are conducted by comparing to seven state-of-the-art supervised discretisation algorithms using six well-known classifiers on 19 UCI data sets. Experimental results demonstrate that the proposed discretisation algorithm can automatically generate a set of features (feature intervals) that produce the best classification results on average.

The cactus tree of a metric space

Finite cuts have been studied in several different contexts. Whyburn [26] in 1928 showed that the set of cut points of a Peano continuum has the structure of a “dendrite”. This “dendritic” decomposition of continua has been extended and used to prove several results in continua theory. We recall here that a continuum is a compact, connected Hausdorff space and a Peano continuum is a locally connected metric continuum. If X is a continuum, we say that a point c is a cut point of X if X fcg is not connected. Whyburn’s work was extended by others and the more abstract framework of pretrees proposed by Ward [25] has proved adequate for studying cuts; see Bowditch [6], Adeleke and Neumann [2] and our paper [18].