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Biomedical subjects

Richard A Bilonick

Publications and source records attributed to Richard A Bilonick.

7 recordsLinked to original sources
PubMed2007

Glaucoma detection with matrix and standard achromatic perimetry.

BACKGROUND: Matrix perimetry is a new iteration of frequency-doubling technology (FDT) which uses a smaller target size in the standard achromatic perimetry presentation pattern. AIM: To compare the performance of matrix and Swedish interactive thresholding algorithm (SITA) perimetry in detecting glaucoma diagnosed by structural assessment. DESIGN: Prospective cross-sectional study. METHODS: 76 eyes from 15 healthy subjects and 61 consecutive glaucoma suspects and patients with glaucoma were included. All patients underwent optic nerve head (ONH) photography, SITA and matrix perimetries, and optical coherence tomography (OCT) within a 6-month period. Glaucoma diagnosis was established by either glaucomatous optic neuropathy or OCT by assessing retinal nerve fibre layer (RNFL) thickness. Mean deviation (MD), pattern standard deviation (PSD), glaucoma hemifield test and cluster of abnormal testing locations were recorded from matrix and SITA perimetries. RESULTS: Similar correlations were observed with matrix and SITA perimetry MD and PSD with either cup-to-disc ratio or OCT mean RNFL. The area under the receiver operating characteristic (AROC) curves of MD and PSD for discriminating between healthy and glaucomatous eyes ranged from 0.69 to 0.81 for matrix perimetry and from 0.75 to 0.77 for SITA perimetry. There were no significant differences among any corresponding matrix and SITA perimetry AROCs. CONCLUSIONS: Matrix and SITA perimetries had similar capabilities for distinguishing between healthy and glaucomatous eyes regardless of whether the diagnosis was established by ONH or OCT-RNFL assessment.

Adult↗
PubMed2006

Glaucoma detection with the Heidelberg retina tomograph 3.

PURPOSE: To compare the ability of the Heidelberg retina tomograph version 3 (HRT 3) and HRT version 2 (HRT 2) to discriminate between healthy and glaucomatous eyes. DESIGN: Retrospective cross-sectional study. PARTICIPANTS: Seventy-one eyes of 71 healthy volunteers and 50 eyes of 50 glaucoma patients were studied. The average visual field mean deviation of the glaucoma group was -6.03+/-5.78 dB. INTERVENTION: All participants had comprehensive ocular examinations, perimetry, and HRT scanning within 6 months. HRT 2 data were analyzed using HRT 3 software without modifying the disc margin. MAIN OUTCOME MEASURES: Discrimination capabilities between healthy and glaucomatous eyes were determined by areas under the receiver operating characteristics (AROCs) curves. Comparisons between corresponding AROCs obtained by HRT 2 and HRT 3 analyses were performed using the nonparametric DeLong method. Agreement between classifications as defined by the different analysis methods was quantified by kappa analysis. RESULTS: The individual stereometric parameters with the best discrimination were linear cup/disc ratio (AROC = 0.897; 95% confidence interval [CI], 0.836-0.958) for standard HRT 3 analysis and horizontal retinal nerve fiber layer curvature (0.905) for HRT 3 glaucoma probability score (GPS) analysis. Areas under the receiver operating characteristics for discrimination between glaucomatous and healthy eyes of the overall classification by HRT 2 Moorfields regression analysis (MRA), HRT 3 MRA, and GPS were 0.927 (95% CI, 0.877-0.977), 0.934 (0.888-0.980), and 0.880 (0.812-0.948), respectively. The difference between the 3 AROCs was not significant (P = 0.44). The agreement between HRT 2 and HRT 3 overall MRA classification was good (kappa = 0.70; CI, 0.59-0.80) with HRT 3 tending to report more abnormalities than HRT 2 analysis. The agreement between overall HRT 3 MRA and overall GPS was kappa = 0.58 (CI, 0.45-0.70). CONCLUSIONS: The glaucoma discriminating ability of the new HRT 3 software is similar to that of the previous generation HRT 2. The GPS analysis showed promising results in differentiating between healthy and glaucomatous eyes without the need for subjective operator input.

Adult↗
PubMed2005

The Steubenville comprehensive air monitoring program (SCAMP): overview and statistical considerations.

