[Prediction of renal transplantation outcome using artificial neural networks and investigating important risk factors].

BACKGROUND: Renal Transplantation is the final choice for some patients with ESRD (End-Stage Renal Disease), but some transplantations suffer from acute or chronic rejection, so its very important to predict the outcome of transplantation. METHOD: s. The dataset was extracted from records of 4572 patients with kidney transplantations. We applied an Artificial Neural Network (ANN) model to predict transplantation outcome. Moreover, novel features have been explored which enhanced the prediction performance. RESULTS: The results show that the well configured neural networks can predict renal transplant outcome with a sensitivity and specificity of higher than 86%. The results show creatinine is the most important risk factor that affects the renal transplantation outcome. CONCLUSION: The designed neural networks can properly predict the transplantation outcome with the accuracy of 86%. Recipient creatinine is the most important variable in the prediction of the renal outcome.

Group-level comparison of brain connectivity networks.

BACKGROUND: Functional connectivity (FC) studies are often performed to discern different patterns of brain connectivity networks between healthy and patient groups. Since many neuropsychiatric disorders are related to the change in these patterns, accurate modelling of FC data can provide useful information about disease pathologies. However, analysing functional connectivity data faces several challenges, including the correlations of the connectivity edges associated with network topological characteristics, the large number of parameters in the covariance matrix, and taking into account the heterogeneity across subjects. METHODS: This study provides a new statistical approach to compare the FC networks between subgroups that consider the network topological structure of brain regions and subject heterogeneity. RESULTS: The power based on the heterogeneity structure of identity scaled in a sample size of 25 exhibited values greater than 0.90 without influencing the degree of correlation, heterogeneity, and the number of regions. This index had values above 0.80 in the small sample size and high correlation. In most scenarios, the type I error was close to 0.05. Moreover, the application of this model on real data related to autism was also investigated, which indicated no significant difference in FC networks between healthy and patient individuals. CONCLUSIONS: The results from simulation data indicated that the proposed model has high power and near-nominal type I error rates in most scenarios.

Survival analysis in gastric cancer: a multi-center study among Iranian patients.

BACKGROUND: Gastric cancer (GC) has been considered as the 5th most common type of cancer and the third leading cause of cancer-associated death worldwide. The aim of this historical cohort study was to evaluate the survival predictors for all patients with GC using the Cox proportional hazards, extended Cox, and gamma-frailty models. METHODS: This historical cohort study was performed according to documents of 1695 individuals having GC referred to three medical centers in Iran from 2001 to 2018. First, most significant prognostic risk factors on survival were selected, Cox proportional hazards, extended Cox, gamma-frailty models were applied to evaluate the effects of the risk factors, and then these models were compared with the Akaike information criterion. RESULTS: The age of patients, body mass index (BMI), tumor size, type of treatment and grade of the tumor increased the hazard rate (HR) of GC patients in both the Cox and frailty models (P < 0.05). Also, the size of the tumor and BMI were considered as time-varying variables in the extended Cox model. Moreover, the frailty model showed that there is at least an unknown factor, genetic or environmental factors, in the model that is not measured (P < 0.05). CONCLUSIONS: Some prognostic factors, including age, tumor size, the grade of the tumor, type of treatment and BMI, were regarded as indispensable predictors in patients of GC. Frailty model revealed that there are unknown or latent factors, genetic and environmental factors, resulting in the biased estimates of the regression coefficients.

Relationship between serum high sensitivity C-reactive protein with angiographic severity of coronary artery disease and traditional cardiovascular risk factors.

