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Background: Kidney transplant outcomes are broadly associated with transplant recipients' capacity in following a complex and continuous self-management regimen. Health information technology has the potential to empower patients. This systematic review aimed to determine the impacts of IT-based interventions for self-management in kidney transplant recipients.Methods: A comprehensive investigation was performed in MEDLINE (via PubMed) and EMBASE (via Scopus) in April 2019. Eligible studies were the randomized controlled trials which aimed to design an automated IT-based intervention. All English papers including adult kidney transplant recipients were included. To assess the clinical trial's quality, Cochrane Collaboration's assessment tool was employed. The articles were integrated based on category of outcomes, characteristics of interventions, and their impact. The interventions were classified based on the used IT-based tools, including smart phones, coverage tools, computer systems, and a combination of several tools. The impact of interventions was defined as: (1) positive effect (i.e. statistically significant), and (2) no effect (i.e. not statistically significant).Results: A total of 2392 articles were retrieved and eight publications were included for full-text analysis. Interventions include those involving the use of computerized systems (3 studies), smart phone application (3 studies), and multiple components (2 studies). The studies evaluated 30 outcomes in total, including 24 care process and 6 clinical outcomes. In 18 (80%) out of 30 outcomes, interventions had a statistically significant positive effect, 66% in process and 33% in clinical outcomes.Conclusions: IT-based interventions (e.g. mobile health applications, wearable devices, and computer systems) can improve self-management in kidney transplant recipients (including clinical and care process outcomes). However, further evaluation studies are required to quantify the impact of IT-based self-management interventions on short- and long-term clinical outcomes as well as health care costs and patients' quality of life. [ABSTRACT FROM AUTHOR]

Introduction: On March 20, 2020, the World Health Organization (WHO) announced the spread of SARS-CoV-2 infection in most countries worldwide as a pandemic. COVID-19 is mainly disseminated through human-to-human transmission route via direct contact and respiratory droplets. Telehealth and/or telemedicine technologies are beneficial methods that could be employed to deal with pandemic situation of communicable infections. The purpose of this proposed systematic review study is to sum up the functionalities, applications, and technologies of telemedicine during COVID-19 outbreak. Material and Methods: This review will be carried out in accordance with the Cochrane Handbook and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) reporting guidelines. PubMed and Scopus databases were searched for related articles. Randomized and nonrandomized controlled trials published in English in scientific journals were identified to be evaluated for eligibility. Articles conducted on telemedicine services (TMS) during COVID-19 outbreak (2019-2020) were identified to be evaluated. Results: The literature search for related articles in PubMed and Scopus databases led to the identification and retrieval of a total of 1118 and 485 articles, respectively. After eliminating duplicate articles, title and abstract screening process was performed for the remaining 1440 articles. The current study findings are anticipated to be used as a guide by researchers, decision makers, and managers to design, implement, and assess TMS during COVID-19 crisis. Conclusion: As far as we know, this systematic review is conducted to comprehensively evaluate TM methods and technologies developed with the aim of controlling and managing COVID-19 pandemic. This study highlights important applications of telemedicine in pandemic conditions, which could be employed by future health systems in controlling and managing communicable infections when an outbreak occurs. [ABSTRACT FROM AUTHOR]

Introduction: SARS-CoV-2 has disseminated globally, and COVID-19 has been labeled as a public health emergency of global concern by the World Health Organization. Since 2019-nCoV (2019 new coronavirus) has a long incubation period and high infectivity, e-Health and its subsets in medical informatics have evolved as a suitable solution to enable the continuity of health services delivery. Also, new health care models are required during the COVID-19 pandemic. The proposed systematic review aims to examine and summarize evidence related to medical informatics applications in COVID-19 crisis, as evidence-based approaches. Material and Methods: A research team consisting of experts in the fields of medical informatics and systematic review methods were guided this review according to the Cochrane Handbook and PRISMA reporting guidelines. PubMed and Scopus databases were searched. Eligibility criteria for including studies reviewed was randomized and non-randomized controlled trials published in English language. Articles performed on medical informatics applications in COVID-19 pandemic during 2019-2020 were identified. Two independent reviewers will assess articles eligibility and extract data into a spreadsheet using a structured pilot-tested form. Collected data and evidence will be synthesized using a thematic synthesis approach. The risk of bias will be assessed in all included studies using appropriate tools. Results: The literature search led to the identification of a total of 1882 and 854 articles retrieved from the PubMed and Scopus databases, respectively. After removing duplicates, 2716 articles remained and underwent title and abstract screening process. The results of this review are expected to be served as a basis for assisting researchers, decision makers, medical informatics specialists, politicians, and others in developing, implementing, and evaluating IT-based tools and interventions to help medical staff in combating and eradicating COVID-19. Conclusion: This systematic review is the first comprehensive evaluation of MI methods aiming to control and manage covid-19 pandemic. This study highlights applications of medical informatics in pandemic situation and will help future researchers to take the most advantage of using MI in the health system. [ABSTRACT FROM AUTHOR]

Despite the promise of decision support for improving care, alerts are often overridden or ignored. We evaluated Dutch general practitioners' intention to accept decision support in a proposed implementation based on clinical rules regarding care for elderly patients, and their reasons for wanting or not wanting support. We developed a survey based on literature and structured interviews and distributed it to all doctors who would receive support in the proposed implementation (n = 43), of which 65 percent responded. The survey consisted of six questions for each of 20 clinical rules. Despite concerns about interruption, doctors tended to choose more interruptive forms of support. Doctors wanted support when they felt the rule represented minimal care, perceived a need to improve care, and felt responsible for the action and that they might forget to perform the action; doctors declined support due to feeling that it was unnecessary and due to concerns about interruption. [ABSTRACT FROM AUTHOR]

This study evaluated the effect of intermittent fasting during Ramadan, the Muslim religious season of fasting, on body composition among 95 adults (65 male adults) with a mean age of 45.4 years with metabolic syndrome in Iran. The individuals were classified retrospectively into fasting and nonfasting groups based on fasting for a minimum of 10 days during Ramadan. Body composition, physical activity, and dietary intake were assessed both at baseline before the fast began and after Ramadan. Those who fasted a minimum of 10 days had significant reductions in body weight (−1.5 kg) and body mass index, body fat mass (−1.2 kg), fat free mass (−0.4 kg), skeletal muscle mass (−0.3 kg), and visceral fat area (−5.7 cm2). Also, they showed significant decreases in the total body water, intracellular water, 50-kHz whole-body phase angle (−0.13 degrees), and total physical activity. Fasting resulted in a 1.5-kg weight loss, of which the percentage losses were loss in body fat mass, 76%; body water loss, 18%; and protein loss, 6%, and also decrease in daily dietary intake during fasting in those who fasted. Fasting during Ramadan, which restricts the time of eating and caloric restriction, may be effective as dietary interventions in patients with metabolic syndrome to reduce body weight, fat mass, and visceral fat while retaining lean mass. [ABSTRACT FROM AUTHOR]

Background: Previous research has identified key factors affecting in vitro fertilization or intracytoplasmic sperm injection success, yet the lack of a standardized approach for various treatments remains a challenge. Objective: The objective of this study is to utilize a machine learning approach to identify the principal predictors of success in in vitro fertilization and intracytoplasmic sperm injection treatments. Materials and Methods: We collected data from 734 individuals at 2 infertility centers in Mashhad, Iran between November 2016 and March 2017. We employed feature selection methods to reduce dimensionality in a random forest model, guided by hesitant fuzzy sets (HFSs). A hybrid approach enhanced predictor identification and accuracy (ACC), as assessed using machine learning metrics such as Matthew’s correlation coefficient, runtime, ACC, area under the receiver operating characteristic curve, precision or positive predictive value, recall, and F-Score, demonstrating the effectiveness of combining feature selection methods. Results: Our hybrid feature selection method excelled with the highest ACC (0.795), area under the receiver operating characteristic curve (0.72), and F-Score (0.8), while selecting only 7 features. These included follicle-stimulation hormone (FSH), 16Cells, FAge, oocytes, quality of transferred embryos (GIII), compact, and unsuccessful. Conclusion: We introduced HFSs in our novel method to select influential features for predicting infertility success rates. Using a multi-center dataset, HFSs improved feature selection by reducing the number of features based on standard deviation among criteria. Results showed significant differences between pregnant and non-pregnant groups for selected features, including FSH, FAge, 16Cells, oocytes, GIII, and compact. We also found a significant correlation between FAge and fetal heart rate and clinical pregnancy rate, with the highest FSH level (31.87%) observed for doses ranging from 10-13 (mIU/ml). [ABSTRACT FROM AUTHOR]

