Development and validation of a novel pedometer algorithm to quantify extended characteristics of the locomotor behavior of dairy cows

Behavior is one of the most important indicators for assessing cattle health and well-being. The objective of this study was to develop and validate a novel algorithm to monitor locomotor behavior of loose-housed dairy cows based on the output of the RumiWatch pedometer (ITIN+HOCH GmbH, Fütterungstechnik, Liestal, Switzerland). Data of locomotion were acquired by simultaneous pedometer measurements at a sampling rate of 10 Hz and video recordings for manual observation later. The study consisted of 3 independent experiments. Experiment 1 was carried out to develop and validate the algorithm for lying behavior, experiment 2 for walking and standing behavior, and experiment 3 for stride duration and stride length. The final version was validated, using the raw data, collected from cows not included in the development of the algorithm. Spearman correlation coefficients were calculated between accelerometer variables and respective data derived from the video recordings (gold standard). Dichotomous data were expressed as the proportion of correctly detected events, and the overall difference for continuous data was expressed as the relative measurement error. The proportions for correctly detected events or bouts were 1 for stand ups, lie downs, standing bouts, and lying bouts and 0.99 for walking bouts. The relative measurement error and Spearman correlation coefficient for lying time were 0.09% and 1; for standing time, 4.7% and 0.96; for walking time, 17.12% and 0.96; for number of strides, 6.23% and 0.98; for stride duration, 6.65% and 0.75; and for stride length, 11.92% and 0.81, respectively. The strong to very high correlations of the variables between visual observation and converted pedometer data indicate that the novel RumiWatch algorithm may markedly improve automated livestock management systems for efficient health monitoring of dairy cows.

VOR gain by head impulse video-oculography differentiates acute vestibular neuritis from stroke

OBJECTIVE Vestibular neuritis is often mimicked by stroke (pseudoneuritis). Vestibular eye movements help discriminate the two conditions. We report vestibulo-ocular reflex (VOR) gain measures in neuritis and stroke presenting acute vestibular syndrome (AVS). METHODS Prospective cross-sectional study of AVS (acute continuous vertigo/dizziness lasting >24 h) at two academic centers. We measured horizontal head impulse test (HIT) VOR gains in 26 AVS patients using a video HIT device (ICS Impulse). All patients were assessed within 1 week of symptom onset. Diagnoses were confirmed by clinical examinations, brain magnetic resonance imaging with diffusion-weighted images, and follow-up. Brainstem and cerebellar strokes were classified by vascular territory-posterior inferior cerebellar artery (PICA) or anterior inferior cerebellar artery (AICA). RESULTS Diagnoses were vestibular neuritis (n = 16) and posterior fossa stroke (PICA, n = 7; AICA, n = 3). Mean HIT VOR gains (ipsilesional [standard error of the mean], contralesional [standard error of the mean]) were as follows: vestibular neuritis (0.52 [0.04], 0.87 [0.04]); PICA stroke (0.94 [0.04], 0.93 [0.04]); AICA stroke (0.84 [0.10], 0.74 [0.10]). VOR gains were asymmetric in neuritis (unilateral vestibulopathy) and symmetric in PICA stroke (bilaterally normal VOR), whereas gains in AICA stroke were heterogeneous (asymmetric, bilaterally low, or normal). In vestibular neuritis, borderline gains ranged from 0.62 to 0.73. Twenty patients (12 neuritis, six PICA strokes, two AICA strokes) had at least five interpretable HIT trials (for both ears), allowing an appropriate classification based on mean VOR gains per ear. Classifying AVS patients with bilateral VOR mean gains of 0.70 or more as suspected strokes yielded a total diagnostic accuracy of 90%, with stroke sensitivity of 88% and specificity of 92%. CONCLUSION Video HIT VOR gains differ between peripheral and central causes of AVS. PICA strokes were readily separated from neuritis using gain measures, but AICA strokes were at risk of being misclassified based on VOR gain alone.

