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Background Patients with COVID-19 present with a variety of clinical manifestations, ranging from mild or asymptomatic disease to severe illness and death. Whilst previous studies have clarified these and several other aspects of COVID-19, one of the ongoing challenges regarding COVID-19 is to determine which patients are at risk of adverse outcomes of COVID-19 infection. It is hypothesized that this is the result of insufficient inhibition of the immune response, with the vagus nerve being an important neuro-immuno-modulator of inflammation. Vagus nerve activity can be non-invasively indexed by heart-rate-variability (HRV). Therefore, we aimed to assess the prognostic value of HRV, as a surrogate marker for vagus nerve activity, in predicting mortality and intensive care unit (ICU) referral, in patients hospitalized with COVID-19. Methods A retrospective cohort study including all consecutive patients (n = 271) diagnosed and hospitalized with COVID-19 between March 2020 and May 2020, without a history of cardiac arrhythmias (including atrial and ventricular premature contractions), pacemaker, or current bradycardia (heart rate 110 bpm). HRV was based on one 10s ECG recorded at admission. 3-week survival and ICU referral were examined. Results HRV indexed as standard deviation of normal to normal heartbeat intervals (SDNN) predicted survival (H.R. = 0.53 95%CI: 0.31-0.92). This protective role was observed only in patients aged 70 years and older, not in younger patients. HRV below median value also predicted ICU referral within the first week of hospitalization (H.R = 0.51, 95%CI: 0.29-0.90, P = 0.021). Conclusion Higher HRV predicts greater chances of survival, especially in patients aged 70 years and older with COVID-19, independent of major prognostic factors. Low HRV predicts ICU indication and admission in the first week after hospitalization.

Purpose Insufficient antimicrobial exposure has been associated with worse clinical outcomes. Reportedly , flucloxacillin target attainment in critically ill patients was heterogeneous considering the study population selection and reported target attainment percentages. Therefore, we assessed flucloxacillin population pharmacokinetics (PK) and target attainment in critically ill patients. Methods This prospective, multicenter, observational study was conducted from May 2017 to October 2019 and included adult, critically ill patients administered flucloxacillin intravenously. Patients with renal replacement therapy or liver cirrhosis were excluded. We developed and qualified an integrated PK model for total and unbound serum flucloxacillin concentrations. Monte Carlo dosing simulations were performed to assess target attainment. The unbound target serum concentration was four times the minimum inhibitory concentration (MIC) for ≥ 50% of the dosing interval (ƒT >4xMIC  ≥ 50%). Results We analyzed 163 blood samples from 31 patients. A one-compartment model with linear plasma protein binding was selected as most appropriate. Dosing simulations revealed 26% ƒT >2 mg/L  ≥ 50% following continuous infusion of 12 g flucloxacillin and 51% ƒT >2 mg/L  ≥ 50% for 24 g. Conclusion Based on our dosing simulations, standard flucloxacillin daily doses of up to 12 g may substantially enhance the risk of underdosing in critically ill patients. Prospective validation of these model predictions is needed.

There is a lack of rapid, non-invasive tools that aid early prognostication in patients with return of spontaneous circulation (ROSC) after Out-of-Hospital Cardiac Arrest (OHCA). The shock index (SI) and modified shock index (MSI) have shown to be useful in several medical conditions, including myocardial infarction. In this study, we assessed the prognostic value of SI and MSI at Emergency Department (ED) triage on survival to discharge of OHCA patients. A single-center retrospective observational cohort study. All OHCA patients with a period of ROSC between 2014 and 2019 were included. Data collection was based on the Utstein criteria. The SI and MSI at ED triage were calculated by dividing heart rate by systolic blood pressure or mean arterial pressure. Survival rates were compared between patients with a high and low SI and MSI. Subsequent Cox regression analysis was performed. A total of 403 patients were included, of which 46% survived until hospital discharge. An elevated SI and MSI was defined by SI ≥ 1.00 and MSI ≥ 1.30. Survival to discharge, 30-day- and one-year survival were significantly lower in patients with an elevated SI and MSI (p < 0.001). An elevated SI and MSI was also associated with a higher rate of recurrent loss of circulation in the ED (p < 0.001). The 30-day survival hazard ratio was 2.24 (1.56–3.22) for SI and 2.46 (1.71–3.53) for MSI; the one-year survival hazard ratio was 2.20 (1.54–3.15) for SI and 2.38 (1.66–3.40) for MSI. Survival to discharge and 30-day survival are lower in OHCA patients with an elevated SI and MSI at ED triage. Further studies are warranted to elucidate the causational mechanisms underlying the association between elevated SI or MSI and worse outcomes.

