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.

New Physical, Mental, and Cognitive Problems 1 Year after ICU Admission: A Prospective Multicenter Study.

Rationale: Comprehensive studies addressing the incidence of physical, mental, and cognitive problems after ICU admission are lacking. With an increasing number of ICU survivors, an improved understanding of post-ICU problems is necessary. Objectives: To determine the occurrence and cooccurrence of new physical, mental, and cognitive problems among ICU survivors 1 year after ICU admission, their impact on daily functioning, and risk factors associated with 1-year outcomes. Methods: Prospective multicenter cohort study, including ICU patients ⩾16 years of age, admitted for ⩾12 hours between July 2016 and June 2019. Patients, or proxies, rated their health status before and 1 year after ICU admission using questionnaires. Measurements and Main Results: Validated questionnaires were used to measure frailty, fatigue, new physical symptoms, anxiety and depression, post-traumatic stress disorder, cognitive impairment, and quality of life. Of the 4,793 patients included, 2,345 completed the questionnaires both before and 1 year after ICU admission. New physical, mental, and/or cognitive problems 1 year after ICU admission were experienced by 58% of the medical patients, 64% of the urgent surgical patients, and 43% of the elective surgical patients. Urgent surgical patients experienced a significant deterioration in their physical and mental functioning, whereas elective surgical patients experienced a significant improvement. Medical patients experienced an increase in symptoms of depression. A significant decline in cognitive functioning was experienced by all types of patients. Pre-ICU health status was strongly associated with post-ICU health problems. Conclusions: Overall, 50% of ICU survivors suffer from new physical, mental, and/or cognitive problems. An improved insight into the specific health problems of ICU survivors would enable more personalized post-ICU care.

Pharmacological inhibition of phosphodiesterase 7 enhances consolidation processes of spatial memory.

Augmentation of cAMP signaling through inhibition of phosphodiesterases (PDE) is known to enhance plasticity and memory. Inhibition of PDE4 enhances consolidation into memory, but less is known about the role of other cAMP specific PDEs. Here, we tested the effects of oral treatment with a selective inhibitor of PDE7 of nanomolar potency on spatial and contextual memory. In an object location task, doses of 0.3-3 mg/kg administered 3 h after training dose-dependently attenuated time-dependent forgetting in rats. Significant enhancement of memory occurred at a dose of 3 mg/kg with corresponding brain levels consistent with PDE7 inhibition. The same dose given prior to training augmented contextual fear conditioning. In mice, daily dosing before training enhanced spatial memory in two different incremental learning paradigms in the Barnes Maze. Drug treated mice made significantly less errors locating the escape in a probe-test 24 h after the end of training, and they exhibited hippocampal-dependent spatial search strategies more frequently than controls, which tended to show serial sampling of escape locations. Acquisition and short-term memory, in contrast, were unaffected. Our data provide evidence for a role of PDE7 in the consolidation of hippocampal-dependent memory. We suggest that targeting PDE7 for memory enhancement may provide an alternative to PDE4 inhibitors, which tend to have undesirable gastrointestinal side-effects.

The Dutch Data Warehouse, a multicenter and full-admission electronic health records database for critically ill COVID-19 patients.

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.

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.

A stable home-base promotes allocentric memory representations of episodic-like everyday spatial memory.

A key issue in neurobiological studies of episodic-like memory is the geometric frame of reference in which memory traces of experience are stored. Assumptions are sometimes made that specific protocols favour either allocentric (map-like) or egocentric (body-centred) representations. There are, however, grounds for suspecting substantial ambiguity about coding strategy, including the necessity to use both frames of reference occasionally, but tests of memory representation are not routinely conducted. Using rats trained to find and dig up food in sandwells at a particular place in an event arena (episodic-like 'action-where' encoding), we show that a protocol previously thought to foster allocentric encoding is ambiguous but more predisposed towards egocentric encoding. Two changes in training protocol were examined with a view to promoting preferential allocentric encoding-one in which multiple start locations were used within a session as well as between sessions; and another that deployed a stable home-base to which the animals had to carry food reward. Only the stable home-base protocol led to excellent choice performance which rigorous analyses revealed to be blocked by occluding extra-arena cues when this was done after encoding but before recall. The implications of these findings for studies of episodic-like memory are that the representational framework of memory at the start of a recall trial will likely include a path direction in the egocentric case but path destination in the allocentric protocol. This difference should be observable in single-unit recording or calcium-imaging studies of spatially-tuned cells.

