Predicting COVID-19 prognosis in the ICU remained challenging: external validation in a multinational regional cohort

Objective: Many prediction models for Coronavirus Disease 2019 (COVID-19) have been developed. External validation is mandatory before implementation in the Intensive Care Unit (ICU). We selected and validated prognostic models in the Euregio Intensive Care COVID (EICC) cohort. Study design and setting: In this multinational cohort study, routine data from COVID-19 patients admitted to ICUs within the Euregio Meuse-Rhine were collected from March to August 2020. COVID-19 models were selected based on model type, predictors, outcomes, and reporting. Furthermore, general ICU scores were assessed. Discrimination was assessed by area under the receiver operating characteristic curves (AUCs) and calibration by calibration-in-the-large and calibration plots. A random-effects meta-analysis was used to pool results. Results: 551 patients were admitted. Mean age was 65.4±11.2 years, 29% were female, and ICU mortality was 36%. Nine out of 238 published models were externally validated. Pooled AUCs were between 0.53 and 0.70 and calibration-in-the-large between -9% and 6%. Calibration plots showed generally poor but, for the 4C Mortality score and SEIMC score, moderate calibration. Conclusion: Of the nine prognostic models that were externally validated in the EICC cohort, only two showed reasonable discrimination and moderate calibration. For future pandemics, better models based on routine data are needed to support admission decision-making

Delirium in older COVID-19 patients:Evaluating risk factors and outcomes

Objectives: A high incidence of delirium has been reported in older patients with Coronavirus disease 2019 (COVID-19). We aimed to identify determinants of delirium, including the Clinical Frailty Scale, in hospitalized older patients with COVID-19. Furthermore, we aimed to study the association of delirium independent of frailty with in-hospital outcomes in older COVID-19 patients. Methods: This study was performed within the framework of the multi-center COVID-OLD cohort study and included patients aged ≥60 years who were admitted to the general ward because of COVID-19 in the Netherlands between February and May 2020. Data were collected on demographics, co-morbidity, disease severity, and geriatric parameters. Prevalence of delirium during hospital admission was recorded based on delirium screening using the Delirium Observation Screening Scale (DOSS) which was scored three times daily. A DOSS score ≥3 was followed by a delirium assessment by the ward physician In-hospital outcomes included length of stay, discharge destination, and mortality. Results: A total of 412 patients were included (median age 76, 58% male). Delirium was present in 82 patients. In multivariable analysis, previous episode of delirium (Odds ratio [OR] 8.9 [95% CI 2.3–33.6] p = 0.001), and pre-existent memory problems (OR 7.6 [95% CI 3.1–22.5] p < 0.001) were associated with increased delirium risk. Clinical Frailty Scale was associated with increased delirium risk (OR 1.63 [95%CI 1.40–1.90] p < 0.001) in univariable analysis, but not in multivariable analysis. Patients who developed delirium had a shorter symptom duration and lower levels of C-reactive protein upon presentation, whereas vital parameters did not differ. Patients who developed a delirium had a longer hospital stay and were more often discharged to a nursing home. Delirium was associated with mortality (OR 2.84 [95% CI1.71–4.72] p < 0.001), but not in multivariable analyses. Conclusions: A previous delirium and pre-existent memory problems were associated with delirium risk in COVID-19. Delirium was not an independent predictor of mortality after adjustment for frailty

Validating an image-based fNIRS approach with fMRI and a working memory task

In the current study, we extend a previous methodological pipeline by adding a novel image reconstruction approach to move functional near-infrared (fNIRS) signals from channel-space on the surface of the head to voxel-space within the brain volume. We validate this methodology by comparing voxel-wise fNIRS results to functional magnetic resonance imaging (fMRI) results from a visual working memory (VWM) task using two approaches. In the first approach, significant voxel-wise correlations were observed between fNIRS and fMRI measures for all experimental conditions across brain regions in the fronto-parieto-temporal cortices. In the second approach, we conducted separate multi-factorial ANOVAs on fNIRS and fMRI measures and then examined the correspondence between main and interaction effects within common regions of interest. Both fMRI and fNIRS showed similar trends in activation within the VWM network when the number of items held in working memory increases. These results validate the image-based fNIRS approach

Origins of Spatial Working Memory Deficits in Schizophrenia: An Event-Related fMRI and Near-Infrared Spectroscopy Study

