METHODS: In an open-label, randomized trial, we enrolled critically ill adults who had been undergoing ventilation for less than 12 hours in the ICU and were expected to continue to receive ventilatory support for longer than the next calendar day to receive dexmedetomidine as the sole or primary sedative or to receive usual care (propofol, midazolam, or other sedatives). The target range of sedation-scores on the Richmond Agitation and Sedation Scale (which is scored from -5 [unresponsive] to +4 [combative]) was -2 to +1 (lightly sedated to restless). The primary outcome was the rate of death from any cause at 90 days.
RESULTS: We enrolled 4000 patients at a median interval of 4.6 hours between eligibility and randomization. In a modified intention-to-treat analysis involving 3904 patients, the primary outcome event occurred in 566 of 1948 (29.1%) in the dexmedetomidine group and in 569 of 1956 (29.1%) in the usual-care group (adjusted risk difference, 0.0 percentage points; 95% confidence interval, -2.9 to 2.8). An ancillary finding was that to achieve the prescribed level of sedation, patients in the dexmedetomidine group received supplemental propofol (64% of patients), midazolam (3%), or both (7%) during the first 2 days after randomization; in the usual-care group, these drugs were administered as primary sedatives in 60%, 12%, and 20% of the patients, respectively. Bradycardia and hypotension were more common in the dexmedetomidine group.
CONCLUSIONS: Among patients undergoing mechanical ventilation in the ICU, those who received early dexmedetomidine for sedation had a rate of death at 90 days similar to that in the usual-care group and required supplemental sedatives to achieve the prescribed level of sedation. More adverse events were reported in the dexmedetomidine group than in the usual-care group. (Funded by the National Health and Medical Research Council of Australia and others; SPICE III ClinicalTrials.gov number, NCT01728558.).
DESIGN: Systematic review and meta-analysis of non-randomized trials.
PATIENTS: Databases of EMBASE, MEDLINE and CENTRAL were systematically searched from its inception until March 2021.
INTERVENTIONS: COVID-19 patients being positioned in the prone position either whilst awake or mechanically ventilated.
MEASUREMENTS: Primary outcomes were oxygenation parameters (PaO₂/FiO₂ ratio, PaCO₂, SpO₂). Secondary outcomes included the rate of intubation and mortality rate.
RESULTS: Thirty-five studies (n = 1712 patients) were included in this review. In comparison to the supine group, prone position significantly improved the PaO₂/FiO₂ ratio (study = 13, patients = 1002, Mean difference, MD 52.15, 95% CI 37.08 to 67.22; p
METHODS: This is a prospective observational study conducted among critically ill patients aged ≥18 years, intubated and mechanically ventilated within 48 h of ICU admission and stayed in the ICU for at least 72 h. Information on baseline characteristics and nutritional risk status (the modified Nutrition Risk in Critically ill [NUTRIC] score) was collected on day 1. Nutritional intake was recorded daily until death, discharge, or until the twelfth evaluable days. Mortality status was assessed on day 60 based on the patient's hospital record. Patients were divided into 3 groups a) received <2/3 of prescribed energy and protein (both <2/3), b) received ≥2/3 of prescribed energy and protein (both ≥2/3) and c) either energy or protein received were ≥2/3 of prescribed (either ≥2/3). The relationship between the three groups with 60-day mortality was examined by using logistic regression with adjustment for potential confounders. Sensitivity analysis was performed to examine the influence of ICU length of stay (≥7 days) and nutritional risk status.
RESULTS: Data were collected from 154 mechanically ventilated patients (age, 51.3 ± 15.7 years; body mass index, 26.5 ± 6.7 kg/m2; 54% male). The mean modified NUTRIC score was 5.7 ± 1.9, with 56% of the patients at high nutritional risk. The patients received 64.5 ± 21.6% of the amount of energy and 56.4 ± 20.6% of the amount of protein prescribed. Provision of energy and protein at ≥2/3 compared with <2/3 of the prescribed amounts was associated with a trend towards increased 60-day mortality (Adjusted odds ratio [Adj OR] 2.23; 95% confidence interval [CI], 0.92-5.38; p = 0.074). No difference in mortality status was found between energy and protein provision at either ≥2/3 compared with <2/3 of the prescribed amounts (Adj OR 1.61, 95% CI, 0.58-4.45; p = 0.357). Nutritional risk status, not ICU length of stay, influenced the relationship between nutritional adequacy and 60-day mortality.
CONCLUSIONS: Energy and protein adequacy of ≥2/3 of the prescribed amounts were associated with a trend towards increased 60-day mortality among mechanically ventilated critically ill patients. However, neither energy nor protein adequacy alone at ≥ or <2/3 adequacy affect 60-day mortality. Increased mortality was associated with provision of energy and protein at ≥2/3 of the prescribed amounts, which only affected patients with low nutritional risk.
METHODS: Data from 275 breaths aggregated from all mechanically ventilated patients at Christchurch Hospital were used in this study. The breath specific respiratory elastance is calculated using a time-varying elastance model. A pressure reconstruction method is proposed to reconstruct pressure waves identified as being affected by SB effort. The area under the curve of the time-varying respiratory elastance (AUC Edrs) are calculated and compared, where unreconstructed waves yield lower AUC Edrs. The difference between the reconstructed and unreconstructed pressure is denoted as a surrogate measure of SB effort.
