ObjectiveTo assess the psychometric properties of the Health Assessment Questionnaire (HAQ) disab... more ObjectiveTo assess the psychometric properties of the Health Assessment Questionnaire (HAQ) disability index (DI) in patients with gout.To assess the psychometric properties of the Health Assessment Questionnaire (HAQ) disability index (DI) in patients with gout.MethodsThis study was conducted in a multicenter cohort of patients with gout whose data were collected at baseline (time 0) and 6 months later (time 6). Reliability was assessed by test–retest reliability (intraclass correlation coefficient [ICC]) and internal consistency (Cronbach's alpha coefficient). Construct validity was assessed with convergent validity (HAQ DI correlation with Short Form 36 [SF-36]) and discriminative validity (HAQ DI correlation with clinical features). Sensitivity to change was determined by comparing HAQ DI time 0 versus HAQ DI time 6 (percentage of change, effect size, smallest real difference [SRD], and Guyatt's responsiveness index [GRI]).This study was conducted in a multicenter cohort of patients with gout whose data were collected at baseline (time 0) and 6 months later (time 6). Reliability was assessed by test–retest reliability (intraclass correlation coefficient [ICC]) and internal consistency (Cronbach's alpha coefficient). Construct validity was assessed with convergent validity (HAQ DI correlation with Short Form 36 [SF-36]) and discriminative validity (HAQ DI correlation with clinical features). Sensitivity to change was determined by comparing HAQ DI time 0 versus HAQ DI time 6 (percentage of change, effect size, smallest real difference [SRD], and Guyatt's responsiveness index [GRI]).ResultsWe included 206 patients (96.6% men, mean ± SD age and disease duration 56.3 ± 12.4 years and 9.3 ± 8.5 years, respectively). Of these, 52.4% had joint pain, 22.8% swelling, 32.5% reduced joint mobility, and 36.9% tophi. The mean HAQ DI score was 0.59 ± 0.77 (95% confidence interval [95% CI] 0.49–0.70). ICC (n = 36, evaluations at baseline and 5 days later) was 0.76. Cronbach's alphas were 0.91 (95% CI 0.88–0.92, P = 0.000) for the 20 HAQ DI items and 0.93 (95% CI 0.92–0.94, P = 0.000) for the 8 HAQ DI categories. The HAQ DI correlated in predictable ways with SF-36 subscales and clinical variables, and discriminated between subgroups with and without any joint pain, swelling, and tophi. Concerning sensitivity to change (n = 167), the difference between HAQ DI time 0 and HAQ DI time 6 was 0.31 ± 0.58 (effect size 0.62, SRD 0.59, and GRI 1.91). ΔHAQ DI correlated with Δpain (r = 0.349, P = 0.000).We included 206 patients (96.6% men, mean ± SD age and disease duration 56.3 ± 12.4 years and 9.3 ± 8.5 years, respectively). Of these, 52.4% had joint pain, 22.8% swelling, 32.5% reduced joint mobility, and 36.9% tophi. The mean HAQ DI score was 0.59 ± 0.77 (95% confidence interval [95% CI] 0.49–0.70). ICC (n = 36, evaluations at baseline and 5 days later) was 0.76. Cronbach's alphas were 0.91 (95% CI 0.88–0.92, P = 0.000) for the 20 HAQ DI items and 0.93 (95% CI 0.92–0.94, P = 0.000) for the 8 HAQ DI categories. The HAQ DI correlated in predictable ways with SF-36 subscales and clinical variables, and discriminated between subgroups with and without any joint pain, swelling, and tophi. Concerning sensitivity to change (n = 167), the difference between HAQ DI time 0 and HAQ DI time 6 was 0.31 ± 0.58 (effect size 0.62, SRD 0.59, and GRI 1.91). ΔHAQ DI correlated with Δpain (r = 0.349, P = 0.000).ConclusionThe HAQ DI is a valid and reliable measure of functioning in patients with gout.The HAQ DI is a valid and reliable measure of functioning in patients with gout.
We present results of a verification study of totally automated optical proximity correction (OPC... more We present results of a verification study of totally automated optical proximity correction (OPC) for mask redesign to enhance process capability. OPC was performed on an aggressive 0.35 micrometer i-line LSI logic SRAM design using the automated OPC generation code Eoptimask, employing the aerial image simulation code FAIM, both from Vector Technologies, Inc. Three different tests were performed, varying in the aggressiveness and type of corrections made. The key issues addressed in this work are the predictive capability of the aerial image simulation and, particularly, the ability of automatically generated OPC to significantly improve the fidelity of the final printed resist image for different geometries. The results of our study clearly demonstrate the utility of automated OPC based on aerial image simulation. Key experimental results include: two-fold increase of depth of focus latitude; demonstration of the feasibility of full off-axis illumination on the stepper; successful resolution of different feature types (posts, lines and spaces) on the wafer to correct CD at a single common exposure and focus condition. Future research will address detailed issues in reticle manufacture and inspection which are critical for cost-effective large-scale OPC.