Background To compare three computer-assisted quantitative electroencephalography (EEG) prediction models for the outcome prediction of comatose patients after cardiac arrest regarding predictive performance and robustness to artifacts. Methods A total of 871 continuous EEGs recorded up to 3 days after cardiac arrest in intensive care units of five teaching hospitals in the Netherlands were retrospectively analyzed. Outcome at 6 months was dichotomized as “good” (Cerebral Performance Category 1–2) or “poor” (Cerebral Performance Category 3–5). Three prediction models were implemented: a logistic regression model using two quantitative features, a random forest model with nine features, and a deep learning model based on a convolutional neural network. Data from two centers were used for training and fivefold cross-validation ( n  = 663), and data from three other centers were used for external validation ( n  = 208). Model output was the probability of good outcome. Predictive performances were evaluated by using receiver operating characteristic analysis and the calculation of predictive values. Robustness to artifacts was evaluated by using an artifact rejection algorithm, manually added noise, and randomly flattened channels in the EEG. Results The deep learning network showed the best overall predictive performance. On the external test set, poor outcome could be predicted by the deep learning network at 24 h with a sensitivity of 54% (95% confidence interval [CI] 44–64%) at a false positive rate (FPR) of 0% (95% CI 0–2%), significantly higher than the logistic regression (sensitivity 33%, FPR 0%) and random forest models (sensitivity 13%, FPR, 0%) ( p  < 0.05). Good outcome at 12 h could be predicted by the deep learning network with a sensitivity of 78% (95% CI 52–100%) at a FPR of 12% (95% CI 0–24%) and by the logistic regression model with a sensitivity of 83% (95% CI 83–83%) at a FPR of 3% (95% CI 3–3%), both significantly higher than the random forest model (sensitivity 1%, FPR 0%) ( p  < 0.05). The results of the deep learning network were the least affected by the presence of artifacts, added white noise, and flat EEG channels. Conclusions A deep learning model outperformed logistic regression and random forest models for reliable, robust, EEG-based outcome prediction of comatose patients after cardiac arrest.

A retrospective cohort study including all consecutive patients (n = 271) diagnosed and hospitalized with COVID-19 between March 2020 and May 2020, without a history of cardiac arrhythmias (including atrial and ventricular premature contractions), pacemaker, or current bradycardia (heart rate 110 bpm). HRV was based on one 10s ECG recorded at admission. 3-week survival and ICU referral were examined. HRV indexed as standard deviation of normal to normal heartbeat intervals (SDNN) predicted survival (H.R. = 0.53 95%CI: 0.31-0.92). This protective role was observed only in patients aged 70 years and older, not in younger patients. HRV below median value also predicted ICU referral within the first week of hospitalization (H.R = 0.51, 95%CI: 0.29-0.90, P = 0.021). Higher HRV predicts greater chances of survival, especially in patients aged 70 years and older with COVID-19, independent of major prognostic factors. Low HRV predicts ICU indication and admission in the first week after hospitalization.

Objective: To develop a reliable 2-compartment population pharmacokinetic (PK) model for unbound ceftriaxone in a critically ill population and determine an optimal dosing regimen.Materials and methods: This was a prospective, single-center, observational study of critically ill patients treated with ceftriaxone. Unbound serum ceftriaxone concentrations were measured using validated ultrafiltration and ultra-performance liquid chromatography-tandem mass spectrometry. PK analysis and dosing simulations were performed using an iterative 2-stage Bayesian fitting procedure and Monte Carlo simulations. The PK/pharmacodynamics (PD) target was attained when unbound serum ceftriaxone concentrations exceeded 4 times the minimum inhibitory concentration (MIC) for ≥ 60% of the dosing interval (ƒT>4xMIC ≥ 60%).Results: 91 patients were enrolled, and 173 unbound ceftriaxone concentrations were acquired. The population PK parameter estimates were hepatic clearance 5.2 ± 0.9 L/h/1.85m2, the unbound renal clearance of ceftriaxone divided by the creatinine clearance 0.61 ± 0.24, lean body mass corrected volume of distribution of the central compartment 0.82 ± 0.21 L/kg, and intercompartmental distribution rate constant from central to peripheral compartment 0.18 ± 0.08 h–1. Dosing simulations predicted ƒT>4 mg/L of 88% (95% CI: 69 – 100%) for 2,000 mg ceftriaxone once daily and ƒT>4 mg/L of 100% (95% CI: 100 – 100%) both for 1,000 mg twice daily and continuous infusion of 2,000 mg daily.Conclusion: We developed a reliable population PK model for unbound ceftriaxone in a critically ill population. Dosing simulations revealed ƒT>4 mg/L ≥ 60% for 1,000 mg twice daily and 2,000 mg once daily or by continuous infusion.

