Predicting survival of Iranian COVID-19 patients infected by various variants including omicron from CT Scan images and clinical data using deep neural networks

Purpose: The rapid spread of the COVID-19 omicron variant virus has resulted in an overload of hospitals around the globe. As a result, many patients are deprived of hospital facilities, increasing mortality rates. Therefore, mortality rates can be reduced by efficiently assigning facilities to higher-risk patients. Therefore, it is crucial to estimate patients' survival probability based on their conditions at the time of admission so that the minimum required facilities can be provided, allowing more opportunities to be available for those who need them. Although radiologic findings in chest computerized tomography scans show various patterns, considering the individual risk factors and other underlying diseases, it is difficult to predict patient prognosis through routine clinical or statistical analysis. Method: In this study, a deep neural network model is proposed for predicting survival based on simple clinical features, blood tests, axial computerized tomography scan images of lungs, and the patients' planned treatment. The model's architecture combines a Convolutional Neural Network and a Long Short Term Memory network. The model was trained using 390 survivors and 108 deceased patients from the Rasoul Akram Hospital and evaluated 109 surviving and 36 deceased patients infected by the omicron variant. Results: The proposed model reached an accuracy of 87.5% on the test data, indicating survival prediction possibility. The accuracy was significantly higher than the accuracy achieved by classical machine learning methods without considering computerized tomography scan images (p-value <= 4E-5). The images were also replaced with hand-crafted features related to the ratio of infected lung lobes used in classical machine-learning models. The highest-performing model reached an accuracy of 84.5%, which was considerably higher than the models trained on mere clinical information (p-value <= 0.006). However, the performance was still significantly less than the deep model (p-value <= 0.016). Conclusion: The proposed deep model achieved a higher accuracy than classical machine learning methods trained on features other than computerized tomography scan images. This proves the images contain extra information. Meanwhile, Artificial Intelligence methods with multimodal inputs can be more reliable and accurate than computerized tomography severity scores.

The Internet of Medical Things: Opportunities, Benefits, Challenges and Concerns

In this narrative review, we investigate the potential opportunities and benefits, as well as the challenges and concerns of integrating the Internet of Things in healthcare. The opportunities include enhanced patient monitoring and management, improved efficiency and resource utilization, personalized and precision medicine, empowering patients and promoting self-management, and data-driven decision-making, while the challenges include security and privacy risks, interoperability and integration, regulatory and compliance issues, ethical considerations and impact on healthcare professionals and patients. These challenges must be carefully weighed against the benefits before deployment of the IoMT-enabled services.

How Interoperability Challenges Are Addressed in Healthcare IoT Projects

The rapid development and implementation of Internet of Medical Things has made interoperability a serious challenge. In this scoping review, we provide an overview of the interoperability challenge, as reported in the health literature, and highlight the proposed solutions. After searching between January 2018 and June 2023 in Compendex via Engineering Village and PubMed, we found 18 publications. The interoperability challenges identified were device heterogeneity, system heterogeneity, data standardization, security and safety, system and architecture standard, system and workflow integration and regulatory and compliance requirements. Solutions included ontology approaches, conceptual semantic frameworks, improved standards, design of middleware, and using blockchain technology.

Clinical Decision Support Systems for Brain Tumour Diagnosis and Prognosis: A Systematic Review

CDSSs are being continuously developed and integrated into routine clinical practice as they assist clinicians and radiologists in dealing with an enormous amount of medical data, reduce clinical errors, and improve diagnostic capabilities. They assist detection, classification, and grading of brain tumours as well as alert physicians of treatment change plans. The aim of this systematic review is to identify various CDSSs that are used in brain tumour diagnosis and prognosis and rely on data captured by any imaging modality. Based on the 2020 preferred reporting items for systematic reviews and meta-analyses (PRISMA) protocol, the literature search was conducted in PubMed and Engineering Village Compendex databases. Different types of CDSSs identified through this review include Curiam BT, FASMA, MIROR, HealthAgents, and INTERPRET, among others. This review also examines various CDSS tool types, system features, techniques, accuracy, and outcomes, to provide the latest evidence available in the field of neuro-oncology. An overview of such CDSSs used to support clinical decision-making in the management and treatment of brain tumours, along with their benefits, challenges, and future perspectives has been provided. Although a CDSS improves diagnostic capabilities and healthcare delivery, there is lack of specific evidence to support these claims. The absence of empirical data slows down both user acceptance and evaluation of the actual impact of CDSS on brain tumour management. Instead of emphasizing the advantages of implementing CDSS, it is important to address its potential drawbacks and ethical implications. By doing so, it can promote the responsible use of CDSS and facilitate its faster adoption in clinical settings.

Interoperable E-Health System Using Structural and Semantic Interoperability Approaches in CAREPATH

Technical and semantic interoperability are broadly used components of interoperability technology in healthcare. Technical Interoperability provides interoperability interfaces to enable data exchange within different healthcare systems, despite any underlying heterogeneity. Semantic interoperability make different healthcare systems understand and interpret the meaning of the data that is exchanged, by using and mapping standardized terminologies, coding systems, and data models to describe the concept and structure of data. We propose a solution using Semantic and Structural Mapping techniques within CAREPATH; a research project designed to develop ICT solutions for the care management of elderly multimorbid patients with mild cognitive impairment or mild dementia. Our technical interoperability solution supplies a standard-based data exchange protocol to enable information exchange between local care systems and CAREPATH components. Our semantic interoperability solution supplies programmable interfaces, in order to semantically mediate different clinical data representation formats and incorporating data format and terminology mapping features. The solution offers a more reliable, flexible and resource efficient method across EHRs.

How Do Iranian Researchers Measure Spirituality in Health Studies? A Scoping Review

Background

Despite the existing literature on the effect of spirituality on health, lack of consensus on definition and evaluation methods are major barriers to applying the results of these studies. In this scoping review, we intend to identify the instruments used for evaluating spirituality in health in Iran and evaluate their domains.

