The Effect of Lower Tidal Volume Ventilation Facilitated by Extracorporeal Carbon Dioxide Removal Compared With Conventional Lung Protective Ventilation on Cardiac Function.

OBJECTIVES: Lower tidal volume ventilation (targeting 3 mL/kg predicted body weight, PBW) facilitated by extracorporeal carbon dioxide removal (ECCO2R) has been investigated as a potential therapy for acute hypoxemic respiratory failure (AHRF) in the pRotective vEntilation with veno-venouS lung assisT in respiratory failure (REST) trial. We investigated the effect of this strategy on cardiac function, and in particular the right ventricle. DESIGN: Substudy of the REST trial. SETTING: Nine U.K. ICUs. PATIENTS: Patients with AHRF (Pao2/Fio2 < 150 mm Hg [20 kPa]). INTERVENTION: Transthoracic echocardiography and N-terminal pro-B-type natriuretic peptide (NT-proBNP) measurements were collected at baseline and postrandomization in patients randomized to ECCO2R or usual care. MEASUREMENTS: The primary outcome measures were a difference in tricuspid annular plane systolic excursion (TAPSE) on postrandomization echocardiogram and difference in NT-proBNP postrandomization. RESULTS: There were 21 patients included in the echocardiography cohort (ECCO2R, n = 13; usual care, n = 8). Patient characteristics were similar in both groups at baseline. Median (interquartile range) tidal volumes were lower in the ECCO2R group compared with the usual care group postrandomization; 3.6 (3.1-4.2) mL/kg PBW versus 5.2 (4.9-5.7) mL/kg PBW, respectively (p = 0.01). There was no difference in the primary outcome measure of mean (sd) TAPSE in the ECCO2R and usual care groups postrandomization; 21.3 (5.4) mm versus 20.1 (3.2) mm, respectively (p = 0.60). There were 75 patients included in the NT-proBNP cohort (ECCO2R, n = 36; usual care, n = 39). Patient characteristics were similar in both groups at baseline. Median (interquartile range [IQR]) tidal volumes were lower in the ECCO2R group than the usual care group postrandomization; 3.8 (3.3-4.2) mL/kg PBW versus 6.7 (5.8-8.1) mL/kg PBW, respectively (p < 0.0001). There was no difference in median (IQR) NT-proBNP postrandomization; 1121 (241-5370) pg/mL versus 1393 (723-4332) pg/mL in the ECCO2R and usual care groups, respectively (p = 0.30). CONCLUSIONS: In patients with AHRF, a reduction in tidal volume facilitated by ECCO2R, did not modify cardiac function.

Simvastatin in Critically Ill Patients with Covid-19.

BACKGROUND: The efficacy of simvastatin in critically ill patients with coronavirus disease 2019 (Covid-19) is unclear. METHODS: In an ongoing international, multifactorial, adaptive platform, randomized, controlled trial, we evaluated simvastatin (80 mg daily) as compared with no statin (control) in critically ill patients with Covid-19 who were not receiving statins at baseline. The primary outcome was respiratory and cardiovascular organ support-free days, assessed on an ordinal scale combining in-hospital death (assigned a value of -1) and days free of organ support through day 21 in survivors; the analyis used a Bayesian hierarchical ordinal model. The adaptive design included prespecified statistical stopping criteria for superiority (>99% posterior probability that the odds ratio was >1) and futility (>95% posterior probability that the odds ratio was <1.2). RESULTS: Enrollment began on October 28, 2020. On January 8, 2023, enrollment was closed on the basis of a low anticipated likelihood that prespecified stopping criteria would be met as Covid-19 cases decreased. The final analysis included 2684 critically ill patients. The median number of organ support-free days was 11 (interquartile range, -1 to 17) in the simvastatin group and 7 (interquartile range, -1 to 16) in the control group; the posterior median adjusted odds ratio was 1.15 (95% credible interval, 0.98 to 1.34) for simvastatin as compared with control, yielding a 95.9% posterior probability of superiority. At 90 days, the hazard ratio for survival was 1.12 (95% credible interval, 0.95 to 1.32), yielding a 91.9% posterior probability of superiority of simvastatin. The results of secondary analyses were consistent with those of the primary analysis. Serious adverse events, such as elevated levels of liver enzymes and creatine kinase, were reported more frequently with simvastatin than with control. CONCLUSIONS: Although recruitment was stopped because cases had decreased, among critically ill patients with Covid-19, simvastatin did not meet the prespecified criteria for superiority to control. (REMAP-CAP ClinicalTrials.gov number, NCT02735707.).

