Climate protection, health and other motives for active transport - results of a cross-sectional survey in Germany.

BACKGROUND: Active transport- for example walking and bicycling to travel from place to place- may improve physical fitness and health and mitigate climate change if it replaces motorised transport. The aim of this study is to analyse the active transport behaviour of adults living in Germany, to investigate differences among population groups and to determine whether climate protection is a frequent motive for this behaviour. METHODS: This study uses self-reported data of 4,971 adults who participated in a national health survey (German Health Update 2021), which was conducted as a telephone survey from July to December 2021. Associations between active transport behaviour and corresponding motives with sociodemographic and health-related variables were analysed using logistic regression models. RESULTS: Of the adult population, 83% use active transport at least once a week. The frequency and duration of walking per week are significantly higher than those for bicycling (walking 214 min/week; bicycling 57 min/week). Those with a lower education level are less likely to practise active transport than those with a higher education level. Furthermore, women are less likely to use a bicycle for transport than men. Among those practising active transport, the most frequently mentioned motive is "is good for health" (84%) followed by "to be physically active" (74%) and "is good for the climate/environment" (68%). Women and frequent bicyclists (at least 4 days/week) mention climate protection as a motive more often than men and those bicycling occasionally. CONCLUSIONS: The improvement of active transport, especially among people with lower education and women (for bicycling), may benefit from better insights into motives and barriers. Climate protection is an important motivator for practising active transport within the adult population living in Germany and should therefore have greater emphasis in behavioural change programmes.

Distribution and determinants of glycosylated hemoglobin in adolescents - Results from a nationwide population-based survey in Germany.

The role of glycosylated hemoglobin (HbA1c) in youth is largely unclear. The aims of this study are to investigate the distribution and potential determinants of HbA1c among a population-based sample of adolescents. The German Health Interview and Examination Survey for Children and Adolescents (KiGGS) Wave 2 includes a nationwide representative sample of 0-17-year-old participants. For this evaluation, data from a randomly selected subgroup aged 14-17 years and without diagnosed diabetes was included (n = 857). Percentile-based HbA1c values (measured at laboratory in whole blood samples by high performance liquid chromatography) were calculated to examine HbA1c distribution. Multivariable linear regression analyses were performed to investigate factors (age, sex, parental socioeconomic status, body mass index (BMI), birth weight, smoking, alcohol consumption, healthy food diversity, sport activity, oral contraceptive use) associated with HbA1c. The mean HbA1c level was 5.2% (minimum: 3.9%, P10: 4.8%, P50: 5.1%, P90: 5.5%, maximum: 6.7%). Overall, 2.8% of adolescents had an HbA1c value in the prediabetic range (5.7-6.4%) and 0.1% had an undiagnosed diabetes (≥6.5%). Multivariable regression analysis showed an inverse association of age with HbA1c (17 vs. 14 years: ß: -1.18; 95% CI -2.05, -0.31). Higher HbA1c values were observed for higher BMI-standard deviation scores (SDS) (ß: 0.24; 95% CI -0.04, 0.52) and smoking (ß: 0.73; 95% CI -0.12, 1.57), but these tendencies were non-significant. In sex-stratified analysis, smoking and birth weight were significantly associated with HbA1c in boys. Among adolescents without diagnosed diabetes in Germany, HbA1c values ranged from 3.9% to 6.7%. To ensure health in adulthood, the influence of determinants on HbA1c levels in younger age should be further investigated.

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) reveals potential lipid markers between infrapatellar fat pad biopsies of osteoarthritis and cartilage defect patients.

The incidence of osteoarthritis (OA) has been expected to increase due to an aging population, as well as an increased incidence of intra-articular (osteo-) chondral damage. Lipids have already been shown to be involved in the inflammatory process of OA. This study aims at revealing region-specific lipid profiles of the infrapatellar fat pad (IPFP) of OA or cartilage defect patients by matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), which could be used as biomarkers for early OA detection. A higher presence of phospholipids was found in OA patients compared with cartilage defect patients. In addition, a higher abundance of ether-linked phosphatidylethanolamines (PE O-s) containing arachidonic acid was specifically found in OA patients compared with cartilage defect patients. These lipids were mainly found in the connective tissue of the IPFP. Specific lipid species were associated to OA patients compared with cartilage defect patients. PE O-s have been suggested as possible biomarkers for OA. As these were found more abundantly in the connective tissue, the IPFP's intra-tissue heterogeneity might play an important role in biomarker discovery, implying that the amount of fibrous tissue is associated with OA.