Methods

We searched PubMed, Scopus and Web of Science, Islamic World Science Citation Center, Scientific Information Database, and Magiran between 1994 and 2020. We then identified the questionnaires and searched for the original article reporting the development or translation, as well as the psychometric evaluation process. We extracted data on their type (developed/translated), and other psychometric properties. Finally, we categorized the questionnaires accordingly.

Results

After selecting the studies and evaluating the questionnaires, we identified 33 questionnaires evaluating religiosity (10 questionnaires), spiritual health (8 questionnaires), spirituality (5 questionnaires), religious attitude (4 questionnaires), spiritual need (3 questionnaires) and spiritual coping (3 questionnaires). Other existing questionnaires had issues in the development or translation process or lacked reported psychometric evaluations.

Conclusion

Many questionnaires have been used in spiritual health studies in the Iranian population. These questionnaires cover different subscales according to their theoretical base and the developers' perspectives. Researchers should be informed about these aspects of the questionnaires and select the instruments meticulously based on the aim of their study and the characteristics of the questionnaires.

Improving data adequacy of ultrasonography reports for non-alcoholic fatty liver disease (NAFLD) through a national structured template

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) is a prevalent disorder that increases due to lifestyle, the rising rate of obesity, and population ages worldwide. Diagnostic ways, including sonography, do not have an explicit reporting structure.

PURPOSE

To create a structure template for NAFLD reporting, investigate its completeness, and assess the specialist opinions of using it in clinical practice.

MATERIAL AND METHODS

A structured reporting template (SRT) was designed and implemented in four stages. At first, important features were extracted from a comprehensive literature review and were evaluated by 10 radiologists and gastroenterologists using the Likert scale. Finally, the usefulness of the SRT in comparison with the conventional reporting template (CRT) was judged by 10 gastroenterologists completing the questionnaire.

RESULTS

Demographic information and sonography of the liver, gallbladder, and spleen organs were the most critical features. The completeness scores of SRT reports were higher than CRT scores for almost all the factors studied. The difference in the scores was significant for most of the parameters. Moreover, the total completeness score increased from 42% in CRT to 92% in SRT. A comparison of the report adequacy of two reports was seen in all items. The SRT obtained more rates from specialists.

CONCLUSION

Introduction of the SRT for NAFLD significantly enhanced the completeness of reporting to reduce variability in the interpretation of the related reports by clinicians. Nevertheless, more studies are needed to generalize the results in real scales for patients with NAFLD.

Preliminary report of Iranian Registry of Alzheimer's disease in Tehran province: A cross‐sectional study in Iran

Background and Aims

Alzheimer's disease (AD) is the main cause of dementia and over the 55 million people live with dementia worldwide. We aimed to establish the first database called the Iranian Alzheimer's Disease Registry to create a powerful source for future research in the country. In this report, the design and early results of the Iranian Alzheimer's Disease Registry will be described.

Methods

We performed this multicenter investigation and patients' data including age, sex, educational level, disease status, Mini‐Mental State Examination (MMSE), and Geriatric Depression Scale (GDS) from 2018 to 2021 were collected, registered, and analyzed by GraphPad Prism software.

Results

Totally 200 AD patients were registered in our database. 107 (54%) were women and age of 147 (74%) were over 65. The mean age for men and women was 76.20 ± 8.29 and 76.40 ± 8.83 years, respectively. 132 (66%) were married and 64 (32%) were illiterate. Also, 94 (47%) were in the moderate stage of disease, and 150 (75%) lived at home together with their families. The most frequent neurological comorbidity was psychosis (n = 72, 36%), while hypertension was the most common non‐neurological comorbidity (n = 104, 52%). The GDS score of women in the mild stage (5.23 ± 2.9 vs. 6.9 ± 2.6, p = 0.005) and moderate stage (5.36 ± 2.4 vs. 8.21 ± 2.06, p = <0.001) of the disease was significantly greater than men. In univariate analysis, MMSC score was remarkably associated with stroke (β = −2.25, p = 0.03), psychosis (β = −2.18, p = 0.009), diabetes (β = 3.6, p = <0.001), and hypercholesteremia (β = 1.67, p = 0.05). Also, the MMSE score showed a notable relationship with stroke (β = −2.13, p = 0.05) and diabetes (β = 3.26, p = <0.001) in multivariate analysis.

Conclusion

Iranian Alzheimer's Disease Registry can provide epidemiological and clinical data to use for purposes such as enhancing the current AD management in clinical centers, filling the gaps in preventative care, and establishing effective monitoring and cure for the disease.

CAREPATH: Developing Digital Integrated Care Solutions for Multimorbid Patients with Dementia

CAREPATH project is focusing on providing an integrated solution for sustainable care for multimorbid elderly patients with dementia or mild cognitive impairment. The project has a digitally enhanced integrated patient-centered care approach clinical decision and associated intelligent tools with the aim to increase patients' independence, quality of life and intrinsic capacity. In this paper, the conceptual aspects of the CAREPATH project, in terms of technical and clinical requirements and considerations, are presented.

HIV prevalence among men who have sex with men in Iran: A systematic review and meta-analysis

Background: The need for informed policymaking highlights the importance of data on human immunodeficiency virus (HIV) prevalence on key populations. In this systematic review and meta-analysis, we aimed to provide an overview of HIV prevalence in men who have sex with men (MSM) in Iran.

Methods: We searched literature published between January 2008 and December 2019 to identify studies reporting the prevalence of HIV infection or acquired immunodeficiency syndrome (AIDS) in a population of adult Iranian men with history of sexual contact with other men. We employed Metaprop command in Stata to pool proportions from different studies.

Results: Among the 16 studies retrieved, 2 were performed on MSM population directly, 7 among people who inject drugs, 4 among prisoners, 2 among the homeless, and 1 among methamphetamine users. HIV prevalence was 7% (95% CI, 5%-10%) based on the meta-analysis, although noticeable heterogeneity existed because of target population, study year, and study location, which imposed limitations to provide a robust summary measure for the prevalence of HIV.

