24 research outputs found

    Peri-operative red blood cell transfusion in neonates and infants: NEonate and Children audiT of Anaesthesia pRactice IN Europe: A prospective European multicentre observational study

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    BACKGROUND: Little is known about current clinical practice concerning peri-operative red blood cell transfusion in neonates and small infants. Guidelines suggest transfusions based on haemoglobin thresholds ranging from 8.5 to 12 g dl-1, distinguishing between children from birth to day 7 (week 1), from day 8 to day 14 (week 2) or from day 15 (≄week 3) onwards. OBJECTIVE: To observe peri-operative red blood cell transfusion practice according to guidelines in relation to patient outcome. DESIGN: A multicentre observational study. SETTING: The NEonate-Children sTudy of Anaesthesia pRactice IN Europe (NECTARINE) trial recruited patients up to 60 weeks' postmenstrual age undergoing anaesthesia for surgical or diagnostic procedures from 165 centres in 31 European countries between March 2016 and January 2017. PATIENTS: The data included 5609 patients undergoing 6542 procedures. Inclusion criteria was a peri-operative red blood cell transfusion. MAIN OUTCOME MEASURES: The primary endpoint was the haemoglobin level triggering a transfusion for neonates in week 1, week 2 and week 3. Secondary endpoints were transfusion volumes, 'delta haemoglobin' (preprocedure - transfusion-triggering) and 30-day and 90-day morbidity and mortality. RESULTS: Peri-operative red blood cell transfusions were recorded during 447 procedures (6.9%). The median haemoglobin levels triggering a transfusion were 9.6 [IQR 8.7 to 10.9] g dl-1 for neonates in week 1, 9.6 [7.7 to 10.4] g dl-1 in week 2 and 8.0 [7.3 to 9.0] g dl-1 in week 3. The median transfusion volume was 17.1 [11.1 to 26.4] ml kg-1 with a median delta haemoglobin of 1.8 [0.0 to 3.6] g dl-1. Thirty-day morbidity was 47.8% with an overall mortality of 11.3%. CONCLUSIONS: Results indicate lower transfusion-triggering haemoglobin thresholds in clinical practice than suggested by current guidelines. The high morbidity and mortality of this NECTARINE sub-cohort calls for investigative action and evidence-based guidelines addressing peri-operative red blood cell transfusions strategies. TRIAL REGISTRATION: ClinicalTrials.gov, identifier: NCT02350348

    Relative cerebral hyperperfusion during cardiopulmonary bypass is associated with risk for postoperative delirium: a cross-sectional cohort study

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    Abstract Background Our objective was to evaluate if changes in on-pump cerebral blood flow, relative to the pre-bypass baseline, are associated with the risk for postoperative delirium (POD) following cardiac surgery. Methods In 47 consecutive adult patients, right middle cerebral artery blood flow velocity (MCAV) was assessed using transcranial Doppler sonography. Individual values, measured during cardiopulmonary bypass (CPB), were normalized to the pre-bypass baseline value and termed MCAVrel. An MCAVrel > 100% was defined as cerebral hyperperfusion. Prevalence of POD was assessed using the Confusion Assessment Method for the Intensive Care Unit. Results Overall prevalence of POD was 27%. In the subgroup without POD, 32% of patients had experienced relative cerebral hyperperfusion during CPB, compared to 67% in the subgroup with POD (p < 0.05). The mean averaged MCAVrel was 90 (±21) % in the no-POD group vs. 112 (±32) % in the POD group (p < 0.05), and patients developing delirium experienced cerebral hyperperfusion during CPB for about 39 (±35) min, compared to 6 (±11) min in the group without POD (p < 0.001). In a subcohort with pre-bypass baseline MCAV (MCAVbas) below the median MCAVbas of the whole cohort, prevalence of POD was 17% when MCAVrel during CPB was kept below 100%, but increased to 53% when these patients actually experienced relative cerebral hyperperfusion. Conclusions Our results suggest a critical role for cerebral hyperperfusion in the pathogenesis of POD following on-pump open-heart surgery, recommending a more individualized hemodynamic management, especially in the population at risk

    Maximizing prediction probability PK as an alternative semiparametric approach to estimate the plasma effect-site equilibration rate constant ke0.