Physical, Mental, and Cognitive Health Status of ICU Survivors Before ICU Admission: A Cohort Study.

OBJECTIVES: Although patient's health status before ICU admission is the most important predictor for long-term outcomes, it is often not taken into account, potentially overestimating the attributable effects of critical illness. Studies that did assess the pre-ICU health status often included specific patient groups or assessed one specific health domain. Our aim was to explore patient's physical, mental, and cognitive functioning, as well as their quality of life before ICU admission. DESIGN: Baseline data were used from the longitudinal prospective MONITOR-IC cohort study. SETTING: ICUs of four Dutch hospitals. PATIENTS: Adult ICU survivors (n = 2,467) admitted between July 2016 and December 2018. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Patients, or their proxy, rated their level of frailty (Clinical Frailty Scale), fatigue (Checklist Individual Strength-8), anxiety and depression (Hospital Anxiety and Depression Scale), cognitive functioning (Cognitive Failure Questionnaire-14), and quality of life (Short Form-36) before ICU admission. Unplanned patients rated their pre-ICU health status retrospectively after ICU admission. Before ICU admission, 13% of all patients was frail, 65% suffered from fatigue, 28% and 26% from symptoms of anxiety and depression, respectively, and 6% from cognitive problems. Unplanned patients were significantly more frail and depressed. Patients with a poor pre-ICU health status were more often likely to be female, older, lower educated, divorced or widowed, living in a healthcare facility, and suffering from a chronic condition. CONCLUSIONS: In an era with increasing attention for health problems after ICU admission, the results of this study indicate that a part of the ICU survivors already experience serious impairments in their physical, mental, and cognitive functioning before ICU admission. Substantial differences were seen between patient subgroups. These findings underline the importance of accounting for pre-ICU health status when studying long-term outcomes.

Azetidine-based selective glycine transporter-1 (GlyT1) inhibitors with memory enhancing properties.

A strategy to conformationally restrain a series of GlyT1 inhibitors identified potent analogs that exhibited slowly interconverting rotational isomers. Further studies to address this concern led to a series of azetidine-based inhibitors. Compound 26 was able to elevate CSF glycine levels in vivo and demonstrated potency comparable to Bitopertin in an in vivo rat receptor occupancy study. Compound 26 was subsequently shown to enhance memory in a Novel Object Recognition (NOR) behavioral study after a single dose of 0.03 mg/kg, and in a contextual fear conditioning (cFC) study after four QD doses of 0.01-0.03 mg/kg.

Breath-synchronized electrical stimulation of the expiratory muscles in mechanically ventilated patients: a randomized controlled feasibility study and pooled analysis.

BACKGROUND: Expiratory muscle weakness leads to difficult ventilator weaning. Maintaining their activity with functional electrical stimulation (FES) may improve outcome. We studied feasibility of breath-synchronized expiratory population muscle FES in a mixed ICU population ("Holland study") and pooled data with our previous work ("Australian study") to estimate potential clinical effects in a larger group. METHODS: Holland: Patients with a contractile response to FES received active or sham expiratory muscle FES (30 min, twice daily, 5 days/week until weaned). Main endpoints were feasibility (e.g., patient recruitment, treatment compliance, stimulation intensity) and safety. Pooled: Data on respiratory muscle thickness and ventilation duration from the Holland and Australian studies were combined (N = 40) in order to estimate potential effect size. Plasma cytokines (day 0, 3) were analyzed to study the effects of FES on systemic inflammation. RESULTS: Holland: A total of 272 sessions were performed (active/sham: 169/103) in 20 patients (N = active/sham: 10/10) with a total treatment compliance rate of 91.1%. No FES-related serious adverse events were reported. Pooled: On day 3, there was a between-group difference (N = active/sham: 7/12) in total abdominal expiratory muscle thickness favoring the active group [treatment difference (95% confidence interval); 2.25 (0.34, 4.16) mm, P = 0.02] but not on day 5. Plasma cytokine levels indicated that early FES did not induce systemic inflammation. Using a survival analysis approach for the total study population, median ventilation duration and ICU length of stay were 10 versus 52 (P = 0.07), and 12 versus 54 (P = 0.03) days for the active versus sham group. Median ventilation duration of patients that were successfully extubated was 8.5 [5.6-12.2] versus 10.5 [5.3-25.6] days (P = 0.60) for the active (N = 16) versus sham (N = 10) group, and median ICU length of stay was 10.5 [8.0-14.5] versus 14.0 [9.0-19.5] days (P = 0.36) for those active (N = 16) versus sham (N = 8) patients that were extubated and discharged alive from the ICU. During ICU stay, 3/20 patients died in the active group versus 8/20 in the sham group (P = 0.16). CONCLUSION: Expiratory muscle FES is feasible in selected ICU patients and might be a promising technique within a respiratory muscle-protective ventilation strategy. The next step is to study the effects on weaning and ventilator liberation outcome. TRIAL REGISTRATION: ClinicalTrials.gov, ID NCT03453944. Registered 05 March 2018-Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT03453944 .