Conclusion: There is a potential risk of observing a high prevalence of HIV in MSM that could hamper the results of various preventive strategies and their achievements in other subpopulations.

A multi-centre survey on hospital malnutrition: result of PNSI study

Background

Disease-related malnutrition is associated with adverse outcomes such as increased rates of morbidity and mortality, prolonged hospital stay, and extra costs of health care. This study was conducted to assess nutritional status among patients and to determine the risk factors for malnutrition in Iran university f.

Methods

Persian Nutritional Survey In Hospitals (PNSI) was a cross-sectional study that conducted in 20 university hospitals across Iran. All the patients with age range of 18 to 65 years, who were admitted or discharged, were assessed by subjective global assessment (SGA).

Results

In total, 2109 patients were evaluated for malnutrition. Mean values of age and body mass index were 44.68 ± 14.65 years and 25.44 ± 6.25 kg/m², respectively. Malnutrition (SGA-B & C) was identified in 23.92% of the patients, 26.23 and 21% of whom were among the admitted and discharged patients, respectively. The highest prevalence of malnutrition was in burns (77.70%) and heart surgery (57.84%) patients. Multivariate analysis presented male gender (OR = 1.02, P < 0.00), malignant disease (OR = 1.40, P < 0.00), length of hospital stay (OR = 1.20, P < 0.00), and polypharmacy (OR = 1.06, P < 0.00) as independent risk factors for malnutrition. Malnutrition was not associated with age (P = 0.10).

Conclusion

This study provides an overall and comprehensive illustration of hospital malnutrition in Iran university hospitals, finding that one out of four patients were malnourished; thus, appropriate consideration and measures should be taken to this issue.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12937-021-00741-1.

Developing a Prognostic Model to Predict Mortality in Patients with Acute Bacterial Meningitis

Bacterial meningitis is one of the harmful and deadly infectious diseases, and any delay in its treatment will lead to death. In this paper, a prognostic model was developed to predict the risk of death amongst probable cases of bacterial meningitis. Our prognostic model was developed using a decision tree algorithm on the national meningitis registry of the Iranian Center for Disease and Prevention (ICDCP) containing 3,923 records of meningitis suspected cases in 2018-2019. The most important features have been selected for the model construction. This model can predict the mortality risk for the meningitis probable cases with 78% accuracy, 84% sensitivity, and 73% specificity. The identified variables in prognosis the death included age and CSF protein level. CSF protein level (mg/dl) <= 65 versus > 65 provided the first branch of our decision tree. The highest mortality risk (85.8%) was seen in the patients >65 CSF protein level with 30 years < of age. For the patients <=30 year of age with CSF protein level >137 (mg/dl), the mortality risk was 60%. The prognostic factors identified in the present study draw the attention of clinicians to provide early specific measures, such as the admission of patients with a higher risk of death to intensive care units (ICU). It could also provide a helpful risk score tool in decision-making in the early phases of admission in pandemics, decrease mortality rate and improve public health operations efficiently in infectious diseases.

Progress towards Every Newborn Action Plan (ENAP) implementation in Iran: obstacles and bottlenecks

Background

Neonatal mortality accounts for more than 47% of deaths among children under five globally but proper care at and around the time of birth could prevent about two-thirds of these deaths. The Every Newborn Action Plan (ENAP) offers a plan and vision to improve and achieve equitable and high-quality care for mothers and newborns. We applied the bottleneck analysis tool offered by ENAP to identify obstacles and bottlenecks hindering the scale-up of newborn care across seven health system building blocks.

Methods

We applied the every newborn bottleneck analysis tool to identify obstacles hindering the scale-up of newborn care across seven health system building blocks. We used qualitative methods to collect data from five medical universities and their corresponding hospitals in three provinces. We also interviewed other national experts, key informants, and stakeholders in neonatal care. In addition, we reviewed and qualitatively analyzed the performance report of neonatal care and services from 16 medical universities around the country.

Results

We identified many challenges and bottlenecks in the scale-up of newborn care in Iran. The major obstacles included but were not limited to the lack of a single leading and governing entity for newborn care, insufficient financial resources for neonatal care services, insufficient number of skilled health professionals, and inadequate patient transfer.

Conclusions

To address identified bottlenecks in neonatal health care in Iran, some of our recommendations were as follows: establishing a single national authorizing and leading entity, allocating specific budget to newborn care, matching high-quality neonatal health care providers to the needs of all urban and rural areas, maintaining clear policies on the distribution of NICUs to minimize the need for patient transfer, and using the available and reliable private sector NICU ambulances for safe patient transfer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12884-021-03800-x.

Obstructive Sleep Apnea: A Prediction Model Using Supervised Machine Learning Method

Obstructive Sleep Apnea (OSA) is the most common breathing-related sleep disorder, leading to increased risk of health problems. In this study, we investigated and evaluated the supervised machine learning methods to predict OSA. We used popular machine learning algorithms to develop the prediction models, using a dataset with non-invasive features containing 231 records. Based on the methodology, the CRISP-DM, the dataset was checked and the blanked data were replaced with average/most frequented items. Then, the popular machine learning algorithms were applied for modeling and the 10-fold cross-validation method was used for performance comparison purposes. The dataset has 231 records, of which 152 (65.8%) were diagnosed with OSA. The majority was male (143, 61.9%). The results showed that the best prediction model with an overall AUC reached the Naïve Bayes and Logistic Regression classifier with 0.768 and 0.761, respectively. The SVM with 93.42% sensitivity and the Naïve Bayes of 59.49% specificity can be suitable for screening high-risk people with OSA. The machine learning methods with easily available features had adequate power of discrimination, and physicians can screen high-risk OSA as a supplementary tool.