Serum high-sensitivity C-reactive protein (hs-CRP) is predictive of coronary artery disease (CAD). The aim of this study was to examine the possible association of hs-CRP with presence and severity of CAD and traditional CAD risk factors. This case-control study was carried out on 2,346 individuals from September 2011 to May 2013. Of these 1,187 had evidence of coronary disease, and were subject to coronary angiography, and the remainder were healthy controls (n = 1,159). Characteristics were determined using standard laboratory techniques and serum Hs-CRP levels were estimated using enzyme-linked immunosorbent assay (ELISA) kits, and severity of CAD was assessed according to the score of obstruction in coronary artery. Serum hs-CRP levels were higher in those with severe coronary disease, who had stenosis ≥ 50% stenosis of at least one coronary artery (all p < 0.001 vs. individuals in healthy control), and correlated significantly with the score for coronary artery disease (all p < 0.01). After adjustment for conventional risk factors, regression analysis revealed that smoking habits, fasting blood glucose, total cholesterol, high-density lipoprotein, hs-CRP, blood pressure, anxiety, dietary intake of vitamin E, and cholesterol remained as independent determinants for angiographic severity of CAD. The area under the receiving operating characteristic (ROC) curve for serum hs-CRP was 0.869 (CI 95% 0.721-0.872, p < 0.001). The optimal values for the cut-off point was a serum hs-CRP of 2.78 mg/l (sensitivity 80.20%, specificity 85%) to predict severity of CAD. Increased serum hs-CRP levels are significantly associated with angiographic severity of CAD, suggesting its value as a biomarkers for predicting CAD.

Novoglan device for treatment of adult phimosis: Novoglan-01 open-label clinical trial on safety, efficacy and tolerability.

Background: At present, the only definitive treatment for adult phimosis is circumcision, which is a surgical removal of the prepuce. Novoglan is a novel device that could offer patients with phimosis an alternative to surgery. It is based on application of custom-moulded balloons for gradual skin remodelling and prepuce dilatation. This open-label clinical trial aimed to investigate the safety, efficacy and tolerability of the Novoglan treatment. Methods: A prospective trial was conducted on 20 patients with adult phimosis recruited at Macquarie University Hospital and Princess Alexandra Hospital. After eligibility screening and enrolment, patients were provided with the Novoglan product and training. The treatment involved twice daily 10-minute applications for a duration of 4-8 weeks with patient's degree of phimosis assessed before and at 6-8 weeks after the initiation of the treatment. Participants were also asked to complete questionnaires aimed to assess the safety and tolerability of the Novoglan treatment. Results: The treatment was successful with improved foreskin retraction in 90% of patients and all patients achieving full foreskin retraction after the treatment. Ninety-five percent of patients reported reduced level of anxiety, and over 60% of patients reported reduced pain/discomfort during sexual activity or in general. Similarly, 95% of patients were moderately-to-very satisfied with the treatment and would recommend Novoglan to others. No adverse events were observed and only 15% of participants reported minor side effects. Conclusions: The Novoglan-01 trial demonstrated high safety, efficacy and tolerability of the Novoglan treatment for adult phimosis and its high potential as a conservative alternative to circumcision or steroid cream treatment. Trial Registration: The Novoglan-01 study has been registered with the Australia and New Zealand Clinical Trial Registry under the reference ACTRN 1262 10009 24853, dated 15 July 2021.

The trend analysis of neurological disorders as major causes of death and disability according to human development, 1990-2019.

This study aims to assess the trends in the incidence rate of neurological disorders in developed and developing countries worldwide during 1990-2019. The age-standardized incidence rate (per 100000 persons) of neurological disorders was the primary outcome, extracted from the Global Burden of Disease database for 189 countries and territories from 1990 to 2019. Using the Human Development Index (HDI), countries were classified into developed (HDI ≥ 0.7) and developing (HDI < 0.7) groups. Longitudinal analysis was performed using the Latent Growth Model (LGM) to assess the change in the incidence rate of neurological disorders over time in these groups. In developed countries, the most increasing rate is related to depressive disorders, with a rising rate of 40.15 in 100000 every five years (p = 0.001). Alzheimer's and dementia, Parkinson and multiple sclerosis are in the next rank, with increasing rates of 8.77, 1.24, and .02, respectively (all p < 0.001). Over time, the significant decreasing trend has been determined related to conducting disorder, attention-deficit and hyperactivity, meningitis, anxiety, and eating disorders, with the rates of - 13.92, - 4.96, - 2.7, - 1.6, and - 1.44, respectively (all p < 0.05). In developing countries, meningitis, conduct disorder, attention-deficit and hyperactivity, stroke, and autism spectrum showed a significant decreasing trend over time, with rates of - 15.45, - 5.84, - 2.56, - 1.86, and - 1.07, respectively (all p < 0.05). Headache disorder has the most increasing rate of 79.5, following depressive (rate 35.32), substance use (rate 14.99), anxiety (rate 7.18), and eating (rate 3.4) disorders. Also, Alzheimer's and dementia, bipolar disorder, schizophrenia, Parkinson's, brain and central nervous system cancer, and multiple sclerosis are in the next rank and had significant increasing trends (all p < 0.05). Given the high economic and social burden of neurological disorders, the rate of these diseases in most countries does not seem to have dropped remarkably. The heterogeneous incidence rate in some world countries seems to be due to underestimating and gaps in epidemiological information. It is necessary to provide exact registry systems for health policies, especially in developing countries.

