Experiences with and needs for aftercare following the death of a loved one in the ICU: a mixed-methods study among bereaved relatives.

BACKGROUND: Bereaved relatives of intensive care unit (ICU) patients are at increased risk of psychological complaints. Aftercare might help them cope with processing the ICU admission and their loved one's death. There is little (qualitative) evidence on how bereaved relatives experience aftercare. Also, the COVID-19 pandemic likely impacted aftercare provision. We aim to examine how many relatives in Dutch ICUs received aftercare before and during the pandemic and to qualitatively describe their experiences and needs regarding aftercare. METHODS: A mixed-methods study among relatives of patients who died in an ICU before or during the COVID-19 pandemic. Bereaved relatives in six ICUs completed a questionnaire (n = 90), including two items on aftercare. These were analyzed using descriptive statistics and Chi-squared tests. Subsequently, both relatives that received and relatives that did not receive aftercare were interviewed about their experiences and needs regarding aftercare. The interviews were thematically analyzed. RESULTS: After the passing of a loved one, 44% of the relatives were asked by a healthcare professional from the hospital how they were doing, and 26% had had a follow-up conversation. Both happened more often during the first wave of the pandemic than during the second wave or before the pandemic. The most common reason for not having had a follow-up conversation was not knowing about this option (44%), followed by not feeling a need (26%). Regarding the latter, interviewed relatives explained that this would not revive their loved one or that they had already discussed everything they wanted. Relatives who wanted a follow-up conversation, wanted this because this would help them realize the severity of their loved one's illness, to exchange personal experiences, and/or to thank the ICU team. Those with a follow-up conversation said that they had reviewed the medical course of the admission and/or discussed their (mental) well-being. CONCLUSIONS: ICU healthcare professionals may play a vital role in addressing aftercare needs by asking relatives how they are doing in the weeks following the death of their loved one and offering them a follow-up conversation with an ICU physician. We recommend to include aftercare for bereaved relatives in ICU guidelines.

Support for relatives in the intensive care unit: lessons from a cross-sectional multicentre cohort study during the COVID-19 pandemic.

BACKGROUND: Support for relatives is highly important in the intensive care unit (ICU). During the first COVID-19 wave  support for relatives had to be changed considerably. The alternative support could have decreased the quality and sense of support. We aimed to evaluate how support for relatives in Dutch ICUs was organised during the first COVID-19 wave and how this was experienced by these relatives in comparison to relatives from pre-COVID-19 and the second wave. Additionally, we aimed to investigate which elements of support are associated with positive experiences. METHODS: We performed a cross-sectional multicentre cohort study in six Dutch ICUs in the Netherlands. Written questionnaires were distributed among relatives of ICU patients from pre-COVID-19, the first wave and the second wave. The questionnaire included questions on demographics, the organisation of support, and the experiences and satisfaction of relatives with the support. RESULTS: A total of 329 relatives completed the questionnaire (52% partner, 72% woman and 63% ICU stay of 11 days or longer). Support for relatives of ICU patients during the first COVID-19 wave differed significantly from pre-COVID-19 and the second wave. Differences were found in all categories of elements of support: who, when, how and what. Overall, relatives from the three time periods were very positive about the support. The only difference in satisfaction between the three time periods, was the higher proportion of relatives indicating that healthcare professionals had enough time for them during the first wave. Elements of support which were associated with many positive experiences and satisfaction were: fixed timeslot, receiving information (e.g. leaflets) on ≥ 2 topics, discussing > 5 topics with healthcare professionals, and being offered emotional support. CONCLUSIONS: Although, support for relatives in the ICU changed considerably during the COVID-19 pandemic, relatives were still positive about this support. The altered support gave insight into avenues for improvement for future comparable situations as well as for normal daily ICU practice: e.g. daily contact at a fixed timeslot, offering video calling between patients and relatives, and offering emotional support. ICUs should consider which elements need improvement in their practice.

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.

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.

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.

Ischaemic electrocardiogram patterns and its association with survival in out-of-hospital cardiac arrest patients without ST-segment elevation myocardial infarction: a COACT trials' post-hoc subgroup analysis.