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    Contains fulltext : 79856.pdf (publisher's version ) (Closed access)BACKGROUND: The k(e)(0) value is the first order rate constant determining the equilibration of drugs between plasma or end-tidal concentration and effect-site (e.g., brain) concentration. Parametric and semiparametric approaches have been used for estimating individual k(e)(0) values and describing the drug-response curve. In this study, we introduce a new semiparametric approach calculating k(e)(0) values for isoflurane, sevoflurane, and desflurane by maximizing the prediction probability P(K). METHODS: Data from 45 patients scheduled for a radical prostatectomy were analyzed. After lumbar epidural catheterization, patients received remifentanil and propofol solely for induction of anesthesia. Thereafter, epidural analgesia was initiated, and isoflurane, sevoflurane, or desflurane (15 patients each) was added to maintain unconsciousness. At least 45 min later, end-tidal concentrations were varied between 0.5 and 2 minimum alveolar anesthetic concentration. We estimated an individual k(e)(0) value for each patient by optimizing the prediction probability P(K) (P(K)-based k(e)(0)) or by minimizing the area within the hysteresis loop (area-based k(e)(0)). Data are mean +/- sd. RESULTS: Both semiparametric approaches led to comparable k(e)(0) values with 0.18 +/- 0.06 min(-1) (P(K) based) and 0.15 +/- 0.04 min(-1) (area based) for isoflurane and 0.17 +/- 0.08 min(-1) (P(K) based) and 0.16 +/- 0.11 min(-1) (area based) for sevoflurane. k(e)(0) values for desflurane (P(K) based: 0.30 +/- 0.17min(-1); area based: 0.32 +/- 0.25 min(-1)) were significantly higher than for isoflurane and sevoflurane. CONCLUSION: Maximizing the prediction probability P(K) for estimating k(e)(0) seems to be a promising method that researchers could use on an exploratory basis

    Slow recovery from inactivation regulates the availability of voltage-dependent Na+ channels in hippocampal granule cells, hilar neurons and basket cells

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    Fundamental to the understanding of CNS function is the question of how individual neurons integrate multiple synaptic inputs into an output consisting of a sequence of action potentials carrying information coded as spike frequency. The availability for activation of neuronal Na+ channels is critical for this process and is regulated both by fast and slow inactivation processes. Here, we have investigated slow inactivation processes in detail in hippocampal neurons.Slow inactivation was induced by prolonged (10-300 s) step depolarisations to -10 mV at room temperature. In isolated hippocampal dentate granule cells (DGCs), recovery from this inactivation was biexponential, with time constants for the two phases of slow inactivation τslow,1 and τslow,2 ranging from 1 to 10 s and 20 to 50 s, respectively. Both τslow,1 and τslow,2 were related to the duration of prior depolarisation by a power law function of the form τ(t) =a (t/a)b, where t is the duration of the depolarisation, a is a constant kinetic setpoint and b is a scaling power. This analysis yielded values of a= 0.034 s and b= 0.62 for τslow,1 and a= 24 s and b= 0.30 for τslow,2 in the rat.When a train of action potential-like depolarisations of different frequencies (50, 100, 200 Hz) was used to induce inactivation, a similar relationship was found between the frequency of depolarisation and both τslow,1 and τslow,2 (a= 0.58 s, b= 0.39 for τslow,1 and a= 3.77 s and b= 0.42 for τslow,2).Using nucleated patches from rat hippocampal slices, we have addressed possible cell specific differences in slow inactivation. In fast-spiking basket cells a similar scaling relationship can be found (a= 3.54 s and b= 0.39) as in nucleated patches from DGCs (a= 2.3 s and b= 0.48) and non-fast-spiking hilar neurons (a= 2.57 s and b= 0.49).Likewise, comparison of human and rat granule cells showed that properties of ultra-slow recovery from inactivation are conserved across species. In both species ultra-slow recovery was biexponential with both τslow,1 and τslow,2 being related to the duration of depolarisation t, with a= 0.63 s and b= 0.44 for τslow,1 and a= 25 s and b= 0.37 for τslow,2 for the human subject.In summary, we describe in detail how the biophysical properties of Na+ channels result in a complex interrelationship between availability of sodium channels and membrane potential or action potential frequency that may contribute to temporal integration on a time scale of seconds to minutes in different types of hippocampal neurons

    Spectral entropy and bispectral index as measures of the electroencephalographic effects of propofol.

