Early association between respiratory mechanics and radiological changes in mechanically ventilated critically ill patients with COVID-19

The chest X-ray (CXR) Brixia scoring system was developed exclusively for COVID-19 severity assessment. However, no association between the score and respiratory mechanics during mechanical ventilation has been examined. Our aim was to evaluate the association between the CXR Brixia score and respiratory mechanics on the first day of mechanical ventilation in critically ill COVID-19 patients. A total of 77 COVID-19 patients who underwent mechanical ventilation and CXR in the ICU setting were retrospectively included. The CXR Brixia scoring system was applied, and respiratory mechanics data were recorded on the first day of invasive mechanical ventilation. Median Simplified Acute Physiologic Score II (SAPSII) and Sequential Organ Failure Assessment (SOFA) scores were 40 (31-54) and 6 (4-8), respectively. The median Brixia score was 14 (11-16). The correlation between the Brixia score and static compliance or driving pressure was significant, at r = -0.38, p < 0.001 and r = 0.33, p = 0.003, respectively. Using multivariable linear regression, the model with the B zone was significantly better associated with static compliance (F = 11.5, R2 = 0.14, p = 0.001) and driving pressure (F = 11.3, R2 = 0.13, p = 0.001). In logistic regression analysis, the Brixia score (OR 1.24; 95% CI 1.07, 1.45; p = 0.005), B zone (OR 2.60; 95% CI 1.30, 5.20; p = 0.007), C zone (OR 2.50; 95% CI 1.23, 5.11; p = 0.012), A zone (OR 2.01; 95% CI 1.16, 3.44; p = 0.012), and D zone (OR 1.84; 95% CI 1.07, 3.17; p = 0.027) significantly predicted a driving pressure > 14 cmH2O. There is a relationship between changes in Brixia-scored chest X-ray images and compliance and driving pressure on the first day of invasive mechanical ventilation. We identified some CXR areas using the Brixia score, and evaluation of the Brixia score may provide additional information for predicting respiratory mechanics.

Feasibility of the optimal cerebral perfusion pressure value identification without a delay that is too long

Optimal cerebral perfusion pressure (CPPopt)-targeted treatment of traumatic brain injury (TBI) patients requires 2-8 h multi-modal monitoring data accumulation to identify CPPopt value for individual patient. Minimizing the time required for monitoring data accumulation is needed to improve the efficacy of CPPopt-targeted therapy. A retrospective analysis of multimodal physiological monitoring data from 87 severe TBI patients was performed by separately representing cerebrovascular autoregulation (CA) indices in relation to CPP, arterial blood pressure (ABP), and intracranial pressure (ICP) to improve the existing CPPopt identification algorithms. Machine learning (ML)-based algorithms were developed for automatic identification of informative data segments that were used for reliable CPPopt, ABPopt, ICPopt and the lower/upper limits of CA (LLCA/ULCA) identification. The reference datasets of the informative data segments and, artifact-distorted segments, and the datasets of different clinical situations were used for training the ML-based algorithms, allowing us to choose the appropriate individualized CPP-, ABP- or ICP-guided management for 79% of the full monitoring time for the studied population. The developed ML-based algorithms allow us to recognize informative physiological ABP/ICP variations within 24 min intervals with an accuracy up to 79% (compared to the initial accuracy of 74%) and use these segments for timely optimal value identification or CA limits determination in CPP, ABP or ICP data. Prospective clinical studies are needed to prove the efficiency of the developed algorithms.

Comparative effectiveness of intracranial hypertension management guided by ventricular versus intraparenchymal pressure monitoring: a CENTER-TBI study

OBJECTIVE

To compare outcomes between patients with primary external ventricular device (EVD)-driven treatment of intracranial hypertension and those with primary intraparenchymal monitor (IP)-driven treatment.

METHODS

The CENTER-TBI study is a prospective, multicenter, longitudinal observational cohort study that enrolled patients of all TBI severities from 62 participating centers (mainly level I trauma centers) across Europe between 2015 and 2017. Functional outcome was assessed at 6 months and a year. We used multivariable adjusted instrumental variable (IV) analysis with "center" as instrument and logistic regression with covariate adjustment to determine the effect estimate of EVD on 6-month functional outcome.

RESULTS

A total of 878 patients of all TBI severities with an indication for intracranial pressure (ICP) monitoring were included in the present study, of whom 739 (84%) patients had an IP monitor and 139 (16%) an EVD. Patients included were predominantly male (74% in the IP monitor and 76% in the EVD group), with a median age of 46 years in the IP group and 48 in the EVD group. Six-month GOS-E was similar between IP and EVD patients (adjusted odds ratio (aOR) and 95% confidence interval [CI] OR 0.74 and 95% CI [0.36-1.52], adjusted IV analysis). The length of intensive care unit stay was greater in the EVD group than in the IP group (adjusted rate ratio [95% CI] 1.70 [1.34-2.12], IV analysis). One hundred eighty-seven of the 739 patients in the IP group (25%) required an EVD due to refractory ICPs.

CONCLUSION

We found no major differences in outcomes of patients with TBI when comparing EVD-guided and IP monitor-guided ICP management. In our cohort, a quarter of patients that initially received an IP monitor required an EVD later for ICP control. The prevalence of complications was higher in the EVD group.

PROTOCOL

The core study is registered with ClinicalTrials.gov , number NCT02210221, and the Resource Identification Portal (RRID: SCR_015582).