AIMS: ST-depression and T-wave inversion are frequently present on the post-resuscitation electrocardiogram (ECG). However, the prognostic value of ischaemic ECG patterns is unknown. METHODS AND RESULTS: In this post-hoc subgroup analysis of the Coronary Angiography after Cardiac arrest (COACT) trial, the first in-hospital post-resuscitation ECG in out-of-hospital cardiac arrest patients with a shockable rhythm was analysed for ischaemic ECG patterns. Ischaemia was defined as ST-depression of ≥0.1 mV, T-wave inversion in ≥2 contiguous leads, or both. The primary endpoint was 90-day survival. Secondary endpoints were rate of acute unstable lesions, levels of serum troponin-T, and left ventricular function. Of the 510 out-of-hospital cardiac arrest patients, 340 (66.7%) patients had ischaemic ECG patterns. Patients with ischaemic ECG patterns had a worse 90-day survival compared with those without [hazard ratio 1.51; 95% confidence interval (CI) 1.08-2.12; P = 0.02]. A higher sum of ST-depression was associated with lower survival (log-rank = 0.01). The rate of acute unstable lesions (14.5 vs. 15.8%; odds ratio 0.90; 95% CI 0.51-1.59) did not differ between the groups. In patients with ischaemic ECG patterns, maximum levels of serum troponin-T (µg/L) were higher [0.595 (interquartile range 0.243-1.430) vs. 0.359 (0.159-0.845); ratio of geometric means 1.58; 1.13-2.20] and left ventricular function (%) was worse (44.7 ± 12.5 vs. 49.9 ± 13.3; mean difference -5.13; 95% CI -8.84 to -1.42). Adjusted for age and time to return of spontaneous circulation, ischaemic ECG patterns were no longer associated with survival. CONCLUSION: Post-arrest ischaemic ECG patterns were associated with worse 90-day survival. A higher sum of ST-depression was associated with lower survival. Adjusted for age and time to return of spontaneous circulation, ischaemic ECG patterns were no longer associated with survival.

Cost Analysis From a Randomized Comparison of Immediate Versus Delayed Angiography After Cardiac Arrest.

Background In patients with out-of-hospital cardiac arrest without ST-segment elevation, immediate coronary angiography did not improve clinical outcomes when compared with delayed angiography in the COACT (Coronary Angiography After Cardiac Arrest) trial. Whether 1 of the 2 strategies has benefits in terms of health care resource use and costs is currently unknown. We assess the health care resource use and costs in patients with out-of-hospital cardiac arrest. Methods and Results A total of 538 patients were randomly assigned to a strategy of either immediate or delayed coronary angiography. Detailed health care resource use and cost-prices were collected from the initial hospital episode. A generalized linear model and a gamma distribution were performed. Generic quality of life was measured with the RAND-36 and collected at 12-month follow-up. Overall total mean costs were similar between both groups (EUR 33 575±19 612 versus EUR 33 880±21 044; P=0.86). Generalized linear model: (ß, 0.991; 95% CI, 0.894-1.099; P=0.86). Mean procedural costs (coronary angiography and percutaneous coronary intervention, coronary artery bypass graft) were higher in the immediate angiography group (EUR 4384±3447 versus EUR 3028±4220; P<0.001). Costs concerning intensive care unit and ward stay did not show any significant difference. The RAND-36 questionnaire did not differ between both groups. Conclusions The mean total costs between patients with out-of-hospital cardiac arrest randomly assigned to an immediate angiography or a delayed invasive strategy were similar during the initial hospital stay. With respect to the higher invasive procedure costs in the immediate group, a strategy awaiting neurological recovery followed by coronary angiography and planned revascularization may be considered. Registration URL: https://trialregister.nl; Unique identifier: NL4857.

Targeted Temperature Management in Out-of-Hospital Cardiac Arrest With Shockable Rhythm: A Post Hoc Analysis of the Coronary Angiography After Cardiac Arrest Trial.