Today's antiretroviral combination regimens can induce significant and sustained decreases in human immunodeficiency virus (HIV)-RNA levels, allowing the immune system to recover. To what extent immune reconstitution is possible and what factors determine the outcome have thus far not been resolved. We studied 19 subjects, treated for 2 years with protease inhibitor-containing triple therapy, who had a strong suppression of HIV-RNA levels. CD4+ T-cell numbers increased from medians of 170 to 420 × 106 cells/L, but in a number of subjects T-cell numbers did not further increase after week 72, without having reached normal values. Long-term CD4+ T-cell change was mainly caused by a slow but continuous increase in naive CD4+ T cells (CD45RA+CD62L+) and was predicted by the baseline number of these cells. Our data indicate that long-term immunological recovery is gradual, even during strong suppression of viral replication, not always complete, and dependent on the preexisting level of naive CD4+ T cells.

Objective Compare duration of mechanical ventilation (MV), weaning time, ICU-LOS (ICU-LOS), efficacy and safety of remifentanil-based regimen with conventional sedation and analgesia. Design Centre randomised, open-label, crossover, ‘real-life’ study. Setting 15 Dutch hospitals. Patients Adult medical and post-surgical ICU patients with anticipated short-term (2–3 days) MV. Interventions Patient cohorts were randomised to remifentanil-based regimen ( n  = 96) with propofol as required, for a maximum of 10 days, or to conventional regimens ( n  = 109) of propofol, midazolam or lorazepam combined with fentanyl or morphine. Measurements and main results Outcomes were weaning time, duration of MV, ICU-LOS, sedation- and analgesia levels, intensivist/ICU nurse satisfaction, adverse events, mean arterial pressure, heart rate. Median duration of ventilation (MV) was 5.1 days with conventional treatment versus 3.9 days with remifentanil (NS). The remifentanil-based regimen reduced median weaning time by 18.9 h ( P  = 0.0001). Median ICU-LOS was 7.9 days versus 5.9 days, respectively (NS). However, the treatment effects on duration of MV and ICU stay were time-dependent: patients were almost twice as likely to be extubated ( P  = 0.018) and discharged from the ICU ( P  = 0.05) on day 1–3. Propofol doses were reduced by 20% ( P  = 0.05). Remifentanil also improved sedation-agitation scores ( P  < 0.0001) and intensivist/ICU nurse satisfaction ( P  < 0.0001). All other outcomes were comparable. Conclusions In patients with an expected short-term duration of MV, remifentanil significantly improves sedation and agitation levels and reduces weaning time. This contributes to a shorter duration of MV and ICU-LOS.

Low-molecular-weight heparins are frequently used to prevent venous thromboembolism. Vasopressor therapy may be associated with inadequate anti-factor Xa activity, thereby increasing the risk of venous thromboembolism. We aimed to assess the association between anti-factor Xa activity and norepinephrine dose in intensive care unit (ICU) patients treated with subcutaneous dalteparin for venous thromboembolism prophylaxis. This was a prospective observational pilot study in adult ICU patients treated with dalteparin 5,000 IU subcutaneously once daily and norepinephrine > 0.25 µg/kg/min. Peak anti-factor Xa activity was monitored and dalteparin doses were adjusted following a predefined dose algorithm. From November 2016 to April 2018, 32 patients were included. No correlation was found between norepinephrine dose and anti-factor Xa activity (r = -0.01, 95% confidence interval = -0.47 - 0.27, p = 0.57). Furthermore, following dalteparin 5,000 IU once daily, 28% of the patients showed anti-factor Xa activity < 0.10 IU/mL. Higher body mass index (BMI) (p < 0.001) but not patients' norepinephrine dose, age, or serum creatinine were risk factors for anti-factor Xa activity < 0.10 IU/mL. Dose increments to 7,500 IU once daily resulted in anti-factor Xa activity ≥ 0.10 IU/mL in all 5 patients (p = 0.043). In this cohort of ICU patients, no association was found between norepinephrine dose and anti-factor Xa activity following subcutaneous dalteparin 5,000-IU administration once daily. Furthermore, nearly one-third of the patients showed anti-factor Xa activity below the target concentration for venous thromboembolism prophylaxis. Higher BMI was an independent risk factor for reduced anti-Xa activity.