Average concentrations of particulate matter with an aerodynamic diameter less than or equal to 2.5 microm (PM2.5) in Steubenville, OH, have decreased by more than 10 microg/m3 since the landmark Harvard Six Cities Study associated the city's elevated PM2.5 concentrations with adverse health effects in the 1980s. Given the promulgation of a new National Ambient Air Quality Standard (NAAQS) for PM2.5 in 1997, a current assessment of PM2.5 in the Steubenville region is warranted. The Steubenville Comprehensive Air Monitoring Program (SCAMP) was conducted from 2000 through 2002 to provide such an assessment. The program included both an outdoor ambient air monitoring component and an indoor and personal air sampling component. This paper, which is the first in a series of four that will present results from the outdoor portion of SCAMP, provides an overview of the outdoor ambient air monitoring program and addresses statistical issues, most notably autocorrelation, that have been overlooked by many PM2.5 data analyses. The average PM2.5 concentration measured in Steubenville during SCAMP (18.4 microg/m3) was 3.4 microg/m3 above the annual PM2.5 NAAQS. On average, sulfate and organic material accounted for approximately 31% and 25%, respectively, of the total PM2.5 mass. Local sources contributed an estimated 4.6 microg/m3 to Steubenville's mean PM2.5 concentration. PM2.5 and each of its major ionic components were significantly correlated in space across all pairs of monitoring sites in the region, suggesting the influence of meteorology and long-range transport on regional PM2.5 concentrations. Statistically significant autocorrelation was observed among time series of PM2.5 and component data collected at daily and 1-in-4-day frequencies during SCAMP. Results of spatial analyses that accounted for autocorrelation were generally consistent with findings from previous studies that did not consider autocorrelation; however, these analyses also indicated that failure to account for autocorrelation can lead to incorrect conclusions about statistical significance.

Air Pollutants↗
PubMed2005

The Steubenville comprehensive air monitoring program (SCAMP): associations among fine particulate matter, co-pollutants, and meteorological conditions.

We determined 24-hr average ambient concentrations of PM2.5 and its ionic and carbonaceous components in Steubenville, OH, between May 2000 and May 2002. We also determined daily average gaseous co-pollutant concentrations, meteorological conditions, and pollen and mold spore counts. Data were analyzed graphically and by linear regression and time series models. Multiple-day episodes of elevated fine particulate matter (PM2.5) concentrations often occurred during periods of locally high temperature (especially during summer), high pressure, or low wind speed (especially during winter) and generally ended with the passage of a frontal system. After removing autocorrelation, we observed statistically significant positive associations between concentrations of PM2.5 and concentrations of CO, NOx, and SO2. Associations with NOx and CO exhibited significant seasonal dependencies, with the strongest correlations during fall and winter. NOx, CO, SO2, O3, temperature, relative humidity, and wind speed were all significant predictors of PM2.5 concentration in a time-series model with external regressors, which successfully accounted for 79% of the variance in log-transformed daily PM2.5 concentrations. Coefficient estimates for NOx and temperature varied significantly by season. The results provide insight that may be useful in the development of future PM2.5 reduction strategies for Steubenville. Additionally, they demonstrate the need for PM epidemiology studies in Steubenville (and elsewhere) to carefully consider the potential confounding effects of gaseous co-pollutants, such as CO and NOx, and their seasonally dependent associations with PM2.5.

Air Pollutants↗
PubMed2005

The Steubenville Comprehensive Air Monitoring Program (SCAMP): analysis of short-term and episodic variations in PM2.5 concentrations using hourly air monitoring data.

One-hour average ambient concentrations of particulate matter (PM) with an aerodynamic diameter < 2.5 microm (PM2.5) were determined in Steubenville, OH, between June 2000 and May 2002 with a tapered element oscillating microbalance (TEOM). Hourly average gaseous copollutant [carbon monoxide (CO), sulfur dioxide (SO2), nitrogen oxide (NOx), and ozone (O3)] concentrations and meteorological conditions also were measured. Although 75% of the 14,682 hourly PM2.5 concentrations measured during this period were < or = 17 microg/m3, concentrations > 65 microg/m3 were observed 76 times. On average, PM2.5 concentrations at Steubenville exhibited a diurnal pattern of higher early morning concentrations and lower afternoon concentrations, similar to the diurnal profiles of CO and NO(x). This pattern was highly variable; however, PM2.5 concentrations > 65 microg/m3 were never observed during the mid-afternoon between 1:00 p.m. and 5:00 p.m. EST. Twenty-two episodes centered on one or more of these elevated concentrations were identified. Five episodes occurred during the months June through August; the maximum PM2.5 concentration during these episodes was 76.6 microg/m3. Episodes occurring during climatologically cooler months often featured higher peak concentrations (five had maximum concentrations between 95.0 and 139.6 microg/m3), and many exhibited strong covariation between PM2.5 and CO, NO(x), or SO2. Case studies suggested that nocturnal surface-based temperature inversions were influential in driving high nighttime concentrations of these species during several cool season episodes, which typically had dramatically lower afternoon concentrations. These findings provide insights that may be useful in the development of PM2.5 reduction strategies for Steubenville, and suggest that studies assessing possible health effects of PM2.5 should carefully consider exposure issues related to the intraday timing of PM2.5 episodes, as well as the potential for toxicological interactions among PM2.5, and primary gaseous pollutants.

Air Pollutants↗