OBJECTIVES: The optimal targeted temperature in patients with shockable rhythm is unclear, and current guidelines recommend targeted temperature management with a correspondingly wide range between 32°C and 36°C. Our aim was to study survival and neurologic outcome associated with targeted temperature management strategy in postarrest patients with initial shockable rhythm. DESIGN: Observational substudy of the Coronary Angiography after Cardiac Arrest without ST-segment Elevation trial. SETTING: Nineteen hospitals in The Netherlands. PATIENTS: The Coronary Angiography after Cardiac Arrest trial randomized successfully resuscitated patients with shockable rhythm and absence of ST-segment elevation to a strategy of immediate or delayed coronary angiography. In this substudy, 459 patients treated with mild therapeutic hypothermia (32.0-34.0°C) or targeted normothermia (36.0-37.0°C) were included. Allocation to targeted temperature management strategy was at the discretion of the physician. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: After 90 days, 171 patients (63.6%) in the mild therapeutic hypothermia group and 129 (67.9%) in the targeted normothermia group were alive (hazard ratio, 0.86 [95% CI, 0.62-1.18]; log-rank p = 0.35; adjusted odds ratio, 0.89; 95% CI, 0.45-1.72). Patients in the mild therapeutic hypothermia group had longer ICU stay (4 d [3-7 d] vs 3 d [2-5 d]; ratio of geometric means, 1.32; 95% CI, 1.15-1.51), lower blood pressures, higher lactate levels, and increased need for inotropic support. Cerebral Performance Category scores at ICU discharge and 90-day follow-up and patient-reported Mental and Physical Health Scores at 1 year were similar in the two groups. CONCLUSIONS: In the context of out-of-hospital cardiac arrest with shockable rhythm and no ST-elevation, treatment with mild therapeutic hypothermia was not associated with improved 90-day survival compared with targeted normothermia. Neurologic outcomes at 90 days as well as patient-reported Mental and Physical Health Scores at 1 year did not differ between the groups.

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.

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.

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.

Early warning scores to assess the probability of critical illness in patients with COVID-19.

OBJECTIVE: Validated clinical risk scores are needed to identify patients with COVID-19 at risk of severe disease and to guide triage decision-making during the COVID-19 pandemic. The objective of the current study was to evaluate the performance of early warning scores (EWS) in the ED when identifying patients with COVID-19 who will require intensive care unit (ICU) admission for high-flow-oxygen usage or mechanical ventilation. METHODS: Patients with a proven SARS-CoV-2 infection with complete resuscitate orders treated in nine hospitals between 27 February and 30 July 2020 needing hospital admission were included. Primary outcome was the performance of EWS in identifying patients needing ICU admission within 24 hours after ED presentation. RESULTS: In total, 1501 patients were included. Median age was 71 (range 19-99) years and 60.3% were male. Of all patients, 86.9% were admitted to the general ward and 13.1% to the ICU within 24 hours after ED admission. ICU patients had lower peripheral oxygen saturation (86.7% vs 93.7, p≤0.001) and had a higher body mass index (29.2 vs 27.9 p=0.043) compared with non-ICU patients. National Early Warning Score 2 (NEWS2) ≥ 6 and q-COVID Score were superior to all other studied clinical risk scores in predicting ICU admission with a fair area under the receiver operating characteristics curve of 0.740 (95% CI 0.696 to 0.783) and 0.760 (95% CI 0.712 to 0.800), respectively. NEWS2 ≥6 and q-COVID Score ≥3 discriminated patients admitted to the ICU with a sensitivity of 78.1% and 75.9%, and specificity of 56.3% and 61.8%, respectively. CONCLUSION: In this multicentre study, the best performing models to predict ICU admittance were the NEWS2 and the Quick COVID-19 Severity Index Score, with fair diagnostic performance. However, due to the moderate performance, these models cannot be clinically used to adequately predict the need for ICU admission within 24 hours in patients with SARS-CoV-2 infection presenting at the ED.

Effect of Low-Normal vs High-Normal Oxygenation Targets on Organ Dysfunction in Critically Ill Patients: A Randomized Clinical Trial.