Background: Deaf or hard-of-hearing children experience difficulties in learning health principles. But technology has significantly improved their ability to learn. The challenge in e-learning is to design attractive applications while having an educational aspect. Objective: The aims of this study were to determine the pedagogical effectiveness of a health education application for deaf and hard of hearing students in elementary schools, and to investigate the student's perceptions in different educational grades about the educational effectiveness of the text, graphics, video clips, and animation in the application. Methods: The study design was quasi experimental and was conducted in Mashhad in 2016. Study population were deaf or hard-of-hearing students in elementary schools. The intervention included health application training to deaf and hard-of-hearing students in Mashhad. A questionnaire was used for data gathering. The pedagogical effectiveness was determined by measuring the modified Adapted Pedagogical Index. This index was created based on the characteristics of the application and study population. Statistical analysis was performed using the Kruskal-Wallis and Mann--Whitney tests with Bonferroni adjustment by SPSS 22. Results: Eighty-two students participated in the intervention. The value of modified Adapted Pedagogical Index was 0.669, indicating that the application was effective. The results of Kruskal-Wallis H and Mann--Whitney U test showed significant differences in different educational grades. (p<0.008) Conclusion: Using information technology can improve the education of deaf and hard-of-hearing students. Modified Adapted Pedagogical Index can be used for evaluation of non-interactive applications for elementary school children who are deaf or hard of hearing. [ABSTRACT FROM AUTHOR]

Background: S. epidermidis is one of predominant members of human normal microflora, however it may be the main cause of nosocomial infections related to medical devices put into the body and thus the biofilm formation is a main route for pathogenesis which is affected by icaADBC operon. In this study, the prevalence of IS256 sequence among ica-positive and biofilm non-producer clinical isolates of S. epidermidis was investigated. Methods: In this study, 100 clinical isolates of S. epidermidis were collected from different infections. The IS256 sequence, icaADBC operon and biofilm formation by microtiter plate assay were evaluated among them. The antibiotic susceptibility of these isolates was done with disc diffusion by using c efoxitin, ciprofloxacin, erythromycin, gentamycin, oxacillin and tetracycline discs. Results: Of 100 isolates, 18 (18%) were ica operon-positive from which 18%, 14%, 16% and 17% contained icaA, icaD, icaB and icaC genes, respectively. Moreover, 14 of 18 (77.77%) ica-positive isolates amplified the IS256 gene. The biofilm formation by microtiter plate assay showed that 18 (18%) isolates were strong biofilm producers, 21 (21%) produced intermediate level biofilm and 14 (14%) and 47 (47%) isolates were weak and non-biofilm producers, respectively. in the antibiotic susceptibility test, the majority of isolates were resistant to oxacillin and lowest resistance was against ciprofloxacin. Conclusion: The statistical analysis with p<0.05 exhibited that there was a reverse relation between biofilm production and the insertion of IS256, and in fact the higher prevalence of IS256 among isolates, the biofilm formation declined. Data showed that amongst most of ica-positive isolates, the IS256 was detected and therefore other genetic factors affect the expression of this operon. [ABSTRACT FROM AUTHOR]

Background: Cesarean delivery on maternal request (CDMR) is one of the main reasons for cesarean delivery in Iran, and women often need help in making a decision about the delivery options available to them. The main objective of this study is to evaluate the effect of a computerized decision aid (CDA) system on empowering pregnant women in choosing an appropriate mode of delivery. This CDA contrasts the advantages and disadvantages of vaginal versus cesarean section delivery in terms of their value to the individual woman.Methods/design: The protocol concerns a randomized trial study that will be performed among Iranian women. Four hundred pregnant women will be recruited from two private and two public prenatal centers in Mashhad, Iran. They will be randomly assigned to either an intervention or a control group. The designed CDA will be provided to the intervention group, whereas the control group will only receive routine care. The CDA provides educational contents as well as some recommendations. The CDA's knowledge base is obtained from the results of studies on predictors of cesarean delivery. The CDA's software will be installed on women's computers for use at home. The two primary outcomes for the study are O'Connor's Decisional Conflict Scale and knowledge as measured by true/false questions. Actual mode of delivery (vaginal versus cesarean) will be compared in the two groups.Discussion: We investigate the effect of a CDA on empowering pregnant women in terms of reducing their decisional conflict as well as on improving their clinical knowledge pertaining to mode of delivery.Trial Registration: This trial is registered with the Iran Trial Registrar under registration number IRCT2015093010777N4 and registration date 26 October 2015. [ABSTRACT FROM AUTHOR]

Objectives: Considering the positive effects of certain nutrients on depression, increasingly prevalent in the contemporary societies, we investigated the nutritional content of prescribed and prohibited foodstuffs for depressed patients in Iranian Traditional Medicine resources. Materials and Methods: In order to conduct the study, credible sources of Iranian Traditional Medicine were primarily reviewed for the prescribed and prohibited foodstuffs for depressed patients. USDA database, as a well-known and valuable source, was then visited to determine the amount of effective nutrients in each foodstuff. Finally, the obtained amounts were compared with each other in three food groups, namely vegetables, fruits and nuts and also high protein products. Results: In Iranian Traditional Medicine texts, the following are prescribed for depression management: basil, coriander, spinach, lettuce, squash, peppermint, dill, chicory, celery, chard, quince, cucumber, watermelon, grape, peach, pomegranate, banana, apple, currant, pistachio, dried fig, almond, egg, chicken, lamb, and trout; cabbage, eggplant, onion, garlic, broad beans, lentils, and beef, meanwhile, are prohibited. In this regard, the effective nutritional content of these foodstuffs was obtained and then compared in the three food groups. Conclusion: This study revealed that spinach, lettuce, chicory, and squash (vegetables), pomegranate and almond (fruits and nuts) and ultimately trout (high protein products) are the best effective foodstuffs on depressed patients from nutritional content aspect. [ABSTRACT FROM AUTHOR]

Background Previous efforts such as Assessing Care of Vulnerable Elders (ACOVE) provide quality indicators for assessing the care of elderly patients, but thus far little has been done to leverage this knowledge to improve care for these patients. We describe a clinical decision support system to improve general practitioner (GP) adherence to ACOVE quality indicators and a protocol for investigating impact on GPs' adherence to the rules. Design We propose two randomized controlled trials among a group of Dutch GP teams on adherence to ACOVE quality indicators. In both trials a clinical decision support system provides un-intrusive feedback appearing as a color-coded, dynamically updated, list of items needing attention. The first trial pertains to real-time automatically verifiable rules. The second trial concerns non-automatically verifiable rules (adherence cannot be established by the clinical decision support system itself, but the GPs report whether they will adhere to the rules). In both trials we will randomize teams of GPs caring for the same patients into two groups, A and B. For the automatically verifiable rules, group A GPs receive support only for a specific inter-related subset of rules, and group B GPs receive support only for the remainder of the rules. For non-automatically verifiable rules, group A GPs receive feedback framed as actions with positive consequences, and group B GPs receive feedback framed as inaction with negative consequences. GPs indicate whether they adhere to non-automatically verifiable rules. In both trials, the main outcome measure is mean adherence, automatically derived or self-reported, to the rules. Discussion We relied on active end-user involvement in selecting the rules to support, and on a model for providing feedback displayed as color-coded real-time messages concerning the patient visiting the GP at that time, without interrupting the GP's workflow with pop-ups. While these aspects are believed to increase clinical decision support system acceptance and its impact on adherence to the selected clinical rules, systems with these properties have not yet been evaluated. Trial registration Controlled Trials NTR3566. [ABSTRACT FROM AUTHOR]

Background An early and proper diagnosis of acute on chronic liver failure ( ACLF), together with the identification of indicators associated with disease severity is critical for outcome prediction and therapy. Objective To systematically identify and summarize prognostic indicators for patients with ACLF and to evaluate the predictive value of these indicators. Methods Embase and Ovid-Medline were searched for English-language articles. The search criteria focused on identifying clinical trials and observational studies reporting on indicators used for prediction of mortality in patients with ACLF. Results Of 2382 studies identified, 19 were included for detailed analysis. Thirteen different definitions of ACLF were found. The main differences were related to acute deterioration in liver function, coagulopathy and hyperbilirubinaemia/jaundice. Seventy three prognostic indicators and their association with mortality were extracted and categorized into seven categories: general markers ( n = 13), viral markers ( n = 6), bio-markers ( n = 22), hemodynamics ( n = 1), morphology/histology ( n = 17), scoring systems ( n = 10) and treatments ( n = 4). Conclusions The ambiguity and variability in the definition of ACLF and in its predictive indicators hampers comparability among studies. There is a need for a single uniform definition of ACLF. Also absence of a gold standard is an obstacle to render one indicator superior to another. The age, hepatic encephalopathy, model for end-stage liver disease score, total bilirubin and International normalized ratio (prothrombin time) appeared to be promising candidates for evaluation in future studies. The result of this review may be useful as a starting point in developing a standard list of indicators for clinical outcome that concur with the clinicians' subjective views on prognosis in ACLF. [ABSTRACT FROM AUTHOR]