Nutritional adequacy in critically ill patients: Result of PNSI study

BACKGROUND & AIMS

Critically ill patients are provided with the intensive care medicine to prevent further complications, including malnutrition, disease progression, and even death. This study was intended to assess nutritional support and its' efficacy in the Intensive Care Units (ICUs) of Iran.

METHODS

This cross-sectional study assessed 50 ICU's patients out of 25 hospitals in the 10 major regions of Iran's health system and was performed using the multistage cluster sampling design. The data were collected from patient's medical records, ICU nursing sheets, patients or their relatives from 2017 to 2018. Nutritional status was investigated by modified NUTRIC score and food frequency checklist.

RESULTS

This study included 1321 ICU patients with the mean age of 54.8 ± 19.97 years, mean mNUTRIC score of 3.4 ± 2.14, and malnutrition rate of 32.6%. The mean time of first feeding was the second day and most of patients (66%) received nutrition support, mainly through enteral (57.2%) or oral (37%) route during ICU stay. The patients received 59.2 ± 37.78 percent of required calorie and 55.5 ± 30.04 percent of required protein. Adequate intake of energy and protein was provided for 16.2% and 10.7% of the patients, respectively. The result of regression analysis showed that the odds ratio of mNUTRIC score was 0.85 (95% confidence interval [CI] = 0.74-0.98) and APACHE II was 0.92 (95%CI = 0.89-0.95) for the prediction of energy deficiency. Nutrition intake was significantly different from patient's nutritional requirements both in terms of energy (p < 0.001) and protein (p < 0.001). Also, mean mNUTRIC score varied notably (p = 0.011) with changing in energy intake, defined as underfeeding, adequate feeding, and overfeeding.

CONCLUSION

The present findings shown that, provided nutritional care for ICU patients is not adequate for their requirements and nutritional status.

Randomized Controlled Trial: The effects of Short Message Service on mothers' oral health knowledge and practice

OBJECTIVE

Mobile health has provided an effective means to educate, empower, and provide access to health services for individuals and groups. This study aimed to compare the effects of gain-frame and loss-frame SMS on the knowledge and practice of mothers with children under the age of six years regarding pediatric oral health.

RESEARCH DESIGN

This randomized controlled trial was conducted in kindergartens and preschool centers of Shiraz, Iran in 2016. There were 71 mothers in the gain-frame group, 66 in the loss-frame group and 74 in the control group. The data were collected before and three-four weeks after the intervention. Data analysis used descriptive statistics, independent t-test, ANOVA, Pearson correlation test, ANCOVA, and post-hoc LSD test (Least Significant Difference).

RESULTS

There was a significant difference between the control (8.83±2.03) and gain-frame (11.8±2.17, p⟨0.001) and loss-frame (12.09±1.94, p⟨0.001) groups for post-test knowledge scores. A difference was also observed between the control group (56.27±11.53) and gain-frame (60.8±7.77, p⟨0.001) and loss-frame (60.25±8.96, p⟨0.001) groups for post-test practice scores. No difference was found between the gain-frame and loss-frame groups for the post-test scores (p=0.69).

CONCLUSION

Gain-frame and loss-frame SMS had similar impacts on the mothers' knowledge and practices about their children's oral health. However, both improved the mothers' knowledge and practice. Therefore, regardless of the style of text message framing, this method may be useful for educating mothers.

Nutritional status of patients hospitalized in the intensive care unit: A comprehensive report from Iranian hospitals, 2018

INTRODUCTION AND AIM

Malnutrition is a complication of hospitalization in critically ill patients. This event is occurred because of disease and therapeutic processes for curing the patients. Determination of nutritional status helps physicians and clinical nutritionists decide on the best regimen which should be prescribed for a patient. In the current study, we aimed to report the nutritional status ofpatientshospitalizedin the intensive care unit (ICU).

METHOD OF STUDY

We used three standard tolls, including Subjective global assessment (SGA), Nutrition Risk in the Critically Ill (NUTRIC) Score and nutrition risk screening (NRS) questionnaires via a multi-stage sampling for different ICU wards of 32 university hospitals in Iran. Frequencies and rates of nutritional scores, comparative studies, and determined agreement of scoring systems and nutritional status in any ward of hospitals were evaluated.

RESULTS

There were 771 males and 540 female Cancer and trauma patients had the best and worst nutritional scores, respectively. Using NRS and NUTRIC, the low-risk scores were more frequent than thehigh-riskscores among ICU patients. SGA showed that most patients were in grades A (well nutritional status) or B (moderate nutritional status), andfew caseswere in grade C (poor nutritional status).The high-risk nutritional score wasobtained for older patients. NUTRIC and NRS had better agreement for diagnosis and differentiation of malnutrition than NUTRIC-SGA or NRS-SGA pairs. However, there was no strong agreement between the mentioned pairs.

CONCLUSION

Nutritional status of patients hospitalized in ICU wards in Iran wassomewhat better than other countries that this could be due to the highly observed guidelines of patient's care in Iran. Anyway,it is suggested that a more precise tool of nutritional scoresto be validated for patients hospitalized in ICU·In addition, better medical care needs a well evaluation of nutritional insufficiencies and what is necessary for compensation using complementary regimens.

The Survey of Willingness and Use of Information and Communication Technologies by People with Low Back Pain

Introduction: Regular physical activity is effective in the treatment of low back pain. However, adherence to these exercises is difficult. Nowadays, the health care industry is using various forms of ICT to provide services to patients. Therefore, the aim of this study was to survey the willingness and use of information and communication technologies among people with low back pain.Method: This is an analytical study conducted in 2017. In this study, 200 samples low back pain were collected by use of convenience sampling method. The data collection tool was a checklist.Result: Nighty-nine percent of the participants used mobile phones based on Android; in addition, 51% of people stated that they were familiar with the Internet. Also, people with the mean age and standard deviation of 37 ± 9 were willing to use ICT tools more compared with people with the mean age and standard deviation of 45±13; in addition, they had a high willingness to use ICT tools and low willingness to use traditional tools (p<0.001).Conclusion: In general, the results showed that a large number of people with low back pain were willing to use ICT tools to receive care services (like exercise therapy). The majority of people with low back pain used social networks and they had smart phones based on the Android whose services were used widely. So the technologies such as smartphones, laptops, social networks and internet services could be used for e-learning.  