ObjectiveTo assess the psychometric properties of the Health Assessment Questionnaire (HAQ) disab... more ObjectiveTo assess the psychometric properties of the Health Assessment Questionnaire (HAQ) disability index (DI) in patients with gout.To assess the psychometric properties of the Health Assessment Questionnaire (HAQ) disability index (DI) in patients with gout.MethodsThis study was conducted in a multicenter cohort of patients with gout whose data were collected at baseline (time 0) and 6 months later (time 6). Reliability was assessed by test–retest reliability (intraclass correlation coefficient [ICC]) and internal consistency (Cronbach's alpha coefficient). Construct validity was assessed with convergent validity (HAQ DI correlation with Short Form 36 [SF-36]) and discriminative validity (HAQ DI correlation with clinical features). Sensitivity to change was determined by comparing HAQ DI time 0 versus HAQ DI time 6 (percentage of change, effect size, smallest real difference [SRD], and Guyatt's responsiveness index [GRI]).This study was conducted in a multicenter cohort of patients with gout whose data were collected at baseline (time 0) and 6 months later (time 6). Reliability was assessed by test–retest reliability (intraclass correlation coefficient [ICC]) and internal consistency (Cronbach's alpha coefficient). Construct validity was assessed with convergent validity (HAQ DI correlation with Short Form 36 [SF-36]) and discriminative validity (HAQ DI correlation with clinical features). Sensitivity to change was determined by comparing HAQ DI time 0 versus HAQ DI time 6 (percentage of change, effect size, smallest real difference [SRD], and Guyatt's responsiveness index [GRI]).ResultsWe included 206 patients (96.6% men, mean ± SD age and disease duration 56.3 ± 12.4 years and 9.3 ± 8.5 years, respectively). Of these, 52.4% had joint pain, 22.8% swelling, 32.5% reduced joint mobility, and 36.9% tophi. The mean HAQ DI score was 0.59 ± 0.77 (95% confidence interval [95% CI] 0.49–0.70). ICC (n = 36, evaluations at baseline and 5 days later) was 0.76. Cronbach's alphas were 0.91 (95% CI 0.88–0.92, P = 0.000) for the 20 HAQ DI items and 0.93 (95% CI 0.92–0.94, P = 0.000) for the 8 HAQ DI categories. The HAQ DI correlated in predictable ways with SF-36 subscales and clinical variables, and discriminated between subgroups with and without any joint pain, swelling, and tophi. Concerning sensitivity to change (n = 167), the difference between HAQ DI time 0 and HAQ DI time 6 was 0.31 ± 0.58 (effect size 0.62, SRD 0.59, and GRI 1.91). ΔHAQ DI correlated with Δpain (r = 0.349, P = 0.000).We included 206 patients (96.6% men, mean ± SD age and disease duration 56.3 ± 12.4 years and 9.3 ± 8.5 years, respectively). Of these, 52.4% had joint pain, 22.8% swelling, 32.5% reduced joint mobility, and 36.9% tophi. The mean HAQ DI score was 0.59 ± 0.77 (95% confidence interval [95% CI] 0.49–0.70). ICC (n = 36, evaluations at baseline and 5 days later) was 0.76. Cronbach's alphas were 0.91 (95% CI 0.88–0.92, P = 0.000) for the 20 HAQ DI items and 0.93 (95% CI 0.92–0.94, P = 0.000) for the 8 HAQ DI categories. The HAQ DI correlated in predictable ways with SF-36 subscales and clinical variables, and discriminated between subgroups with and without any joint pain, swelling, and tophi. Concerning sensitivity to change (n = 167), the difference between HAQ DI time 0 and HAQ DI time 6 was 0.31 ± 0.58 (effect size 0.62, SRD 0.59, and GRI 1.91). ΔHAQ DI correlated with Δpain (r = 0.349, P = 0.000).ConclusionThe HAQ DI is a valid and reliable measure of functioning in patients with gout.The HAQ DI is a valid and reliable measure of functioning in patients with gout.
We present results of a verification study of totally automated optical proximity correction (OPC... more We present results of a verification study of totally automated optical proximity correction (OPC) for mask redesign to enhance process capability. OPC was performed on an aggressive 0.35 micrometer i-line LSI logic SRAM design using the automated OPC generation code Eoptimask, employing the aerial image simulation code FAIM, both from Vector Technologies, Inc. Three different tests were performed, varying in the aggressiveness and type of corrections made. The key issues addressed in this work are the predictive capability of the aerial image simulation and, particularly, the ability of automatically generated OPC to significantly improve the fidelity of the final printed resist image for different geometries. The results of our study clearly demonstrate the utility of automated OPC based on aerial image simulation. Key experimental results include: two-fold increase of depth of focus latitude; demonstration of the feasibility of full off-axis illumination on the stepper; successful resolution of different feature types (posts, lines and spaces) on the wafer to correct CD at a single common exposure and focus condition. Future research will address detailed issues in reticle manufacture and inspection which are critical for cost-effective large-scale OPC.
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Papers by mario garza