Introduction: Acute liver failure is a rare disease with high mortality and liver transplantation is the only life saving therapy. Accurate prognosis of ALF is crucial for proper intervention. Aim: To identify and characterize newly developed prognostic models of mortality for ALF patients, assess study quality, identify important variables and provide recommendations for the development of improved models in the future. Methods: The online databases MEDLINE® (1950-2012) and EMBASE® (1980-2012) were searched for English-language articles that reported original data from clinical trials or observational studies on prognostic models in ALF patients. Studies were included if they developed a new model or modified existing prognostic models. The studies were evaluated based on an existing framework for scoring the methodological and reporting quality of prognostic models. Results: Twenty studies were included, of which 18 reported on newly developed models, 1 on modification of the Kings College Criteria (KCC) and 1 on the Model for End-Stage Liver Disease (MELD). Ten studies compared the newly developed models to previously existing models (e.g. KCC); they all reported that the new models were superior. In the 12-point methodological quality score, only one study scored full points. On the 38-point reporting score, no study scored full points. There was a general lack of reporting on missing values. In addition, none of the studies used performance measures for calibration and accuracy (e.g. Hosmer-Lemeshow statistics, Brier score), and only 5 studies used the AUC as a measure of discrimination. Conclusions: There are many studies on prognostic models for ALF but they show methodological and reporting limitations. Future studies could be improved by better reporting and handling of missing data, the inclusion of model calibration aspects, use of absolute risk measures, explicit considerations for variable selection, the use of a more extensive set of reference models and more thorough validation. [ABSTRACT FROM AUTHOR]

Purpose: The aim of our study was to explore, using an innovative method, the effect of temporal changes in the mortality prediction performance of an existing model on the quality of care assessment. The prognostic model (rSAPS-II) was a recalibrated Simplified Acute Physiology Score-II model developed for very elderly Intensive Care Unit (ICU) patients. Methods: The study population comprised all 12,143 consecutive patients aged 80 years and older admitted between January 2004 and July 2009 to one of the ICUs of 21 Dutch hospitals. The prospective dataset was split into 30 equally sized consecutive subsets. Per subset, we measured the model's discrimination [area under the curve (AUC)], accuracy (Brier score), and standardized mortality ratio (SMR), both without and after repeated recalibration. All performance measures were considered to be stable if <2 consecutive points fell outside the green zone [mean ± 2 standard deviation (SD)] and none fell outside the yellow zone (mean ± 4SD) of pre-control charts. We compared proportions of hospitals with SMR>1 without and after repeated recalibration for the year 2009. Results: For all subsets, the AUCs were stable, but the Brier scores and SMRs were not. The SMR was downtrending, achieving levels significantly below 1. Repeated recalibration rendered it stable again. The proportions of hospitals with SMR>1 and SMR<1 changed from 15 versus 85% to 35 versus 65%. Conclusions: Variability over time may markedly vary among different performance measures, and infrequent model recalibration can result in improper assessment of the quality of care in many hospitals. We stress the importance of the timely recalibration and repeated validation of prognostic models over time. [ABSTRACT FROM AUTHOR]

Abstract: Introduction: Although the use of computerized decision support systems (CDSS) in glucose control in the ICU has been reported, little is known about the effect of the systems’ operating modes on the quality of glucose control. The objective of this study was to evaluate the effect of providing patient-specific and patient non-specific computerized advice on timing of blood glucose level (BGL) measurements. Our hypothesis was that both levels of support would be effective for improving the quality of glucose regulation and safety, with patient specific advice being the most effective strategy. Patients and methods: A prospective study was performed in a 30-bed mixed medical-surgical intensive care unit (ICU) of a university hospital. In phase 1 the CDSS provided non-specific advice and thereafter, in phase 2, the system provided specific advice on timing of BGL measurements. The primary outcome measure was delay in BGL measurements before and after the two levels of support. Secondary endpoints were sampling frequency, mean BGL, BGL within pre-defined targets, time to capture target, incidences of severe hypoglycemia and hyperglycemia. These indicators were analyzed over the course of time using Statistical Control Charts. The analysis was restricted to patients with at least two blood glucose measurements. Results: Data of 3934 patient admissions were evaluated, which corresponded to 119,116 BGL measurements. The BGL sampling interval, delays in BG sampling, and percentage of hypoglycemia all decreased after introducing either of the two levels of decision support. The effect was however larger for the patient specific CDSS. Mean BGL, time to capture target, hyperglycemia index, percentage of hyperglycemia events and “in range” measurements remained unchanged and stable after introducing both patient non-specific and patient specific decision support. Conclusion: Adherence to protocol sampling rules increased by using decision support with a larger effect at the patient specific level. This led to a decrease in the percentage of hypoglycemia events and improved safety. The use of the CDSS at both levels, however, did not improve the quality of glucose control as measured by our indicators. More research is needed to investigate whether other socio-technical factors are in play. [Copyright &y& Elsevier]

Objective: To systematically review the medical literature on the association between glucose variability measures and mortality in critically ill patients. Methods: Studies assessing the association between a measure of glucose variability and mortality that reported original data from a clinical trial or observational study on critically ill adult patients were searched in Ovid MEDLINE and Ovid EMBASE. Data on patient populations, study designs, glucose regulations, statistical approaches, outcome measures, and glucose variability indicators (their definition and applicability) were extracted. Result: Twelve studies met the inclusion criteria; 13 different indicators were used to measure glucose variability. Standard deviation and the presence of both hypo- and hyperglycemia were the most common indicators. All studies reported a statistically significant association between mortality and at least one glucose variability indicator. In four studies both blood glucose levels and severity of illness were considered as confounders, but only one of them checked model assumptions to assert inference validity. Conclusions: Glucose variability has been quantified in many different ways, and in each study at least one of them appeared to be associated with mortality. Because of methodological limitations and the possibility of reporting bias, it is still unsettled whether and in which quantification this association is independent of other confounders. Future research will benefit from using an indicator reference subset for glucose variability, metrics that are linked more directly to negative physiological effects, more methodological rigor, and/or better reporting. [ABSTRACT FROM AUTHOR]

Glucose control (GC) with insulin decreases morbidity and mortality of critically ill patients. In this study we investigated GC performance over time during implementation of GC strategies within three intensive care units (ICUs) and in routine clinical practice. All adult critically ill patients who stayed for >24 h between 1999 and 2007 were included. Effects of implementing local GC guidelines and guideline revisions on effectiveness/efficiency-related indicators, safety-related indicators, and protocol-related indicators were measured. Data of 17,111 patient admissions were evaluated, with 714,141 available blood glucose levels (BGL) measurements. Mean BGL, time to reach target, hyperglycemia index, sampling frequency, percentage of hyperglycemia events, and in-range measurements statistically changed after introducing GC in all ICUs. The introduction of simple rules on GC had the largest effect. Subsequent changes in the protocol had a smaller effect than the introduction of the protocol itself. As soon as the protocol was introduced, in all ICUs the percentage of hypoglycemia events increased. Various revisions were implemented to reduce hypoglycemia events, but levels never returned to those from pre-implementation. More intensive implementation strategies including the use of a decision support system resulted in better control of the process. There are various strategies to achieve GC in routine clinical practice but with variable success. All of them were associated with an increase in hypoglycemia events, but GC was never stopped. Instead, these events have been accepted and managed. Statistical process control is a useful tool for monitoring phenomena over time and captures within-institution changes. [ABSTRACT FROM AUTHOR]

Abstract: Objective: To identify all published studies evaluating computerized physician order entry (CPOE) in the inpatient setting and uniformly classify these studies on outcome measure and study design. Data sources: All studies that evaluated the effect of CPOE on outcomes pertaining to the medication process in inpatients were electronically searched in MEDLINE® (1966 to August 2006), EMBASE® (1980 to August 2006) and the Cochrane library. In addition, the bibliographies of retrieved articles were manually searched. Articles were selected if one of their main objectives was CPOE evaluation in an inpatient setting. Review method: Identified titles and abstracts were independently screened by three reviewers to determine eligibility for further review. Results: We found 67 articles, which included articles on CPOE evaluation on some outcome at the time of ordering. Most papers evaluated multiple outcome measures. The outcome measures were clustered in the following categories: adherence (n =22); alerts and appropriateness of alerts (n =7); safety (n =21); time (n =7); costs and (organizational) efficiency (n =23); and satisfaction, usage and usability (n =10). Most studies used a before–after design (n =35) followed by observational studies (n =24) and randomized controlled trials (n =8). Conclusion: The impact of CPOE systems was especially positive in the category adherence to guidelines, but also to some extent in alerts and appropriateness of alerts; costs and organizational efficiency; and satisfaction and usability. Although on average, there seems to be a positive effect of CPOE on safety, studies tended to be non-randomized and were focused on medication error rates, not powered to detect a difference in adverse drug event rates. Some recent studies suggested that errors, adverse drug events (ADEs) and even mortality increased after CPOE implementation. Only in the category time the impact has been shown to be negative, but this only refers to the physician''s time, not the net time. Except for safety, on the whole spectrum of outcomes, results of RCT studies were in line with non-RCT study results. [Copyright &y& Elsevier]

