This study explored and reviewed the logistic regression (LR) model, a multivariable method for modeling the relationship between multiple independent variables and a categorical dependent variable, with emphasis on m...This study explored and reviewed the logistic regression (LR) model, a multivariable method for modeling the relationship between multiple independent variables and a categorical dependent variable, with emphasis on medical research. Thirty seven research articles published between 2000 and 2018 which employed logistic regression as the main statistical tool as well as six text books on logistic regression were reviewed. Logistic regression concepts such as odds, odds ratio, logit transformation, logistic curve, assumption, selecting dependent and independent variables, model fitting, reporting and interpreting were presented. Upon perusing the literature, considerable deficiencies were found in both the use and reporting of LR. For many studies, the ratio of the number of outcome events to predictor variables (events per variable) was sufficiently small to call into question the accuracy of the regression model. Also, most studies did not report on validation analysis, regression diagnostics or goodness-of-fit measures;measures which authenticate the robustness of the LR model. Here, we demonstrate a good example of the application of the LR model using data obtained on a cohort of pregnant women and the factors that influence their decision to opt for caesarean delivery or vaginal birth. It is recommended that researchers should be more rigorous and pay greater attention to guidelines concerning the use and reporting of LR models.展开更多
Due to the development of CT (Computed Tomography), MRI (Magnetic Resonance Imaging), PET (Positron Emission Tomography), EBCT (Electron Beam Computed Tomography), SMRI (Stereotactic Magnetic Resonance Imaging), etc. ...Due to the development of CT (Computed Tomography), MRI (Magnetic Resonance Imaging), PET (Positron Emission Tomography), EBCT (Electron Beam Computed Tomography), SMRI (Stereotactic Magnetic Resonance Imaging), etc. has enhanced the distinguishing rate and scanning rate of the imaging equipments. The diagnosis and the process of getting useful information from the image are got by processing the medical images using the wavelet technique. Wavelet transform has increased the compression rate. Increasing the compression performance by minimizing the amount of image data in the medical images is a critical task. Crucial medical information like diagnosing diseases and their treatments is obtained by modern radiology techniques. Medical Imaging (MI) process is used to acquire that information. For lossy and lossless image compression, several techniques were developed. Image edges have limitations in capturing them if we make use of the extension of 1-D wavelet transform. This is because wavelet transform cannot effectively transform straight line discontinuities, as well geographic lines in natural images cannot be reconstructed in a proper manner if 1-D transform is used. Differently oriented image textures are coded well using Curvelet Transform. The Curvelet Transform is suitable for compressing medical images, which has more curvy portions. This paper describes a method for compression of various medical images using Fast Discrete Curvelet Transform based on wrapping technique. After transformation, the coefficients are quantized using vector quantization and coded using arithmetic encoding technique. The proposed method is tested on various medical images and the result demonstrates significant improvement in performance parameters like Peak Signal to Noise Ratio (PSNR) and Compression Ratio (CR).展开更多
Introduction: Cancer is a chronic debilitating disease that unnerves patients, communities, and nations. At some point in cancer patient’s disease experience, chemotherapy is used, and the patient is expected to adhe...Introduction: Cancer is a chronic debilitating disease that unnerves patients, communities, and nations. At some point in cancer patient’s disease experience, chemotherapy is used, and the patient is expected to adhere to treatment to improve survival and quality of life. Methods: This multisite Cluster Randomized Trial (CRT) evaluated the effectiveness of mobile phone Short Message Service (SMS) support on the adherence to treatment schedules among adult cancer patients in Kenya. Data was collected using questionnaires. Ethical approvals were obtained from relevant Ethical Review Boards (ERBs). Results: The mean adherence was 83%. There was a significant difference between treatment arms in relation to the adherence. The intervention arm had a higher mean adherence difference, M = 3.913, 95% CI 2.632-5.193, t (402) = 6.006, p ≤ 0.001), with Cohen’s d = 0.60. Although not significant, (χ<sup>2</sup>dd = 0.151, df = 1, p = 2.064), more women were perfect adheres than males. Perfect adherers were satisfied with SMS support (χ<sup>2</sup>dd = 7.620, df = 1, p = 0.06), were in the intervention arm (χ<sup>2</sup>dd = 22.942, df = 1, p ≤ 0.001), and had trust in the care provider (χ<sup>2</sup>dd = 10.591 p ≤ 0.001). SMS support was not significant in the multivariate analysis but had an estimated effect size of 0.958 (z = 1.424, p = 0.154, CI = 0.242-3.781), indicating that mean adherence was slightly better in the presence of the intervention. Conclusions: SMS-support intervention has demonstrated superiority in influencing adherence. Further, health system-related factors have a significant influence on the adherence to chemotherapy treatment. Interventions to re-design health systems that are responsive to unmet care needs of cancer patients must be explored. .展开更多