Post-saccadic Eye Movement Indices Under Cognitive Load: A Path Analysis to Determine Visual Performance.

Purpose: The evidence on the linear relationship between cognitive load, saccade, fixation, and task performance was uncertain. We tested pathway models for degraded task performance resulting from changes in saccadic and post-saccadic fixation under cognitive load. Methods: Participants' (n = 38) eye movements were recorded using a post-saccadic discrimination task with and without arithmetic operations to impose cognitive load, validated through recording heart rate variability and subjective measurement. Results: Results showed that cognitive load led to longer latencies of saccade and fixation; more inaccurate responses and fewer secondary saccades (P < 0.001). Longer saccade latencies influenced task performance indirectly via increases in fixation latency, therefore, longer reaction times and higher response errors were observed due to limited fixation duration on desired target. Conclusion: We suggest that latency and duration of fixation indicate efficiency of information processing and can predict the speed and accuracy of task performance under cognitive load.

Development of web-based dynamic nomogram to predict survival in patients with gastric cancer: a population-based study.

Gastric cancer (GC) is the fifth most frequent malignancy worldwide and the third leading cause of cancer-associated mortality. The study's goal was to construct a predictive model and nomograms to predict the survival of GC patients. This historical cohort study assessed 733 patients who underwent treatments for GC. The univariate and multivariable Cox proportional hazard (CPH) survival analyses were applied to identify the factors related to overall survival (OS). A dynamic nomogram was developed as a graphical representation of the CPH regression model. The internal validation of the nomogram was evaluated by Harrell's concordance index (C-index) and time-dependent AUC. The results of the multivariable Cox model revealed that the age of patients, body mass index (BMI), grade of tumor, and depth of tumor elevate the mortality hazard of gastric cancer patients (P < 0.05). The built nomogram had a discriminatory performance, with a C-index of 0.64 (CI 0.61, 0.67). We constructed and validated an original predictive nomogram for OS in patients with GC. Furthermore, nomograms may help predict the individual risk of OS in patients treated for GC.

Attributes of Organizational Health Literacy in Health Care Centers in Iran: A Qualitative Content Analysis Study.

Organizational Health Literacy (OHL) is described as a new concept to remote health organizations to implement practices, policies, and systems that make it easier for patients to use, understand, and navigate health information to take care their own health. In Iran, there is no consensus on the attributes of OHL, and its practical implications and scope have not been evaluated. This manuscript is one of the first attempts to explain the attributes of the OHL in health care centers in Iran. This study is a content analysis survey, which was guided by the attributes of the OHL provided by Brach et al. and 26 semi-structured interviews were conducted with Iranian health professionals and employees of healthcare organizations from June 2020 to January 2021. A data analysis was performed using the MAXQDA 10 software. Across the study, ten sub-themes, 21 subcategories, and 67 codes emerged. The 10 main attributes of OHL were management, integration of health literacy in the organization, workforce, participation, range of HL skills, HL strategies, access, media variety, the role of the organization in crisis, and costs. These attributes may guide the planning of health care centers improvements and have the potential to promote health service reforms and public health policy.

Impact of Best-Fitted Control Selection on Effect Size: An Example in Functional GI Disorder Case-Control Studies.