Abnormal prefrontal functioning plays a central role in the working memory (WM) deficits of schizophrenic patients, but the nature of the relationship between WM and prefrontal activation remains undetermined. Using two functional neuroimaging methods, we investigated the neural correlates of remembering and forgetting in schizophrenic and healthy participants. We focused on the brain activation during WM maintenance phase with event-related functional magnetic resonance imaging (fMRI). We also examined oxygenated hemoglobin changes in relation to memory performance with the near-infrared spectroscopy (NIRS) using the same spatial WM task. Distinct types of correct and error trials were segregated for analysis. fMRI data indicated that prefrontal activation was increased during WM maintenance on correct trials in both schizophrenic and healthy subjects. However, a significant difference was observed in the functional asymmetry of frontal activation pattern. Healthy subjects showed increased activation in the right frontal, temporal and cingulate regions. Schizophrenic patients showed greater activation compared with control subjects in left frontal, temporal and parietal regions as well as in right frontal regions. We also observed increased ‘false memory’ errors in schizophrenic patients, associated with increased prefrontal activation and resembling the activation pattern observed on the correct trials. NIRS data replicated the fMRI results. Thus, increased frontal activity was correlated with the accuracy of WM in both healthy control and schizophrenic participants. The major difference between the two groups concerned functional asymmetry; healthy subjects recruited right frontal regions during spatial WM maintenance whereas schizophrenic subjects recruited a wider network in both hemispheres to achieve the same level of memory performance. Increased “false memory” errors and accompanying bilateral prefrontal activation in schizophrenia suggest that the etiology of memory errors must be considered when comparing group performances. Finally, the concordance of fMRI and NIRS data supports NIRS as an alternative functional neuroimaging method for psychiatric research

Impaired Prefrontal Hemodynamic Maturation in Autism and Unaffected Siblings

BACKGROUND: Dysfunctions of the prefrontal cortex have been previously reported in individuals with autism spectrum disorders (ASD). Previous studies reported that first-degree relatives of individuals with ASD show atypical brain activity during tasks associated with social function. However, developmental changes in prefrontal dysfunction in ASD and genetic influences on the phenomena remain unclear. In the present study, we investigated the change in hemoglobin concentration in the prefrontal cortex as measured with near-infrared spectroscopy, in children and adults with ASD during the letter fluency test. Moreover, to clarify the genetic influences on developmental changes in the prefrontal dysfunction in ASD, unaffected siblings of the ASD participants were also assessed. METHODOLOGY/PRINCIPAL FINDINGS: Study participants included 27 individuals with high-functioning ASD, age- and IQ-matched 24 healthy non-affected siblings, and 27 unrelated healthy controls aged 5 to 39 years. The relative concentration of hemoglobin ([Hb]) in the prefrontal cortex was measured during the letter fluency task. For children, neither the [oxy-Hb] change during the task nor task performances differed significantly among three groups. For adults, the [oxy-Hb] increases during the task were significantly smaller in the bilateral prefrontal cortex in ASD than those in control subjects, although task performances were similar. In the adult siblings the [oxy-Hb] change was intermediate between those in controls and ASDs. CONCLUSION/SIGNIFICANCE: Although indirectly due to a cross-sectional design, the results of this study indicate altered age-related change of prefrontal activity during executive processing in ASD. This is a first near-infrared spectroscopy study that implies alteration in the age-related changes of prefrontal activity in ASD and genetic influences on the phenomena

Brain Cortical Mapping by Simultaneous Recording of Functional Near Infrared Spectroscopy and Electroencephalograms from the Whole Brain During Right Median Nerve Stimulation

To investigate relationships between hemodynamic responses and neural activities in the somatosensory cortices, hemodynamic responses by near infrared spectroscopy (NIRS) and electroencephalograms (EEGs) were recorded simultaneously while subjects received electrical stimulation in the right median nerve. The statistical significance of the hemodynamic responses was evaluated by a general linear model (GLM) with the boxcar design matrix convoluted with Gaussian function. The resulting NIRS and EEGs data were stereotaxically superimposed on the reconstructed brain of each subject. The NIRS data indicated that changes in oxy-hemoglobin concentration increased at the contralateral primary somatosensory (SI) area; responses then spread to the more posterior and ipsilateral somatosensory areas. The EEG data indicated that positive somatosensory evoked potentials peaking at 22 ms latency (P22) were recorded from the contralateral SI area. Comparison of these two sets of data indicated that the distance between the dipoles of P22 and NIRS channels with maximum hemodynamic responses was less than 10 mm, and that the two topographical maps of hemodynamic responses and current source density of P22 were significantly correlated. Furthermore, when onset of the boxcar function was delayed 5–15 s (onset delay), hemodynamic responses in the bilateral parietal association cortices posterior to the SI were more strongly correlated to electrical stimulation. This suggests that GLM analysis with onset delay could reveal the temporal ordering of neural activation in the hierarchical somatosensory pathway, consistent with the neurophysiological data. The present results suggest that simultaneous NIRS and EEG recording is useful for correlating hemodynamic responses to neural activity