Background: Medication errors, and the resultant adverse drug events (ADEs), are one of the main preventable causes of morbidity and mortality. Computerised physician order entry (CPOE) is reported to reduce the frequency of these errors. However, CPOE systems themselves may be associated with errors. The aim of this study was to investigate the effects of a CPOE system that displays an initial default dose for gentamycin and tobramycin administration on the frequency of medication errors and potential ADEs in patients with renal insufficiency.Methods: Gentamycin and tobramycin prescriptions from the CPOE records of a Dutch tertiary adult intensive care unit were retrospectively compared with doses recommended by a locally developed guideline. The default dose for gentamycin and tobramycin in the CPOE system is 240 mg/day. A dose prescribing error was defined as an administered dose that exceeded the recommended dose by >10%.Results: Three hundred and ninty two prescriptions, relating to 253 patients (of whom 184 had renal insufficiency), were analysed. There was a high frequency (58%, 227 of 392) of prescriptions that used the CPOE system's default dose of 240 mg/day. The dose was wrong in 73% (165) of these orders. Default orders for patients with renal insufficiency amounted to 52% (132 of 259). A total of 86% (113 of 132) of these resulted in potential ADEs compared with 53% (66 of 124) for the rest of orders (p < 0.0001).Discussion: A markedly high frequency of prescriptions followed the default dose value and, in patients with renal insufficiency, there was a high frequency of doses exceeding the guideline recommendation (+10%), amounting to potential ADEs.Conclusion: Initial CPOE dose values for prescribing gentamycin and tobramycin, which are based on a fixed default value, form a source of potential ADEs for patients with renal insufficiency. [ABSTRACT FROM AUTHOR]

Infertility is a significant health problem and assisted reproductive technologies to treat infertility. Despite all efforts, the success rate of these methods is still low. Also, each of these methods has side effects and costs. Therefore, accurate prediction of treatment success rate is a clinical challenge. This retrospective study aimed to internally validate and compare various machine learning models for predicting the clinical pregnancy rate (CPR) of infertility treatment. For this purpose, data from 1931 patients consisting of in vitro fertilization (IVF) or intra cytoplasmic sperm injection (ICSI) (733) and intra uterine insemination (IUI) (1196) treatments were included. Also, no egg or sperm donation data were used. The performance of machine learning algorithms to predict clinical pregnancy were expressed in terms of accuracy, recall, F-score, positive predictive value (PPV), brier score (BS), Matthew correlation coefficient (MCC), and receiver operating characteristic. The significance of the features with CPR and AUCs was evaluated by Student's t test and DeLong's algorithm. Random forest (RF) model had the highest accuracy in the IVF/ICSI treatment. The sensitivity, F1 score, PPV, and MCC of the RF model were 0.76, 0.73, 0.80, and 0.5, respectively. These values for IUI treatment were 0.84, 0.80, 0.82, and 0.34, respectively. The BS was 0.13 and 0.15 for IVF/ICS and IUI, respectively. In addition, the estimated AUCs of the RF model for IVF/ICS and IUI were 0.73 and 0.7, respectively. Some essential features were obtained based on RF ranking for the two datasets, including age, follicle stimulation hormone, endometrial thickness, and infertility duration. The results showed a strong relationship between clinical pregnancy and a woman's age. Also, endometrial thickness and the number of follicles decreased with increasing female age in both treatments. [ABSTRACT FROM AUTHOR]

Background: Inflammatory bowel disease (IBD) imposes a huge burden on the healthcare systems and greatly declines the patient's quality of life. However, there is a paucity of detailed data regarding information and supportive needs as well as sources and methods of obtaining information to control different aspects of the disease from the perspectives of the patients themselves. This study aimed to establish the IBD patients' preferences of informational and supportive needs through Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). Methods: IBD patients were recruited from different centers. Considering inclusion and exclusion criteria, 521 participants were filled a predefined questionnaire. This questionnaire was prepared through literature review of the recent well-known guidelines on the needs of IBD patients, which was further approved by the experts of IBD area in three rounds of Delphi consensus. It includes 56 items in four sections of informational needs (25), supportive needs (15), sources of information (7), and methods of obtaining information (9). Results: In particular, EFA was used to apply data reduction and structure detection. Given that this study tries to identify patterns, structures as well as inter-relationships and classification of the variables, EFA was utilized to simplify presentation of the variables in a way that large amounts of observations transform into fewer ones. Accordingly, the EFA identified five factors out of 25 items in the information needs section, three factors out of 15 items in the supportive needs section, two factors out of 7 items in the information sources section, and two factors out of 9 items in the information presentation methods. Through the CFA, all 4 models were supported by Root Mean Squared Error of Approximation (RMSEA); Incremental Fit Index (IFI); Comparative Fit Index (CFI); Tucker-Lewis Index (TLI); and SRMR. These values were within acceptable ranges, indicating that the twelve factors achieved from EFA were validated. Conclusions: This study introduced a reliable 12-factor model as an efficient tool to comprehensively identify preferences of IBD patients in informational and supportive needs along with sources and methods of obtaining information. An in-depth understanding of the needs of IBD patients facilitates informing and supporting health service provision. It also assists patients in a fundamental way to improve adaptation and increase the quality of life. We suggest that health care providers consider the use of this tool in clinical settings in order to precisely assess its efficacy. [ABSTRACT FROM AUTHOR]

Introduction: Prolonged Length of Stay (LOS) in ED (Emergency Department) has been associated with poor clinical outcomes. Prediction of ED LOS may help optimize resource utilization, clinical management, and benchmarking. This study aims to systematically review models for predicting ED LOS and to assess the reporting and methodological quality about these models. Methods: The online database PubMed, Scopus, and Web of Science (10 Sep 2023) was searched for English language articles that reported prediction models of LOS in ED. Identified titles and abstracts were independently screened by two reviewers. All original papers describing either development (with or without internal validation) or external validation of a prediction model for LOS in ED were included. Results: Of 12,193 uniquely identified articles, 34 studies were included (29 describe the development of new models and five describe the validation of existing models). Different statistical and machine learning methods were applied to the papers. On the 39-point reporting score and 11-point methodological quality score, the highest reporting scores for development and validation studies were 39 and 8, respectively. Conclusion: Various studies on prediction models for ED LOS were published but they are fairly heterogeneous and suffer from methodological and reporting issues. Model development studies were associated with a poor to a fair level of methodological quality in terms of the predictor selection approach, the sample size, reproducibility of the results, missing imputation technique, and avoiding dichotomizing continuous variables. Moreover, it is recommended that future investigators use the confirmed checklist to improve the quality of reporting. [ABSTRACT FROM AUTHOR]

This study addresses the challenges associated with emergency department (ED) overcrowding and emphasizes the need for efficient risk stratification tools to identify high-risk patients for early intervention. While several scoring systems, often based on logistic regression (LR) models, have been proposed to indicate patient illness severity, this study aims to compare the predictive performance of ensemble learning (EL) models with LR for in-hospital mortality in the ED. A cross-sectional single-center study was conducted at the ED of Imam Reza Hospital in northeast Iran from March 2016 to March 2017. The study included adult patients with one to three levels of emergency severity index. EL models using Bagging, AdaBoost, random forests (RF), Stacking and extreme gradient boosting (XGB) algorithms, along with an LR model, were constructed. The training and validation visits from the ED were randomly divided into 80% and 20%, respectively. After training the proposed models using tenfold cross-validation, their predictive performance was evaluated. Model performance was compared using the Brier score (BS), The area under the receiver operating characteristics curve (AUROC), The area and precision–recall curve (AUCPR), Hosmer–Lemeshow (H–L) goodness-of-fit test, precision, sensitivity, accuracy, F1-score, and Matthews correlation coefficient (MCC). The study included 2025 unique patients admitted to the hospital's ED, with a total percentage of hospital deaths at approximately 19%. In the training group and the validation group, 274 of 1476 (18.6%) and 152 of 728 (20.8%) patients died during hospitalization, respectively. According to the evaluation of the presented framework, EL models, particularly Bagging, predicted in-hospital mortality with the highest AUROC (0.839, CI (0.802–0.875)) and AUCPR = 0.64 comparable in terms of discrimination power with LR (AUROC (0.826, CI (0.787–0.864)) and AUCPR = 0.61). XGB achieved the highest precision (0.83), sensitivity (0.831), accuracy (0.842), F1-score (0.833), and the highest MCC (0.48). Additionally, the most accurate models in the unbalanced dataset belonged to RF with the lowest BS (0.128). Although all studied models overestimate mortality risk and have insufficient calibration (P > 0.05), stacking demonstrated relatively good agreement between predicted and actual mortality. EL models are not superior to LR in predicting in-hospital mortality in the ED. Both EL and LR models can be considered as screening tools to identify patients at risk of mortality. [ABSTRACT FROM AUTHOR]

