The Application of Internet of Things for the Elderly Health Safety: A Systematic Review.

The elderly population is projected to increase from 8.5% in 2015 to 12% in 2030 and 16% in 2050. This growing demographic is chronically vulnerable to various age-related diseases and injuries like falling, leading to long-term pain, disability, or death. Thus, there is a need to use the potential of novel technologies to support the elderly regarding patient safety matters in particular. Internet of Things (IoT) has recently been introduced to improve the lifestyle of the elderly. This study aimed to evaluate the studies that have researched the use of the IoT for elderly patients' safety through performance metrics, accuracy, sensitivity, and specificity. We conducted a systematic review on the research question. To do this, we searched PubMed, EMBASE, Web of Science, Scopus, Google Scholar, and Science Direct databases by combining the related keywords. A data extraction form was used for data gathering through which English, full-text articles on the use of the IoT for the safety of elderly patients were included. The support vector machine technique has the most frequency of use compared to other techniques. Motion sensors were the most widely used type. The United States with four studies had the highest frequencies. The performance of IoT to ensure the elderly's safety was relatively good. It, however, needs to reach a stage of maturity for universal use.

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.

Assessing the quality of electronic medical records in academic hospitals: A multi-center study in Iran.

Objective: The present study aimed to assess the quality of electronic medical records (EMR) retrieved from hospital information systems (HIS) of three educational hospitals in Mashhad, Iran. Methods: In this multi-center, cross-sectional study, inpatient electronic records collected from three academic hospitals were categorized into five data groups, namely demographics (D); care handler (CH), indicating the doers of the medical actions; diagnosis and treatment (DT); administrative and financial (AF); and laboratory and Para clinic (LP). Next, we asked 25 physicians from the three academic hospitals to determine data elements of medical research and education value (called research and educational data) in every group. Flowingly, the quality of the five data groups (completeness * accuracy) was reported for entire sampled data and those specified as research and educational data, based on the exact concordance between electronic medical records and corresponding paper records. HISRA, standing for HIS recording ability, was also assessed compared to data elements of standard paper forms. Results: For entire data, HISRA was 58.5%. In all hospitals, the highest data quality (more than 90%) belongs to D and AF data groups, and the lowest quality goes to CH and DT groups (less than 50%, and 60%, respectively). For research and educational data, HISRA was 47%, and the quality of D and AF data groups were the highest (nearly 100%), while CH and DT stood around 50% and 60% in order. The quality of the LP data group was almost 85% in all hospitals but hospital C (well over 30%). Total data quality for the hospitals was almost less than 70%. Conclusions: The low quality of electronic medical records was mostly a result of incompleteness, while the accuracy was relatively good. Results showed that the HIS application development mainly focused on administrative and financial aspects rather than academic and clinical goals.

The Accuracy of Electrical Impedance Tomography for Breast Cancer Detection: A Systematic Review and Meta-Analysis.

Introduction: Incidence of breast cancer (BC) in 2020 is about 2.26 million new cases. It is the first common cancer accounting for 11.7% of all cancer worldwide. Disease complications and the mortality rate of breast cancer are highly dependent on the early diagnosis. Therefore, novel human breast-imaging techniques play an important role in minimizing the breast cancer morbidity and mortality rate. Electrical impedance tomography (EIT) is a noninvasive technique to image the breast using the electrical impedance behavior of the body tissues. Objectives: The aims of this manuscript are as follows: (1) a comprehensive investigation of the accuracy of EIT for breast cancer diagnosis through searching pieces of evidence in the valid databases and (2) meta-analyses of the results. Methods: The systematic search was performed in the electronic databases including PubMed, Web of Science, EMBASE, Science Direct, ProQuest, Scopus, and Google Scholar without time and language limitation until January 2021. Search terms were "EIT" and "Breast Cancer" with their synonyms. Relevant studies were included based on PRISMA and study objectives. Quality of studies and risk of bias were performed by QUADAS-2 tools. Then, relevant data were extracted in Excel form. The hierarchical/bivariate meta-analysis was performed with "metandi" package for the ROC plot of sensitivity and specificity. Forest plot of the Accuracy index and double arcsine transformations was applied to stabilize the variance. The heterogeneity of the studies was evaluated by the forest plots, χ2 test (assuming a significance at the a-level of 10%), and the I2 statistic for the Accuracy index. Results: A total of 4027 articles were found. Finally, 12 of which met our criteria. Overall, these articles included studies of 5487 breast cancer patients. EIT had an overall pooled sensitivity and specificity of 75.88% (95% CI, 61.92% to 85.89%) and 82.04% (95% CI, 69.72% to 90.06%), respectively. The pooled diagnostic odds ratio was 14.37 (95% CI, 6.22% to 33.20%), and the pooled effect of accuracy was 0.79 with 95% CI (0.73, 0.83). Conclusions: This study showed that EIT can be used as a useful method alongside mammography. EIT sensitivity could not be compared with the sensitivity of MRI, but in terms of specificity, it can be considered as a new method that probably can get more attention. Furthermore, large-scale studies will be needed to support the evidence.

