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Abstract Background For mechanically ventilated critically ill COVID-19 patients, prone positioning has quickly become an important treatment strategy, however, prone positioning is labor intensive and comes with potential adverse effects. Therefore, identifying which critically ill intubated COVID-19 patients will benefit may help allocate labor resources. Methods From the multi-center Dutch Data Warehouse of COVID-19 ICU patients from 25 hospitals, we selected all 3619 episodes of prone positioning in 1142 invasively mechanically ventilated patients. We excluded episodes longer than 24 h. Berlin ARDS criteria were not formally documented. We used supervised machine learning algorithms Logistic Regression, Random Forest, Naive Bayes, K-Nearest Neighbors, Support Vector Machine and Extreme Gradient Boosting on readily available and clinically relevant features to predict success of prone positioning after 4 h (window of 1 to 7 h) based on various possible outcomes. These outcomes were defined as improvements of at least 10% in PaO2/FiO2 ratio, ventilatory ratio, respiratory system compliance, or mechanical power. Separate models were created for each of these outcomes. Re-supination within 4 h after pronation was labeled as failure. We also developed models using a 20 mmHg improvement cut-off for PaO2/FiO2 ratio and using a combined outcome parameter. For all models, we evaluated feature importance expressed as contribution to predictive performance based on their relative ranking. Results The median duration of prone episodes was 17 h (11–20, median and IQR, N = 2632). Despite extensive modeling using a plethora of machine learning techniques and a large number of potentially clinically relevant features, discrimination between responders and non-responders remained poor with an area under the receiver operator characteristic curve of 0.62 for PaO2/FiO2 ratio using Logistic Regression, Random Forest and XGBoost. Feature importance was inconsistent between models for different outcomes. Notably, not even being a previous responder to prone positioning, or PEEP-levels before prone positioning, provided any meaningful contribution to predicting a successful next proning episode. Conclusions In mechanically ventilated COVID-19 patients, predicting the success of prone positioning using clinically relevant and readily available parameters from electronic health records is currently not feasible. Given the current evidence base, a liberal approach to proning in all patients with severe COVID-19 ARDS is therefore justified and in particular regardless of previous results of proning.

Abstract Introduction Determining the optimal timing for extubation can be challenging in the intensive care. In this study, we aim to identify predictors for extubation failure in critically ill patients with COVID-19. Methods We used highly granular data from 3464 adult critically ill COVID patients in the multicenter Dutch Data Warehouse, including demographics, clinical observations, medications, fluid balance, laboratory values, vital signs, and data from life support devices. All intubated patients with at least one extubation attempt were eligible for analysis. Transferred patients, patients admitted for less than 24 h, and patients still admitted at the time of data extraction were excluded. Potential predictors were selected by a team of intensive care physicians. The primary and secondary outcomes were extubation without reintubation or death within the next 7 days and within 48 h, respectively. We trained and validated multiple machine learning algorithms using fivefold nested cross-validation. Predictor importance was estimated using Shapley additive explanations, while cutoff values for the relative probability of failed extubation were estimated through partial dependence plots. Results A total of 883 patients were included in the model derivation. The reintubation rate was 13.4% within 48 h and 18.9% at day 7, with a mortality rate of 0.6% and 1.0% respectively. The grandient-boost model performed best (area under the curve of 0.70) and was used to calculate predictor importance. Ventilatory characteristics and settings were the most important predictors. More specifically, a controlled mode duration longer than 4 days, a last fraction of inspired oxygen higher than 35%, a mean tidal volume per kg ideal body weight above 8 ml/kg in the day before extubation, and a shorter duration in assisted mode (