Everyday memory: towards a translationally effective method of modelling the encoding, forgetting and enhancement of memory.

The testing of cognitive enhancers could benefit from the development of novel behavioural tasks that display better translational relevance for daily memory and permit the examination of potential targets in a within-subjects manner with less variability. We here outline an optimized spatial 'everyday memory' task. We calibrate it systematically by interrogating certain well-established determinants of memory and consider its potential for revealing novel features of encoding-related gene activation. Rats were trained in an event arena in which food was hidden in sandwells in a different location everyday. They found the food during an initial memory-encoding trial and were then required to remember the location in six alternative choice or probe trials at various time-points later. Training continued daily over a period of 4 months, realizing a stable high level of performance and characterized by delay-dependent forgetting over 24 h. Spaced but not massed access to multiple rewards enhanced the persistence of memory, as did post-encoding administration of the PDE4 inhibitor Rolipram. Quantitative PCR and then genome-wide analysis of gene expression led to a new observation - stronger gene-activation in hippocampus and retrosplenial cortex following spaced than massed training. In a subsidiary study, a separate group of animals replicated aspects of this training profile, going on to show enhanced memory when training was subject to post-encoding environmental novelty. Distinctive features of this protocol include its potential validity as a model of memory encoding used routinely by human subjects everyday, and the possibility of multiple within-subject comparisons to speed up assays of novel compounds.

Phosphorylation of K+ channels at single residues regulates memory formation.

Phosphorylation is a ubiquitous post-translational modification of proteins, and a known physiological regulator of K+ channel function. Phosphorylation of K()channels by kinases has long been presumed to regulate neuronal processing and behavior. Although circumstantial evidence has accumulated from behavioral studies of vertebrates and invertebrates, the contribution to memory of single phosphorylation sites on K+ channels has never been reported. We have used gene targeting in mice to inactivate protein kinase A substrate residues in the fast-inactivating subunit Kv4.2 (T38A mutants), and in the small-conductance Ca2+ -activated subunit SK1 (S105A mutants). Both manipulations perturbed a specific form of memory, leaving others intact. T38A mutants had enhanced spatial memory for at least 4 wk after training, whereas performance in three tests of fear memory was unaffected. S105A mutants were impaired in passive avoidance memory, sparing fear, and spatial memory. Together with recent findings that excitability governs the participation of neurons in a memory circuit, this result suggests that the memory type supported by neurons may depend critically on the phosphorylation of specific K+ channels at single residues.

Post-intensive care syndrome in primary care: The development of new diseases and primary care services utilisation - a prospective cohort study.

BACKGROUND: Patients experience long-lasting health problems defined as post-intensive care syndrome (PICS) after Intensive Care Unit (ICU) admission. Little is known about PICS in primary care. OBJECTIVES: To investigate whether ICU survivors encounter more new International Classification of Primary Care-2 (ICPC-2) diagnoses and general practitioner (GP) contact compared to patients with similar comorbidity without ICU admission. METHODS: Prospective multicentre cohort study in three Dutch general practices. Numbers of disease-episodes and GP contacts of ICU survivors ≥ 16 years admitted between 2008 and 2017 were extracted from GPs' information systems. A non-ICU reference cohort was matched 1:1 for age, sex, follow-up period and comorbidity groups from patients' medical history. Negative binominal regression analysis was used to compare both cohorts 0-3, 3-6, 6-12 months, 1-2 and 2-5 years after ICU admission and 1 year prior to admission. RESULTS: ICU survivors (n = 199) encountered more new disease-episodes 1 year before (mean 3.97 (95% confidence interval [CI] 3.50-4.52]]; reference 2.36 [1.28-3.17]) to 2-5 years after ICU admission (3.65 [3.15-4.26]; reference 2.86 [2.52-3.22]). ICU survivors also had more GP contacts 1 year before (mean 19.61 [17.31-22.17]; reference 10.02 [7.81-12.38]) to 2-5 years after ICU admission (18.53 [15.58-21.85]; reference 12.03 [10.33-13.91]). Patients with prior ICU admission did not encounter patterns in specific ICPC-2 chapters compared to non-ICU patients. CONCLUSION: Patients admitted to the ICU encounter more new primary care disease-episodes and GP contacts. As patients present their symptoms to their GP first, it is therefore up to the GP to recognise these critical illness-related symptoms.

