Recovery from kidney failure associated with chronic thromboembolic pulmonary hypertension following pulmonary thomboendarterectomy.

The occurrence of renal failure in pulmonary hypertension (PH) is an ominous sign and implies excessive adverse hemodynamic factors. Pharmacologic agents to treat the PH are the mainstay of management, whereas diuretics assist in management of fluid overload. However, when such measures fail, dialysis and ultrafiltration (UF) become necessary to manage progressive azotemia and hypervolemia. Reversal of PH is essential to interrupt this vicious cycle of multisystem failure; otherwise, the need for renal replacement therapy would be permanent.

Improving Dry Matter Intake Estimates Using Precision Body Weight on Cattle Grazed on Extensive Rangelands.

An essential component required for calculating stocking rates for livestock grazing extensive rangeland is dry matter intake (DMI). Animal unit months are used to simplify this calculation for rangeland systems to determine the rate of forage consumption and the cattle grazing duration. However, there is an opportunity to leverage precision technology deployed on rangeland systems to account for the individual animal variation of DMI and subsequent impacts on herd-level decisions regarding stocking rate. Therefore, the objectives of this study were, first, to build a precision system model (PSM) to predict total DMI (kg) and required pasture area (ha) using precision body weight (BW), and second, to evaluate differences in PSM-predicted stocking rates compared to the traditional herd-level method using initial or estimated mid-season BW. A deterministic model was constructed in both Vensim (version 10.1.2) and Program R (version 4.2.3) to incorporate individual precision BW data into a commonly used rangeland equation using %BW to estimate individual DMI, daily herd DMI, and area (ha) required to meet animal DMI requirements throughout specific grazing periods. Using the PSM, differences in outputs were evaluated using three scenarios: (1) initial BW (business as usual); (2) average mid-season BW; and (3) individual precision BW using data from two precision rangeland experiments conducted at the South Dakota State University Cottonwood Field Station. The data from the two experiments were used to develop PSM case studies. The trial data were collected using precision weight data (SmartScale™) collected from replacement heifers (Case study 1, n = 60) and steers (Case study 2, n = 254) grazing native rangeland. In Case study 1 (heifers), Scenario 1 versus Scenario 3 resulted in an additional 73.41 ha required. Results from Case study 2 indicated an average additional 4.4 ha required per pasture when comparing Scenario 3 versus Scenario 1. Sensitivity analyses resulted in a difference between maximum and minimum simulated values of 27,995 and 4265 kg forage consumed, and 122 and 8.9 pasture ha required for Case studies 1 and 2, respectively. Thus, results from the scenarios indicate an opportunity to identify both under- and over-stocking situations using precision DMI estimates, which helps to identify high-leverage precision tools that have practical applications for enhancing animal and plant productivity and environmental sustainability on extensive rangelands.

Clinical variability and novel neurodevelopmental findings in 49, XXXXY syndrome.

49, XXXXY is a rare chromosomal syndrome due to double nondisjunction of the replicating X chromosome. Considered a severe variant of XXY or Klinefelter syndrome, boys with this chromosome constitution are assumed to have severe mental retardation (MR) in addition to craniofacial, genital, endocrine, and heart abnormalities. Here, we present a multidisciplinary analysis including the clinical and neurobehavioral aspects of this condition in 20 boys with 49, XXXXY who share a common phenotype and neurobehavioral profile. The phenotypic presentation of the boys with 49, XXXXY shares some characteristics with 47, XXY, but there are also other unique and distinctive features. Previously unappreciated intact nonverbal skills are evident in conjunction with moderate to severe developmental dyspraxia. Variability in clinical and cognitive functioning may reflect skewed X inactivation, mosaicism, or other factors that warrant further investigation.

Identification of infants at risk for autism spectrum disorder and developmental language delay prior to 12 months.

Studies have shown an increased head circumference and the absence of the head tilt reflex as possible risk factors for autism spectrum disorder, allowing for early detection at 12 months in typically developing population of infants. Our aim was to develop a screening tool to identify infants prior to 12 months at risk for autism spectrum disorder and developmental learning delay, not affected by literacy or primary parental language, and provide immediate determination of risk for autism spectrum disorder. An abrupt head circumference acceleration and the absence of head tilt reflex by 9 months were used to identify infants at risk for autism spectrum disorder. Stability of early findings was then investigated when compared to comprehensive standardized neurodevelopmental assessment results and complete neurological and genetics evaluations. A total of 1024 typically developing infants were enrolled by 9 months, with 14 identified as at risk for autism spectrum disorder and 33 for developmental learning delay. There was a good positive predictive value for the identification of autism spectrum disorder prior to 12 months. This study demonstrates an efficient means to identify infants at risk for autism spectrum disorder by 9 months of age and serves to alert primary care providers of infants who are vulnerable for autism spectrum disorder before symptoms are discernible by clinical judgment of primary care providers, parental concerns, or by screening questionnaires.