Abstract Background The Coronavirus disease 2019 (COVID-19) pandemic has underlined the urgent need for reliable, multicenter, and full-admission intensive care data to advance our understanding of the course of the disease and investigate potential treatment strategies. In this study, we present the Dutch Data Warehouse (DDW), the first multicenter electronic health record (EHR) database with full-admission data from critically ill COVID-19 patients. Methods A nation-wide data sharing collaboration was launched at the beginning of the pandemic in March 2020. All hospitals in the Netherlands were asked to participate and share pseudonymized EHR data from adult critically ill COVID-19 patients. Data included patient demographics, clinical observations, administered medication, laboratory determinations, and data from vital sign monitors and life support devices. Data sharing agreements were signed with participating hospitals before any data transfers took place. Data were extracted from the local EHRs with prespecified queries and combined into a staging dataset through an extract–transform–load (ETL) pipeline. In the consecutive processing pipeline, data were mapped to a common concept vocabulary and enriched with derived concepts. Data validation was a continuous process throughout the project. All participating hospitals have access to the DDW. Within legal and ethical boundaries, data are available to clinicians and researchers. Results Out of the 81 intensive care units in the Netherlands, 66 participated in the collaboration, 47 have signed the data sharing agreement, and 35 have shared their data. Data from 25 hospitals have passed through the ETL and processing pipeline. Currently, 3464 patients are included in the DDW, both from wave 1 and wave 2 in the Netherlands. More than 200 million clinical data points are available. Overall ICU mortality was 24.4%. Respiratory and hemodynamic parameters were most frequently measured throughout a patient's stay. For each patient, all administered medication and their daily fluid balance were available. Missing data are reported for each descriptive. Conclusions In this study, we show that EHR data from critically ill COVID-19 patients may be lawfully collected and can be combined into a data warehouse. These initiatives are indispensable to advance medical data science in the field of intensive care medicine.

The purpose of this research was to identify the need for gender equality education. For this purpose, the views of mathematics, science, and information technology teachers on the current situation of gender equality in schools were determined. In addition, the awareness of sixth, seventh and eighth grade middle school students on gender equality was examined. This study was a descriptive research conducted in a qualitative context. In data collection, an interview form on teachers' views and a written view form on students' awareness about gender equality were used. Research data were collected in the spring semester of the 2017-2018 academic year. As a result of the research, it is thought that an interdisciplinary gender equality education will be beneficial to improve students' awareness.

The purpose of this study is to determine and compare how undergraduate students' attitudes towards on-line exams vary depending on gender and some technological variables. This study was carried out by using a survey method. As data collection tool, the Undergraduate Students Attitude Scale Towards On-line Exams which consists of 21 items, each with five response alternatives covering attitudes of undergraduate students towards on-line exams was used. Scale was developed by Author & Author (2022). In this research, scale was administered to 1361 undergraduate school students from four different universities 2020-2021 academic year in Turkey. The convenience sampling method was used for selecting participants. The data were analyzed by One-Way ANOVA and independent-sample t- tests using a statistical package program (SPSS 10.0). As a result, Wi-Fi-using undergraduate students had higher attitude scores in Taking Precautions, Individual Characteristics dimensions and in total scores of USASOE. Female undergraduate students had higher attitude scores in the Taking Precautions dimension. Moreover, students who spend more hours on the internet had higher attitude scores and in on-line exams computer using students also had higher attitudes. Finally, in the Taking Precautions dimension, students who always or sometimes attend on-line courses had more positive attitudes than the ones who never attend on-line courses.

The general aim of the study was to improve students' awareness of gender equality. An instructional design was developed in which mathematics, science, information technologies and software (ITS) courses were integrated, with the theme of gender equality at the center. The method of the study was determined as a case study. The participants of the study were 21 sixth-grade students at a public school in Turkey. Research data were collected using the "Views Form on Gender Equality" and "Practice Evaluation Form" developed by the researchers. According to the students' views, it was determined that an interdisciplinary education on gender equality had positive effects on improving students' awareness of gender equality. When the students' views about the practice process were examined, it was seen that the positive opinions about the process were high in number, and students presented few negative views.