Clinical and organizational factors associated with mortality during the peak of first COVID-19 wave: the global UNITE-COVID study

Purpose: To accommodate the unprecedented number of critically ill patients with pneumonia caused by coronavirus disease 2019 (COVID-19) expansion of the capacity of intensive care unit (ICU) to clinical areas not previously used for critical care was necessary. We describe the global burden of COVID-19 admissions and the clinical and organizational characteristics associated with outcomes in critically ill COVID-19 patients. Methods: Multicenter, international, point prevalence study, including adult patients with SARS-CoV-2 infection confirmed by polymerase chain reaction (PCR) and a diagnosis of COVID-19 admitted to ICU between February 15th and May 15th, 2020. Results: 4994 patients from 280 ICUs in 46 countries were included. Included ICUs increased their total capacity from 4931 to 7630 beds, deploying personnel from other areas. Overall, 1986 (39.8%) patients were admitted to surge capacity beds. Invasive ventilation at admission was present in 2325 (46.5%) patients and was required during ICU stay in 85.8% of patients. 60-day mortality was 33.9% (IQR across units: 20%–50%) and ICU mortality 32.7%. Older age, invasive mechanical ventilation, and acute kidney injury (AKI) were associated with increased mortality. These associations were also confirmed specifically in mechanically ventilated patients. Admission to surge capacity beds was not associated with mortality, even after controlling for other factors. Conclusions: ICUs responded to the increase in COVID-19 patients by increasing bed availability and staff, admitting up to 40% of patients in surge capacity beds. Although mortality in this population was high, admission to a surge capacity bed was not associated with increased mortality. Older age, invasive mechanical ventilation, and AKI were identified as the strongest predictors of mortality

Co-infection and ICU-acquired infection in COIVD-19 ICU patients: a secondary analysis of the UNITE-COVID data set

Background: The COVID-19 pandemic presented major challenges for critical care facilities worldwide. Infections which develop alongside or subsequent to viral pneumonitis are a challenge under sporadic and pandemic conditions; however, data have suggested that patterns of these differ between COVID-19 and other viral pneumonitides. This secondary analysis aimed to explore patterns of co-infection and intensive care unit-acquired infections (ICU-AI) and the relationship to use of corticosteroids in a large, international cohort of critically ill COVID-19 patients.Methods: This is a multicenter, international, observational study, including adult patients with PCR-confirmed COVID-19 diagnosis admitted to ICUs at the peak of wave one of COVID-19 (February 15th to May 15th, 2020). Data collected included investigator-assessed co-infection at ICU admission, infection acquired in ICU, infection with multi-drug resistant organisms (MDRO) and antibiotic use. Frequencies were compared by Pearson's Chi-squared and continuous variables by Mann-Whitney U test. Propensity score matching for variables associated with ICU-acquired infection was undertaken using R library MatchIT using the "full" matching method.Results: Data were available from 4994 patients. Bacterial co-infection at admission was detected in 716 patients (14%), whilst 85% of patients received antibiotics at that stage. ICU-AI developed in 2715 (54%). The most common ICU-AI was bacterial pneumonia (44% of infections), whilst 9% of patients developed fungal pneumonia; 25% of infections involved MDRO. Patients developing infections in ICU had greater antimicrobial exposure than those without such infections. Incident density (ICU-AI per 1000 ICU days) was in considerable excess of reports from pre-pandemic surveillance. Corticosteroid use was heterogenous between ICUs. In univariate analysis, 58% of patients receiving corticosteroids and 43% of those not receiving steroids developed ICU-AI. Adjusting for potential confounders in the propensity-matched cohort, 71% of patients receiving corticosteroids developed ICU-AI vs 52% of those not receiving corticosteroids. Duration of corticosteroid therapy was also associated with development of ICU-AI and infection with an MDRO.Conclusions: In patients with severe COVID-19 in the first wave, co-infection at admission to ICU was relatively rare but antibiotic use was in substantial excess to that indication. ICU-AI were common and were significantly associated with use of corticosteroids

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.Perioperative Medicine: Efficacy, Safety and Outcome (Anesthesiology/Intensive Care