Multiple imputation for missing continuous and dichotomous data: The effects of patterns of missingness and variable correlations on type I error with small samples

The purpose of this study is to investigate the effects of predictor variable correlations and patterns of missingness with dichotomous and/or continuous data in small samples when missing data is multiply imputed. Missing data of predictor variables is multiply imputed under three different multivariate models: the multivariate normal model for continuous data, the multinomial model for dichotomous data and the general location model for mixed dichotomous and continuous data. Subsequent to the multiple imputation process, Type I error rates of the regression coefficients obtained with logistic regression analysis are estimated under various conditions of correlation structure, sample size, type of data and patterns of missing data. The distributional properties of average mean, variance and correlations among the predictor variables are assessed after the multiple imputation process. ^ For continuous predictor data under the multivariate normal model, Type I error rates are generally within the nominal values with samples of size n = 100. Smaller samples of size n = 50 resulted in more conservative estimates (i.e., lower than the nominal value). Correlation and variance estimates of the original data are retained after multiple imputation with less than 50% missing continuous predictor data. For dichotomous predictor data under the multinomial model, Type I error rates are generally conservative, which in part is due to the sparseness of the data. The correlation structure for the predictor variables is not well retained on multiply-imputed data from small samples with more than 50% missing data with this model. For mixed continuous and dichotomous predictor data, the results are similar to those found under the multivariate normal model for continuous data and under the multinomial model for dichotomous data. With all data types, a fully-observed variable included with variables subject to missingness in the multiple imputation process and subsequent statistical analysis provided liberal (larger than nominal values) Type I error rates under a specific pattern of missing data. It is suggested that future studies focus on the effects of multiple imputation in multivariate settings with more realistic data characteristics and a variety of multivariate analyses, assessing both Type I error and power. ^

Optimal Test for Parameter Instability When the Unstable Process and the Error Distribution are Unknown

This paper proposes asymptotically optimal tests for unstable parameter process under the feasible circumstance that the researcher has little information about the unstable parameter process and the error distribution, and suggests conditions under which the knowledge of those processes does not provide asymptotic power gains. I first derive a test under known error distribution, which is asymptotically equivalent to LR tests for correctly identified unstable parameter processes under suitable conditions. The conditions are weak enough to cover a wide range of unstable processes such as various types of structural breaks and time varying parameter processes. The test is then extended to semiparametric models in which the underlying distribution in unknown but treated as unknown infinite dimensional nuisance parameter. The semiparametric test is adaptive in the sense that its asymptotic power function is equivalent to the power envelope under known error distribution.

Second, do less harm: The state of states' medical error reporting programs

Statement of the problem and public health significance. Hospitals were designed to be a safe haven and respite from disease and illness. However, a large body of evidence points to preventable errors in hospitals as the eighth leading cause of death among Americans. Twelve percent of Americans, or over 33.8 million people, are hospitalized each year. This population represents a significant portion of at risk citizens exposed to hospital medical errors. Since the number of annual deaths due to hospital medical errors is estimated to exceed 44,000, the magnitude of this tragedy makes it a significant public health problem. ^ Specific aims. The specific aims of this study were threefold. First, this study aimed to analyze the state of the states' mandatory hospital medical error reporting six years after the release of the influential IOM report, "To Err is Human." The second aim was to identify barriers to reporting of medical errors by hospital personnel. The third aim was to identify hospital safety measures implemented to reduce medical errors and enhance patient safety. ^ Methods. A descriptive, longitudinal, retrospective design was used to address the first stated objective. The study data came from the twenty-one states with mandatory hospital reporting programs which report aggregate hospital error data that is accessible to the public by way of states' websites. The data analysis included calculations of expected number of medical errors for each state according to IOM rates. Where possible, a comparison was made between state reported data and the calculated IOM expected number of errors. A literature review was performed to achieve the second study aim, identifying barriers to reporting medical errors. The final aim was accomplished by telephone interviews of principal patient safety/quality officers from five Texas hospitals with more than 700 beds. ^ Results. The state medical error data suggests vast underreporting of hospital medical errors to the states. The telephone interviews suggest that hospitals are working at reducing medical errors and creating safer environments for patients. The literature review suggests the underreporting of medical errors at the state level stems from underreporting of errors at the delivery level. ^