BACKGROUND: Effect sizes are the most useful quantities for communicating the practical significance of results and helping to facilitate cumulative science. We hypothesize that the selection of the best-fitted controls can significantly affect the estimated effect sizes in case-control studies. Therefore, we decided to exemplify and clarify this effect on effect size using a large data set. The objective of this study was to investigate the association among variables in functional gastrointestinal disorders (FGIDs) and mental health problems, common ailments that reduce the quality of life of a large proportion of the community worldwide. METHOD: In this methodological study, we constitute case and control groups in our study framework using the Epidemiology of Psychological, Alimentary Health and Nutrition (SEPAHAN) dataset of 4763 participants. We devised four definitions for control in this extensive database of FGID patients and analyzed the effect of these definitions on the odds ratio (OR): 1. conventional control: without target disorder/syndrome (sample size 4040); 2. without any positive criteria: criterion-free control (sample size 1053); 3. syndrome-free control: without any disorder/syndrome (sample size 847); 4. symptom-free control: without any symptoms (sample size 204). We considered a fixed case group that included 723 patients with a Rome III-based definition of functional dyspepsia. Psychological distress, anxiety, and depression were considered as dependent variables in the analysis. Logistic regression was used for association analysis, and the odds ratio and 95% confidence interval (95%CI) for OR were reported as the effect size. RESULTS: The estimated ORs indicate that the strength of the association in the first case-control group is the lowest, and the fourth case-control group, including controls with completely asymptomatic people, is the highest. Ascending effect sizes were obtained in the conventional, criterion-free, syndrome-free, and symptom-free control groups. These results are consistent for all three psychological disorders, psychological distress, anxiety, and depression. CONCLUSIONS: This study shows that a precise definition of the control is mandatory in every case-control study and affects the estimated effect size. In clinical settings, the selection of symptomatic controls using the conventional definition could significantly diminish the effect size.

An Analysis of the Areas Occupied by Vessels in the Ocular Surface of Diabetic Patients: An Application of a Nonparametric Tilted Additive Model.

(1) Background: As diabetes melllitus (DM) can affect the microvasculature, this study evaluates different clinical parameters and the vascular density of ocular surface microvasculature in diabetic patients. (2) Methods: In this cross-sectional study, red-free conjunctival photographs of diabetic individuals aged 30-60 were taken under defined conditions and analyzed using a Radon transform-based algorithm for vascular segmentation. The Areas Occupied by Vessels (AOV) images of different diameters were calculated. To establish the sum of AOV of different sized vessels. We adopt a novel approach to investigate the association between clinical characteristics as the predictors and AOV as the outcome, that is Tilted Additive Model (TAM). We use a tilted nonparametric regression estimator to estimate the nonlinear effect of predictors on the outcome in the additive setting for the first time. (3) Results: The results show Age (p-value = 0.019) and Mean Arterial Pressure (MAP) have a significant linear effect on AOV (p-value = 0.034). We also find a nonlinear association between Body Mass Index (BMI), daily Urinary Protein Excretion (UPE), Hemoglobin A1C, and Blood Urea Nitrogen (BUN) with AOV. (4) Conclusions: As many predictors do not have a linear relationship with the outcome, we conclude that the TAM will help better elucidate the effect of the different predictors. The highest level of AOV can be seen at Hemoglobin A1C of 9% and AOV increases when the daily UPE exceeds 600 mg. These effects need to be considered in future studies of ocular surface vessels of diabetic patients.

Regularized Weighted Nonparametric Likelihood Approach for High-Dimension Sparse Subdistribution Hazards Model for Competing Risk Data.

Variable selection and penalized regression models in high-dimension settings have become an increasingly important topic in many disciplines. For instance, omics data are generated in biomedical researches that may be associated with survival of patients and suggest insights into disease dynamics to identify patients with worse prognosis and to improve the therapy. Analysis of high-dimensional time-to-event data in the presence of competing risks requires special modeling techniques. So far, some attempts have been made to variable selection in low- and high-dimension competing risk setting using partial likelihood-based procedures. In this paper, a weighted likelihood-based penalized approach is extended for direct variable selection under the subdistribution hazards model for high-dimensional competing risk data. The proposed method which considers a larger class of semiparametric regression models for the subdistribution allows for taking into account time-varying effects and is of particular importance, because the proportional hazards assumption may not be valid in general, especially in the high-dimension setting. Also, this model relaxes from the constraint of the ability to simultaneously model multiple cumulative incidence functions using the Fine and Gray approach. The performance/effectiveness of several penalties including minimax concave penalty (MCP); adaptive LASSO and smoothly clipped absolute deviation (SCAD) as well as their L2 counterparts were investigated through simulation studies in terms of sensitivity/specificity. The results revealed that sensitivity of all penalties were comparable, but the MCP and MCP-L2 penalties outperformed the other methods in term of selecting less noninformative variables. The practical use of the model was investigated through the analysis of genomic competing risk data obtained from patients with bladder cancer and six genes of CDC20, NCF2, SMARCAD1, RTN4, ETFDH, and SON were identified using all the methods and were significantly correlated with the subdistribution.