[Eating Habits with Climate Impact: At Which Meals and How Often Do 6- to 11-year-olds Eat Meat and Meat Products?] / Klimarelevante Ernährungsgewohnheiten: Zu welchen Mahlzeiten und wie häufig essen 6- bis 11-Jährige Fleisch und Wurstwaren?

BACKGROUND: Climate change presents one of the greatest public health challenges. Regarding diet, the production of animal-based foods contributes significantly to greenhouse gas emissions. In Germany, even children often eat more meat and meat products than is recommended for a healthy diet. To plan, implement, and tailor interventions to the needs of different target groups, it is crucial to better understand people's eating habits. METHODS: Using data from 4-day eating records of 1,190 participants of the EsKiMo II study (Nutrition study as KiGGS module, 2nd survey), which was carried out nationwide in Germany from 2015 to 2017, a detailed analysis of the consumption of meat and meat products of children aged 6-11 years, including consumption quantities and frequencies with regard to different meals, was conducted. RESULTS: On average, children ate 71 g of meat and meat products per day, 2/3 of the amount during lunch and dinner. More red meat (pork, beef, and lamb) were chosen than poultry. Almost half of the children ate these food items twice a day, another 40% once a day. Only five percent consumed meat or meat products less than once a day. CONCLUSIONS: Meat and meat products are therefore part of the daily diet of almost all children at this age with a general high intake among both boys and girls. Consumption could be reduced by replacing meat and meat products with vegetarian dishes or plant-based sandwich fillings, particularly for lunch and dinner. While school lunch can considerably contribute to a healthy and climate-friendly diet, families should also reduce meat servings at dinner.

An Orbitrap/Time-of-Flight Mass Spectrometer for Photofragment Ion Imaging and High-Resolution Mass Analysis of Native Macromolecular Assemblies.

We discuss the design, development, and evaluation of an Orbitrap/time-of-flight (TOF) mass spectrometry (MS)-based instrument with integrated UV photodissociation (UVPD) and time/mass-to-charge ratio (m/z)-resolved imaging for the comprehensive study of the higher-order molecular structure of macromolecular assemblies (MMAs). A bespoke TOF analyzer has been coupled to the higher-energy collisional dissociation cell of an ultrahigh mass range hybrid quadrupole-Orbitrap MS. A 193 nm excimer laser was employed to photofragment MMA ions. A combination of microchannel plates (MCPs)-Timepix (TPX) quad and MCPs-phosphor screen-TPX3CAM assemblies have been used as axial and orthogonal imaging detectors, respectively. The instrument can operate in four different modes, where the UVPD-generated fragment ions from the native MMA ions can be measured with high-mass resolution or imaged in a mass-resolved manner to reveal the relative positions of the UVPD fragments postdissociation. This information is intended to be utilized for retrieving higher-order molecular structural details that include the conformation, subunit stoichiometry, and molecular interactions as well as to understand the dissociation dynamics of the MMAs in the gas phase.

Perspectives of individuals on reducing meat consumption to mitigate climate change: protocol for a scoping review.

INTRODUCTION: High consumption of red and processed meat increases the risk of several chronic diseases. Many people, especially in high-income countries, eat more meat than recommended by nutritional and health agencies. Meat production also has negative impacts on the environment and contributes to climate change. Therefore, climate protection, besides health or animal welfare, could motivate individuals to eat less meat. Willingness to reduce meat consumption and motives to do so are not yet fully understood. METHODS AND ANALYSIS: Based on the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) extended guidelines, a scoping review of peer-reviewed original studies will be conducted to address three questions: What is the evidence regarding (1) the willingness of individuals to reduce meat consumption to mitigate climate change, (2) the awareness of individuals about the link between their meat consumption and the potential to mitigate climate change and (3) individuals having reduced meat consumption for the reason of climate protection? We will search the databases Medline (via PubMed), Scopus, Embase, Greenfile (via Ebsco) and PsynDex/CurrentContent/Agris (via Livivo) using a systematic search string. Studies from 2015 onwards, published in English, German, Danish or Dutch, will be included. We will include observational studies, qualitative studies, intervention studies (if they include surveys) and reviews. Data will be summarised in a narrative synthesis, comprising methods, population characteristics, meat type under study, indicators measured and limitations. Key findings will be grouped according to the research questions. This scoping review will help clarify the role of climate protection in individual reduction of meat consumption and identify research gaps in this field. ETHICS AND DISSEMINATION: Formal ethical approval is not required, as primary data will not be collected in this study. Findings of this scoping review will be presented at scientific conferences and published in a peer-reviewed journal. TRIAL REGISTRATION NUMBER: https://doi.org/10.17605/OSF.IO/MWB85.