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    Contains fulltext : 50138.pdf (publisher's version ) (Closed access)Recently, Datex-Ohmeda introduced the Entropy Moduletrade mark for measuring depth of anesthesia. Based on the Shannon entropy of the electroencephalogram, state entropy (SE) and response entropy (RE) are computed. We investigated the dose-response relationship of SE and RE during propofol anesthesia in comparison with the Bispectral Indextrade mark (BIS). Twenty patients were studied without surgical stimulus. Anesthesia was induced by a constant propofol infusion of 2000 mg/h (451 +/- 77 microg x min(-1) x kg(-1)) via a large forearm vein. Propofol was infused until substantial burst suppression occurred (more than 50%) or mean arterial blood pressure decreased to <60 mm Hg. Hereafter, infusions were stopped until recovery of BIS values up to 60 was reached. Subsequently, the constant propofol infusion of 2000 mg/h was restarted to increase depth of anesthesia and again decreased (infusion was stopped) within the BIS value range of 40-60. The coefficient of determination (R2) and the prediction probability (P(K)) were calculated to evaluate the performance of SE, RE, and BIS to predict changing propofol effect-site concentrations. R2 values for SE, RE, and BIS of 0.88 +/- 0.08, 0.89 +/- 0.07, and 0.92 +/- 0.06, respectively, were similar. The calculated P(K) values, however, revealed a significant difference between SE and RE compared with BIS, with P(K) = 0.77 +/- 0.09, 0.76 +/- 0.10, and 0.84 +/- 0.06, respectively. BIS seems to show slight advantages in predicting propofol effect-site concentrations compared with SE and RE, as measured by P(K) but not as measured by R2

    Key characteristics impacting survival of COVID-19 extracorporeal membrane oxygenation

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    Background Severe COVID-19 induced acute respiratory distress syndrome (ARDS) often requires extracorporeal membrane oxygenation (ECMO). Recent German health insurance data revealed low ICU survival rates. Patient characteristics and experience of the ECMO center may determine intensive care unit (ICU) survival. The current study aimed to identify factors affecting ICU survival of COVID-19 ECMO patients. Methods 673 COVID-19 ARDS ECMO patients treated in 26 centers between January 1st 2020 and March 22nd 2021 were included. Data on clinical characteristics, adjunct therapies, complications, and outcome were documented. Block wise logistic regression analysis was applied to identify variables associated with ICU-survival. Results Most patients were between 50 and 70 years of age. PaO2_{2}/FiO2_{2} ratio prior to ECMO was 72 mmHg (IQR: 58–99). ICU survival was 31.4%. Survival was significantly lower during the 2nd wave of the COVID-19 pandemic. A subgroup of 284 (42%) patients fulfilling modified EOLIA criteria had a higher survival (38%) (p = 0.0014, OR 0.64 (CI 0.41–0.99)). Survival differed between low, intermediate, and high-volume centers with 20%, 30%, and 38%, respectively (p = 0.0024). Treatment in high volume centers resulted in an odds ratio of 0.55 (CI 0.28–1.02) compared to low volume centers. Additional factors associated with survival were younger age, shorter time between intubation and ECMO initiation, BMI > 35 (compared to < 25), absence of renal replacement therapy or major bleeding/thromboembolic events. Conclusions Structural and patient-related factors, including age, comorbidities and ECMO case volume, determined the survival of COVID-19 ECMO. These factors combined with a more liberal ECMO indication during the 2nd wave may explain the reasonably overall low survival rate. Careful selection of patients and treatment in high volume ECMO centers was associated with higher odds of ICU survival
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