The Health Literacy Status and Its Role in Interventions in Iran: A Systematic and Meta-Analysis.

There are increasing calls for public health policies to realize the visions of a health literate society and health literacy on a global scale. However, there are still more gaps in what researchers recognize and what steps they should take to improve health literacy (HL) skills. This review aimed to measure the HL status of the Iranian population and the effect size of the underlying association between HL and other health outcomes, and to examine the effectiveness of HL interventions on improving the functional dimension of HL, self-efficacy, and health-promoting behaviors. All full text published articles written in English and Persian language were included from inception until January 2019, but the type of study is not limited. A total of 52 potentially relevant articles with data on 36,523 participants were included in this review. In the population with health conditions, the average HL score was 62.51 (95% CI: 59.95-65.08), while in the patient population, the HL score was 64.04 (95% CI: 60.64-67.45). Health literacy was positively and significantly correlated with self-care behaviors 0.42 (95% CI; 0.35-0.49), self-efficacy 0.35 (95% CI; 0.26-0.43), knowledge 0.50 (95% CI; 0.44-0.55), communication skills 0.33 (95% CI; 0.25-0.41), and health promotion behaviors 0.39 (95% CI; 0.35-0.44). The meta-analyses showed that overall, HL interventions significantly improved HL status, self-efficacy, and health promotion behaviors. Results indicate that HL status was in the range of marginal HL level in the Iranian population. Our finding highlights the beneficial impact of HL intervention on health-promoting behaviors and self-efficacy, particularly in low literacy/socioeconomic status people.

Nomogram to Predict the Overall Survival of Colorectal Cancer Patients: A Multicenter National Study.

BACKGROUND: Colorectal cancer (CRC) is the third foremost cause of cancer-related death and the fourth most commonly diagnosed cancer globally. The study aimed to evaluate the survival predictors using the Cox Proportional Hazards (CPH) and established a novel nomogram to predict the Overall Survival (OS) of the CRC patients. MATERIALS AND METHODS: A historical cohort study, included 1868 patients with CRC, was performed using medical records gathered from Iran's three tertiary colorectal referral centers from 2006 to 2019. Two datasets were considered as train set and one set as the test set. First, the most significant prognostic risk factors on survival were selected using univariable CPH. Then, independent prognostic factors were identified to construct a nomogram using the multivariable CPH regression model. The nomogram performance was assessed by the concordance index (C-index) and the time-dependent area under the ROC curve. RESULTS: The age of patients, body mass index (BMI), family history, tumor grading, tumor stage, primary site, diabetes history, T stage, N stage, and type of treatment were considered as significant predictors of CRC patients in univariable CPH model (p < 0.2). The multivariable CPH model revealed that BMI, family history, grade and tumor stage were significant (p < 0.05). The C-index in the train data was 0.692 (95% CI, 0.650-0.734), as well as 0.627 (0.670, 0.686) in the test data. CONCLUSION: We improved a novel nomogram diagram according to factors for predicting OS in CRC patients, which could assist clinical decision-making and prognosis predictions in patients with CRC.

Impact of Self-Efficacy Strategies Education on Self-Care Behaviors among Heart Failure Patients.