Reflection on Mobile Applications for Blood Pressure Management: A Systematic Review on Potential Effects and Initiatives

INTRODUCTION

Ischemic heart disease and stroke have been considered as the first global leading cause of death in last decades [1]. Blood pressure (BP) management is one of the easiest ways suggested for preventing and controlling cardiovascular diseases before the patient develops complications and death-following outcomes. Appearance of technology advancements in the health system has motivated researchers and health providers to study its different aspects and applications in order to improve disease prevention and management. Following these efforts, mobile health (mHealth) technologies were presented to provide people with fast and easier-to-use services. Although there are some unsolved challenges, these technologies have become popular among many people. As an important part of mHealth, mobile applications (apps) have been the focused subject of many studies in the last decade. The objective of this systematic review is to assess the potential effects of mobile apps designed for BP management by scrutinizing the related studies.

MATERIALS AND METHODS

Search methods: We searched the following electronic databases in December 2016: Medline (PubMed), National Center for Biotechnology Information (NCBI), Cochrane Central Register of Controlled Trials (CENTRAL), PsycINFO, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Education Resources Information Center(ERIC), Web of Science, ProQuest, and Google Scholar. No language restriction and start point limitation were imposed.

SELECTION CRITERIA

We included studies that evaluated and assessed mobile apps for BP management and related clinical trials that considered mobile app as the only difference between intervention and control groups.

DATA COLLECTION AND ANALYSIS

Two review authors applied the eligibility criteria, extracted data and assessed the quality of included studies.

RESULTS

Literature search resulted in 13 included studies and 27 reviews. 12 records of 13 included studies identified as interventional studies. The review showed that the mobile apps may improve individual's BP condition and medication adherence.

CONCLUSION

Most of the studies had emphasized positive effects of mobile apps in BP management. However, there is a necessity for performing further investigations due to the identified issues in this study such as low number of participants and limited intervention period in randomized controlled trials, and interventions limited to only hypertensive or high-risked individual.

Decision tree-based modelling for identification of potential interactions between type 2 diabetes risk factors: a decade follow-up in a Middle East prospective cohort study

OBJECTIVE

The current study was undertaken for use of the decision tree (DT) method for development of different prediction models for incidence of type 2 diabetes (T2D) and for exploring interactions between predictor variables in those models.

DESIGN

Prospective cohort study.

SETTING

Tehran Lipid and Glucose Study (TLGS).

METHODS

A total of 6647 participants (43.4% men) aged >20 years, without T2D at baselines ((1999-2001) and (2002-2005)), were followed until 2012. 2 series of models (with and without 2-hour postchallenge plasma glucose (2h-PCPG)) were developed using 3 types of DT algorithms. The performances of the models were assessed using sensitivity, specificity, area under the ROC curve (AUC), geometric mean (G-Mean) and F-Measure.

PRIMARY OUTCOME MEASURE

T2D was primary outcome which defined if fasting plasma glucose (FPG) was ≥7 mmol/L or if the 2h-PCPG was ≥11.1 mmol/L or if the participant was taking antidiabetic medication.

RESULTS

During a median follow-up of 9.5 years, 729 new cases of T2D were identified. The Quick Unbiased Efficient Statistical Tree (QUEST) algorithm had the highest sensitivity and G-Mean among all the models for men and women. The models that included 2h-PCPG had sensitivity and G-Mean of (78% and 0.75%) and (78% and 0.78%) for men and women, respectively. Both models achieved good discrimination power with AUC above 0.78. FPG, 2h-PCPG, waist-to-height ratio (WHtR) and mean arterial blood pressure (MAP) were the most important factors to incidence of T2D in both genders. Among men, those with an FPG≤4.9 mmol/L and 2h-PCPG≤7.7 mmol/L had the lowest risk, and those with an FPG>5.3 mmol/L and 2h-PCPG>4.4 mmol/L had the highest risk for T2D incidence. In women, those with an FPG≤5.2 mmol/L and WHtR≤0.55 had the lowest risk, and those with an FPG>5.2 mmol/L and WHtR>0.56 had the highest risk for T2D incidence.

CONCLUSIONS

Our study emphasises the utility of DT for exploring interactions between predictor variables.

Classification-based data mining for identification of risk patterns associated with hypertension in Middle Eastern population: A 12-year longitudinal study

Hypertension is a critical public health concern worldwide. Identification of risk factors using traditional multivariable models has been a field of active research. The present study was undertaken to identify risk patterns associated with hypertension incidence using data mining methods in a cohort of Iranian adult population.Data on 6205 participants (44% men) age > 20 years, free from hypertension at baseline with no history of cardiovascular disease, were used to develop a series of prediction models by 3 types of decision tree (DT) algorithms. The performances of all classifiers were evaluated on the testing data set.The Quick Unbiased Efficient Statistical Tree algorithm among men and women and Classification and Regression Tree among the total population had the best performance. The C-statistic and sensitivity for the prediction models were (0.70 and 71%) in men, (0.79 and 71%) in women, and (0.78 and 72%) in total population, respectively. In DT models, systolic blood pressure (SBP), diastolic blood pressure, age, and waist circumference significantly contributed to the risk of incident hypertension in both genders and total population, wrist circumference and 2-h postchallenge plasma glucose among women and fasting plasma glucose among men. In men, the highest hypertension risk was seen in those with SBP > 115 mm Hg and age > 30 years. In women those with SBP > 114 mm Hg and age > 33 years had the highest risk for hypertension. For the total population, higher risk was observed in those with SBP > 114 mm Hg and age > 38 years.Our study emphasizes the utility of DTs for prediction of hypertension and exploring interaction between predictors. DT models used the easily available variables to identify homogeneous subgroups with different risk pattern for the hypertension.