Practical Recommendations for the Preoperative Screening and Protective Protocols in Cancer Surgeries During COVID-19: A Systematic Review.

Introduction: The new coronavirus (COVID-19) has posed many new challenges to the health care and the timing of surgical care. At the beginning of the pandemic many guidelines recommended postponing elective surgical procedures to reallocate resources. As regards, delay in cancer treatment could be effective on cancer progression. The aim of this systematic review was to outline a guideline for preoperative screening before cancer surgeries and protecting health care workers during the pandemic. Materials and Methods: This study was conducted through a search in electronic databases up to August 2020. PubMed, EMBASE, Web of Science, Scopus, Science Direct, and Google Scholar databases were searched without time limitation. The keywords were a combination of preoperative, cancer surgery, COVID-19, and their synonyms. Results: The most commonly used ways to triage preoperatively were telephone pre-assessment for suspicious symptoms and history of contact or travel, 14-day self-isolation, in- hospital queries at admission, temperature monitoring, and isolation in a single room COVID-free ward or physical distancing. Reverse transcription-polymerase chain reaction (RT-PCR) test 24-72 h before operation was recommended commonly, except in inaccessible centers, but non-contrast chest-CT scan is not routinely advised for elective surgeries to salvage medical resources. Recommended personal protective equipment (PPE) for staffs were wearing N95 mask in addition to gown, gloves, eye protection in aerosol-generating procedures (AGPs), and wearing gloves, hats, and disposable surgical masks, practice distancing, and hand hygiene for all staffs. Meanwhile team separation of hospital staffs caring for COVID-19 patients, segregated areas for COVID-19 clean and contact, restriction of visitors and family members, and personal distancing are mostly recommended. Conclusion: We hope this review would be a guidance for triage, preoperative testing, and summarizing safety principles during COVID-19 pandemic alongside with surgical reintegration.

Informational Needs in Patients With Breast Cancer With Lymphedema: Is It Important?

INTRODUCTION: Lymphedema is one of the complications of breast cancer treatment. It has no cure yet and can affect the quality of life. This study aimed to identify and investigate informational needs, preferred delivery methods, and time of receiving information about lymphedema for these patients. METHODS: One hundred participants were recruited through Lymphedema Clinic in Motamed Cancer Institute in Tehran, Iran, through convenience sampling and were asked to complete a self-administered survey. Data collection took place on all opening days between October 2018 and mid-March 2019. RESULTS: Most of the participants were above 40 years, have a diploma, homemaker, and the average income of most of the participants (57.2%) was low. The importance of having lymphedema information was very high for them. Most of them wanted detailed information at diagnosis of breast cancer. The preferred information of delivery methods were private sessions and social networks. CONCLUSIONS: Patients with breast cancer who have lymphedema have high needs as regards concise lymphedema information. Private sessions with physicians and social networks can provide detailed information for them.

A Systematic Review of Electronic Health (eHealth) interventions to improve physical activity in patients with breast cancer.