Background: Self-efficacy in self-care behaviors is an effective framework for measuring patients' degree of ability to perform self-care behaviors that significantly affect their recovery process and quality of life. This study was designed to investigate the effects of education based on self-efficacy strategies on self-care behaviors in heart failure patients. Methods: A semi-experimental study was conducted on 80 heart failure patients divided into 2 equal groups of test and control. The intervention group received three 60-minute practical and theoretical training sessions based on self-care and self-efficacy strategies, while the control group received the usual care services. Self-care behaviors and self-efficacy were evaluated before training, shortly after training, and 3 months after the training program using the Sullivan self-efficacy questionnaire for heart failure patients and the European self-care behaviors questionnaires. Results: The mean age of the patients was 55.00±8.48 and 51.61±8.51 years in the intervention and control groups, respectively. Women comprised 73.7% (n=59) of the study population. The mean score for the self-care and self-efficacy questionnaires in the experimental group was 23.50±6.58 and 18.57±6.64, correspondingly, before the intervention, which increased to 42.64±6.74 (P<0.014) and 32.29±7.06 (P<0.001), respectively, shortly after the intervention. A significant improvement also occurred at 3 months' follow-up (P<0.001). Self-care behaviors also revealed a positive correlation with self-efficacy shortly after the intervention (r=0.82, P<0.001) and 3 months after the intervention (r=0.85, P<0.001). Conclusion: The implementation of educational interventions based on self-efficacy strategies could have positive effects on health-promoting behaviors among heart failure patients.

Review of Organizational Health Literacy Practice at Health Care Centers: Outcomes, Barriers and Facilitators.

The term organizational health literacy (OHL) is a new concept that emerged to address the challenge of predominantly in patients with limited health literacy (HL). There is no consensus on how OHL can improve HL activities and health outcomes in healthcare organizations. In this study, a systematic review of the literature was conducted to understand the evidence for the effectiveness of OHL and its health outcome, and the facilitators and barriers that influence the implementation of OHL. A literature search was done using six databases, the gray literature method and reference hand searches. Thirteen potentially articles with data on 1254 health organizations were included. Eight self-assessment tools and ten OHL attributes have been identified. Eleven quality-improvement characteristics and 15 key barriers were reviewed. Evidence on the effectiveness of HL tools provides best practices and recommendations to enhance OHL capacities. Results indicated that shifting to a comprehensive OHL would likely be a complex process because HL is not usually integrated into the healthcare organization's vision and strategic planning. Further development of OHL requires radical, simultaneous, and multiple changes. Thus, there is a need for the healthcare system to consider HL as an organizational priority, that is, be responsive.

Bayesian Spatial Survival Analysis of Duration to Cure among New Smear-Positive Pulmonary Tuberculosis (PTB) Patients in Iran, during 2011-2018.

Mycobacterium tuberculosis is the causative agent of tuberculosis (TB), and pulmonary TB is the most prevalent form of the disease worldwide. One of the most concrete actions to ensure an effective TB control program is monitoring TB treatment outcomes, particularly duration to cure; but, there is no strong evidence in this respect. Thus, the primary aim of this study was to examine the possible spatial variations of duration to cure and its associated factors in Iran using the Bayesian spatial survival model. All new smear-positive PTB patients have diagnosed from March 2011 to March 2018 were included in the study. Out of 34,744 patients, 27,752 (79.90%) patients cured and 6992 (20.10%) cases were censored. For inferential purposes, the Markov chain Monte Carlo algorithms are applied in a Bayesian framework. According to the Bayesian estimates of the regression parameters in the proposed model, a Bayesian spatial log-logistic model, the variables gender (male vs. female, TR = 1.09), altitude (>750 m vs. ≤750 m, TR = 1.05), bacilli density in initial smear (3+ and 2+ vs. 1-9 Basil & 1+, TR = 1.09 and TR = 1.02, respectively), delayed diagnosis (>3 months vs. <1 month, TR = 1.02), nationality (Iranian vs. other, TR = 1.02), and location (urban vs. rural, TR = 1.02) had a significant influence on prolonging the duration to cure. Indeed, pretreatment weight (TR = 0.99) was substantially associated with shorter duration to cure. In summary, the spatial log-logistic model with convolution prior represented a better performance to analyze the duration to cure of PTB patients. Also, our results provide valuable information on critical determinants of duration to cure. Prolonged duration to cure was observed in provinces with low TB incidence and high average altitude as well. Accordingly, it is essential to pay a special attention to such provinces and monitor them carefully to reduce the duration to cure while maintaining a focus on high-risk provinces in terms of TB prevalence.

