Self-care among older adults

Defining self-care as treatment for a perceived symptom, this paper posits that explanations for such illness behavior will differ depending on whether symptoms experienced are perceived as not serious and most amenable to self-treatment or more serious and less likely to respond to self-care. Borrowing from the Health Belief Model, two major concepts, a health set (consisting of five measures of perceived physical and mental health) and an attitude set (comprising four indicators of belief in physician efficacy) are included to explain rates of self-care across all reported symptoms. Self-care rate, calculated as the percentage of experienced symptoms self-treated without professional advice, was slightly higher for persons whose symptoms were seen as less serious. Measures of self-assessed health were related to self-care for those less severe symptoms, while lower faith in doctors as well as health were more closely related to the ailments perceived as more serious. Implications of the results for further studies are discussed.     

An assessment of the radiological module of NEONATE as an aid in interpreting chest X-ray findings by nonradiologists

NEONATE is a prototype of an expert system for the Newborn Intensive Care Unit developed at the Primary Children's Medical Center in Salt Lake City, Utah. A pilot study was undertaken to see if the addition of radiological frames to the NEONATE software could aid attending Neonatologists to interpret chest X-ray films. A set of radiological frames was created from rules generated by a radiologist. The performance of these radiological frames was compared to the performance of other radiologists using the Kappa statistic to measure agreement. There is a good agreement between the computer's decisions and the radiologists' decisions. The radiological frames were also tested to see if they help physicians who are not trained in radiology. A system that compares the residents' interpretation and the computer's interpretation to a gold standard interpretation was developed. It shows that the computer helps the first and second year residents, but not the third year residents. This article suggests that NEONATE's interpretation of chest X-ray findings are close to the radiologists' interpretations. While NEONATE's radiological frames help novice physicians in reaching better chest X-ray interpretation, the current study suggests that they are not likely to help a Neonatologist.     

The effects of secretin on prolactin, estradiol, vasoactive intestinal polypeptide, and somatostatin levels in women

The effect of graded doses of intravenous secretin (0.5, 1.0, and 2.0 CU.kg-1.h-1) on serum prolactin and estradiol levels, as well as plasma vasoactive intestinal polypeptide and somatostatin levels was studied in 6 normally cycling and healthy women, and compared with the hormone levels obtained by a control infusion with physiologic saline (0.15 mol/l). A significant decrease in serum prolactin concentrations was found with increasing doses of secretin at steady-state levels of plasma secretin (+30 to +60 min). A significant negative correlation (p less than 0.007, r = -0.2764) existed between serum prolactin and plasma secretin concentrations at steady-state conditions. No effect of graded doses of secretin was observed on serum estradiol levels and plasma concentrations of vasoactive intestinal polypeptide and somatostatin. The results suggest a dose-related inhibitory effect of secretin on prolactin release in women.     

The voltage-gated sodium channel gene SCN2A and idiopathic generalized epilepsy.

We tested the hypothesis that genetic variation in the human sodium channel gene SCN2A confers liability to idiopathic generalized epilepsy (IGE). We performed a systematic search for mutations in 46 familial IGE cases and detected three novel polymorphisms, however, allele frequencies did not differ significantly between patients and controls. A rare mutation (R1918H) was identified in one patient but was absent in one further affected family member. Thus, our results do not suggest a major role of SCN2A in the etiology of IGE.     

Forecasting Daily Patient Volumes in the Emergency Department

Background: Shifts in the supply of and demand for emergency department (ED) resources make the efficient allocation of ED resources increasingly important. Forecasting is a vital activity that guides decision‐making in many areas of economic, industrial, and scientific planning, but has gained little traction in the health care industry. There are few studies that explore the use of forecasting methods to predict patient volumes in the ED. Objectives: The goals of this study are to explore and evaluate the use of several statistical forecasting methods to predict daily ED patient volumes at three diverse hospital EDs and to compare the accuracy of these methods to the accuracy of a previously proposed forecasting method. Methods: Daily patient arrivals at three hospital EDs were collected for the period January 1, 2005, through March 31, 2007. The authors evaluated the use of seasonal autoregressive integrated moving average, time series regression, exponential smoothing, and artificial neural network models to forecast daily patient volumes at each facility. Forecasts were made for horizons ranging from 1 to 30 days in advance. The forecast accuracy achieved by the various forecasting methods was compared to the forecast accuracy achieved when using a benchmark forecasting method already available in the emergency medicine literature. Results: All time series methods considered in this analysis provided improved in‐sample model goodness of fit. However, postsample analysis revealed that time series regression models that augment linear regression models by accounting for serial autocorrelation offered only small improvements in terms of postsample forecast accuracy, relative to multiple linear regression models, while seasonal autoregressive integrated moving average, exponential smoothing, and artificial neural network forecasting models did not provide consistently accurate forecasts of daily ED volumes. Conclusions: This study confirms the widely held belief that daily demand for ED services is characterized by seasonal and weekly patterns. The authors compared several time series forecasting methods to a benchmark multiple linear regression model. The results suggest that the existing methodology proposed in the literature, multiple linear regression based on calendar variables, is a reasonable approach to forecasting daily patient volumes in the ED. However, the authors conclude that regression‐based models that incorporate calendar variables, account for site‐specific special‐day effects, and allow for residual autocorrelation provide a more appropriate, informative, and consistently accurate approach to forecasting daily ED patient volumes.     

Thromboxane synthetase inhibitors and antihypertensive agents. 2. N-[(1H-imidazol-1-yl)alkyl]-1H-isoindole-1,3(2H)-diones and N-[(1H-1,2,4-triazol-1-yl)alkyl]-1H-isoindole-1,3(2H)-diones as unique antihypertensive agents

A series of N-[(1H-heteroaryl)alkyl]-1H-isoindole-1,3(2H)-diones were prepared as part of a continuing investigation into the biological properties of compounds that were both thromboxane synthetase inhibitors and potential antihypertensive agents. The most active thromboxane synthetase inhibition was found for the title imidazole derivatives wherein a hexyl or octyl chain separated the heterocyclic ends of the molecule (5,6) or with substitution on the isoindole portion of the molecule (18, 19, 21, 22, 25, 26). Compounds with shorter alkyl chain separations had good antihypertensive effects (1-5, 8-10, 19-22, 27-30). Butyl derivative 3 was chosen for further evaluation as a potential antihypertensive agent with thromboxane synthetase inhibitory properties.