Drug–drug interactions (DDIs) can harm patients admitted to the intensive care unit (ICU). Yet, clinical decision support systems (CDSSs) aimed at helping physicians prevent DDIs are plagued by low-yield alerts, causing alert fatigue and compromising patient safety. The aim of this multicentre study was to evaluate the effect of tailoring potential DDI alerts to the ICU setting on the frequency of administered high-risk drug combinations. We implemented a cluster randomised stepped-wedge trial in nine ICUs in the Netherlands. Five ICUs already used potential DDI alerts. Patients aged 18 years or older admitted to the ICU with at least two drugs administered were included. Our intervention was an adapted CDSS, only providing alerts for potential DDIs considered as high risk. The intervention was delivered at the ICU level and targeted physicians. We hypothesised that showing only relevant alerts would improve CDSS effectiveness and lead to a decreased number of administered high-risk drug combinations. The order in which the intervention was implemented in the ICUs was randomised by an independent researcher. The primary outcome was the number of administered high-risk drug combinations per 1000 drug administrations per patient and was assessed in all included patients. This trial was registered in the Netherlands Trial Register (identifier NL6762) on Nov 26, 2018, and is now closed. In total, 10 423 patients admitted to the ICU between Sept 1, 2018, and Sept 1, 2019, were assessed and 9887 patients were included. The mean number of administered high-risk drug combinations per 1000 drug administrations per patient was 26·2 (SD 53·4) in the intervention group (n=5534), compared with 35·6 (65·0) in the control group (n=4353). Tailoring potential DDI alerts to the ICU led to a 12% decrease (95% CI 5–18%; p=0·0008) in the number of administered high-risk drug combinations per 1000 drug administrations per patient, after adjusting for clustering and prognostic factors. This cluster randomised stepped-wedge trial showed that tailoring potential DDI alerts to the ICU setting significantly reduced the number of administered high-risk drug combinations. Our list of high-risk drug combinations can be used in other ICUs, and our strategy of tailoring alerts based on clinical relevance could be applied to other clinical settings. ZonMw. [ABSTRACT FROM AUTHOR]

Background: Self-management education resources for inflammatory bowel disease (IBD) using concepts remain infrequent. We aim to describe the development and evaluation process of educational material for self-management in IBD based on patient preferences and expert opinions. Research design and methods: The method of this study includes two main phases of development and validation in five steps in the following order: (1) identification of information needs for patients with IBD; (2) content development with a comprehensive literature review and scientific texts related to IBD; (3) measuring the face validity of the content based on the expert opinions in the field of IBD; (4) validation of the content with the experts in the field of IBD; and (5) validation by target audiences. Results: The expert panel comprises ten gastroenterologists, nutritionists, psychologists, gynecologists, and nurses. The total suitability score is 79.5%. The final draft version of the educational self-management material was presented to 30 IBD patients who were satisfied (n = 24; 80%) with the material. Conclusions: This study shows the development process and is validated for face and content validity by the academic multidisciplinary expert panel and target group. Patients and their caregivers can use this content to cope with their disease. [ABSTRACT FROM AUTHOR]

Detecting clinical keratoconus (KCN) poses a challenging and time-consuming task. During the diagnostic process, ophthalmologists are required to review demographic and clinical ophthalmic examinations in order to make an accurate diagnosis. This study aims to develop and evaluate the accuracy of deep convolutional neural network (CNN) models for the detection of keratoconus (KCN) using corneal topographic maps. We retrospectively collected 1758 corneal images (978 normal and 780 keratoconus) from 1010 subjects of the KCN group with clinically evident keratoconus and the normal group with regular astigmatism. To expand the dataset, we developed a model using Variational Auto Encoder (VAE) to generate and augment images, resulting in a dataset of 4000 samples. Four deep learning models were used to extract and identify deep corneal features of original and synthesized images. We demonstrated that the utilization of synthesized images during training process increased classification performance. The overall average accuracy of the deep learning models ranged from 99% for VGG16 to 95% for EfficientNet-B0. All CNN models exhibited sensitivity and specificity above 0.94, with the VGG16 model achieving an AUC of 0.99. The customized CNN model achieved satisfactory results with an accuracy and AUC of 0.97 at a much faster processing speed compared to other models. In conclusion, the DL models showed high accuracy in screening for keratoconus based on corneal topography images. This is a development toward the potential clinical implementation of a more enhanced computer-aided diagnosis (CAD) system for KCN detection, which would aid ophthalmologists in validating the clinical decision and carrying out prompt and precise KCN treatment. [ABSTRACT FROM AUTHOR]

Liposome nanoparticles have emerged as promising drug delivery systems due to their unique properties. Assessing particle size and polydispersity index (PDI) is critical for evaluating the quality of these liposomal nanoparticles. However, optimizing these parameters in a laboratory setting is both costly and time-consuming. This study aimed to apply a machine learning technique to assess the impact of specific factors, including sonication time, extrusion temperature, and compositions, on the size and PDI of liposomal nanoparticles. Liposomal solutions were prepared and subjected to sonication with varying values for these parameters. Two compositions: (A) HSPC:DPPG:Chol:DSPE-mPEG2000 at 55:5:35:5 molar ratio and (B) HSPC:Chol:DSPE-mPEG2000 at 55:40:5 molar ratio, were made using remote loading method. Ensemble learning (EL), a machine learning technique, was employed using the Least-squares boosting (LSBoost) algorithm to accurately model the data. The dataset was randomly split into training and testing sets, with 70% allocated for training. The LSBoost algorithm achieved mean absolute errors of 1.652 and 0.0105 for modeling the size and PDI, respectively. Under conditions where the temperature was set at approximately 60 °C, our EL model predicted a minimum particle size of 116.53 nm for composition (A) with a sonication time of approximately 30 min. Similarly, for composition (B), the model predicted a minimum particle size of 129.97 nm with sonication times of approximately 30 or 55 min. In most instances, a PDI of less than 0.2 was achieved. These results highlight the significant impact of optimizing independent factors on the characteristics of liposomal nanoparticles and demonstrate the potential of EL as a decision support system for identifying the best liposomal formulation. We recommend further studies to explore the effects of other independent factors, such as lipid composition and surfactants, on liposomal nanoparticle characteristics. [ABSTRACT FROM AUTHOR]

Background: Antibiotic prescribing is common worldwide. There are several original studies about antibiotic prescribing in the healthcare setting of Iran reporting different levels of prescribing. The aim of this systematic review and meta-analysis was to determine the prevalence of antibiotic prescribing in both inpatient and outpatient settings in Iran, an example of a developing country. Methods: To identify published studies on antibiotic prescribing, databases such as ISI, Scopus, PubMed, Google Scholar, and Electronic Persian were searched in Iran till January 2020. Eligible studies were those analyzing original data on the prescription and use of antibiotics in outpatient or inpatient settings in Iran. Moreover, all studies that used an intervention to improve antibiotic prescribing were included. The quality of the included studies was assessed using self-administered quality assessment criteria. The meta-analysis of prevalence of antibiotic prescribing was conducted based on the meta-analysis of observational studies in epidemiology guidelines. To calculate pooled rates, the random-effects model was used. Results: A total of 54 studies (39 outpatients and 15 inpatients) were included in this study. The median of antibiotic prescribing in the outpatient and inpatient settings accounted for 45.25% and 68.2% of patients, respectively. The results of meta-analysis also showed that the antibiotic prescribing accounted for 45% of prescriptions in outpatient settings and 39.5%, 66%, and 75.3% of patients in all wards, pediatrics wards, and ICU wards of inpatient settings, respectively. The most commonly prescribed antibiotic classes in outpatient settings were penicillins, cephalosporins, and macrolides, while in inpatient settings, these were cephalosporins, penicillins, and carbapenems. There were seven studies using interventions to improve antibiotic prescribing pattern. It should be mentioned that intervention in a study had a statistically significant effect on improving antibiotic prescribing (p <.05). Conclusion: Prevalence of antibiotic prescribing in Iran is high. Our findings highlight the need for urgent action to improve prescription practices. It seems that developing a national plan to improve antibiotic prescribing is necessary. [ABSTRACT FROM AUTHOR]

Liposome nanoparticles have emerged as promising drug delivery systems due to their unique properties. Assessing particle size and polydispersity index (PDI) is critical for evaluating the quality of these liposomal nanoparticles. However, optimizing these parameters in a laboratory setting is both costly and time-consuming. This study aimed to apply a machine learning technique to assess the impact of specific factors, including sonication time, extrusion temperature, and compositions, on the size and PDI of liposomal nanoparticles. Liposomal solutions were prepared and subjected to sonication with varying values for these parameters. Two compositions: (A) HSPC:DPPG:Chol:DSPE-mPEG2000 at 55:5:35:5 molar ratio and (B) HSPC:Chol:DSPE-mPEG2000 at 55:40:5 molar ratio, were made using remote loading method. Ensemble learning (EL), a machine learning technique, was employed using the Least-squares boosting (LSBoost) algorithm to accurately model the data. The dataset was randomly split into training and testing sets, with 70% allocated for training. The LSBoost algorithm achieved mean absolute errors of 1.652 and 0.0105 for modeling the size and PDI, respectively. Under conditions where the temperature was set at approximately 60 °C, our EL model predicted a minimum particle size of 116.53 nm for composition (A) with a sonication time of approximately 30 min. Similarly, for composition (B), the model predicted a minimum particle size of 129.97 nm with sonication times of approximately 30 or 55 min. In most instances, a PDI of less than 0.2 was achieved. These results highlight the significant impact of optimizing independent factors on the characteristics of liposomal nanoparticles and demonstrate the potential of EL as a decision support system for identifying the best liposomal formulation. We recommend further studies to explore the effects of other independent factors, such as lipid composition and surfactants, on liposomal nanoparticle characteristics. [ABSTRACT FROM AUTHOR]

Introduction: Vitamin D deficiency has been reported to affect liver function biomarkers. This study was aimed to investigate the effect of consuming vitamin D fortified low-fat dairy products on liver function tests in adults with abdominal obesity. Methods: This total blinded randomized controlled trial was undertaken on otherwise healthy abdominally obese adults living in Mashhad, Iran. Milk and yogurt were fortified with 1500 IU vitamin D3 nano-capsules. Participants were randomized to receive fortified milk (n = 73), plain milk (n = 73), fortified yogurt (n = 69), and plain yogurt (n = 74) for 10 weeks. Blood samples were taken at baseline and at the end of the study to assess serum levels of vitamin D, alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase (ALP), and Gamma glutamyl transferase. Results: A total of 289 participants completed the study (54% female). The groups were homogenous in terms of age, sex, weight, energy intake, and physical activity level (p-value > 0.05). After the trial, vitamin D serum levels were significantly increased in both groups receiving fortified products (both p < 0.001). There was a significant time*group effect only in serum ALP (p < 0.001). Conclusion: Consumption of dairy products fortified by 1500 IU vitamin D3 might have detrimental effects on serum levels of some liver enzymes in individuals with abdominal obesity. Further studies needed to determine these effects and underlying mechanisms. Trial registration: IRCT20101130005280N27. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article "Frequency and Nature of Drug-drug Interactions in a Dutch University Hospital," by J.E. Zwart-van Rijkom and colleagues in the 2009 issue.