为了进一步提高pAUC(Partial area under curve)估计精度和医学诊断测试精确性,提出了一种基于密度比模型的pAUC半参数估计方法,并从理论和仿真两个方面研究其性质。首先,根据密度比模型,用半参数极大似然估计方法得到了pAUC半参数估计...为了进一步提高pAUC(Partial area under curve)估计精度和医学诊断测试精确性,提出了一种基于密度比模型的pAUC半参数估计方法,并从理论和仿真两个方面研究其性质。首先,根据密度比模型,用半参数极大似然估计方法得到了pAUC半参数估计量,并用大样本理论分析了它的统计性能;然后,对pAUC半参数估计方法在实际应用中的性能进行了仿真,并与现有精度较高的pAUC非参数估计方法进行比较。研究发现,pAUC半参数估计量不仅具有相合渐近正态性等重要的统计性质,而且比已有的非参数pAUC估计量具有更高的渐近估计效率和精确度。将该pAUC半参数估计方法应用于乳腺癌诊断模型的筛选,得到了一个预测精度更高的新乳腺癌诊断模型,结果表明该方法在实际应用中能提高医学诊断测试的精度。展开更多
BACKGROUND The quality of warfarin therapy can be determined by the time in the therapeutic range(TTR)of international normalized ratio(INR).The estimated minimum TTR needed to achieve a benefit from warfarin therapy...BACKGROUND The quality of warfarin therapy can be determined by the time in the therapeutic range(TTR)of international normalized ratio(INR).The estimated minimum TTR needed to achieve a benefit from warfarin therapy is≥60%.AIM To determine TTR and the predictors of poor TTR among atrial fibrillation patients who receive warfarin therapy.METHODS A retrospective observational study was conducted at a cardiology referral center in Selangor,Malaysia.A total of 420 patients with atrial fibrillation and under follow-up at the pharmacist led Warfarin Medication Therapeutic Adherence Clinic between January 2014 and December 2018 were included.Patients’clinical data,information related to warfarin therapy,and INR readings were traced through electronic Hospital Information system.A data collection form was used for data collection.The percentage of days when INR was within range was calculated using the Rosendaal method.The poor INR control category was defined as a TTR<60%.Predictors for poor TTR were further determined by using logistic regression.RESULTS A total of 420 patients[54.0%male;mean age 65.7(10.9)years]were included.The calculated mean and median TTR were 60.6%±20.6%and 64%(interquartile range 48%-75%),respectively.Of the included patients,57.6%(n=242)were in the good control category and 42.4%(n=178)were in the poor control category.The annual calculated mean TTR between the year 2014 and 2018 ranged from 59.7%and 67.3%.A high HAS-BLED score of≥3 was associated with poor TTR(adjusted odds ratio,2.525;95%confidence interval:1.6-3.9,P<0.001).CONCLUSION In our population,a high HAS-BLED score was associated with poor TTR.This could provide an important insight when initiating an oral anticoagulant for these patients.Patients with a high HAS-BLED score may obtain less benefit from warfarin therapy and should be considered for other available oral anticoagulants for maximum benefit.展开更多
文摘This study explored and reviewed the logistic regression (LR) model, a multivariable method for modeling the relationship between multiple independent variables and a categorical dependent variable, with emphasis on medical research. Thirty seven research articles published between 2000 and 2018 which employed logistic regression as the main statistical tool as well as six text books on logistic regression were reviewed. Logistic regression concepts such as odds, odds ratio, logit transformation, logistic curve, assumption, selecting dependent and independent variables, model fitting, reporting and interpreting were presented. Upon perusing the literature, considerable deficiencies were found in both the use and reporting of LR. For many studies, the ratio of the number of outcome events to predictor variables (events per variable) was sufficiently small to call into question the accuracy of the regression model. Also, most studies did not report on validation analysis, regression diagnostics or goodness-of-fit measures;measures which authenticate the robustness of the LR model. Here, we demonstrate a good example of the application of the LR model using data obtained on a cohort of pregnant women and the factors that influence their decision to opt for caesarean delivery or vaginal birth. It is recommended that researchers should be more rigorous and pay greater attention to guidelines concerning the use and reporting of LR models.
文摘Due to the development of CT (Computed Tomography), MRI (Magnetic Resonance Imaging), PET (Positron Emission Tomography), EBCT (Electron Beam Computed Tomography), SMRI (Stereotactic Magnetic Resonance Imaging), etc. has enhanced the distinguishing rate and scanning rate of the imaging equipments. The diagnosis and the process of getting useful information from the image are got by processing the medical images using the wavelet technique. Wavelet transform has increased the compression rate. Increasing the compression performance by minimizing the amount of image data in the medical images is a critical task. Crucial medical information like diagnosing diseases and their treatments is obtained by modern radiology techniques. Medical Imaging (MI) process is used to acquire that information. For lossy and lossless image compression, several techniques were developed. Image edges have limitations in capturing them if we make use of the extension of 1-D wavelet transform. This is because wavelet transform cannot effectively transform straight line discontinuities, as well geographic lines in natural images cannot be reconstructed in a proper manner if 1-D transform is used. Differently oriented image textures are coded well using Curvelet Transform. The Curvelet Transform is suitable for compressing medical images, which has more curvy portions. This paper describes a method for compression of various medical images using Fast Discrete Curvelet Transform based on wrapping technique. After transformation, the coefficients are quantized using vector quantization and coded using arithmetic encoding technique. The proposed method is tested on various medical images and the result demonstrates significant improvement in performance parameters like Peak Signal to Noise Ratio (PSNR) and Compression Ratio (CR).
