Introduction Coronavirus disease 2019 (COVID-19) appeared in China in December 2019 and has spread around the world. High Interleukin-6 (IL-6) levels in COVID-19 patients suggest that a cytokine storm may play a major role in the pathophysiology and are considered as a relevant parameter in predicting most severe course of disease. The aim of this study was to assess repeated IL-6 levels in critically ill COVID-19 patients admitted to our Intensive Care Unit (ICU) and to evaluate their relationship with patient’s severity and outcome. Methods We conducted a retrospective study on patients admitted to the ICU with a diagnosis of COVID-19 between March 10 (i.e. the date of the first admitted patients) and April 30, 2020. Demographic, clinical and laboratory data were collected at admission. On the day of IL-6 blood concentration measurement, we also collected results of D-Dimers, C-Reactive Protein, white blood cells and lymphocytes count, lactate dehydrogenase (LDH) and ferritin as well as microbiological samples, whenever present. Results Of a total of 65 patients with COVID-19 admitted to our ICU we included 41 patients with repeated measure of IL-6. There was a significant difference in IL-6 levels between survivors and non-survivors over time (p = 0.001); moreover, non survivors had a significantly higher IL-6 maximal value when compared to survivors (720 [349–2116] vs. 336 [195–646] pg/mL, p = 0.01). The IL-6 maximal value had a significant predictive value of ICU mortality (AUROC 0.73 [95% CI 0.57–0.89]; p = 0.01). Conclusions Repeated measurements of IL-6 can help clinicians in identifying critically ill COVID-19 patients with the highest risk of poor prognosis.

Brain hypoxia can occur after non-traumatic subarachnoid hemorrhage (SAH), even when levels of intracranial pressure (ICP) remain normal. Brain tissue oxygenation (PbtO2) can be measured as a part of a neurological multimodal neuromonitoring. Low PbtO2 has been associated with poor neurologic recovery. There is scarce data on the impact of PbtO2 guided-therapy on patients’ outcome. This single-center cohort study (June 2014–March 2020) included all patients admitted to the ICU after SAH who required multimodal monitoring. Patients with imminent brain death were excluded. Our primary goal was to assess the impact of PbtO2-guided therapy on neurological outcome. Secondary outcome included the association of brain hypoxia with outcome. Of the 163 patients that underwent ICP monitoring, 62 were monitored with PbtO2 and 54 (87%) had at least one episode of brain hypoxia. In patients that required treatment based on neuromonitoring strategies, PbtO2-guided therapy (OR 0.33 [CI 95% 0.12–0.89]) compared to ICP-guided therapy had a protective effect on neurological outcome at 6 months. In this cohort of SAH patients, PbtO2-guided therapy might be associated with improved long-term neurological outcome, only when compared to ICP-guided therapy.

Background Neurological outcome and mortality of patients suffering from poor grade subarachnoid hemorrhage (SAH) may have changed over time. Several factors, including patients’ characteristics, the presence of hydrocephalus and intraparenchymal hematoma, might also contribute to this effect. The aim of this study was to assess the temporal changes in mortality and neurologic outcome in SAH patients and identify their predictors. Methods We performed a single center retrospective cohort study from 2004 to 2018. All non-traumatic SAH patients with poor grade on admission (WFNS score of 4 or 5) who remained at least 24 h in the hospital were included. Time course was analyzed into four groups according to the years of admission (2004–2007; 2008–2011; 2012–2015 and 2016–2018). Results A total of 353 patients were included in this study: 202 patients died (57 %) and 260 (74 %) had unfavorable neurological outcome (UO) at 3 months. Mortality tended to decrease in in 2008–2011 and 2016–2018 periods (HR 0.55 [0.34–0.89] and HR 0.33 [0.20–0.53], respectively, when compared to 2004–2007). The proportion of patients with UO remained high and did not vary significantly over time. Patients with WFNS 5 had higher mortality (68 % vs. 34 %, p = 0.001) and more frequent UO (83 % vs. 54 %, p = 0.001) than those with WFNS 4. In the multivariable analysis, WFNS 5 was independently associated with mortality (HR 2.12 [1.43–3.14]) and UO (OR 3.23 [1.67–6.25]). The presence of hydrocephalus was associated with a lower risk of mortality (HR 0.60 [0.43–0.84]). Conclusions Both hospital mortality and UO remained high in poor grade SAH patients. Patients with WFNS 5 on admission had worse prognosis than others; this should be taken into consideration for future clinical studies.

Objectives: The aim of this study was to assess the diagnostic role of eosinophils count in COVID-19 patients. Methods: Retrospective analysis of patients admitted to our hospital with suspicion of COVID-19. Demographic, clinical and laboratory data were collected on admission. Eosinopenia was defined as eosinophils < 100 cells/mm3. The outcomes of this study were the association between eosinophils count on admission and positive real-time reverse transcription polymerase chain reaction (rRT-PCR) test and with suggestive chest computerized tomography (CT) of COVID-19 pneumonia. Results: A total of 174 patients was studied. Of those, 54% had positive rRT-PCR for SARS-CoV-2. A chest CT-scan was performed in 145 patients; 71% showed suggestive findings of COVID-19. Eosinophils on admission had a high predictive accuracy for positive rRT-PCR and suggestive chest CT-scan (area under the receiver operating characteristic—ROC curve, 0.84 (95% CIs 0.78–0.90) and 0.84 (95% CIs 0.77–0.91), respectively). Eosinopenia and high LDH were independent predictors of positive rRT-PCR, whereas eosinopenia, high body mass index and hypertension were predictors for suggestive CT-scan findings. Conclusions: Eosinopenia on admission could predict positive rRT-PCR test or suggestive chest CT-scan for COVID-19. This laboratory finding could help to identify patients at high-risk of COVID-19 in the setting where gold standard diagnostic methods are not available.