Abstract Background The identification of risk factors for adverse outcomes and prolonged intensive care unit (ICU) stay in COVID-19 patients is essential for prognostication, determining treatment intensity, and resource allocation. Previous studies have determined risk factors on admission only, and included a limited number of predictors. Therefore, using data from the highly granular and multicenter Dutch Data Warehouse, we developed machine learning models to identify risk factors for ICU mortality, ventilator-free days and ICU-free days during the course of invasive mechanical ventilation (IMV) in COVID-19 patients. Methods The DDW is a growing electronic health record database of critically ill COVID-19 patients in the Netherlands. All adult ICU patients on IMV were eligible for inclusion. Transfers, patients admitted for less than 24 h, and patients still admitted at time of data extraction were excluded. Predictors were selected based on the literature, and included medication dosage and fluid balance. Multiple algorithms were trained and validated on up to three sets of observations per patient on day 1, 7, and 14 using fivefold nested cross-validation, keeping observations from an individual patient in the same split. Results A total of 1152 patients were included in the model. XGBoost models performed best for all outcomes and were used to calculate predictor importance. Using Shapley additive explanations (SHAP), age was the most important demographic risk factor for the outcomes upon start of IMV and throughout its course. The relative probability of death across age values is visualized in Partial Dependence Plots (PDPs), with an increase starting at 54 years. Besides age, acidaemia, low P/F-ratios and high driving pressures demonstrated a higher probability of death. The PDP for driving pressure showed a relative probability increase starting at 12 cmH2O. Conclusion Age is the most important demographic risk factor of ICU mortality, ICU-free days and ventilator-free days throughout the course of invasive mechanical ventilation in critically ill COVID-19 patients. pH, P/F ratio, and driving pressure should be monitored closely over the course of mechanical ventilation as risk factors predictive of these outcomes.

OBJECTIVES:. As coronavirus disease 2019 is a novel disease, treatment strategies continue to be debated. This provides the intensive care community with a unique opportunity as the population of coronavirus disease 2019 patients requiring invasive mechanical ventilation is relatively homogeneous compared with other ICU populations. We hypothesize that the novelty of coronavirus disease 2019 and the uncertainty over its similarity with noncoronavirus disease 2019 acute respiratory distress syndrome resulted in substantial practice variation between hospitals during the first and second waves of coronavirus disease 2019 patients. DESIGN:. Multicenter retrospective cohort study. SETTING:. Twenty-five hospitals in the Netherlands from February 2020 to July 2020, and 14 hospitals from August 2020 to December 2020. PATIENTS:. One thousand two hundred ninety-four critically ill intubated adult ICU patients with coronavirus disease 2019 were selected from the Dutch Data Warehouse. Patients intubated for less than 24 hours, transferred patients, and patients still admitted at the time of data extraction were excluded. MEASUREMENTS AND MAIN RESULTS:. We aimed to estimate between-ICU practice variation in selected ventilation parameters (positive end-expiratory pressure, Fio2, set respiratory rate, tidal volume, minute volume, and percentage of time spent in a prone position) on days 1, 2, 3, and 7 of intubation, adjusted for patient characteristics as well as severity of illness based on Pao2/Fio2 ratio, pH, ventilatory ratio, and dynamic respiratory system compliance during controlled ventilation. Using multilevel linear mixed-effects modeling, we found significant (p ≤ 0.001) variation between ICUs in all ventilation parameters on days 1, 2, 3, and 7 of intubation for both waves. CONCLUSIONS:. This is the first study to clearly demonstrate significant practice variation between ICUs related to mechanical ventilation parameters that are under direct control by intensivists. Their effect on clinical outcomes for both coronavirus disease 2019 and other critically ill mechanically ventilated patients could have widespread implications for the practice of intensive care medicine and should be investigated further by causal inference models and clinical trials.

This mixed-methods study explored the nature, effectiveness, and policy implications of the fee-charging private supplementary tutoring (PT)--including online--that first-year Kazakhstani university students attended over the last 12 months. The data were collected from 952 participants using a close-ended questionnaire followed by semi-structured online interviews with 22 participants. The study found that the PT market expanded during the COVID-19 pandemic, during which 750 out of the 952 participants (81%) received PT. Lack of parental follow-up, limited preparation by schoolteachers on how to deliver online classes during the pandemic, and insufficient support by regular schools for students taking university entrance examinations prompted the participants to seek PT, mainly to obtain state tuition grants for highly selective universities. Despite the health risks of face-to-face PT during the COVID-19 pandemic, several participants did take part in it. The participants exercised their agency by reflecting not only on the drawbacks of online PT but also its advantages, including saving time, energy, and money and being able to revisit the taught material several times, thus, enhancing comprehension. The pedagogical implications of fair access to higher education and regulating PT by introducing codes of practice are presented.