A Comparison between Decision Tree and Random Forest in Determining the Risk Factors Associated with Type 2 Diabetes.

BACKGROUND: We aimed to identify the associated risk factors of type 2 diabetes mellitus (T2DM) using data mining approach, decision tree and random forest techniques using the Mashhad Stroke and Heart Atherosclerotic Disorders (MASHAD) Study program. STUDY DESIGN: A cross-sectional study. METHODS: The MASHAD study started in 2010 and will continue until 2020. Two data mining tools, namely decision trees, and random forests, are used for predicting T2DM when some other characteristics are observed on 9528 subjects recruited from MASHAD database. This paper makes a comparison between these two models in terms of accuracy, sensitivity, specificity and the area under ROC curve. RESULTS: The prevalence rate of T2DM was 14% among these subjects. The decision tree model has 64.9% accuracy, 64.5% sensitivity, 66.8% specificity, and area under the ROC curve measuring 68.6%, while the random forest model has 71.1% accuracy, 71.3% sensitivity, 69.9% specificity, and area under the ROC curve measuring 77.3% respectively. CONCLUSIONS: The random forest model, when used with demographic, clinical, and anthropometric and biochemical measurements, can provide a simple tool to identify associated risk factors for type 2 diabetes. Such identification can substantially use for managing the health policy to reduce the number of subjects with T2DM .

Providing an imputation algorithm for missing values of longitudinal data using Cuckoo search algorithm: A case study on cervical dystonia.

BACKGROUND: Missing values in data are found in a large number of studies in the field of medical sciences, especially longitudinal ones, in which repeated measurements are taken from each person during the study. In this regard, several statistical endeavors have been performed on the concepts, issues, and theoretical methods during the past few decades. METHODS: Herein, we focused on the missing data related to patients excluded from longitudinal studies. To this end, two statistical parameters of similarity and correlation coefficient were employed. In addition, metaheuristic algorithms were applied to achieve an optimal solution. The selected metaheuristic algorithm, which has a great search functionality, was the Cuckoo search algorithm. RESULTS: Profiles of subjects with cervical dystonia (CD) were used to evaluate the proposed model after applying missingness. It was concluded that the algorithm used in this study had a higher accuracy (98.48%), compared with similar approaches. CONCLUSION: Concomitant use of similar parameters and correlation coefficients led to a significant increase in accuracy of missing data imputation.

Distribution of Different Sized Ocular Surface Vessels in Diabetics and Normal Individuals.

PURPOSE: To compare the distribution of different sized vessels using digital photographs of the ocular surface of diabetic and normal individuals. METHODS: In this cross-sectional study, red-free conjunctival photographs of diabetic and normal individuals, aged 30-60 years, were taken under defined conditions and analyzed using a Radon transform-based algorithm for vascular segmentation. The image areas occupied by vessels (AOV) of different diameters were calculated. The main outcome measure was the distribution curve of mean AOV of different sized vessels. Secondary outcome measures included total AOV and standard deviation (SD) of AOV of different sized vessels. RESULTS: Two hundred and sixty-eight diabetic patients and 297 normal (control) individuals were included, differing in age (45.50 ± 5.19 vs. 40.38 ± 6.19 years, P < 0.001), systolic (126.37 ± 20.25 vs. 119.21 ± 15.81 mmHg, P < 0.001) and diastolic (78.14 ± 14.21 vs. 67.54 ± 11.46 mmHg, P < 0.001) blood pressures. The distribution curves of mean AOV differed between patients and controls (smaller AOV for larger vessels in patients; P < 0.001) as well as between patients without retinopathy and those with non-proliferative diabetic retinopathy (NPDR); with larger AOV for smaller vessels in NPDR (P < 0.001). Controlling for the effect of confounders, patients had a smaller total AOV, larger total SD of AOV, and a more skewed distribution curve of vessels compared to controls. CONCLUSION: Presence of diabetes mellitus is associated with contraction of larger vessels in the conjunctiva. Smaller vessels dilate with diabetic retinopathy. These findings may be useful in the photographic screening of diabetes mellitus and retinopathy.