Blood lactate concentrations are often used to assess global tissue perfusion in critically ill patients; however, there are scarce data on lactate concentrations after subarachnoid hemorrhage (SAH). We aimed to assess the prognostic role of serial blood lactate measurements on hospital mortality and neurological outcomes at 3 months after SAH. We reviewed all SAH patients admitted to the intensive care unit from 2007 to 2019 and recorded the highest daily arterial lactate concentration for the first 6 days. Patients with no lactate concentration were excluded. Hyperlactatemia was defined as a blood lactate concentration >2.0 mmol/L. A total of 456 patients were included: 158 (35%) patients died in hospital and 209 (46%) had an unfavorable outcome (UO) at 3 months. The median highest lactate concentration was 2.7 (1.8–3.9) mmol/L. Non-survivors and patients with UO had significantly higher lactate concentrations compared to other patients. Hyperlactatemia increased the chance of dying (OR 4.19 (95% CI 2.38–7.39)) and of having UO in 3 months (OR 4.16 (95% CI 2.52–6.88)) after adjusting for confounding factors. Therefore, initial blood lactate concentrations have prognostic implications in patients with SAH; their role in conjunction with other prognostic indicators should be evaluated in prospective studies.

Background Brain hypoxia can occur after spontaneous subarachnoid hemorrhage (SAH), even when levels of intracranial pressure (ICP) remain normal. Brain tissue oxygenation (PbtO2) can be measured as a part of a neurological multimodal neuromonitoring Low PbtO2 has been associated with poor neurologic recovery. There is scarce data on the impact of PbtO2 guided-therapy on patients’ outcome. Methods This single-center cohort study (June 2014-March 2020) included all patients admitted to the ICU after SAH who required multimodal monitoring. Patients with imminent brain death were excluded. Our primary goal was to assess the impact of PbtO2-guided therapy on neurological outcome. Secondary outcome included the association of brain hypoxia with outcome. Results Of the 163 patients that underwent ICP monitoring, 62 were monitored with PbtO2 and 54 (87%) had at least one episode of brain hypoxia. In patients that required treatment based on neuromonitoring strategies, PbtO2-guided therapy (OR 0.33 [CI 95% 0.12–0.90]) compared to ICP-guided therapy had a protective effect on neurological outcome at 6 months. Brain hypoxia was associated with unfavorable neurological (OR 4.51 [95% CI 1.17–17.45]). Conclusions In this cohort of SAH patients, PbtO2-guided therapy when compared to ICP guided therapy may be associated with improved long-term neurological outcome.

BackgroundElectroencephalography (EEG) is widely used to monitor critically ill patients. However, EEG interpretation requires the presence of an experienced neurophysiologist and is time-consuming. Aim of this study was to evaluate whether parameters derived from an automated pupillometer (AP) might help to assess the degree of cerebral dysfunction in critically ill patients.MethodsProspective study conducted in the Department of Intensive Care of Erasme University Hospital in Brussels, Belgium. Pupillary assessments were performed using the AP in three subgroups of patients, concomitantly monitored with continuous EEG: “anoxic brain injury”, “Non-anoxic brain injury” and “other diseases”. An independent neurologist blinded to patient's history and AP results scored the degree of encephalopathy and reactivity on EEG using a standardized scale. The mean value of Neurologic Pupil Index (NPi), pupillary size, constriction rate, constriction and dilation velocity (CV and DV) and latency for both eyes, obtained using the NPi®-200 (Neuroptics, Laguna Hills, CA, USA), were reported.ResultsWe included 214 patients (mean age 60 years, 55% male). EEG tracings were categorized as: mild (n = 111, 52%), moderate (n = 65, 30%) or severe (n = 16, 8%) encephalopathy; burst-suppression (n = 19, 9%) or suppression background (n = 3, 1%); a total of 38 (18%) EEG were classified as “unreactive”. We found a significant difference in all pupillometry variables among different EEG categories. Moreover, an unreactive EEG was associated with lower NPi, pupil size, pupillary reactivity, CV and DV and a higher latency than reactive recordings. Low DV (Odds ratio 0.020 [95% confidence intervals 0.002–0.163]; p &lt; 0.01) was independently associated with an unreactive EEG, together with the use of analgesic/sedative drugs and high lactate concentrations. In particular, DV values had an area under the curve (AUC) of 0.86 [0.79–0.92; p &lt; 0.01] to predict the presence of unreactive EEG. In subgroups analyses, AUC of DV to predict unreactive EEG was lower (0.72 [0.56–0.87]; p &lt; 0.01) in anoxic brain injury than Non-anoxic brain injury (0.92 [0.85–1.00]; p &lt; 0.01) and other diseases (0.96 [0.90–1.00]; p &lt; 0.01).ConclusionsThis study suggests that low DV measured by the AP might effectively identify an unreactive EEG background, in particular in critically ill patients without anoxic brain injury.

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