The Challenge of Incomplete Data in Accelerometer Studies: Characteristics of Nonparticipation and Noncompliance in a Nationwide Sample of Adolescents and Young Adults in Germany.

BACKGROUND: Incomplete data due to nonparticipation and noncompliance with the study protocol can bias the results of studies. We investigated how a nationwide accelerometer sample of adolescents and young adults is affected by such incomplete data. METHODS: We analyzed cross-sectional data from 6465 participants (11-31 y old) who participated in a national health survey in Germany (KiGGS Wave 2; 2014-2017). The data included information about the participation in the measurement of physical activity using accelerometers, compliance with the wear-time protocol, and sociodemographic and health-related variables. Multivariable regression analyses were conducted to detect factors associated with incomplete data. RESULTS: Of the total sample, 78.0% participated in the accelerometer part of the study, and 83.5% of the participants with data available complied with the wear-time protocol. In 11- to 17-year-olds, the likelihood of having incomplete accelerometer data was higher in boys, older adolescents, adolescents with a lower sociodemographic status, adolescents with overweight, adolescents not participating in organized sport, adolescents not speaking only German at home, current smokers, and adolescents having a higher soft drink consumption. In 18- to 31-year-olds, the likelihood of having incomplete accelerometer data was higher in men, adults with a lower educational level, adults not speaking only German at home, and adults who smoke. CONCLUSIONS: Our results suggest that accelerometer samples are biased such that participants with more beneficial health behaviors provide complete accelerometer data more often. This knowledge should be used to design effective recruitment strategies and should be considered when interpreting results of accelerometer studies.

Time-Resolved Imaging of High Mass Proteins and Metastable Fragments Using Matrix-Assisted Laser Desorption/Ionization, Axial Time-of-Flight Mass Spectrometry, and TPX3CAM.

The Timepix (TPX) is a position- and time-sensitive pixelated charge detector that can be coupled with time-of-flight mass spectrometry (TOF MS) in combination with microchannel plates (MCPs) for the spatially and temporally resolved detection of biomolecules. Earlier generation TPX detectors used in previous studies were limited by a moderate time resolution (at best 10 ns) and single-stop detection for each pixel that hampered the detection of ions with high mass-to-charge (m/z) values at high pixel occupancies. In this study, we have coupled an MCP-phosphor screen-TPX3CAM detection assembly that contains a silicon-coated TPX3 chip to a matrix-assisted laser desorption/ionization (MALDI)-axial TOF MS. A time resolution of 1.5625 ns, per-pixel multihit functionality, simultaneous measurement of TOF and time-over-threshold (TOT) values, and kHz readout rates of the TPX3 extended the m/z detection range of the TPX detector family. The detection of singly charged intact Immunoglobulin M ions of m/z value approaching 1 × 106 Da has been demonstrated. We also discuss the utilization of additional information on impact coordinates and TOT provided by the TPX3 compared to conventional MS detectors for the enhancement of the quality of the mass spectrum in terms of signal-to-noise (S/N) ratio. We show how the reduced dead time and event-based readout in TPX3 compared to the TPX improves the sensitivity of high m/z detection in both low and high mass measurements (m/z range: 757-970,000 Da). We further exploit the imaging capabilities of the TPX3 detector for the spatial and temporal separation of neutral fragments generated by metastable decay at different locations along the field-free flight region by simultaneous application of deflection and retarding fields.

Dietary Patterns in Adolescent Obesity as Predictors of Long-Term Success Following an Intensive Inpatient Lifestyle Programme.

(1) Background: Lifestyle interventions for adolescents with obesity show minor long-term effects on anthropometric parameters. The persistence of dietary changes after obesity inpatient rehabilitation has not been sufficiently investigated. (2) Objectives: To analyse dietary patterns in German adolescents with obesity as predictors of long-term success following an intensive inpatient lifestyle programme regarding food choices as well as body weight and comorbidities. (3) Methods: Food consumption data of 137 German adolescents with obesity aged 10-17 years were collected by a nutrition interview. Cluster analysis was used to group the participants according to their food consumption. Dietary patterns, changes in body weight and insulin resistance were compared over a 2-year-period. (4) Results: Three dietary patterns were identified. Big Eaters (n = 32) consume high amounts of total sugar and meat, Moderate Eaters (n = 66) have a diet comparable to the national average, and Snackers (n = 39) have a particularly high consumption of total sugar. Big Eaters and Snackers significantly reduced the consumption of total sugar. Among Moderate Eaters, no persistent changes were observed. (5) Conclusion: Weight reduction interventions can induce long-lasting changes in the diet of adolescents with obesity. Therefore, the success of a weight reduction intervention should not be determined by weight reduction only.