Information in medical decision making: how consistent is our management?

BACKGROUND: The use of outcomes data in clinical environments requires a correspondingly greater variety of information used in decision making, the measurement of quality, and clinical performance. As information becomes integral in the decision-making process, trustworthy decision support data are required. METHODS: Using data from a national census of certified health information managers, variation in automated data quality management practices was examined. RESULTS: Relatively low overall adoption of automated data management exists in health care organizations, with significant geographic and practice setting variation. Nonuniform regional adoption of computerized data management exists, despite national mandates that promote and in some cases require uniform adoption. Overall, a significant number of respondents (42.7%) indicated that they had not adopted policies and procedures to direct the timeliness of data capture, with 57.3% having adopted such practices. CONCLUSIONS: The inconsistency of patient data policy suggests that provider organizations do not use uniform information management methods, despite growing federal mandates to do so.

Manager's reports of variation in coding accuracy across U.S. oncology centers.

Advances in high-speed data processing capabilities, and the increasing reliance on information systems in comparative data assessment, are creating greater dependence on information systems, with a related need for more timely assessment of coding quality. Assessing the accuracy of coded and classified data becomes critical as the implementation of government compliance management requirements, along with the growing adoption of evidence-based medicine in error detection, serve to challenge healthcare researchers to consider the quality of coded data in management assessments. The implementation of larger, faster and more comprehensive databases in healthcare delivery settings is one response to this changing environment, but at a national level there will need to be some degree of uniformity in their utilization and management, if researchers are expected to rely on comparative benchmarks to fully assess organizational performance. In a nationwide survey of health information managers we found about 81 percent of respondents reported that significant coding errors existed in 5 percent or less of the records in their institutions. About 11 percent of respondents, however, reported that the coding errors existed in six to ten percent of their records. Regional and practice setting variation in reported coding error ranged widely, occurring across organizations as well as area locations. Related impact on comparative data-driven management assessment is discussed.

Data capture of transdermal glucose monitoring through computerized appliance-based virtual remote sensing and alert systems.

Monitoring of blood glucose levels is important to persons with diabetes or pre-diabetic, abnormal glucose indications. Such individuals must determine when insulin is needed to reduce glucose levels in their bodies, or when additional glucose must be administered to raise levels. A conventional technique used by many diabetics to personally monitor their glucose level includes the periodic drawing of blood, the application of blood to a test strip, and determination of blood glucose level using calorimetric, electrochemical, or photometric detection. This technique does not permit continuous or automatic monitoring of levels in the body, but typically must be performed manually, and on a periodic basis. Unfortunately, checking consistency varies widely among individuals, where wide variation of high or low levels of glucose or other analytes may have detrimental effects. The ongoing capture of data through continuous and/or automatic in vivo monitoring of analyte levels, and its inclusion with a user-friendly computer interface, is now possible using a subcutaneous implanted sensor. Such devices are small and comfortable when used, allowing a wide range of life activities. In this technology review we propose one promising model using a combination of emerging, systems-based technologies in non-invasive analyte monitoring, as integrated within household-based health monitoring using home appliances.

Integrating computerized primitives and annotated video patterns: a proposed model for autism diagnosis and research.

The use of computerized, digital video as a means for interactive data capture has been suggested as an alternative to direct observation of behavior. The appeal of observational measures is that they are presumed to be less vulnerable to potential biases from informants, such as parents or teachers, and permit more individualized assessment that may be lost with the use of rating scales. As a potential tool for long-term, automated observation and analysis. In this technology review we propose one promising model for the integration of computerized primitives recognition and annotated video patterns as an approach to large-scale autism diagnosis and research.

Assessing managed care market variation in reports of coding accuracy.

The implementation of larger, faster and more comprehensive databases in healthcare delivery settings is an emerging outgrowth of evidence-based medicine. This study seeks to assess, at a national level, the degree of uniformity across markets in utilization and management of coded medical information. Implications for managers and policymakers, related to comparative managed care data benchmarks, are reviewed.