文摘Introduction: Cancer is a chronic debilitating disease that unnerves patients, communities, and nations. At some point in cancer patient’s disease experience, chemotherapy is used, and the patient is expected to adhere to treatment to improve survival and quality of life. Methods: This multisite Cluster Randomized Trial (CRT) evaluated the effectiveness of mobile phone Short Message Service (SMS) support on the adherence to treatment schedules among adult cancer patients in Kenya. Data was collected using questionnaires. Ethical approvals were obtained from relevant Ethical Review Boards (ERBs). Results: The mean adherence was 83%. There was a significant difference between treatment arms in relation to the adherence. The intervention arm had a higher mean adherence difference, M = 3.913, 95% CI 2.632-5.193, t (402) = 6.006, p ≤ 0.001), with Cohen’s d = 0.60. Although not significant, (χ<sup>2</sup>dd = 0.151, df = 1, p = 2.064), more women were perfect adheres than males. Perfect adherers were satisfied with SMS support (χ<sup>2</sup>dd = 7.620, df = 1, p = 0.06), were in the intervention arm (χ<sup>2</sup>dd = 22.942, df = 1, p ≤ 0.001), and had trust in the care provider (χ<sup>2</sup>dd = 10.591 p ≤ 0.001). SMS support was not significant in the multivariate analysis but had an estimated effect size of 0.958 (z = 1.424, p = 0.154, CI = 0.242-3.781), indicating that mean adherence was slightly better in the presence of the intervention. Conclusions: SMS-support intervention has demonstrated superiority in influencing adherence. Further, health system-related factors have a significant influence on the adherence to chemotherapy treatment. Interventions to re-design health systems that are responsive to unmet care needs of cancer patients must be explored. .
文摘为了进一步提高pAUC(Partial area under curve)估计精度和医学诊断测试精确性,提出了一种基于密度比模型的pAUC半参数估计方法,并从理论和仿真两个方面研究其性质。首先,根据密度比模型,用半参数极大似然估计方法得到了pAUC半参数估计量,并用大样本理论分析了它的统计性能;然后,对pAUC半参数估计方法在实际应用中的性能进行了仿真,并与现有精度较高的pAUC非参数估计方法进行比较。研究发现,pAUC半参数估计量不仅具有相合渐近正态性等重要的统计性质,而且比已有的非参数pAUC估计量具有更高的渐近估计效率和精确度。将该pAUC半参数估计方法应用于乳腺癌诊断模型的筛选,得到了一个预测精度更高的新乳腺癌诊断模型,结果表明该方法在实际应用中能提高医学诊断测试的精度。
文摘BACKGROUND The quality of warfarin therapy can be determined by the time in the therapeutic range(TTR)of international normalized ratio(INR).The estimated minimum TTR needed to achieve a benefit from warfarin therapy is≥60%.AIM To determine TTR and the predictors of poor TTR among atrial fibrillation patients who receive warfarin therapy.METHODS A retrospective observational study was conducted at a cardiology referral center in Selangor,Malaysia.A total of 420 patients with atrial fibrillation and under follow-up at the pharmacist led Warfarin Medication Therapeutic Adherence Clinic between January 2014 and December 2018 were included.Patients’clinical data,information related to warfarin therapy,and INR readings were traced through electronic Hospital Information system.A data collection form was used for data collection.The percentage of days when INR was within range was calculated using the Rosendaal method.The poor INR control category was defined as a TTR<60%.Predictors for poor TTR were further determined by using logistic regression.RESULTS A total of 420 patients[54.0%male;mean age 65.7(10.9)years]were included.The calculated mean and median TTR were 60.6%±20.6%and 64%(interquartile range 48%-75%),respectively.Of the included patients,57.6%(n=242)were in the good control category and 42.4%(n=178)were in the poor control category.The annual calculated mean TTR between the year 2014 and 2018 ranged from 59.7%and 67.3%.A high HAS-BLED score of≥3 was associated with poor TTR(adjusted odds ratio,2.525;95%confidence interval:1.6-3.9,P<0.001).CONCLUSION In our population,a high HAS-BLED score was associated with poor TTR.This could provide an important insight when initiating an oral anticoagulant for these patients.Patients with a high HAS-BLED score may obtain less benefit from warfarin therapy and should be considered for other available oral anticoagulants for maximum benefit.