Background: To implement the new marker in clinical practice, reliability assessment, validation, and standardization of utilization must be applied. This study evaluated the reliability of tumor-infiltrating lymphocytes (TILs) and tumor-stroma ratio (TSR) assessment through conventional microscopy by comparing observers' estimations. Methods: Intratumoral and tumor-front stromal TILs, and TSR, were assessed by three pathologists using 86 CRC HE slides. TSR and TILs were categorized using one and four different proposed cutoff systems, respectively, and agreement was assessed using the intraclass coefficient (ICC) and Cohen's kappa statistics. Pairwise evaluation of agreement was performed using the Fleiss kappa statistic and the concordance rate and it was visualized by Bland–Altman plots. To investigate the association between biomarkers and patient data, Pearson's correlation analysis was applied. Results: For the evaluation of intratumoral stromal TILs, ICC of 0.505 (95% CI: 0.35–0.64) was obtained, kappa values were in the range of 0.21 to 0.38, and concordance rates in the range of 0.61 to 0.72. For the evaluation of tumor-front TILs, ICC was 0.52 (95% CI: 0.32–0.67), the overall kappa value ranged from 0.24 to 0.30, and the concordance rate ranged from 0.66 to 0.72. For estimating the TSR, the ICC was 0.48 (95% CI: 0.35–0.60), the kappa value was 0.49 and the concordance rate was 0.76. We observed a significant correlation between tumor grade and the median of TSR (0.29 (95% CI: 0.032–0.51), p-value = 0.03). Conclusions: The agreement between pathologists in estimating these markers corresponds to poor-to-moderate agreement; implementing immune scores in daily practice requires more concentration in inter-observer agreements. [ABSTRACT FROM AUTHOR]

Background: The study aimed to compare the prognostic accuracy of six different severity-of-illness scoring systems for predicting in-hospital mortality among patients with confirmed SARS-COV2 who presented to the emergency department (ED). The scoring systems assessed were worthing physiological score (WPS), early warning score (EWS), rapid acute physiology score (RAPS), rapid emergency medicine score (REMS), national early warning score (NEWS), and quick sequential organ failure assessment (qSOFA). Materials and methods: A cohort study was conducted using data obtained from electronic medical records of 6,429 confirmed SARS-COV2 patients presenting to the ED. Logistic regression models were fitted on the original severity-of-illness scores to assess the models' performance using the Area Under the Curve for ROC (AUC-ROC) and Precision-Recall curves (AUC-PR), Brier Score (BS), and calibration plots were used to assess the models' performance. Bootstrap samples with multiple imputations were used for internal validation. Results: The mean age of the patients was 64 years (IQR:50--76) and 57.5% were male. The WPS, REMS, and NEWS models had AUROC of 0.714, 0.705, and 0.701, respectively. The poorest performance was observed in the RAPS model, with an AUROC of 0.601. The BS for the NEWS, qSOFA, EWS, WPS, RAPS, and REMS was 0.18, 0.09, 0.03, 0.14, 0.15, and 0.11 respectively. Excellent calibration was obtained for the NEWS, while the other models had proper calibration. Conclusion: The WPS, REMS, and NEWS have a fair discriminatory performance and may assist in risk stratification for SARS-COV2 patients presenting to the ED. Generally, underlying diseases and most vital signs are positively associated with mortality and were different between the survivors and non-survivors. [ABSTRACT FROM AUTHOR]

Background. A comparison of emergency residents' judgments and two derivatives of the Sequential Organ Failure Assessment (SOFA), namely, the mSOFA and the qSOFA, was conducted to determine the accuracy of predicting in-hospital mortality among critically ill patients in the emergency department (ED). Methods. A prospective cohort research was performed on patients over 18 years of age presented to the ED. We used logistic regression to develop a model for predicting in-hospital mortality by using qSOFA, mSOFA, and residents' judgment scores. We compared the accuracy of prognostic models and residents' judgment in terms of the overall accuracy of the predicted probabilities (Brier score), discrimination (area under the ROC curve), and calibration (calibration graph). Analyses were carried out using R software version R-4.2.0. Results. In the study, 2,205 patients with median age of 64 (IQR: 50-77) years were included. There were no significant differences between the qSOFA (AUC 0.70; 95% CI: 0.67-0.73) and physician's judgment (AUC 0.68; 0.65-0.71). Despite this, the discrimination of mSOFA (AUC 0.74; 0.71-0.77) was significantly higher than that of the qSOFA and residents' judgments. Additionally, the AUC-PR of mSOFA, qSOFA, and emergency resident's judgments was 0.45 (0.43-0.47), 0.38 (0.36-0.40), and 0.35 (0.33-0.37), respectively. The mSOFA appears stronger in terms of overall performance: 0.13 vs. 0.14 and 0.15. All three models showed good calibration. Conclusion. The performance of emergency residents' judgment and the qSOFA was the same in predicting in-hospital mortality. However, the mSOFA predicted better-calibrated mortality risk. Large-scale studies should be conducted to determine the utility of these models. [ABSTRACT FROM AUTHOR]

Background: Echinococcosis is a helminthic infection caused by ingestion of the eggs of the parasitic metacestode of one of four members of the Echinococcus genus. Among them, hepatic alveolar echinococcosis (HAE) mimics slow growing liver tumour with subsequent invasion to liver tissues and metastatic dissemination. Liver transplantation (LT) remains as the only treatment option when the lesions exceed the resectability limits. We described the first three cases of HAE who underwent orthotopic LT in Iran. A literature review was also conducted to summarize experiences of different transplant centres around the world. Methods: PubMed, Scopus and Web of Science databases were searched up to April 2017 using keywords related to echinococcosis, liver and transplantation. Results: Including this case report, a total of 150 patients underwent LT due to echinococcosis from 1994 to 2017. The mean age at LT was 38 years (range: 12-71) and 51% were male. About 95% of the transplantations were performed due to HAE. Pre- and post-transplant benzimidazole therapy was considered in 69% and 73% of patients, respectively. Recurrence rate varied between 0% and 60%. The overall 1-, 5- and 10-year survival rates were 60-100%, 67-85% and 49-75%, respectively. Conclusions: LT combined with pre- and post-transplant benzimidazole therapy appears to be feasible and effective for patients with fatal HAE. [ABSTRACT FROM AUTHOR]

Background: Previous efforts such as Assessing Care of Vulnerable Elders (ACOVE) provide quality indicators for assessing the care of elderly patients, but thus far little has been done to leverage this knowledge to improve care for these patients. We describe a clinical decision support system to improve general practitioner (GP) adherence to ACOVE quality indicators and a protocol for investigating impact on GPs' adherence to the rules.Design: We propose two randomized controlled trials among a group of Dutch GP teams on adherence to ACOVE quality indicators. In both trials a clinical decision support system provides un-intrusive feedback appearing as a color-coded, dynamically updated, list of items needing attention. The first trial pertains to real-time automatically verifiable rules. The second trial concerns non-automatically verifiable rules (adherence cannot be established by the clinical decision support system itself, but the GPs report whether they will adhere to the rules). In both trials we will randomize teams of GPs caring for the same patients into two groups, A and B. For the automatically verifiable rules, group A GPs receive support only for a specific inter-related subset of rules, and group B GPs receive support only for the remainder of the rules. For non-automatically verifiable rules, group A GPs receive feedback framed as actions with positive consequences, and group B GPs receive feedback framed as inaction with negative consequences. GPs indicate whether they adhere to non-automatically verifiable rules. In both trials, the main outcome measure is mean adherence, automatically derived or self-reported, to the rules.Discussion: We relied on active end-user involvement in selecting the rules to support, and on a model for providing feedback displayed as color-coded real-time messages concerning the patient visiting the GP at that time, without interrupting the GP's workflow with pop-ups. While these aspects are believed to increase clinical decision support system acceptance and its impact on adherence to the selected clinical rules, systems with these properties have not yet been evaluated.Trial Registration: Controlled Trials NTR3566. [ABSTRACT FROM AUTHOR]