Towards a harmonized European surveillance for dietary and physical activity indicators in young and adult populations.

BACKGROUND: The Policy Evaluation Network proposes a consolidated approach to measure comparable health indicators across European health surveillance systems to evaluate effectiveness of policy action. METHODS: In a stepwise approach, questionnaire items used by the systems for measuring diet and physical activity data to describe health indicators were identified based on their validity, reliability, and suitability to monitor achievement of health recommendations. They were collated to unified questionnaire modules and discussed bilaterally with representatives of these systems to explore barriers and facilitators for implementation. Also, establishment of a methodological competence platform was proposed, in which the surveillance and monitoring systems agree on the priorities and common quality standards for the harmonization process and to coordinate the integration of questionnaire modules into existing systems. RESULTS: In total, seven questionnaire modules were developed, of which two diet and two physical activity modules were proposed for implementation. Each module allows measurement of data reflecting only partial aspects of national and WHO recommendations related to diet and physical activity. Main barriers were the requirements of systems to monitor temporal trends and to minimize costs. Main facilitator for implementation was the systems' use of questionnaire items that were comparable to the unified modules. Representatives agreed to participate in a methodological competence platform. CONCLUSION: We successfully took first steps in the realization of the roadmap towards a harmonization of European surveillance by introducing unified questionnaire modules allowing the collection of comparable health indicators and by initiating the establishment of a competence platform to guide this process.

Predicting responders to prone positioning in mechanically ventilated patients with COVID-19 using machine learning.

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.

Overweight and obesity among adults in Germany - Results from GEDA 2019/2020-EHIS.

Background: Overweight and obesity and their associated secondary diseases are of high public health relevance. Methods: Self-reported body weight and body height data are available in the study German Health Update (GEDA 2019/2020-EHIS). The body mass index (BMI, kg/m2) was calculated and overweight (including obesity, BMI ≥25 kg/m2) and obesity (BMI ≥30 kg/m2) were derived. Results: According to this self-report, 53.5% of adults in Germany are overweight, men more often than women. The obesity prevalence for both sexes is 19.0%. The prevalence of overweight and obesity increases with age in both women and men. Obesity is significantly more prevalent in low education groups compared to high education groups. Compared to GEDA 2012, the prevalence of overweight is unchanged, but the obesity prevalence has continued to increase, particularly among 45- to 64-year-olds. Conclusion: The prevention potential of avoiding overweight and obesity remains high.

Assess and validate predictive performance of models for in-hospital mortality in COVID-19 patients: A retrospective cohort study in the Netherlands comparing the value of registry data with high-granular electronic health records.

PURPOSE: To assess, validate and compare the predictive performance of models for in-hospital mortality of COVID-19 patients admitted to the intensive care unit (ICU) over two different waves of infections. Our models were built with high-granular Electronic Health Records (EHR) data versus less-granular registry data. METHODS: Observational study of all COVID-19 patients admitted to 19 Dutch ICUs participating in both the national quality registry National Intensive Care Evaluation (NICE) and the EHR-based Dutch Data Warehouse (hereafter EHR). Multiple models were developed on data from the first 24 h of ICU admissions from February to June 2020 (first COVID-19 wave) and validated on prospective patients admitted to the same ICUs between July and December 2020 (second COVID-19 wave). We assessed model discrimination, calibration, and the degree of relatedness between development and validation population. Coefficients were used to identify relevant risk factors. RESULTS: A total of 1533 patients from the EHR and 1563 from the registry were included. With high granular EHR data, the average AUROC was 0.69 (standard deviation of 0.05) for the internal validation, and the AUROC was 0.75 for the temporal validation. The registry model achieved an average AUROC of 0.76 (standard deviation of 0.05) in the internal validation and 0.77 in the temporal validation. In the EHR data, age, and respiratory-system related variables were the most important risk factors identified. In the NICE registry data, age and chronic respiratory insufficiency were the most important risk factors. CONCLUSION: In our study, prognostic models built on less-granular but readily-available registry data had similar performance to models built on high-granular EHR data and showed similar transportability to a prospective COVID-19 population. Future research is needed to verify whether this finding can be confirmed for upcoming waves.