RESULTS: The pressure reconstruction method yielded a median AUC Edrs of 19.21 [IQR: 16.30-22.47]cmH2Os/l. In contrast, the median AUC Edrs for unreconstructed M-wave data was 20.41 [IQR: 16.68-22.81]cmH2Os/l. The pressure reconstruction method had the least variability in AUC Edrs assessed by the robust coefficient of variation (RCV)=0.04 versus 0.05 for unreconstructed data. Each patient exhibited different levels of SB effort, independent from MV setting, indicating the need for non-invasive, real time assessment of SB effort.
CONCLUSION: A simple reconstruction method enables more consistent real-time estimation of the true, underlying respiratory system mechanics of a SB patient and provides the surrogate of SB effort, which may be clinically useful for clinicians in determining optimal ventilator settings to improve patient care.
DISCUSSION: This review presents the significant clinical aspects and variables of ventilation management, the potential risks associated with suboptimal ventilation management, and a review of the major recent attempts to improve ventilation in the context of these variables. The unique aspect of this review is a focus on these key elements relevant to engineering new approaches. In particular, the need for ventilation strategies which consider, and directly account for, the significant differences in patient condition, disease etiology, and progression within patients is demonstrated with the subsequent requirement for optimal ventilation strategies to titrate for patient- and time-specific conditions.
CONCLUSION: Engineered, protective lung strategies that can directly account for and manage inter- and intra-patient variability thus offer great potential to improve both individual care, as well as cohort clinical outcomes.
METHODS AND DESIGN: The CURE RCT compares two groups of patients requiring invasive MV with a partial pressure of arterial oxygen/fraction of inspired oxygen (PaO2/FiO2) ratio ≤ 200; one criterion of the Berlin consensus definition of moderate (≤ 200) or severe (≤ 100) ARDS. All patients are ventilated using pressure controlled (bi-level) ventilation with tidal volume = 6-8 ml/kg. Patients randomised to the control group will have PEEP selected per standard practice (SPV). Patients randomised to the intervention will have PEEP selected based on a minimal elastance using a model-based computerised method. The CURE RCT is a single-centre trial in the intensive care unit (ICU) of Christchurch hospital, New Zealand, with a target sample size of 320 patients over a maximum of 3 years. The primary outcome is the area under the curve (AUC) ratio of arterial blood oxygenation to the fraction of inspired oxygen over time. Secondary outcomes include length of time of MV, ventilator-free days (VFD) up to 28 days, ICU and hospital length of stay, AUC of oxygen saturation (SpO2)/FiO2 during MV, number of desaturation events (SpO2
METHODS: The model-based method uses a single-compartment lung model (SCM) to simulate the resultant tidal volume of patient pairs at a set ventilation setting. If both patients meet specified safe ventilation criteria under similar ventilation settings, the actual mechanical ventilator settings for Co-MV are determined via simulation using a double-compartment lung model (DCM). This method allows clinicians to analyse Co-MV in silico, before clinical implementation.
RESULTS: The proposed method demonstrates successful patient matching and MV setting in a model-based simulation as well as good discrimination to avoid mismatched patient pairs. The pairing process is based on model-based, patient-specific respiratory mechanics identified from measured data to provide useful information for guiding care. Specifically, the matching is performed via estimation of MV delivered tidal volume (mL/kg) based on patient-specific respiratory mechanics. This information can provide insights for the clinicians to evaluate the subsequent effects of Co-MV. In addition, it was also found that Co-MV patients with highly restrictive respiratory mechanics and obese patients must be performed with extra care.
CONCLUSION: This approach allows clinicians to analyse patient matching in a virtual environment without patient risk. The approach is tested in simulation, but the results justify the necessary clinical validation in human trials.
METHODS: This study shows the design and development of the "VENT" protocol, which integrates the single compartment linear lung model with clinical recommendations from landmark studies, to aid clinical decision-making in selecting mechanical ventilation settings. Using retrospective breath data from a cohort of 24 patients, 3,566 and 2,447 clinically implemented VC and PC settings were extracted respectively. Using this data, a VENT protocol application case study and clinical comparison is performed, and the prediction accuracy of the VENT protocol is validated against actual measured outcomes of pressure and volume.
RESULTS: The study shows the VENT protocols' potential use in narrowing an overwhelming number of possible mechanical ventilation setting combinations by up to 99.9%. The comparison with retrospective clinical data showed that only 33% and 45% of clinician settings were approved by the VENT protocol. The unapproved settings were mainly due to exceeding clinical recommended settings. When utilising the single compartment model in the VENT protocol for forecasting peak pressures and tidal volumes, median [IQR] prediction error values of 0.75 [0.31 - 1.83] cmH2O and 0.55 [0.19 - 1.20] mL/kg were obtained.
CONCLUSIONS: Comparing the proposed protocol with retrospective clinically implemented settings shows the protocol can prevent harmful mechanical ventilation setting combinations for which clinicians would be otherwise unaware. The VENT protocol warrants a more detailed clinical study to validate its potential usefulness in a clinical setting.