The impact of an intensive care unit admission on the health status of relatives of intensive care survivors: A prospective cohort study in primary care.

BACKGROUND: Relatives of intensive care unit (ICU) survivors may suffer from various symptoms after ICU admittance of their relative, known as post-intensive care syndrome-family (PICS-F). Studies regarding PICS-F have been performed but its impact in primary care is unknown. OBJECTIVES: To explore health problems of relatives of ICU survivors in primary care. METHODS: This is an exploratory prospective cohort study in which we combined data from two hospitals and a primary care research network in the Netherlands. ICU survivors who had been admitted between January 2005 and July 2017 were identified and matched by sex and age with up to four chronically ill (e.g. COPD, cardiovascular disease) patients. In both groups, relatives living in the same household were identified and included in this study. Primary outcome was the number of new episodes of care (International Classification of Primary Care-2) for up to five years. Hazard ratios (HRs) for the total number of new episodes were calculated. RESULTS: Relatives of ICU survivors (n = 267, mean age 38.1 years, 41.0% male) had significantly more new care episodes compared to the reference group (n = 705, mean age 36.3 years, 41.1% male) 1-2 years (median 0.11 vs. 0.08, HR 1.26; 95% confidence interval (CI) 1.03-1.54) and 2-5 years (median 0.18 vs. 0.13, HR 1.28; 95%CI 1.06-1.56) after ICU discharge. No differences were found in the period before ICU admission. CONCLUSION: Relatives of ICU survivors present more morbidity in primary care than relatives of chronically ill patients up to five years after ICU discharge.

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.

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.

Inhibition of PDE2 and PDE4 synergistically improves memory consolidation processes.

Phosphodiesterases (PDE) are the only enzymes that degrade cAMP and cGMP which are second messengers crucial to memory consolidation. Different PDE inhibitors have been developed and tested for their memory-enhancing potential, but the occurrence of side effects has hampered clinical progression. As separate inhibition of the PDE2 and PDE4 enzyme family has been shown to enhance memory, we investigated whether concurrent treatment with a PDE2 and PDE4 inhibitor can have synergistic effects on memory consolidation processes. We found that combined administration of PF-999 (PDE2 inhibitor) and roflumilast (PDE4 inhibitor) increases the phosphorylation of the AMPA receptor subunit GluR1 and induces CRE-mediated gene expression. Moreover, when combined sub-effective and effective doses of PF-999 and roflumilast were administered after learning, time-dependent forgetting was abolished in an object location memory task. Pharmacokinetic assessment indicated that combined treatment does not alter exposure of the individual compounds. Taken together, these findings suggest that combined PDE2 and PDE4 inhibition has synergistic effects on memory consolidation processes at sub-effective doses, which could therefore provide a therapeutic strategy with an improved safety profile.

Risk factors for adverse outcomes during mechanical ventilation of 1152 COVID-19 patients: a multicenter machine learning study with highly granular data from the Dutch Data Warehouse.

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.

Some Patients Are More Equal Than Others: Variation in Ventilator Settings for Coronavirus Disease 2019 Acute Respiratory Distress Syndrome.

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.

Phosphodiesterase 1b (PDE1B) Regulates Spatial and Contextual Memory in Hippocampus.

Augmentation of cyclic nucleotide signaling through inhibition of phosphodiesterase (PDE) activity has long been understood to enhance memory. Efforts in this domain have focused predominantly on PDE4, a cAMP-specific phosphodiesterase implicated in consolidation. But less is known about the function of other PDEs expressed in neuroanatomical regions critical to memory. The PDE1 isoforms are the only PDEs to regulate neuronal cAMP and cGMP levels in a Ca2+/Calmodulin (CaM) dependent manner. Here, we show that knock-down of PDE1B in hippocampus of adult mice enhances contextual and spatial memory without effect on non-cognitive behaviors. Pharmacological augmentation of memory in rats was observed with a selective inhibitor of PDE1 dosed before and immediately after training, but not with drug dosed either 1 h after training or before recall. Our data clearly demonstrate a role for the PDE1B isoforms as negative regulators of memory, and they implicate PDE1 in an early phase of consolidation, but not retrieval. Inhibition of PDE1B is a promising therapeutic mechanism for treating memory impairment.