Determinants of Self-Rated Health in Tehran, from Individual Characteristics towards Community-Level Attributes

INTRODUCTION

It is generally believed that the attributes of shared environment affect health of residents beyond the individual risk factors. This study investigates some individual and neighborhood characteristics that may affect self-rated health (SRH) in Iran.

METHODS

Questions were asked about the social capital, economic status and SRH of 1,982 citizens from 200 randomly selected locations in Tehran. The neighborhood characteristics were assessed by an observational checklist. A multilevel model was designed.

RESULTS

SRH was significantly different between neighborhoods (P-value < 0.001) and between economic groups (P-value < 0.001). At the individual level, social capital (SC) and being married had a positive association with SRH, while age, being female and bad economic statuses were negatively associated with SRH. At the neighborhood level, neighborhoods with higher average education were positively association with SRH, and living in neighborhoods under construction had a negative association with SRH.

CONCLUSIONS

These findings highlight the importance of shared social and physical environment, as well as individual characteristics on health, although the mechanisms may still be controversial.

Measuring psychosocial exposures: validation of the Persian of the copenhagen psychosocial questionnaire (COPSOQ)

BACKGROUND

The effect of psychosocial work environment on personal and organizational aspects of employees is well-known; and it is of fundamental importance to have valid tools to evaluate them. This study aims to evaluate the reliability and validity of the Persian version of Copenhagen Psychosocial Questionnaire (COPSOQ).

METHODS

The questionnaire was translated into Persian and then back translated into English by two translators separately. The wording of the final Persian version was established by comparing the translated versions with the original questionnaire. One hundred three health care workers completed the questionnaire. Chronbach's alpha was calculated, and factor analysis was performed.

RESULTS

Factor analysis revealed acceptable validity for the five contexts of the questionnaire. Cronbach's alpha ranged from 0.73 to 0.82 in different contexts.

CONCLUSION

This study revealed that the Persian version of COPSOQ is a reliable and valid instrument for measuring psychosocial factors at work.

An application of association rule mining to extract risk pattern for type 2 diabetes using tehran lipid and glucose study database

BACKGROUND

Type 2 diabetes, common and serious global health concern, had an estimated worldwide prevalence of 366 million in 2011, which is expected to rise to 552 million people, by 2030, unless urgent action is taken.

OBJECTIVES

The aim of this study was to identify risk patterns for type 2 diabetes incidence using association rule mining (ARM).

PATIENTS AND METHODS

A population of 6647 individuals without diabetes, aged ≥ 20 years at inclusion, was followed for 10-12 years, to analyze risk patterns for diabetes occurrence. Study variables included demographic and anthropometric characteristics, smoking status, medical and drug history and laboratory measures.

RESULTS

In the case of women, the results showed that impaired fasting glucose (IFG) and impaired glucose tolerance (IGT), in combination with body mass index (BMI) ≥ 30 kg/m(2), family history of diabetes, wrist circumference > 16.5 cm and waist to height ≥ 0.5 can increase the risk for developing diabetes. For men, a combination of IGT, IFG, length of stay in the city (> 40 years), central obesity, total cholesterol to high density lipoprotein ratio ≥ 5.3, low physical activity, chronic kidney disease and wrist circumference > 18.5 cm were identified as risk patterns for diabetes occurrence.

CONCLUSIONS

Our study showed that ARM is a useful approach in determining which combinations of variables or predictors occur together frequently, in people who will develop diabetes. The ARM focuses on joint exposure to different combinations of risk factors, and not the predictors alone.

The Impact of Oversampling with SMOTE on the Performance of 3 Classifiers in Prediction of Type 2 Diabetes

OBJECTIVE

To evaluate the impact of the synthetic minority oversampling technique (SMOTE) on the performance of probabilistic neural network (PNN), naïve Bayes (NB), and decision tree (DT) classifiers for predicting diabetes in a prospective cohort of the Tehran Lipid and Glucose Study (TLGS).

METHODS

. Data of the 6647 nondiabetic participants, aged 20 years or older with more than 10 years of follow-up, were used to develop prediction models based on 21 common risk factors. The minority class in the training dataset was oversampled using the SMOTE technique, at 100%, 200%, 300%, 400%, 500%, 600%, and 700% of its original size. The original and the oversampled training datasets were used to establish the classification models. Accuracy, sensitivity, specificity, precision, F-measure, and Youden's index were used to evaluated the performance of classifiers in the test dataset. To compare the performance of the 3 classification models, we used the ROC convex hull (ROCCH).

RESULTS

Oversampling the minority class at 700% (completely balanced) increased the sensitivity of the PNN, DT, and NB by 64%, 51%, and 5%, respectively, but decreased the accuracy and specificity of the 3 classification methods. NB had the best Youden's index before and after oversampling. The ROCCH showed that PNN is suboptimal for any class and cost conditions.

CONCLUSIONS

To determine a classifier with a machine learning algorithm like the PNN and DT, class skew in data should be considered. The NB and DT were optimal classifiers in a prediction task in an imbalanced medical database.

Impact of computer-based pregnancy-induced hypertension and diabetes decision AIDS on empowering pregnant women

Objectives

We designed a computer-based decision aid (CDA) for use by pregnant women at home to investigate and participate in solving their pregnancy problems related to pregnancy-induced hypertension (PIH) and gestational diabetes (GD). The system cannot and is not intended to replace visits to physicians; rather it can help women focus on the most important symptoms and provides guidance on when to see a doctor.

Methods

The study is a randomized controlled trial, which is performed among Iranian pregnant women. For subjects, 420 healthy pregnant women have been recruited from two private and two public prenatal centers. The intervention group will receive the CDA for use at home, and the control group will receive care as usual. The CDA relies on knowledge extracted from the national guidelines on PIH and GD.

