Handbook on thermophysical properties of oxygen

Handbook has been compiled by Cryogenic Data Center of National Bureau of Standards. It covers thermodynamic functions, physical properties, and heat transfer data for oxygen. Handbook addresses primarily low temperature regime, but also includes some data above room temperature

Lower use of carotid artery imaging at minority-serving hospitals

Objective: We determined whether site of care explains a previously identified racial disparity in carotid artery imaging. Methods: In this retrospective cohort study, data were obtained from a chart review of veterans hospitalized with ischemic stroke at 127 Veterans Administration hospitals in 2007. Extensive exclusion criteria were applied to obtain a sample who should have received carotid artery imaging. Minority-serving hospitals were defined as the top 10% of hospitals ranked by the proportion of stroke patients who were black. Population level multivariate logistic regression models with adjustment for correlation of patients in hospitals were used to calculate predictive probabilities of carotid artery imaging by race and minority-service hospital status. Bootstrapping was used to obtain 95% confidence intervals (CIs). Results: The sample consisted of 1,534 white patients and 628 black patients. Nearly 40% of all black patients were admitted to 1 of 13 minority-serving hospitals. No racial disparity in receipt of carotid artery imaging was detected within nonminority serving hospitals. However, the predicted probability of receiving carotid artery imaging for white patients at nonminority-serving hospitals (89.7%, 95% CI [87.3%, 92.1%]) was significantly higher than both white patients (78.0% [68.3%, 87.8%] and black patients (70.5% [59.3%, 81.6%]) at minority-serving hospitals. Conclusions: Underuse of carotid artery imaging occurred most often among patients hospitalized at minority-serving hospitals. Further work is required to explore why site of care is a mechanism for racial disparities in this clinically important diagnostic test

Correlation of inpatient and outpatient measures of stroke care quality within veterans health administration hospitals

Background and Purpose—Quality of care delivered in the inpatient and ambulatory settings may be correlated within an integrated health system such as the Veterans Health Administration. We examined the correlation between stroke care quality at hospital discharge and within 6 months postdischarge. Methods—We conducted a cross-sectional hospital-level correlation analyses of chart-abstracted data for 3467 veterans discharged alive after an acute ischemic stroke from 108 Veterans Health Administration medical centers and 2380 veterans with postdischarge follow-up within 6 months in fiscal year 2007. Four risk-standardized processes of care represented discharge care quality: prescription of antithrombotic and antilipidmic therapy, anticoagulation for atrial fibrillation, and tobacco cessation counseling along with a composite measure of defect-free care. Five risk-standardized intermediate outcomes represented postdischarge care quality: achievement of blood pressure, low-density lipoprotein, international normalized ratio, and glycosylated hemoglobin target levels, and delivery of appropriate treatment for poststroke depression along with a composite measure of achieved outcomes. Results—Median risk-standardized composite rate of defect-free care at discharge was 79%. Median risk-standardized postdischarge rates of achieving goal were 56% for blood pressure, 36% for low-density lipoprotein, 41% for international normalized ratio, 40% for glycosylated hemoglobin, and 39% for depression management and the median risk-standardized composite 6-month outcome rate was 44%. The hospital composite rate of defect-free care at discharge was correlated with meeting the low-density lipoprotein goal (r=0.31; P=0.007) and depression management (r=0.27; P=0.03) goal but was not correlated with blood pressure, international normalized ratio, glycosylated hemoglobin goals, nor with the composite measure of achieved postdischarge outcomes (probability values >0.13). Conclusions—Hospital discharge care quality was not consistently correlated with ambulatory care quality

The Role of Native Language and the Fundamental Design of the Auditory System in Detecting Rhythm Changes

Accepted December 13, 2018Purpose: We investigated whether rhythm discrimination is mainly driven by the native language of the listener or by the fundamental design of the human auditory system and universal cognitive mechanisms shared by all people irrespective of rhythmic patterns in their native language. Method: In multiple experiments, we asked participants to listen to 2 continuous acoustic sequences and to determine whether their rhythms were the same or different (AX discrimination). Participants were native speakers of 4 languages with different rhythmic properties (Spanish, French, English, and German) to understand whether the predominant rhythmic patterns of a native language affect sensitivity, bias, and reaction time in detecting rhythmic changes in linguistic (Experiment 2) and in nonlinguistic (Experiments 1 and 2) acoustic sequences. We examined sensitivity and bias measures, as well as reaction times. We also computed Bayes factors in order to assess the effect of native language. Results: All listeners performed better (i.e., responded faster and manifested higher sensitivity and accuracy) when detecting the presence or absence of a rhythm change when the 1st stimulus in an AX test pair exhibited regular rhythm (i.e., a syllable-timed rhythmic pattern) than when the 1st stimulus exhibited irregular rhythm (i.e., stress-timed rhythmic pattern). This result pattern was observed both on linguistic and nonlinguistic stimuli and was not modulated by the native language of the participant. Conclusion: We conclude that rhythm change detection is a fundamental function of a processing system that relies on general auditory mechanisms and is not modulated by linguistic experience.The authors acknowledge support from Spanish Ministry of Economy and Competitiveness Grant PSI2017-82563-P (awarded to A. G. S.), the “Severo Ochoa” Programme for Centres/Units of Excellence in R&D Grant SEV-2015-490 (BCBL), and the Basque Foundation for Science Grant IKERBASQUE (awarded to A. G. S. and M. O.). D. M. G. was supported by Grant PIA/Basal FB0003 from the Chilean Research Council. L. P. was supported by the Spanish Ministry of Economy and Competitiveness via Juan de la Cierva fellowship

Does Inclusion of Stroke Severity in a 30-day Mortality Model Change Standardized Mortality Rates at VA Hospitals?