Technologies used inside and outside museums generate brand new perspectives and learning areas for museum learning. This study analysed 45 empirical studies that included technological tools used in museums as well as those tools that dealt with the museum's visitor's learning achievements. The results of the study show that a variety of cognitive and affective skills have been achieved in ICT-assisted studies. Having different dimensions of interaction, such technologies can be used for different purposes, such as providing general guidance, synthesizing museum learning, consolidating knowledge, designing or experimenting, and/or offering individual experiences with personalized technologies. On the other hand, it appears that technology is still not being used efficiently to the fullest extent of its potential. Therefore, it is recommended that further studies should present more suitable technologies that fit individual differences, have a capacity to increase social interactions, contain enriched specifications, and can be used in a variety of environments.

The purpose of this study was to determine teacher perspectives on emergency remote teaching conducted during the COVID-19 pandemic in science and art centers. The study was carried out using a phenomenological qualitative research design with 41 science and art center teachers from 17 different majors. A content analysis method was employed in this study that used a criterion sampling method and collected data through a semi-structured interview form. The study found that most teachers have not received any training on distance education, technique-based teaching cannot be employed in remote teaching processes, the planned activities remain unfinished, student-student and student-teacher interactions decrease, teachers mostly conduct emergency remote teaching online, and teachers improved themselves in technological equipment and the knowledge of teaching profession together with emergency remote teaching. It was also found that student participation is low and teachers find face-to-face education more effective than emergency remote teaching, experience problems in feedback and revision, cannot perform observation-based measurement and evaluation, and emergency remote teaching increases the workload. Teachers expected that the distance education could be carried out on a part-time basis after the pandemic and that they receive in-service education regarding distance education.

This paper presents a systematic literature review of studies about writing in elementary schools. A systematic search of databases was conducted to select studies. The aim was to identify and categorize difficulties and suggestions. A total of 52 articles published in peer-reviewed journals over the past 21 years were reviewed and analyzed using a well-established systematic literature review methodology, in academic-based research databases, after carefully reviewing the available literature and utilizing relevant sources. This review revealed that the studies mainly emphasize the relation between reading and writing, using technology in teaching writing, acquisition of writing and a method/approach or strategy suggestion, and structure/grammar in writing. Additionally, feedback, affective domain, and teaching writing at an early age are the focus points of other studies. The findings of this literature review allow teachers, administrators, and policy makers to employ and explore efficient writing activities to improve student engagement, motivation, and performance.

This review presents how chess improves student abilities and underlines inferences about chess and its educational benefits. In this study, quantitative samples, experimental designs, or test scores of studies are not the main focus. Numerous empirical studies and limited review studies about chess instruction in the literature express the effect of chess on students' success and mental skills. However, almost all of these studies address only positive effects; this review attempts to explain "how" chess achieves this success. What are the other components of this effect? Is it possible to determine how chess impacts education? The question is how and why chess is considered so effective. Is it possible to present examples by linking basic features of chess, lessons, and cognitive structures?

Abstract Recent decades have witnessed a global expansion of private supplementary tutoring, known as shadow education—additional support in academic subjects that takes place outside of regular school hours. Using the data of 55 countries from the Programme for International Student Assessment (PISA) 2022, this study examines the association between students’ participation in shadow education and their academic achievement in mathematics and how these relationships change for developed, developing, and East Asian regions. This study also sheds light on the moderating effect that socio-economic status has on the relationship between engagement in shadow education and math performance. Multilevel regression analyses revealed that, at the between-school level, only one of the five forms of shadow education, namely the degree to which students received asynchronous video-recorded instruction, was associated with improved math performance. Similarly, at the within-school level, only the degree to which students received video-recorded instruction was statistically significantly associated with improved mathematical outcomes. Incidentally, we find that institutional-related school-level factors such as the overall quality of student–teacher relationships, provision of math-related extra-curricular activities, and support in terms of peer-to-peer tutoring appear to be associated with improved school math performance, while the quality of student–teacher relationships and level of math teacher support also feature positively for students within-schools. Regarding differential effects by region, at the between-school level, only the degree to which students received large-group study or practice was associated with math performance in East Asian countries. With regards to the moderating effect of SES on the positive relationship between asynchronous shadow education and math performance, we find the effects to be negative, suggesting that asynchronous engagement might be more beneficial for students from lower SES backgrounds. Finally, while the overall negative relationships between synchronous forms of shadow education and math performance appear counter-intuitive, we speculate that this may reflect the use of such tutoring for remedial purposes. We suggest that further research into these “remedial reverse effects” in post-COVID AI-bot-capable educational contexts may provide a more definitive understanding of the role that student engagement in shadow education has on their academic performance.