Results

The two primary outcomes for the study are self-efficacy and knowledge. Self-efficacy will be measured by the Stanford self-efficacy scale and knowledge will be evaluated by 15 binary (true/false) questions provided by the researchers. Secondary outcomes include type and frequency of doctor and/or medical center visits; blood pressure and blood sugar changes based on the national guidelines and according to pregnancy records, and anxiety will be assessed by the state component of the short Spielberger anxiety scale.

Conclusions

This paper describes the design of a CDA and a protocol for a randomized controlled trial to study the effects of the CDA on self-efficacy and knowledge of pregnant women pertaining to PIH and GD. Differences in the primary outcomes will be analyzed using 'intention-to-treat' principles.

A diagnostic model for cirrhosis in patients with non-alcoholic fatty liver disease: an artificial neural network approach

BACKGROUND

Timely diagnosis of liver cirrhosis is vital for preventing further liver damage and giving the patient the chance of transplantation. Although biopsy of the liver is the gold standard for cirrhosis assessment, it has some risks and limitations and this has led to the development of new noninvasive methods to determine the stage and prognosis of the patients. We aimed to design an artificial neural network (ANN) model to diagnose cirrhosis patients with non-alcoholic fatty liver disease (NAFLD) using routine laboratory data.

METHODS

Data were collected from 392 patients with NAFLD by the Middle East Research Center in Tehran. Demographic variables, history of diabetes, INR, complete blood count, albumin, ALT, AST and other routine laboratory tests, examinations and medical history were gathered. Relevant variables were selected by means of feature extraction algorithm (Knime software) and were accredited by the experts. A neural network was developed using the MATLAB software.

RESULTS

The best obtained model was developed with two layers, eight neurons and TANSIG and PURLIN functions for layer one and output layer, respectively. The sensitivity and specificity of the model were 86.6% and 92.7%, respectively.

CONCLUSION

The results of this study revealed that the neural network modeling may be able to provide a simple, noninvasive and accurate method for diagnosing cirrhosis only based on routine laboratory data.

Applying decision tree for identification of a low risk population for type 2 diabetes. Tehran Lipid and Glucose Study

AIMS

The aim of this study was to create a prediction model using data mining approach to identify low risk individuals for incidence of type 2 diabetes, using the Tehran Lipid and Glucose Study (TLGS) database.

METHODS

For a 6647 population without diabetes, aged ≥20 years, followed for 12 years, a prediction model was developed using classification by the decision tree technique. Seven hundred and twenty-nine (11%) diabetes cases occurred during the follow-up. Predictor variables were selected from demographic characteristics, smoking status, medical and drug history and laboratory measures.

RESULTS

We developed the predictive models by decision tree using 60 input variables and one output variable. The overall classification accuracy was 90.5%, with 31.1% sensitivity, 97.9% specificity; and for the subjects without diabetes, precision and f-measure were 92% and 0.95, respectively. The identified variables included fasting plasma glucose, body mass index, triglycerides, mean arterial blood pressure, family history of diabetes, educational level and job status.

CONCLUSIONS

In conclusion, decision tree analysis, using routine demographic, clinical, anthropometric and laboratory measurements, created a simple tool to predict individuals at low risk for type 2 diabetes.

Inter-observer and Intra-observer Agreement in Pathological Evaluation of Non-alcoholic Fatty Liver Disease Suspected Liver Biopsies

BACKGROUND

Histopathologic assessment of liver tissue is an essential step in management and follow-up of non-alcoholic fatty liver disease (NAFLD) while inter- and intra-observer variations limit the accuracy of these assessments.

OBJECTIVES

The aim of this study was to assess the inter- and intra-observer reproducibility of histopathologic assessment of liver biopsies based on NAFLD activity score (NAS) scoring system.

MATERIALS AND METHODS

The anonymous liver biopsy samples of 100 consecutive NAFLD suspected adults were randomly assigned to four pathologists. Then, the samples were randomly reassigned to the pathologists for the second time in a way that each sample would be evaluated by two different pathologists. Biopsies were revisited by their first evaluator after two months. The results were reported based on NAS scoring system.

RESULTS

Inter-observer agreement of the pathology scores based on NAS scoring system was acceptable for steatosis, lobular inflammation, and fibrosis, but not for hepatocyte ballooning. The intra-observer agreement was acceptable in all scales, with lowest intra-class correlation observed for lobular inflammation.

CONCLUSIONS

NAS scoring system has good overall inter- and intra-observer agreement, but more attention should be given to defining the hepatocyte ballooning and lobular inflammation, and training the pathologists to improve the accuracy of pathology reports.

Web-site evaluation tools: a case study in reproductive health information

BACKGROUND AND OBJECTIVE

Internet forms an opportunity to inform, teach, and connect professionals and patients. However, much information on Internet is incomplete, inaccurate, or misleading, and not only in the medical domain. Because of the potential for damage from misleading and inaccurate health information, many organizations and individuals have published or implemented scoring tools for evaluating the appropriateness or quality of these resources. The objective of this study is to identify and summarize scoring tools that have evaluated web-sites providing reproductive health information in order to compare them and recommend an overarching evaluation tool.

METHODS

We searched Ovid MEDLINE(R) (1946 to July 2013) and OVID Embase (1980 to July 2013); and included English language studies that have evaluated the quality of websites providing reproductive health information. Studies only assessing the content of websites were excluded.

RESULTS

We identified 5 scoring tools: 1-The HON (health on the net) Code of Conduct for medical and health Web sites, 2-Silberg scores, 3-Hogne Sandvik scale, 4-Jim Kapoun's Criteria for Evaluating Web Pages, and 5-The Health Information Technology Institute (HITI) criteria. We have compared these scales and identified 14 criteria: authorship, ownership, currency, objectivity/content, transparency/source, interactivity, privacy/ethics, financial disclosure, navigability/links, complementarity, advertising policy, design, quantity, and accessibility. We integrated these criteria and introduced a new tool with 10 criteria.

CONCLUSION

Website evaluation tools differ in their evaluation criteria and there is a lack of consensus about which to use; therefore, an integrated easy to use set of criteria is needed.