Background—The Centers for Medicare and Medicaid Services is considering developing a 30-day ischemic stroke hospital-level mortality model using administrative data. We examined whether inclusion of the National Institutes of Health Stroke Scale (NIHSS), a measure of stroke severity not included in administrative data, would alter 30-day mortality rates in the Veterans Health Administration. Methods and Results—A total of 2562 veterans admitted with ischemic stroke to 64 Veterans Health Administration Hospitals in the fiscal year 2007 were included. First, we examined the distribution of unadjusted mortality rates across the Veterans Health Administration. Second, we estimated 30-day all-cause, risk standardized mortality rates (RSMRs) for each hospital by adjusting for age, sex, and comorbid conditions using hierarchical models with and without the inclusion of the NIHSS. Finally, we examined whether adjustment for the NIHSS significantly changed RSMRs for each hospital compared with other hospitals. The median unadjusted mortality rate was 3.6%. The RSMR interquartile range without the NIHSS ranged from 5.1% to 5.6%. Adjustment with the NIHSS did not change the RSMR interquartile range (5.1%–5.6%). Among veterans ≥65 years, the RSMR interquartile range without the NIHSS ranged from 9.2% to 10.3%. With adjustment for the NIHSS, the RSMR interquartile range changed from 9.4% to 10.0%. The plot of 30-day RSMRs estimated with and without the inclusion of the NIHSS in the model demonstrated overlapping 95% confidence intervals across all hospitals, with no hospital significantly below or above the mean-unadjusted 30-day mortality rate. The 30-day mortality measure did not discriminate well among hospitals. Conclusions—The impact of the NIHSS on RSMRs was limited. The small number of stroke admissions and the narrow range of 30-day stroke mortality rates at the facility level in the Veterans Health Administration cast doubt on the value of using 30-day RSMRs as a means of identifying outlier hospitals based on their stroke care quality

Inpatient stroke care quality for Veterans: Are there differences between VA medical centers in the stroke belt and other areas?

Background Stroke mortality has been found to be much higher among residents in the stroke belt region than in the rest of United States, but it is not known whether differences exist in the quality of stroke care provided in Department of Veterans Affairs medical centers in states inside and outside this region. Objective We compared mortality and inpatient stroke care quality between Veterans Affairs medical centers inside and outside the stroke belt region. Methods Study patients were veterans hospitalized for ischemic stroke at 129 Veterans Affairs medical centers. Inpatient stroke care quality was assessed by 14 quality indicators. Multivariable logistic regression models were fit to examine differences in quality between facilities inside and outside the stroke belt, adjusting for patient characteristics and Veterans Affairs medical centers clustering effect. Results Among the 3909 patients, 28·1% received inpatient ischemic stroke care in 28 stroke belt Veterans Affairs medical centers, and 71·9% obtained care in 101 non-stroke belt Veterans Affairs medical centers. Patients cared for in stroke belt Veterans Affairs medical centers were more likely to be younger, Black, married, have a higher stroke severity, and less likely to be ambulatory pre-stroke. We found no statistically significant differences in short- and long-term post-admission mortality and inpatient care quality indicators between the patients cared for in stroke belt and non-stroke belt Veterans Affairs medical centers after risk adjustment. Conclusions These data suggest that a stroke belt does not exist within the Veterans Affairs health care system in terms of either post-admission mortality or inpatient care quality

Estimating and Reporting on the Quality of Inpatient Stroke Care by Veterans Health Administration Medical Centers

Background—Reporting of quality indicators (QIs) in Veterans Health Administration Medical Centers is complicated by estimation error caused by small numbers of eligible patients per facility. We applied multilevel modeling and empirical Bayes (EB) estimation in addressing this issue in performance reporting of stroke care quality in the Medical Centers. Methods and Results—We studied a retrospective cohort of 3812 veterans admitted to 106 Medical Centers with ischemic stroke during fiscal year 2007. The median number of study patients per facility was 34 (range, 12–105). Inpatient stroke care quality was measured with 13 evidence-based QIs. Eligible patients could either pass or fail each indicator. Multilevel modeling of a patient's pass/fail on individual QIs was used to produce facility-level EB-estimated QI pass rates and confidence intervals. The EB estimation reduced interfacility variation in QI rates. Small facilities and those with exceptionally high or low rates were most affected. We recommended 8 of the 13 QIs for performance reporting: dysphagia screening, National Institutes of Health Stroke Scale documentation, early ambulation, fall risk assessment, pressure ulcer risk assessment, Functional Independence Measure documentation, lipid management, and deep vein thrombosis prophylaxis. These QIs displayed sufficient variation across facilities, had room for improvement, and identified sites with performance that was significantly above or below the population average. The remaining 5 QIs were not recommended because of too few eligible patients or high pass rates with little variation. Conclusions—Considerations of statistical uncertainty should inform the choice of QIs and their application to performance reporting