Technological innovation plays an important role in the dynamics of economic growth and in promoting the welfare of the general population. In support of this hypothesis, an empirical study was carried out to assess t...Technological innovation plays an important role in the dynamics of economic growth and in promoting the welfare of the general population. In support of this hypothesis, an empirical study was carried out to assess the spatial distribution of insulin and supplies （glucometers） for the control of diabetes in patients registered in the Public Healthcare System in Salvador, Bahia, from 1998 to 2012. In order to achieve this objective, we applied a combination of data collection strategies, including spatial analysis and discrete choice model estimation. The study proposed to answer the following question： What factors affect access to the supplies required to control diabetes in insulin-dependent patients？ To this end, we assessed the spatial distribution of diabetic patients in Salvador who had received glucometers. The hypothesis asserted that social, economic and geographical factors determine access to the supplies （glucometers） used to control diabetes. Exploratory Spatial Data Analysis （ESDA） was therefore performed using the Global Spatial Autocorrelation Index in order to analyze the spatial distribution of glucometers. We then performed econometric estimations and analyzed the results. The final results initially demonstrated that there were major inconsistencies in the distribution of glucometers; i.e. purely random factors largely determined the probability of obtaining this device. Individual characteristics were not decisive factors in the probability of obtaining a glucometer, which were insteadrelated to type of diabetes and recommended treatment.展开更多
<strong>Objective:</strong> The study aimed to evaluate the performance of the three glucometers compared to standard the laboratory method (Cobas Integra 400 Plus) in measuring blood glucose levels. <s...<strong>Objective:</strong> The study aimed to evaluate the performance of the three glucometers compared to standard the laboratory method (Cobas Integra 400 Plus) in measuring blood glucose levels. <strong>Patients and Methods: </strong>A total of 100 Yemeni diabetic patients were randomly recruited into a comparative cross-sectional study. Venous and finger-pricked blood samples were obtained from all participants and used for blood glucose levels measurement following the standard procedures. <strong>Results:</strong> The mean blood glucose levels for one-hundred diabetic patients using the Gluco Contour TS and Gluco SD Codefree were not significantly different compared with the Cobas Integra 400 Plus (12.14 ± 6.89 mmol/L vs. 12.85 ± 8.83 mmol/L, <span style="white-space:normal;"><i></span>P<span style="white-space:normal;"></i></span> = 0.159;12.50 ± 7.18 mmol/L vs. 12.85 ± 8.83 mmol/L, <i>P</i> = 0.490), respectively. However, there is a significant difference using the Gluco Alert device from that of the Cobas Integra 400 Plus (11.83 ± 6.94 mmol/L vs. 12.85 ± 8.83 mmol/L, <span style="white-space:normal;"><i></span>P<span style="white-space:normal;"></i></span> = 0.046). Furthermore, using the ROC curve at a 95% confidence interval, the Cobas Integra 400 Plus showed a significant agreement with the Gluco Contour TS (51.4%), Gluco SD Codefree (50.4%), and Gluco Alert (39.3%), respectively. For determining accuracy, the sensitivity of the glucometer devices was the following: Gluco SD Codefree (87.3%), Contour TS (85.9%), and Gluco Alert (78.9%). In this regard, the highest specificity was related to Gluco Contour TS (65.5%). <strong>Conclusion:</strong> The correlation between both methods was good, with high sensitivity and specificity in measuring blood glucose levels as indicated by the ROC curve. Thus, we suggest using these glucometers at homes and hospitals as a point of care for diabetic patients.展开更多
文摘Technological innovation plays an important role in the dynamics of economic growth and in promoting the welfare of the general population. In support of this hypothesis, an empirical study was carried out to assess the spatial distribution of insulin and supplies （glucometers） for the control of diabetes in patients registered in the Public Healthcare System in Salvador, Bahia, from 1998 to 2012. In order to achieve this objective, we applied a combination of data collection strategies, including spatial analysis and discrete choice model estimation. The study proposed to answer the following question： What factors affect access to the supplies required to control diabetes in insulin-dependent patients？ To this end, we assessed the spatial distribution of diabetic patients in Salvador who had received glucometers. The hypothesis asserted that social, economic and geographical factors determine access to the supplies （glucometers） used to control diabetes. Exploratory Spatial Data Analysis （ESDA） was therefore performed using the Global Spatial Autocorrelation Index in order to analyze the spatial distribution of glucometers. We then performed econometric estimations and analyzed the results. The final results initially demonstrated that there were major inconsistencies in the distribution of glucometers; i.e. purely random factors largely determined the probability of obtaining this device. Individual characteristics were not decisive factors in the probability of obtaining a glucometer, which were insteadrelated to type of diabetes and recommended treatment.
文摘<strong>Objective:</strong> The study aimed to evaluate the performance of the three glucometers compared to standard the laboratory method (Cobas Integra 400 Plus) in measuring blood glucose levels. <strong>Patients and Methods: </strong>A total of 100 Yemeni diabetic patients were randomly recruited into a comparative cross-sectional study. Venous and finger-pricked blood samples were obtained from all participants and used for blood glucose levels measurement following the standard procedures. <strong>Results:</strong> The mean blood glucose levels for one-hundred diabetic patients using the Gluco Contour TS and Gluco SD Codefree were not significantly different compared with the Cobas Integra 400 Plus (12.14 ± 6.89 mmol/L vs. 12.85 ± 8.83 mmol/L, <span style="white-space:normal;"><i></span>P<span style="white-space:normal;"></i></span> = 0.159;12.50 ± 7.18 mmol/L vs. 12.85 ± 8.83 mmol/L, <i>P</i> = 0.490), respectively. However, there is a significant difference using the Gluco Alert device from that of the Cobas Integra 400 Plus (11.83 ± 6.94 mmol/L vs. 12.85 ± 8.83 mmol/L, <span style="white-space:normal;"><i></span>P<span style="white-space:normal;"></i></span> = 0.046). Furthermore, using the ROC curve at a 95% confidence interval, the Cobas Integra 400 Plus showed a significant agreement with the Gluco Contour TS (51.4%), Gluco SD Codefree (50.4%), and Gluco Alert (39.3%), respectively. For determining accuracy, the sensitivity of the glucometer devices was the following: Gluco SD Codefree (87.3%), Contour TS (85.9%), and Gluco Alert (78.9%). In this regard, the highest specificity was related to Gluco Contour TS (65.5%). <strong>Conclusion:</strong> The correlation between both methods was good, with high sensitivity and specificity in measuring blood glucose levels as indicated by the ROC curve. Thus, we suggest using these glucometers at homes and hospitals as a point of care for diabetic patients.