Background: In pediatrics, many drugs are used without marketing authorization. Recommendations are often based on clinical experience. Therefore, the risk of inappropriate prescription (IP) is high. It is necessary to have a tool for pediatric IP detection. Objectives: This study was performed to develop and validate a Pediatrics: Omission of Prescriptions and Inappropriate Prescriptions (POPI) screening tool to facilitate its use in pediatric practice in Iran. Methods: Using forward- and backward-translation procedures, an efficient and effective tool was provided in the current study and clinical settings. The two-round Delphi technique established content validity. The criteria were then piloted in a cross-sectional study in the pediatric patients of Khorasan Razavi and East Azerbaijan in Iran. Results: A total of 104 explicit criteria (79 IPs and 25 omissions) were obtained and submitted to an 18-member expert panel (including 8 pharmacists, 2 clinical pharmacists, and 8 pediatricians working in a hospital or the community). Then, 98 out of the 104 criteria submitted to the experts were selected after two Delphi rounds (75 IPs and 23 omissions). The content validity and reliability of the tool were obtained by expert assessment (Cronbach's alpha for the entire criteria: 0.60). At least, the rate of one inappropriate prescribed medication was 69% in Mashhad, almost twice that of Tabriz (35%). Conclusions: The modified POPI criteria comprise the first screening tool to assess rational prescriptions for pediatric patients in hospital and outpatient settings. Clinical validation and reliability studies are needed and planned by the authors to evaluate the usability and reliability of this tool. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objective: We systematically reviewed models to predict adult ICU length of stay.Data Sources: We searched the Ovid EMBASE and MEDLINE databases for studies on the development or validation of ICU length of stay prediction models.Study Selection: We identified 11 studies describing the development of 31 prediction models and three describing external validation of one of these models.Data Extraction: Clinicians use ICU length of stay predictions for planning ICU capacity, identifying unexpectedly long ICU length of stay, and benchmarking ICUs. We required the model variables to have been published and for the models to be free of organizational characteristics and to produce accurate predictions, as assessed by R across patients for planning and identifying unexpectedly long ICU length of stay and across ICUs for benchmarking, with low calibration bias. We assessed the reporting quality using the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies.Data Synthesis: The number of admissions ranged from 253 to 178,503. Median ICU length of stay was between 2 and 6.9 days. Two studies had not published model variables and three included organizational characteristics. None of the models produced predictions with low bias. The R was 0.05-0.28 across patients and 0.01-0.64 across ICUs. The reporting scores ranged from 49 of 78 to 60 of 78 and the methodologic scores from 12 of 22 to 16 of 22.Conclusion: No models completely satisfy our requirements for planning, identifying unexpectedly long ICU length of stay, or for benchmarking purposes. Physicians using these models to predict ICU length of stay should interpret them with reservation. [ABSTRACT FROM AUTHOR]

Background. BMI has been evaluated as an old criterion to evaluate obesity in individuals, but it does not assess abdominal obesity and lean mass. We aimed to evaluate the possible relationship of new anthropometric indices (namely, a body shape index (ABSI), the body roundness index (BRI), the visceral adiposity index (VAI), the visceral fat area (VFA), and waist-hip ratio (WHR)), with one of the known critical factors of atherosclerosis, arterial stiffness. Methods. Overall 5921 individuals were enrolled and were divided into four groups according to BMI. Novel anthropometric parameters including, ABSI, BRI, VAI, VFA, and WHR were calculated. The carotid-femoral pulse wave velocity (cf-PWV) was used to evaluate arterial stiffness. Multiple regression analysis was performed to assess the relationship between cf-PWV and innovative Anthropometric indices. Results. This study population consisted of 3109 women and 2812 males. In men with overweight, cf-PWV was significantly related to BMI, ABSI, BRI, WC, VAI, VFA, and WHR. However, among men with obesity, cf-PWV was associated with BRI, VAI, and VFA. Among women with overweight, cf-PWV was also related to all mentioned indices except ABSI; although, cf-PWV was only associated with VFA and WHR in women with obesity. Conclusion. Our results showed that VFA in women and VAI in men are strongly related to arterial stiffness and can be used to identify predictors of vascular disease or organic vascular dysfunction. [ABSTRACT FROM AUTHOR]

Introduction: The cardiovascular intensive care unit (CVICU) registry provides physicians with tools for monitoring, managing, and following up on patients. The CVICU registry provides researchers with the ability to analyze and evaluate integrated data patients. Our goal with this study is to explain the design, development, and deployment of a comprehensive, integrated, qualified cardiovascular intensive care unit registry, as well as to characterize individuals admitted to CVICUs. Material and Methods: From June 2012, a cohort study of ICU admissions for adults (≥18 years) in a teaching hospital’s CVICU began. The study includes retrospective collection of existing data from paper records and hospital information systems (HIS) and ongoing prospective collection using the proposed CVICU registry portal. Results: Between June 2013 and June 2022, 2587 admissions were included, among which 1041 (40.2%) were women, 1546 (59.8%) were man, and the median age was 58 ranging from 18 to 93 years and their mean (SD) age was 56.8 (13) years. About 11.1% of the patients died in the CVICU. The primary indications for CVICU care included mechanical ventilation (29.7%), weaning time or readmission (4.9%), cardiovascular (17.4%), myocardial infarction (1.7%), diabetes (9.3%), hypertension (14.3%). Of these, about 73% had coronary artery bypass grafting (CABG), 15% valve surgery and the remains has other cardiovascular surgeries. About 39% experienced an on-pump surgery. In addition, patients had 6.4 hours weaning time after operation. The overall CVICU length of stay (LOS) rate was 3.6 days and mean predicted by APACHE IV, APACHE II, SOFA, and SAPS II were 5.67, 3.03, 4, and 4 days, respectively. Conclusion: The use of registries equipped physicians and researchers with an integrated data pool to manage and evaluate information. Appropriate patient registries allow effective decision-making for appropriate interventions, resource allocation, and ongoing data monitoring and analysis. Ultimately, this leads to the optimal outcomes for patients. This registry aims to generate valuable knowledge about cardiovascular ICU patients in Iran and to collect accurate and qualified data. [ABSTRACT FROM AUTHOR]

Background: Cardiovascular disease is a leading cause of death in many societies. Arterial stiffness is an initial sign of structural and functional changes in the arterial wall. Pulse wave velocity (PWV) is the gold standard for non-invasive evaluation of aortic stiffness and a modifiable cardiovascular risk factor. Curcumin is a major component of turmeric with known anti-inflammatory and anti-oxidative effects. Since arterial stiffness is affected by inflammation and oxidative stress, it may be improved by curcumin supplementation. The purpose of this clinical trial was to investigate the potential effects of curcumin on improving arterial stiffness in patients with metabolic syndrome. Methods: This placebo-controlled, double-blind, randomized clinical trial was conducted among metabolic syndrome patients. Sixty-six eligible individuals were randomly assigned to active intervention or control groups. The active intervention group received curcumin supplement at a dose of 500 mg daily for 12 weeks, whereas the control group received placebo capsule. Physical activity, daily dietary energy intake, anthropometric, body composition, biochemical, hemodynamic, and arterial stiffness parameters were evaluated at baseline and the end of the study. Results: In this study, body weight decreased significantly in the curcumin group compared to placebo. Also, curcumin intervention improved PWV, which remained significant after adjustment for potential confounding factors (P=0.011). Conclusion: The current clinical trial demonstrated that daily intake of 500 mg of curcumin for 12 weeks can lead to the improvement of arterial stiffness and weight management among subjects with metabolic syndrome. [ABSTRACT FROM AUTHOR]

Background: Cardiovascular disease is a leading cause of death in many societies. Arterial stiffness is an initial sign of structural and functional changes in the arterial wall. Pulse wave velocity (PWV) is the gold standard for non-invasive evaluation of aortic stiffness and a modifiable cardiovascular risk factor. Curcumin is a major component of turmeric with known anti-inflammatory and anti-oxidative effects. Since arterial stiffness is affected by inflammation and oxidative stress, it may be improved by curcumin supplementation. The purpose of this clinical trial was to investigate the potential effects of curcumin on improving arterial stiffness in patients with metabolic syndrome. Methods: This placebo-controlled, double-blind, randomized clinical trial was conducted among metabolic syndrome patients. Sixty-six eligible individuals were randomly assigned to active intervention or control groups. The active intervention group received curcumin supplement at a dose of 500 mg daily for 12 weeks, whereas the control group received placebo capsule. Physical activity, daily dietary energy intake, anthropometric, body composition, biochemical, hemodynamic, and arterial stiffness parameters were evaluated at baseline and the end of the study. Results: In this study, body weight decreased significantly in the curcumin group compared to placebo. Also, curcumin intervention improved PWV, which remained significant after adjustment for potential confounding factors (P=0.011). Conclusion: The current clinical trial demonstrated that daily intake of 500 mg of curcumin for 12 weeks can lead to the improvement of arterial stiffness and weight management among subjects with metabolic syndrome. [ABSTRACT FROM AUTHOR]