Introduction: Criteria for terminating resuscitations have been identified in the literature such as no VF/VT rhythm during cardiopulmonary resuscitation (CPR). People’s perception of death varies depending on social, geographical, cultural, and educational factors. The Death Perception Scale (DPS) was developed to measure these variations. This study aims to evaluate the relationship between individuals’ perspectives on death, the CPR process they apply in the emergency room, and the factors that affect it. Materials and Methods: The study was conducted on physicians working in emergency departments in Hatay province. The participating physicians completed a 39-question test, which included multiple-choice and DPS questions, to record their demographic data, education, and the situations they consider when terminating CPR. The data were collected digitally. IBM SPSS 27 and GraphPad Prism were used for data analysis. Results: 79 physicians participated in the study, the mean age of these physicians was 27.53 ± 3.61, and 45.6% were female. The average tenure as a physician was 2.81 years, while the average duration of work in the emergency department was 2.25 years. No statistically significant relationship was found between the change in the duration of working in the emergency department and the change in the medical profession and DPS among the physicians included in the study. No relationship was found between the degree of the physician (general practitioner, resident, and specialist) and the CPR termination times of the patients. Conclusions: Analyzing individual characteristics with objective values while managing a terminally ill patient will enhance perceptual integrity.

Abstract Objective This study compared the efficacy of ultrasound-guided erector spinae plane block (ESPB) and wound infiltration (WI) for postoperative analgesia in patients who underwent lumbar spinal surgery with instrumentation. Methods In this randomized controlled trial, 80 patients were divided into two groups: ESPB (n = 40) and WI (n = 40). Postoperative pain intensity was assessed via the visual analog scale (VAS) at multiple time points within 24 h. Additionally, opioid consumption, time to first rescue analgesia, incidence of postoperative nausea and vomiting (PONV), and patient satisfaction were evaluated. Results Both ESPB and WI provided effective postoperative pain management, with no significant differences in VAS scores. However, the ESPB group demonstrated a significantly longer duration of analgesia, a shorter time to first rescue analgesia, and lower total tramadol consumption (50 ± 60 mg vs. 100 ± 75 mg; p = 0.010) than did the WI group. Furthermore, a trend toward reduced PONV incidence was observed in the ESPB group, likely due to its opioid-sparing effect. Conclusion While both ESPB and WI provided effective postoperative pain management, ESPB demonstrated a distinct advantage by offering a longer duration of analgesia and significantly reducing opioid consumption. These findings suggest that ESPB is more effective than WI for postoperative analgesia in lumbar spinal surgeries, providing prolonged pain relief and improving patient outcomes. Further studies are warranted to explore its long-term benefits and cost-effectiveness. Trial Registration ClinicalTrials.govPRS: NCT06567964 Date: 08/21/2024 Retrospectively registered.