BACKGROUND: Electronic Health (eHealth) may have a positive effect on healthcare, such as patient education and decreasing the costs of healthcare services. Evidence suggests that such interventions can also improve physical activity (PA) of patients. This systematic review aimed to investigate the effects of PA interventions provided through eHealth on breast cancer patients. METHODS: This study was conducted through a search in electronic databases up to July 2018. PubMed, EMBASE, Cochrane Central Register of Controlled Trials, Web of Science, Scopus, Science Direct, and Google Scholar databases were searched without time limitation. RESULTS: In total, 2187 articles were retrieved and finally 16 articles remained. Five were pre/post and 11 were randomized trial studies. Different platforms were used in these studies including web-based, mobile-based, both web-and-mobile-based and email. In total, these articles comprise 2304 breast cancer patients with the mean age of 51 years and 50% were conducted in the USA. Four studies measured PA using wearable devices such as accelerometers and pedometers. All studies reported an increase in PA level at least in one of moderate or vigorous PA, although not all these results were significant. CONCLUSION: The results show that eHealth interventions can improve the level of PA in breast cancer patients. Although there are numerous eHealth interventions focusing on PA in cancer patients, there is still an essential need for eHealth interventions to be tailored for breast cancer patients specifically. Clinical trials with appropriate methodology, enough intervention time and follow-up are needed to make evidence-based results more generalizable. TRIAL REGISTRATION: PROSPERO CRD42018092422; https://www.crd.york.ac.uk/PROSPERO/.

Colorectal Cancer Registration: Data Approach to Knowledge.

For ensuring the quality of data and facilitating data exchange between healthcare providers and professional organizations, it is necessary to define a standard data set. The main aim of this study was to define a national minimum data set for colorectal cancer in Iran. To develop this data set, a combination of literature review and two rounds of a modified Delphi technique were used. An initial checklist was proposed based on a literature review and comparative studies. Based on the literature review, main categories, including: demographic information, diagnostic information, treatment information, clinical status assessment information, and clinical trial information were proposed. In this study, the national minimum data set of colorectal cancer was collected. Developing this data set through standard contents can improve effective health information exchange for both healthcare providers and health information systems.

Discovery of Hidden Patterns in Breast Cancer Patients, Using Data Mining on a Real Data Set.

The aim is to recognize the unknown atterns in a real breast cancer dataset using data mining algorithms as a new method in medicine. Due to excessive missing data in the collection only data on 665 of 809 patients were available. The other missing values were estimated using the EM algorithm in SPSS21 software. Fields have been converted into discrete fields and finally the APRIORI algorithm has been used to analyze and explore the unknown patterns. After the rule extraction, experts in the field of breast cancer eliminated redundant and meaningless relations. 100 association rules with a confidence value of more than 0.9 explored by the APRIORI algorithm and after the clinical expert feedback, 10 clinically meaningful relations have been detected and reported. Due to the high number of risk factors, the use of data mining is effective for cancer data. These patterns provide the future study hypotheses of specific clinical studies.

Bone Metastasis Prognostic Factors in Breast Cancer.

OBJECTIVE: Bone is the most common site of metastasis in breast cancer. Prognostic factors for predicting bone metastases in breast cancer are controversial yet. In this study, we investigated clinical factors associated with secondary bone metastasis of breast cancer. METHODS: In total, 1690 patients with breast cancer recorded between 2002 and 2012 in Motamed Cancer Institute, Tehran, Iran entered in the retrospective study. We studied age, menopausal status, histologic type, tumor size, number of cancerous axillary lymph nodes, serum concentrations of alkaline phosphatase (ALP), carcinogenicity antigen (CEA), cancer antigen (CA)-153, and hemoglobin (HB) in 2 groups with bone metastases (n = 123) and without it, respectively. We applied logistic regression to identify bone metastasis prognostic factors in breast cancer patients and calculated the cut-off value, sensitivity, and characteristics of independent prognostic factors using receiver operating characteristic (ROC) curve analysis. RESULTS: Menopause, larger tumor size, and the greater number of cancerous axillary lymph nodes increased the chance of bone metastases significantly (P < .05). There was no significant difference between mean groups with and without bone metastases regarding serum concentration of CEA, CA-153, HB, and histopathologic type (P > .05). Logistic regression showed that age (odds ratio (OR) = 1.021), menopausal status (OR = 1.854), number of cancerous axillary lymph nodes (OR = 1.065), a tumor size between 2 and 5 cm diameter (OR = 2.002) and more than 5 cm diameter (OR = 4.009), and ALP (OR = 1.005) are independent prognostic factors associated with bone metastases. The ROC curve showed that the abovementioned factors have comparable predictive accuracy for bone metastases. CONCLUSIONS: Age, menopausal status, number of axillary lymph node metastases, tumor size, and ALP were identified as prognostic factors for bone metastasis in patients with breast cancer. So patients with these characteristics should be monitored more precisely with regular follow-ups.

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.