INCIDENCE, RISK FACTORS, AND OUTCOME OF SUSPECTED CENTRAL VENOUS CATHETER-RELATED INFECTIONS IN CRITICALLY ILL COVID-19 PATIENTS: A MULTICENTER RETROSPECTIVE COHORT STUDY.

ABSTRACT: Background: Aims of this study were to investigate the prevalence and incidence of catheter-related infection, identify risk factors, and determine the relation of catheter-related infection with mortality in critically ill COVID-19 patients. Methods: This was a retrospective cohort study of central venous catheters (CVCs) in critically ill COVID-19 patients. Eligible CVC insertions required an indwelling time of at least 48 hours and were identified using a full-admission electronic health record database. Risk factors were identified using logistic regression. Differences in survival rates at day 28 of follow-up were assessed using a log-rank test and proportional hazard model. Results: In 538 patients, a total of 914 CVCs were included. Prevalence and incidence of suspected catheter-related infection were 7.9% and 9.4 infections per 1,000 catheter indwelling days, respectively. Prone ventilation for more than 5 days was associated with increased risk of suspected catheter-related infection; odds ratio, 5.05 (95% confidence interval 2.12-11.0). Risk of death was significantly higher in patients with suspected catheter-related infection (hazard ratio, 1.78; 95% confidence interval, 1.25-2.53). Conclusions: This study shows that in critically ill patients with COVID-19, prevalence and incidence of suspected catheter-related infection are high, prone ventilation is a risk factor, and mortality is higher in case of catheter-related infection.

Health surveillance indicators for diet and physical activity: what is available in European data sets for policy evaluation?

BACKGROUND: Policies targeting diet and physical activity have the potential to improve health and well-being at a population level. However, the impact of these policies in Europe is currently unknown. Based on existing data, as well as on a needs assessment, we derived a catalogue of indicators that can be employed to evaluate such policies. These indicators may also inform the further development and harmonization of surveillance systems. METHODS: Forty EU experts agreed on a list of key indicators and ranked their priority for future surveillance. We mapped these indicators onto variables provided by ongoing European surveillance systems. Using a Likert scale (well matched, somewhat matched, poorly matched, unmatched), we assessed the suitability of these variables as measures for the indicators. RESULTS: Key indicators included behaviour outcome indicators relating to diet (n = 72) and physical activity and sedentary behaviour (n = 67) as well as upstream determinants of these behaviours. It was possible to map 72% of diet indicators and 86% of physical activity and sedentary behaviour indicators onto at least one variable in an ongoing surveillance system. CONCLUSIONS: Current monitoring and surveillance systems focus mainly on measuring 'downstream' indicators, while gaps exist in policy and environmental level data in dimensions such as inequality, funding and resources and governance.

Characterization of microchannel plate detector response for the detection of native multiply charged high mass single ions in orthogonal-time-of-flight mass spectrometry using a Timepix detector.

Time-of-flight (TOF) systems are one of the most widely used mass analyzers in native mass spectrometry (nMS) for the analysis of non-covalent multiply charged bio-macromolecular assemblies (MMAs). Typically, microchannel plates (MCPs) are employed for high mass native ion detection in TOF MS. MCPs are well known for their reduced detection efficiency when impinged by large slow moving ions. Here, a position- and time-sensitive Timepix (TPX) detector has been added to the back of a dual MCP stack to study the key factors that affect MCP performance for MMA ions generated by nMS. The footprint size of the secondary electron cloud generated by the MCP on the TPX for each individual ion event is analyzed as a measure of MCP performance at each mass-to-charge (m/z) value and resulted in a Poisson distribution. This allowed us to investigate the dependency of ion mass, ion charge, ion velocity, acceleration voltage, and MCP bias voltage on MCP response in the high mass low velocity regime. The study of measurement ranges; ion mass = 195 to 802,000 Da, ion velocity = 8.4 to 67.4 km/s, and ion charge = 1+ to 72+, extended the previously examined mass range and characterized MCP performance for multiply charged species. We derived a MCP performance equation based on two independent ion properties, ion mass and charge, from these results, which enables rapid MCP tuning for single MMA ion detection.

Rapid Evaluation of Coronavirus Illness Severity (RECOILS) in intensive care: Development and validation of a prognostic tool for in-hospital mortality.