Abstract Preeclampsia (PE) occurs due to inadequate spiral artery/trophoblast remodeling in early pregnancy. Endometases are involved in the remodeling of spiral arteries and placental trophoblasts. This study aimed to investigate differences in blood endometase levels between pregnant women with hypertensive disorders (PE and gestational hypertension [GHT]) and healthy pregnant women and to evaluate whether plasma endometase values ​​could play a predictive role in PE or GHT diagnosis. A total of 90 pregnant women (n(PE) = 30, n(GHT) = 30, n(healthy pregnant) = 30) who presented at the hospital between December 2023 and May 2024 and were 26–32 years of age and > 20 weeks pregnant were included in the study. The endometase levels in all pregnant women were determined in maternal blood plasma via enzyme-linked immunosorbent assay. The endometase values were recalculated according to albumin values, and corrected endometase (cEndo) values were determined. No significant differences in blood endometase levels were observed between the groups (p > 0.05). The cEndo value was significantly lower in the PE and GHT groups than in the control group (p 0.05). A statistically significant negative linear relationship was detected between cEndo values and mean systolic blood pressure and mean diastolic blood pressure (p 0.05). Maternal blood cEndo values may play a successful role in distinguishing hypertensive diseases of pregnancy (PE + GHT) from healthy pregnant women. cEndo does not play an effective role in the differential diagnosis between pregnant women with PE and those with GHT. Studies with larger patient populations are needed.

Abstract Background Phlebotomus papatasi is considered the primary vector of Leishmania major parasites that cause zoonotic cutaneous leishmaniasis (ZCL) in the Middle East and North Africa. Phlebotomus papatasi populations have been studied extensively, revealing the existence of different genetic populations and subpopulations over its large distribution range. Genetic diversity and population structure analysis using transcriptome microsatellite markers is important to uncover the vector distribution dynamics, essential for controlling ZCL in endemic areas. Methods In this study, we investigated the level of genetic variation using expressed sequence tag-derived simple sequence repeats (EST-SSRs) among field and colony P. papatasi samples collected from 25 different locations in 11 countries. A total of 302 P. papatasi sand fly individuals were analyzed, including at least 10 flies from each region. Results The analysis revealed a high-level population structure expressed by five distinct populations A through E, with moderate genetic differentiation among all populations. These genetic differences in expressed genes may enable P. papatasi to adapt to different environmental conditions along its distribution range and likely affect dispersal. Conclusions Elucidating the population structuring of P. papatasi is essential to L. major containment efforts in endemic countries. Moreover, the level of genetic variation among these populations may improve our understanding of Leishmania–sand fly interactions and contribute to the efforts of vaccine development based on P. papatasi salivary proteins. Graphical Abstract

Unequal access to language learning resources has been exacerbated by the global expansion of English private tutoring (EPT). Despite its popularity, no study has examined the implications of EPT during the COVID-19 pandemic. Therefore, this mixed-methods study explored the nature and effectiveness of EPT that first-year Kazakhstani undergraduate students had experienced over the previous 12 months during the COVID-19 pandemic. It was informed by Benson's (2011) model of language learning beyond the classroom. Data were collected through a close-ended questionnaire and semi-structured online interviews. The study found that 318 out of 750 (42.4%) had experienced EPT, and 64% of respondents had received face-to-face EPT although it was considered a health risk during the pandemic. All the interviewees perceived EPT sessions as an encouraging environment for coaching towards the university entrance examination and expanding their knowledge. They attributed this mainly to the individual attention they obtained from their tutors, which was lacking in online classes with their English teachers due to teachers' indifferent attitude to students' questions and the limited duration of video conferencing sessions. The participants acted agentively by evaluating the advantages and drawbacks of online EPT. Pedagogical implications and areas for further research are suggested.

Major economic, social, and technological changes in the twenty-first century require a transformation in the everyday practices that educational institutions use to train future innovators. Through a case study on five schools within a network of private schools in Istanbul, Turkey, we explore how school principals and teachers nurture an innovation climate in their schools. Using methodological triangulation that combines semi-structured interviews, participant observation, interactive training sessions, and archival data, we identify four leadership practices that shape a climate conducive to innovation in these schools: (a) fostering the creativity of the members of school society or community, (b) developing a collaborative learning ecosystem, (c) encouraging innovative teaching through online collaborative learning spaces and ICT, and (d) empowering teachers to generate an adaptable curriculum in a flexible work environment. Findings indicate the significance of building a collaborative ecosystem that enables a separation or departure from the mainstream traditional and test-oriented education system in Turkey, which in turn inspires the creativity of teachers and students in the fabric of daily school life.