Sleep quality among health care workers

BACKGROUND

Sleep problems are common complaints in health care workers that can affect quality of life and productivity, both in patients and healthy individuals. This study evaluates the prevalence of low sleep quality in health care workers with no health issues or complaints of sleep problems.

METHODS

In this cross-sectional study was conducted on healthy employees of a health care organization in Tehran. The presence of physical and mental health issues and satisfaction from their sleep quality was assessed by means of a self-administered questionnaire. Sleep quality was evaluated by the Persian version of the Pittsburgh Sleep Quality Index (PSQI). PSQI scores of 5 or less were considered as good sleep quality.

RESULTS

From 925 participants, 56.9% were good sleepers. There was a significant association between poor sleep quality and female sex, divorced, shift-working, and age; it was not associated with education level. Self-rated health (SRH) had a significant positive correlation with sleep quality.

CONCLUSION

Poor sleep quality is common in our study population and associated with a lower SRH. The high prevalence of poor sleep quality in a group of healthy non-complaining employees can be an important early sign of underlying physical or mental health issues. Providing screening and monitoring programs to detect the underlying health conditions and their consequent treatment can promote health and productivity of employees and improve society's health, both directly and indirectly.

Lower intrafamilial transmission rate of hepatitis B in patients with hepatitis d coinfection: a data-mining approach

BACKGROUND

The presence of an infected family member significantly increases the risk of HBV transmission, but many socio-demographic and viral characteristics of family members affect the transmission rate.

OBJECTIVES

In this study, we have used data mining techniques to investigate the impact of different variables in intrafamilial transmission of HBV infection.

PATIENTS AND METHODS

demographic information, viral markers, and medical history of 330 patients with chronic hepatitis B and their offspring attending a referral center in Tehran were collected. Data-mining techniques were administered to detect patterns.

RESULTS

The overall transmission rate was 15.7% (5.4% and 27.3% for male and female index cases respectively). In female patients, HBe Ag positively affected the transmission rate (49% vs. 23.4%). There was a dominant change in transmission rate of female patients with negative results for Hbe Ag with HDV coinfection, where the transmission rate changed from 25% in patients with negative results for HDV Ab to 5% in those with positive results. In Hbe Ag negative male index cases, the transmission rate was 1.3% in cases with positive results for HDV Ab compared to 7% in those with negative findings. The overall transmission rate was statistically different between patients with positive and negative results for HDV Ab (P = 0.016).

CONCLUSIONS

There is a minor but consistent pattern change in the presence of HDV infection which reduces familial transmission of HBV, especially in female patients with negative results for HBe Ag.

Reliability and validity of Persian version of job content questionnaire in health care workers in Iran

BACKGROUND

The effect of poor psychosocial work conditions on health status has widely been discussed in occupational literature. Job Content Questionnaire (JCQ) is a widely accepted instrument for evaluation of psychosocial work conditions.

OBJECTIVE

To determine the reliability and validity of Persian version of JCQ.

METHODS

The questionnaire was translated into Persian and back translated. 490 Iranian health care workers completed the questionnaire. After 4 weeks, 196 participants completed the questionnaire once again.

RESULTS

Factor analyses revealed an acceptable level of structure validity for the questionnaire. Cronbach's α was more than 0.75 for all scales except for psychological demand (α=0.60) and job insecurity (α=0.27). reassessment of participants after 4 weeks revealed an acceptable level of reliability for all scales except depression.

CONCLUSION

The Persian version of JCQ is reliable and valid for assessing work conditions among Iranian health care workers, although revision is needed for job insecurity and depression scales.

Developing a reliable and valid instrument to assess health-affecting aspects of neighborhoods in Tehran

BACKGROUND

Residence characteristics can affect health of residents. This paper reports the development of an instrument assessing these aspects of neighborhoods.

MATERIALS AND METHODS

Literature search and focus group discussions with residents were carried out and relevant items were extracted. Five experts reviewed and commented on the items. An observation instrument with 54 items was composed and completed by two independent observers in 20 randomly selected locations. Due to lack of acceptable reliability in some items, the checklist was revised. The new 22-items checklist in four categories (general characteristics, public green area characteristics, access to services and undesirable features) was completed by two independent trained observers in 28 randomly selected locations.

RESULTS

The items in the final checklist had kappa statistics ranging from 0.63 to 1, with an exception of the item assessing "presence of beggars, homeless or working/street children", with kappa as low as 0.27 due to variability of their presence in different times. Average Kappa statistics was 0.78 for general characteristics, 0.79 for public green area characteristics, 0.84 for access to services, and 0.54 for undesirable features.

CONCLUSION

Neighborhood and health observation instrument seems to have good reliability in city of Tehran. It can probably be used in other large cities of Iran and similar cities elsewhere.

Reliability and validity of Persian version of World Health Organization health and work performance questionnaire in Iranian health care workers

BACKGROUND

The effect of health status on productivity has widely been studied and discussed in literature. Valid and reliable tools are needed to evaluate the levels of health and productivity and provide detailed information, before any intervention is implemented. World Health Organization Health and Work Performance Questionnaire (HPQ) is a widely used instrument in estimating the workplace costs of health problems in terms of reduced job performance, sickness absence, and work-related accidents and injuries.

OBJECTIVE

To assess the reliability and validity of Persian version of HPQ in Iranian health care workers.

METHODS

The questionnaire was translated to Persian and back translated. 102 health care workers completed the questionnaire. Absence and sick-leave data was extracted from administrative records.

RESULTS

Factor analysis revealed acceptable validity for the questionnaire in part A (health). Cronbach's alpha was >0.73 for all scales of Parts B (work) and C (demographic). Questions targeting days of absence and sick-leave had acceptable correlation with administrative records (Pearson's r >0.75), while questions on total hours worked showed lower correlation.

CONCLUSION

Persian version of HPQ can be considered a reliable and valid tool in Iranian health workers.