Nursing-related medication errors: A review of factors that facilitate and hinder error reporting, and recommendations for improvement

Medication errors, one of the most frequent types of medical errors, are a common cause of patient harm in hospital systems today. Nurses at the bedside are in a position to encounter many of these errors since they are there at the start of the process (ordering/prescribing) and the end of the process (administration). One of the recommendations from the IOM (Institute of Medicine) report, "To Err is Human," was for organizations to identify and learn from medical errors through event reporting systems. While many organizations have reporting systems in place, research studies report a significant amount of underreporting by nurses. A systematic review of the literature was performed to identify contributing factors related to the reporting and not reporting of medication errors by nurses at the bedside.^ Articles included in the literature review were primary or secondary studies, dated January 1, 2000 – July 2009, related to nursing medication error reporting. All 634 articles were reviewed with an algorithm developed to standardize the review process and help filter out those that did not meet the study criteria. In addition, 142 article bibliographies were reviewed to find additional studies that were not found in the original literature search.^ After reviewing the 634 articles and the additional 108 articles discovered in the bibliography review, 41 articles met the study criteria and were used in the systematic literature review results.^ Fear of punitive reactions to medication errors was a frequent barrier to error reporting. Nurses fear reactions from their leadership, peers, patients and their families, nursing boards, and the media. Anonymous reporting systems and departments/organizations with a strong safety culture in place helped to encourage the reporting of medication errors by nursing staff.^ Many of the studies included in this literature review do not allow results that can be generalized. The majority of them took place in single institutions/organizations with limited sample sizes. Stronger studies with larger sample sizes need to be performed, utilizing data collection methods that have been validated, to determine stronger correlations between safety cultures and nurse error reporting.^

Information bias and lifetime mortality risks of radiation-induced cancer

Additive and multiplicative models of relative risk were used to measure the effect of cancer misclassification and DS86 random errors on lifetime risk projections in the Life Span Study (LSS) of Hiroshima and Nagasaki atomic bomb survivors. The true number of cancer deaths in each stratum of the cancer mortality cross-classification was estimated using sufficient statistics from the EM algorithm. Average survivor doses in the strata were corrected for DS86 random error ($\sigma$ = 0.45) by use of reduction factors. Poisson regression was used to model the corrected and uncorrected mortality rates with covariates for age at-time-of-bombing, age at-time-of-death and gender. Excess risks were in good agreement with risks in RERF Report 11 (Part 2) and the BEIR-V report. Bias due to DS86 random error typically ranged from $-$15% to $-$30% for both sexes, and all sites and models. The total bias, including diagnostic misclassification, of excess risk of nonleukemia for exposure to 1 Sv from age 18 to 65 under the non-constant relative projection model was $-$37.1% for males and $-$23.3% for females. Total excess risks of leukemia under the relative projection model were biased $-$27.1% for males and $-$43.4% for females. Thus, nonleukemia risks for 1 Sv from ages 18 to 85 (DRREF = 2) increased from 1.91%/Sv to 2.68%/Sv among males and from 3.23%/Sv to 4.02%/Sv among females. Leukemia excess risks increased from 0.87%/Sv to 1.10%/Sv among males and from 0.73%/Sv to 1.04%/Sv among females. Bias was dependent on the gender, site, correction method, exposure profile and projection model considered. Future studies that use LSS data for U.S. nuclear workers may be downwardly biased if lifetime risk projections are not adjusted for random and systematic errors. (Supported by U.S. NRC Grant NRC-04-091-02.) ^

Slope estimation in a parametric measurement error model: A simulation study

In regression analysis, covariate measurement error occurs in many applications. The error-prone covariates are often referred to as latent variables. In this proposed study, we extended the study of Chan et al. (2008) on recovering latent slope in a simple regression model to that in a multiple regression model. We presented an approach that applied the Monte Carlo method in the Bayesian framework to the parametric regression model with the measurement error in an explanatory variable. The proposed estimator applied the conditional expectation of latent slope given the observed outcome and surrogate variables in the multiple regression models. A simulation study was presented showing that the method produces estimator that is efficient in the multiple regression model, especially when the measurement error variance of surrogate variable is large.^