Importance: Hyperoxemia may increase organ dysfunction in critically ill patients, but optimal oxygenation targets are unknown. Objective: To determine whether a low-normal Pao2 target compared with a high-normal target reduces organ dysfunction in critically ill patients with systemic inflammatory response syndrome (SIRS). Design, Setting, and Participants: Multicenter randomized clinical trial in 4 intensive care units in the Netherlands. Enrollment was from February 2015 to October 2018, with end of follow-up to January 2019, and included adult patients admitted with 2 or more SIRS criteria and expected stay of longer than 48 hours. A total of 9925 patients were screened for eligibility, of whom 574 fulfilled the enrollment criteria and were randomized. Interventions: Target Pao2 ranges were 8 to 12 kPa (low-normal, n = 205) and 14 to 18 kPa (high-normal, n = 195). An inspired oxygen fraction greater than 0.60 was applied only when clinically indicated. Main Outcomes and Measures: Primary end point was SOFARANK, a ranked outcome of nonrespiratory organ failure quantified by the nonrespiratory components of the Sequential Organ Failure Assessment (SOFA) score, summed over the first 14 study days. Participants were ranked from fastest organ failure improvement (lowest scores) to worsening organ failure or death (highest scores). Secondary end points were duration of mechanical ventilation, in-hospital mortality, and hypoxemic measurements. Results: Among the 574 patients who were randomized, 400 (70%) were enrolled within 24 hours (median age, 68 years; 140 women [35%]), all of whom completed the trial. The median Pao2 difference between the groups was -1.93 kPa (95% CI, -2.12 to -1.74; P < .001). The median SOFARANK score was -35 points in the low-normal Pao2 group vs -40 in the high-normal Pao2 group (median difference, 10 [95% CI, 0 to 21]; P = .06). There was no significant difference in median duration of mechanical ventilation (3.4 vs 3.1 days; median difference, -0.15 [95% CI, -0.88 to 0.47]; P = .59) and in-hospital mortality (32% vs 31%; odds ratio, 1.04 [95% CI, 0.67 to 1.63]; P = .91). Mild hypoxemic measurements occurred more often in the low-normal group (1.9% vs 1.2%; median difference, 0.73 [95% CI, 0.30 to 1.20]; P < .001). Acute kidney failure developed in 20 patients (10%) in the low-normal Pao2 group and 21 patients (11%) in the high-normal Pao2 group, and acute myocardial infarction in 6 patients (2.9%) in the low-normal Pao2 group and 7 patients (3.6%) in the high-normal Pao2 group. Conclusions and Relevance: Among critically ill patients with 2 or more SIRS criteria, treatment with a low-normal Pao2 target compared with a high-normal Pao2 target did not result in a statistically significant reduction in organ dysfunction. However, the study may have had limited power to detect a smaller treatment effect than was hypothesized. Trial Registration: ClinicalTrials.gov Identifier: NCT02321072.

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.

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.

The effect of immediate coronary angiography after cardiac arrest without ST-segment elevation on left ventricular function. A sub-study of the COACT randomised trial.

BACKGROUND: The effect of immediate coronary angiography and percutaneous coronary intervention (PCI) in patients who are successfully resuscitated after cardiac arrest in the absence of ST-segment elevation myocardial infarction (STEMI) on left ventricular function is currently unknown. METHODS: This prespecified sub-study of a multicentre trial evaluated 552 patients, successfully resuscitated from out-of-hospital cardiac arrest without signs of STEMI. Patients were randomized to either undergo immediate coronary angiography or delayed coronary angiography, after neurologic recovery. All patients underwent PCI if indicated. The main outcomes of this analysis were left ventricular ejection fraction and end-diastolic and systolic volumes assessed by cardiac magnetic resonance imaging or echocardiography. RESULTS: Data on left ventricular function was available for 397 patients. The mean (± standard deviation) left ventricular ejection fraction was 45.2% (±12.8) in the immediate angiography group and 48.4% (±13.2) in the delayed angiography group (mean difference: -3.19; 95% confidence interval [CI], -6.75 to 0.37). Median left ventricular end-diastolic volume was 177 ml in the immediate angiography group compared to 169 ml in the delayed angiography group (ratio of geometric means: 1.06; 95% CI, 0.95-1.19). In addition, mean left ventricular end-systolic volume was 90 ml in the immediate angiography group compared to 78 ml in the delayed angiography group (ratio of geometric means: 1.13; 95% CI 0.97-1.32). CONCLUSION: In patients successfully resuscitated after out-of-hospital cardiac arrest and without signs of STEMI, immediate coronary angiography was not found to improve left ventricular dimensions or function compared with a delayed angiography strategy. CLINICAL TRIAL REGISTRATION: Netherlands Trial Register number, NTR4973.

[Blood pressure control in good hands with the general practicioner?] / Bloeddrukbehandeling bij de huisarts in goede handen?

According to a recent study regarding the management of hypertension in general practice, no therapeutic action was taken during follow-up in 87% of the selected population with uncontrolled hypertension (n = 6400). Older age, lower systolic, diastolic and near-target systolic blood pressure, as well as diabetes were positively associated with therapeutic inertia. This commentary questions whether the observed inertia in fact is appropriate inaction following conscious shared decision making. Also, the role of changing target values in old age in consecutive guidelines is discussed. Furthermore, the pivotal role of practice nurses in the regular follow-up of patients with hypertension and diabetes is outlined, as well as the possibly inadequate supervision by general practitioners in this respect. Finally, the unjustifiable therapeutic inertia in uncontrolled hypertensive diabetic patients is highlighted. However, the commentary concludes that overall the management of hypertension is in the right place in general practice.