BACKGROUND: The prediction of in-hospital mortality for ICU patients with COVID-19 is fundamental to treatment and resource allocation. The main purpose was to develop an easily implemented score for such prediction. METHODS: This was an observational, multicenter, development, and validation study on a national critical care dataset of COVID-19 patients. A systematic literature review was performed to determine variables possibly important for COVID-19 mortality prediction. Using a logistic multivariable model with a LASSO penalty, we developed the Rapid Evaluation of Coronavirus Illness Severity (RECOILS) score and compared its performance against published scores. RESULTS: Our development (validation) cohort consisted of 1480 (937) adult patients from 14 (11) Dutch ICUs admitted between March 2020 and April 2021. Median age was 65 (65) years, 31% (26%) died in hospital, 74% (72%) were males, average length of ICU stay was 7.83 (10.25) days and average length of hospital stay was 15.90 (19.92) days. Age, platelets, PaO2/FiO2 ratio, pH, blood urea nitrogen, temperature, PaCO2, Glasgow Coma Scale (GCS) score measured within +/-24 h of ICU admission were used to develop the score. The AUROC of RECOILS score was 0.75 (CI 0.71-0.78) which was higher than that of any previously reported predictive scores (0.68 [CI 0.64-0.71], 0.61 [CI 0.58-0.66], 0.67 [CI 0.63-0.70], 0.70 [CI 0.67-0.74] for ISARIC 4C Mortality Score, SOFA, SAPS-III, and age, respectively). CONCLUSIONS: Using a large dataset from multiple Dutch ICUs, we developed a predictive score for mortality of COVID-19 patients admitted to ICU, which outperformed other predictive scores reported so far.

Automated 3D Sampling and Imaging of Uneven Sample Surfaces with LA-REIMS.

The analysis of samples with large height variations remains a challenge for mass spectrometry imaging (MSI), despite many technological advantages. Ambient sampling and ionization MS techniques allow for the molecular analysis of sample surfaces with height variations, but most techniques lack MSI capabilities. We developed a 3D MS scanner for the automated sampling and imaging of a 3D surface with laser-assisted rapid evaporative ionization mass spectrometry (LA-REIMS). The sample is moved automatically with a constant distance between the laser probe and sample surface in the 3D MS Scanner. The topography of the surface was scanned with a laser point distance sensor to define the MS measurement points. MS acquisition was performed with LA-REIMS using a surgical CO2 laser coupled to a qTOF instrument. The topographical scan and MS acquisition can be completed within 1 h using the 3D MS scanner for 300 measurement points on uneven samples with a spatial resolution of 2 mm in the top view, corresponding to 22.04 cm2. Comparison between the automated acquisition with the 3D MS scanner and manual acquisition by hand showed that the automation resulted in increased reproducibility between the measurement points. 3D visualizations of molecular distributions related to structural differences were shown for an apple, a marrowbone, and a human femoral head to demonstrate the imaging feasibility of the system. The developed 3D MS scanner allows for the automated sampling of surfaces with uneven topographies with LA-REIMS, which can be used for the 3D visualization of molecular distributions of these surfaces.

How has body weight changed since the beginning of the COVID-19 pandemic?

Background: Measures for containing the COVID-19 pandemic in 2020 and 2021 resulted in drastic changes in physical activity and dietary habits that also impacted body weight. Methods: The representative study German Health Update (GEDA 2021) includes self-reported information about body weight and body height for adults aged 18 years and older (n=2,985) from July to October 2021. In addition, the study asked about changes in body weight since the beginning of the COVID-19 pandemic. Results: For 59% of participants, body weight has not changed since the beginning of the COVID-19 pandemic, 26% report weight gain, and 15% report weight loss. Younger people indicate weight gain more often than older people, and individuals with obesity report weight gain more often than individuals without obesity. 1.5 years after the beginning of the COVID-19 pandemic, the average weight change within the population is approximately +0.34kg. Conclusions: The effects of restrictions in everyday life with regard to the possible negative impacts on body weight should be given greater consideration and should be monitored in the future.

Predictors for extubation failure in COVID-19 patients using a machine learning approach.

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 (< 2 days) compared to their median values. Additionally, a higher C-reactive protein and leukocyte count, a lower thrombocyte count, a lower Glasgow coma scale and a lower body mass index compared to their medians were associated with extubation failure. CONCLUSION: The most important predictors for extubation failure in critically ill COVID-19 patients include ventilatory settings, inflammatory parameters, neurological status, and body mass index. These predictors should therefore be routinely captured in electronic health records.