Zircons, isotope ratios and element analyses from tonalite and oxide gabbro of the mid-ocean ridge from ODP Hole 176-735B

A limiting factor in the accuracy and precision of U/Pb zircon dates is accurate correction for initial disequilibrium in the 238U and 235U decay chains. The longest-lived-and therefore most abundant-intermediate daughter product in the 235U isotopic decay chain is 231Pa (T1/2 = 32.71 ka), and the partitioning behavior of Pa in zircon is not well constrained. Here we report high-precision thermal ionization mass spectrometry (TIMS) U-Pb zircon data from two samples from Ocean Drilling Program (ODP) Hole 735B, which show evidence for incorporation of excess 231Pa during zircon crystallization. The most precise analyses from the two samples have consistent Th-corrected 206Pb/238U dates with weighted means of 11.9325 ± 0.0039 Ma (n = 9) and 11.920 ± 0.011 Ma (n = 4), but distinctly older 207Pb/235U dates that vary from 12.330 ± 0.048 Ma to 12.140 ± 0.044 Ma and 12.03 ± 0.24 to 12.40 ± 0.27 Ma, respectively. If the excess 207Pb is due to variable initial excess 231Pa, calculated initial (231Pa)/(235U) activity ratios for the two samples range from 5.6 ± 1.0 to 9.6 ± 1.1 and 3.5 ± 5.2 to 11.4 ± 5.8. The data from the more precisely dated sample yields estimated DPazircon/DUzircon from 2.2-3.8 and 5.6-9.6, assuming (231Pa)/(235U) of the melt equal to the global average of recently erupted mid-ocean ridge basaltic glasses or secular equilibrium, respectively. High precision ID-TIMS analyses from nine additional samples from Hole 735B and nearby Hole 1105A suggest similar partitioning. The lower range of DPazircon/DUzircon is consistent with ion microprobe measurements of 231Pa in zircons from Holocene and Pleistocene rhyolitic eruptions (Schmitt (2007; doi:10.2138/am.2007.2449) and Schmitt (2011; doi:10.1146/annurev-earth-040610-133330)). The data suggest that 231Pa is preferentially incorporated during zircon crystallization over a range of magmatic compositions, and excess initial 231Pa may be more common in zircons than acknowledged. The degree of initial disequilibrium in the 235U decay chain suggested by the data from this study, and other recent high precision datasets, leads to resolvable discordance in high precision dates of Cenozoic to Mesozoic zircons. Minor discordance in zircons of this age may therefore reflect initial excess 231Pa and does not require either inheritance or Pb loss.

Chronology for the EDML ice core from Dronning Maud Land, Antarctica, over the last 150 000 years

A chronology called EDML1 has been developed for the EPICA ice core from Dronning Maud Land (EDML). EDML1 is closely interlinked with EDC3, the new chronology for the EPICA ice core from Dome-C (EDC) through a stratigraphic match between EDML and EDC that consists of 322 volcanic match points over the last 128 ka. The EDC3 chronology comprises a glaciological model at EDC, which is constrained and later selectively tuned using primary dating information from EDC as well as from EDML, the latter being transferred using the tight stratigraphic link between the two cores. Finally, EDML1 was built by exporting EDC3 to EDML. For ages younger than 41 ka BP the new synchronized time scale EDML1/EDC3 is based on dated volcanic events and on a match to the Greenlandic ice core chronology GICC05 via 10Be and methane. The internal consistency between EDML1 and EDC3 is estimated to be typically ~6 years and always less than 450 years over the last 128 ka (always less than 130 years over the last 60 ka), which reflects an unprecedented synchrony of time scales. EDML1 ends at 150 ka BP (2417 m depth) because the match between EDML and EDC becomes ambiguous further down. This hints at a complex ice flow history for the deepest 350 m of the EDML ice core.