[Doctors and lawyers in the disciplinary board: cooperation with added value]. / Overleg achter gesloten deuren.

Doctors and lawyers in the disciplinary board work together intensively, each from their own professional perspective, whereby the mutual dynamics greatly benefit the quality of the judgments: 1+1=3. How this cooperation takes place is not always visible to outsiders. After all, the session of the disciplinary board is public, but what is discussed before and after the session in the council chamber is decided and only comes out in the form of the ruling. How does that process work in the council chamber? Does the input of lawyers and doctors differ? What if they disagree? How do they reach an agreement? In this contribution two lawyers, a doctor and former doctor (member-lawyer), four authors from the Central Disciplinary Board for Health Care (CTG), give an insight into the chemistry between lawyers and doctors of the CTG.

Outcomes of persons with coronavirus disease 2019 in hospitals with and without standard treatment with (hydroxy)chloroquine.

OBJECTIVE: To compare survival of individuals with coronavirus disease 2019 (COVID-19) treated in hospitals that either did or did not routinely treat patients with hydroxychloroquine or chloroquine. METHODS: We analysed data of COVID-19 patients treated in nine hospitals in the Netherlands. Inclusion dates ranged from 27 February to 15 May 2020, when the Dutch national guidelines no longer supported the use of (hydroxy)chloroquine. Seven hospitals routinely treated patients with (hydroxy)chloroquine, two hospitals did not. Primary outcome was 21-day all-cause mortality. We performed a survival analysis using log-rank test and Cox regression with adjustment for age, sex and covariates based on premorbid health, disease severity and the use of steroids for adult respiratory distress syndrome, including dexamethasone. RESULTS: Among 1949 individuals, 21-day mortality was 21.5% in 1596 patients treated in hospitals that routinely prescribed (hydroxy)chloroquine, and 15.0% in 353 patients treated in hospitals that did not. In the adjusted Cox regression models this difference disappeared, with an adjusted hazard ratio of 1.09 (95% CI 0.81-1.47). When stratified by treatment actually received in individual patients, the use of (hydroxy)chloroquine was associated with an increased 21-day mortality (HR 1.58; 95% CI 1.24-2.02) in the full model. CONCLUSIONS: After adjustment for confounders, mortality was not significantly different in hospitals that routinely treated patients with (hydroxy)chloroquine compared with hospitals that did not. We compared outcomes of hospital strategies rather than outcomes of individual patients to reduce the chance of indication bias. This study adds evidence against the use of (hydroxy)chloroquine in hospitalised patients with COVID-19.

Sex differences in patients with out-of-hospital cardiac arrest without ST-segment elevation: A COACT trial substudy.

BACKGROUND: Whether sex is associated with outcomes of out-of-hospital cardiac arrest (OHCA) is unclear. OBJECTIVES: This study examined sex differences in survival in patients with OHCA without ST-segment elevation myocardial infarction (STEMI). METHODS: Using data from the randomized controlled Coronary Angiography after Cardiac Arrest (COACT) trial, the primary point of interest was sex differences in OHCA-related one-year survival. Secondary points of interest included the benefit of immediate coronary angiography compared to delayed angiography until after neurologic recovery, angiographic and clinical outcomes. RESULTS: In total, 522 patients (79.1% men) were included. Overall one-year survival was 59.6% in women and 63.4% in men (HR 1.18; 95% CI: 0.76-1.81;p = 0.47). No cardiovascular risk factors were found that modified survival. Women less often had significant coronary artery disease (CAD) (37.0% vs. 71.3%;p < 0.001), but when present, they had a worse prognosis than women without CAD (HR 3.06; 95% CI 1.31-7.19;p = 0.01). This was not the case for men (HR 1.05; 95% CI 0.67-1.65;p = 0.83). In both sexes, immediate coronary angiography did not improve one-year survival compared to delayed angiography (women, odds ratio (OR) 0.87; 95% CI 0.58-1.30;p = 0.49; vs. men, OR 0.97; 95% CI 0.45-2.09;p = 0.93). CONCLUSION: In OHCA patients without STEMI, we found no sex differences in overall one-year survival. Women less often had significant CAD, but when CAD was present they had worse survival than women without CAD. This was not the case for men. Both sexes did not benefit from a strategy of immediate coronary angiography as compared to delayed strategy with respect to one-year survival. CLINICAL TRIAL REGISTRATION NUMBER: Netherlands trial register (NTR) 4973.