Background: The quality of data in electronic health records (EHRs) depends on adherence of clinicians to principles of diagnosis documentation. Objective: A concept mapping (CM) approach was used to extract factors related to quality of clinicians' documentation that govern EHR data quality. Method: Influential factors extracted from brainstorming sessions were sorted by individual participants, followed by a quantitative analysis using multidimensional scaling and cluster analysis to categorise sorted factors. Finally, a questionnaire was used to elicit the importance-feasibility of the extracted factors. Results were visualised by cluster maps and Go-Zone plots. Result: Factors were classified into seven clusters: "knowledge about International Classification of Diseases and clinical coding," "need for facilitators and guidelines," "explaining the importance of the issue and defining responsibilities," "cooperation of other personnel," "codify legal requirements," "workload" and "clinical obstacles," as ranked by importance. Conclusion: To enhance the quality of EHR data, a collaboration between physicians, nurses, managers and EHR developers is required. CM is an acceptable approach to meet this objective. Our findings highlight the significance of clinical coding knowledge, awareness about its importance and applicability and use of well-structured information systems. In combination, these three factors can have a strong positive impact on the quality of EHR data. Implications: A list of solutions is provided for policymakers, and two interventions suggested, based on the findings of this study, including the adoption of EHRs that incorporate documentation guidelines. We further propose updated clinical training programs and a monitoring and feedback mechanism to facilitate the EHR documentation process. [ABSTRACT FROM AUTHOR]

Background: For physicians dealing with patients with a limited life expectancy, knowing the time to benefit (TTB) of preventive medication is essential to support treatment decisions. Objective: The aim of this study was to investigate the usefulness of statistical process control (SPC) for determining the TTB in relation to fracture risk with alendronate versus placebo in postmenopausal women. Methods: We performed a post hoc analysis of the Fracture Intervention Trial (FIT), a randomized, controlled trial that investigated the effect of alendronate versus placebo on fracture risk in postmenopausal women. We used SPC, a statistical method used for monitoring processes for quality control, to determine if and when the intervention group benefited significantly more than the control group. SPC discriminated between the normal variations over time in the numbers of fractures in both groups and the variations that were attributable to alendronate. The TTB was defined as the time point from which the cumulative difference in the number of clinical fractures remained greater than the upper control limit on the SPC chart. Results: For the total group, the TTB was defined as 11 months. For patients aged ≥70 years, the TTB was 8 months [absolute risk reduction (ARR) = 1.4 %]; for patients aged <70 years, it was 19 months (ARR = 0.7 %). Conclusion: SPC is a clear and understandable graphical method to determine the TTB. Its main advantage is that there is no need to define a prespecified time point, as is the case in traditional survival analyses. Prescribing alendronate to patients who are aged ≥70 years is useful because the TTB shows that they will benefit after 8 months. Investigators should report the TTB to simplify clinical decision making. [ABSTRACT FROM AUTHOR]

To quantify the optic nerve head (ONH) and peripapillary retinal nerve fiber layer (pRNFL) thickness in patients with Coronavirus Disease-2019 (COVID-19) and compare the measurements with a healthy control group. In a comparative cross-sectional observational study, ONH and pRNFL thickness were evaluated in patients with a history of COVID-19, at least 2 weeks after recovery from the systemic disease, and compared with an age-matched, normal control group. Thirty COVID-19 patients along with 60 age- and gender-matched healthy controls were studied. Mean average pRNFL thickness was 105.0 ± 16.3 µm in the COVID-19 patients, compared to 99.0 ± 9.0 µm in the controls (p =.31). The pRNFL thicknesses in all sectors was higher in patients with a history of COVID-19; however, this did not reach statistical significance. Similarly, ONH parameters were not significantly different between the groups. Patients recovered from COVID-19 had unremarkable alterations in the peripapillary RNFL thickness. ONH: Optic Nerve HeadRNFL: Retinal Nerve Fiber LayerSD-OCT: Spectral-Domain Optical Coherence TomographyCOVID-19: Coronavirus Disease 2019SARS-CoV-2: Severe Acute Respiratory Syndrome Coronavirus 2CNS: Central Nervous SystemACE: Angiotensin-Converting EnzymeRT-PCR: Reverse Transcription-Polymerase Chain Reaction [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to evaluate the retinal and choroidal changes in the macular region of patients with Coronavirus Disease 2019 (COVID-19) using structural spectral-domain optical coherence tomography (SD-OCT) analysis. Methods: This cross-sectional observational case-control study included patients recovered from COVID-19. The COVID-19 in all participants was confirmed using the reverse transcription-polymerase chain reaction (RT-PCR) technique. The participants had mild to moderate degree of disease without a history of hospitalization, steroid usage, or blood saturation below 92%. Macular SD-OCT was performed at least two weeks and up to one month after recovery from systemic COVID-19. Quantitative and qualitative changes detected by macular SD-OCT imaging were evaluated in COVID-19 recovered patients and compared with the results of age-matched normal controls. Results: Participants in this study included 30 cases (60 eyes) and 60 healthy controls (120 eyes). In total, 17 (28.3%) eyes in patient group showed at least one abnormal finding indicated by macular SD-OCT imaging included hyperreflective lesions in different retinal layers. In addition, dilated choroidal vessels and retinal pigment epitheliopathy were evident in 41 (68.3.6%) and 4 (6.6%) eyes in patient group, respectively, and their OCT findings resembled those with pachychoroid spectrum. No statistically significant differences were observed in retinal layers or retinal volume between the two groups. The mean ± SD subfoveal choroidal thickness (SFCT) was determined at 380.3 ± 12.40 μm, which was significantly thicker than that in control group (310.7 ± 57.5 μm) (P < 0.001). Conclusion: Regarding retinal thickness, no significant change was observed in different retina layers of patients with COVID-19; however, there were striking qualitative changes, such as hyperreflective lesions in different retinal layers. The evaluation of choroidal structure and thickness demonstrated remarkable abnormal pachyvessels and significant thickening of the SFCT but the clinical significance of these findings is unknown. [ABSTRACT FROM AUTHOR]

Patients admitted to the intensive care unit (ICU) are frequently exposed to potential drug‐drug interactions (pDDIs). However, reported frequencies of pDDIs in the ICU vary widely between studies. This can be partly explained by significant variation in their methodological approach. Insight into methodological choices affecting pDDI frequency would allow for improved comparison and synthesis of reported pDDI frequencies. This study aimed to evaluate the association between methodological choices and pDDI frequency and formulate reporting recommendations for pDDI frequency studies in the ICU. The MEDLINE database was searched to identify papers reporting pDDI frequency in ICU patients. For each paper, the pDDI frequency and methodological choices such as pDDI definition and pDDI knowledge base were extracted, and the risk of bias was assessed. Each paper was categorized as reporting a low, medium, or high pDDI frequency. We sought associations between methodological choices and pDDI frequency group. Based on this comparison, reporting recommendations were formulated. Analysis of methodological choices showed significant heterogeneity between studies, and 65% of the studies had a medium to high risk of bias. High risk of bias, small sample size, and use of drug prescriptions instead of administrations were related to a higher pDDI frequency. The findings of this review may support researchers in designing a reliable methodology assessing pDDI frequency in ICU patients. The reporting recommendations may contribute to standardization, comparison, and synthesis of pDDI frequency studies, ultimately improving knowledge about pDDIs in and outside the ICU setting. [ABSTRACT FROM AUTHOR]

Background: The first large serosurvey in Iran found a SARS-CoV-2 antibody seroprevalence of 17.1% among the general population in the first wave of the epidemic by April, 2020. The purpose of the current study was to assess the seroprevalence of COVID-19 infection among Iranian general population after the third wave of the disease.Methods: This population-based cross-sectional study was conducted on 7411 individuals aged ≥10 years old in 16 cities across 15 provinces in Iran between January and March, 2021. We randomly sampled individuals registered in the Iranian electronic health record system based on their national identification numbers and invited them by telephone to a healthcare center for data collection. Presence of SARS-CoV-2-specific IgG and IgM antibodies was assessed using the SARS-CoV-2 ELISA kits. The participants were also asked about their recent COVID-19-related symptoms, including cough, fever, chills, sore throat, headache, dyspnea, diarrhea, anosmia, conjunctivitis, weakness, myalgia, arthralgia, altered level of consciousness, and chest pain. The seroprevalence was estimated after adjustment for population weighting and test performance.Results: The overall population-weighted seroprevalence adjusted for test performance was 34.2% (95% CI 31.0-37.3), with an estimated 7,667,874 (95% CI 6,950,412-8,362,915) infected individuals from the 16 cities. The seroprevalence varied between the cities, from the highest estimate in Tabriz (39.2% [95% CI 33.0-45.5]) to the lowest estimate in Kerman (16.0% [95% CI 10.7-21.4]). In the 16 cities studied, 50.9% of the seropositive individuals did not report a history of symptoms suggestive of COVID-19, implying an estimation of 3,902,948 (95% CI 3,537,760-4,256,724) asymptomatic infected individuals.Conclusions: Nearly one in three individuals were exposed to SARS-CoV-2 in the studied cities by March 2021. The seroprevalence increased about two-fold between April, 2020, and March, 2021. [ABSTRACT FROM AUTHOR]