Biomedical subjects

R C Musselman

Publications and source records attributed to R C Musselman.

4 recordsLinked to original sources

PubMed1998

Monitoring the medications of clients with noninsulin-dependent diabetes mellitus.

Noninsulin-dependent diabetes mellitus (NIDDM) (type 2) affects 16 million people in the United States. To effectively monitor such clients in the home, a thorough knowledge of the medications used to control hyperglycemia is needed. Primary failure with monotherapy has been studied and found to occur within 6 years. Combinations of two drug classes now are used to control blood glucose levels. The home health care provider must be aware of the mechanism of action of the different classes of hypoglycemic agents to monitor treatment. This article will discuss the different agents, their mechanism of action, and the use of combination therapies.

Blood Glucose Self-Monitoring↗

PubMed1998

Appendicitis during pregnancy.

Appendicitis during pregnancy is a serious medical condition that requires diagnostic accuracy. If diagnosis is delayed, there is an increased incidence of perforation and peritonitis, which can lead to fetal and maternal mortality and morbidity. Since appendicitis is the leading reason for surgery during pregnancy, healthcare providers must be aware of the signs and symptoms of this disease (Allen, Helling, & Langenfeld, 1989; Weingold, 1983). Pregnancy often blunts the symptoms, making diagnosis difficult (Sharp, 1994; Weingold, 1983). This article discusses the incidence of appendicitis in pregnancy, the signs and symptoms, as well as laboratory and radiologic tests used in diagnosis. The risks to the mother and fetus, along with surgical and medical interventions, are also discussed.

Abdominal Pain↗

PubMed1994

Growth-stage dependent crop yield response to ozone exposure.

Data from four crop yield-loss field trials were examined to determine if analysis using an imposed phenological weighting function based on seasonal growth stage would provide a more accurate indication of impact of ozone exposure. Alfalfa (Medicago sativa L. cv. Moapa 69), dry bean (Phaseolus vulgaris L. cv. California Dark Red kidney), fresh market and processing tomato (Lycopersicon esculentum Mill. cv. 6718 VF and VF-145-B7879, respectively) were grown at 9-11 ambient field plots within southern California comprising an ambient gradient of ozone. The growing season for each crop was artificially divided into 'quarters' composed of equal numbers of whole days and roughly corresponding to specific growth stages. Ozone exposure was calculated for each of these 'quarters' and regressed against final crop yield using 163 different exposure statistics. Weighting functions were developed using reciprocal residual mean square (1/RMS) or percentage of the best 100 exposure statistics of the 163 tested (TOP100) for each of the quarters. The third quarter of the alfalfa season was clearly most responsive to ozone as measured by both of the weighting functions. Third quarter ozone was also weighted highest by both weighting functions for dry bean. Fresh market and processing tomato were each influenced the greatest by second quartero zone as demonstrated by both weighting functions. The occurrence of ozone during physiologically important events (flowering and initial fruit set in second quarter for tomato; pod development in third quarter for dry bean) appeared to influence the yield of these crops the greatest. Growth-stage-dependent phenological weighting of pollutant exposure may result in more effective predictions of levels of ozone exposure resulting in yield reductions.

Journal Article↗

PubMed1988

Selecting ozone exposure statistics for determining crop yield loss from air pollutants.

Numerous ozone exposure statistics were calculated using hourly ozone data from crop yield loss experiments previously conducted for alfalfa, fresh market and processing tomatoes, cotton, and dry beans in an ambient ozone gradient near Los Angeles, California. Exposure statistics examined included peak (maximum daily hourly) and mean concentrations above specific threshold levels, and concentrations during specific time periods of the day. Peak and mean statistics weighted for ozone concentration and time period statistics weighted for hour of the day were also determined. Polynomial regression analysis was used to relate each of 163 ozone statistics to crop yield. Performance of the various statistics was rated by comparing residual mean square (RMS) values. The analyses demonstrated that no single statistic was best for all crop species. Ozone statistics with a threshold level performed well for most crops, but optimum threshold level was dependent upon crop species and varied with the particular statistics calculated. The data indicated that daily hours of exposure above a critical high-concentration threshold related well to crop yield for alfalfa, market tomatoes, and dry beans. The best statistic for cotton yield was an average of all daily peak ozone concentrations. Several different types of ozone statistics performed similarly for processing tomatoes. These analyses suggest that several ozone summary statistics should be examined in assessing the relationship of ambient ozone exposure to crop yield. Where no clear statistical preference is indicated among several statistics, those most biologically relevant should be selected.

Journal Article↗