Neurocognitive correlates of probable posttraumatic stress disorder following traumatic brain injury

Introduction

Neurocognitive problems associated with posttraumatic stress disorder (PTSD) can interact with impairment resulting from traumatic brain injury (TBI).

Research question

We aimed to identify neurocognitive problems associated with probable PTSD following TBI in a civilian sample.

Material and methods

The study is part of the CENTER-TBI project (Collaborative European Neurotrauma Effectiveness Research) that aims to better characterize TBI. For this cross-sectional study, we included patients of all severities aged over 15, and a Glasgow Outcome Score Extended (GOSE) above 3. Participants were assessed at six months post-injury on the PTSD Checklist-5 (PCL-5), the Trail Making Test (TMT), the Rey Auditory Verbal Learning Test (RAVLT) and the Cambridge Neuropsychological Test Automated Battery (CANTAB). Primary analysis was a complete case analysis. Regression analyses were performed to investigate the association between the PCL-5 and cognition.

Results

Of the 1134 participants included in the complete case analysis, 13.5% screened positive for PTSD. Probable PTSD was significantly associated with higher TMT-(B-A) (OR ​= ​1.35, 95% CI: 1.14–1.60, p ​< ​.001) and lower RAVLT-delayed recall scores (OR ​= ​0.74, 95% CI: 0.61–0.91, p ​= ​.004) after controlling for age, sex, psychiatric history, baseline Glasgow Coma Scale and education.

Discussion and conclusion

Poorer performance on cognitive tests assessing task switching and, to a lesser extent, delayed verbal recall is associated with probable PTSD in civilians who have suffered TBI.

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Six months after traumatic brain injury 13.5% of people screen positive for PTSD.

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Task switching performance and verbal memory are related to probable PTSD.

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PTSD severity is related to processing speed and task switching performance.

Establishing prognostic significance of hypoxia predictors in patients with acute cerebral pathology

OBJECTIVES

This research aims to study the prognostic role of serum S100 as a predictor of mortality in vascular and traumatic brain injuries.

METHODS

This prospective cohort study involved 219 patients. In the blood serum, neuron-specific markers (S100, NSE) and glucose, acid-base state and gas composition of arterial blood were obtained at admission, on the 3rd, 5th and 7th days of patients' stay in the intensive care unit.

RESULTS

The most significant risk factor for an unfavorable outcome is the marker S100 with a cut-off point of 0.2 mcg/l. The analysis results indicate a statistically significant direct relationship between S100 > 0.2 mcg/l and NSE ≥ 18.9 ng/ml compared to other variables, while the chance ratio (OR) is 11.9 (95%CI:3.2927-1.6693;). With blood sugar increase above 7.4 mmol/l, the OR is 3.82 (95% CI: 2.1289-0.5539;); with a Glasgow scale below 13 points, the OR is 3.69 (95% CI: 2.1316-0.4819;); with an increase in pCO2 < 43.5 mm Hg, the OR was 3.15 (95% CI: 1.8916- 0.4062;). The obtained model certainty measure according to pseudo R2 Nagelkerke criterion is 263.5, showing the excellent quality of the mathematical model's predictive ability. The developed prognostic model, including the dependent variable S100 and independent variables as predictors of a poor outcome of NSE, pCO2, GCS and Hb, reached a cut-off point of 84.51%, AUC - 0.88 with high levels of sensitivity and specificity: 91.89% and 64.14%, respectively.

NOVELTY

This model can be used to predict the outcome in patients with acute cerebral pathology.

Conjunctival microcirculatory blood flow is altered but not abolished in brain dead patients: a prospective observational study

Background

The conjunctival microcirculation has potential as a window to cerebral perfusion due to related blood supply, close anatomical proximity and easy accessibility for microcirculatory imaging technique, such as sidestream dark field (SDF) imaging. Our study aims to evaluate conjunctival and sublingual microcirculation in brain dead patients and to compare it with healthy volunteers in two diametrically opposed conditions: full stop versus normal arterial blood supply to the brain.

Methods

In a prospective observational study we analyzed conjunctival and sublingual microcirculation using SDF imaging in brain dead patients after reaching systemic hemodynamic targets to optimize perfusion of donor organs, and in healthy volunteers. All brain death diagnoses were confirmed by cerebral angiography. Microcirculatory images were obtained and analyzed using standardized published recommendations. Study registered at ClinicalTrials.gov, number NCT02483273.

Results

Eleven brain dead patients and eleven apparently healthy controls were enrolled in the study. Microvascular flow index (MFI) of small vessels was significantly lower in brain dead patients in comparison to healthy controls in ocular conjunctiva (2.7 [2.4–2.9] vs. 3.0 [2.9–3.0], p = 0.01) and in sublingual mucosa (2.8 [2.6–2.9] vs. 3.0 [2.9–3.0], p = 0.02). Total vessel density (TVD) and perfused vessel density (PVD) of small vessels were significantly lower in brain dead patients in comparison to healthy controls in ocular conjunctiva (10.2 [6.6–14.8] vs. 18.0 [18.0–25.4] mm/mm², p = 0.001 and 5.0 [3.5–7.3] vs. 10.9 [10.9–13.5] 1/mm, p = 0.001), but not in sublingual mucosa.

Conclusion

In comparison to healthy controls brain dead patients had a significant reduction in conjunctival microvascular blood flow and density. However, the presence of conjunctival flow in case general cerebral flow is completely absent makes it impossible to use the conjunctival microcirculation as a substitute for brain flow, and further research should focus on the link between the ocular microcirculation, intracranial pressure and alternative ocular circulation.