Intravenous Vitamin C for Patients Hospitalized With COVID-19: Two Harmonized Randomized Clinical Trials.

Importance: The efficacy of vitamin C for hospitalized patients with COVID-19 is uncertain. Objective: To determine whether vitamin C improves outcomes for patients with COVID-19. Design, Setting, and Participants: Two prospectively harmonized randomized clinical trials enrolled critically ill patients receiving organ support in intensive care units (90 sites) and patients who were not critically ill (40 sites) between July 23, 2020, and July 15, 2022, on 4 continents. Interventions: Patients were randomized to receive vitamin C administered intravenously or control (placebo or no vitamin C) every 6 hours for 96 hours (maximum of 16 doses). Main Outcomes and Measures: The primary outcome was a composite of organ support-free days defined as days alive and free of respiratory and cardiovascular organ support in the intensive care unit up to day 21 and survival to hospital discharge. Values ranged from -1 organ support-free days for patients experiencing in-hospital death to 22 organ support-free days for those who survived without needing organ support. The primary analysis used a bayesian cumulative logistic model. An odds ratio (OR) greater than 1 represented efficacy (improved survival, more organ support-free days, or both), an OR less than 1 represented harm, and an OR less than 1.2 represented futility. Results: Enrollment was terminated after statistical triggers for harm and futility were met. The trials had primary outcome data for 1568 critically ill patients (1037 in the vitamin C group and 531 in the control group; median age, 60 years [IQR, 50-70 years]; 35.9% were female) and 1022 patients who were not critically ill (456 in the vitamin C group and 566 in the control group; median age, 62 years [IQR, 51-72 years]; 39.6% were female). Among critically ill patients, the median number of organ support-free days was 7 (IQR, -1 to 17 days) for the vitamin C group vs 10 (IQR, -1 to 17 days) for the control group (adjusted proportional OR, 0.88 [95% credible interval {CrI}, 0.73 to 1.06]) and the posterior probabilities were 8.6% (efficacy), 91.4% (harm), and 99.9% (futility). Among patients who were not critically ill, the median number of organ support-free days was 22 (IQR, 18 to 22 days) for the vitamin C group vs 22 (IQR, 21 to 22 days) for the control group (adjusted proportional OR, 0.80 [95% CrI, 0.60 to 1.01]) and the posterior probabilities were 2.9% (efficacy), 97.1% (harm), and greater than 99.9% (futility). Among critically ill patients, survival to hospital discharge was 61.9% (642/1037) for the vitamin C group vs 64.6% (343/531) for the control group (adjusted OR, 0.92 [95% CrI, 0.73 to 1.17]) and the posterior probability was 24.0% for efficacy. Among patients who were not critically ill, survival to hospital discharge was 85.1% (388/456) for the vitamin C group vs 86.6% (490/566) for the control group (adjusted OR, 0.86 [95% CrI, 0.61 to 1.17]) and the posterior probability was 17.8% for efficacy. Conclusions and Relevance: In hospitalized patients with COVID-19, vitamin C had low probability of improving the primary composite outcome of organ support-free days and hospital survival. Trial Registration: ClinicalTrials.gov Identifiers: NCT04401150 (LOVIT-COVID) and NCT02735707 (REMAP-CAP).

Inflammatory phenotypes may be more important than age and comorbidities in predicting clinical outcomes in hospitalised patients with COVID-19.

Objectives: In critically ill patients with COVID-19, distinct hyperinflammatory and hypoinflammatory phenotypes have been described, with different outcomes and responses to therapy. We investigated if similar phenotypes exist in non-severe illness. Methods: Consecutive patients with polymerase chain reaction (PCR) confirmed SARS-CoV-2 were examined. Baseline demographics and laboratory investigations were tabulated, including serum C-reactive protein. Patients were divided into those who were hyperinflammatory (defined as C-reactive protein >17 mg/l) or hypoinflammatory. Adverse outcomes, defined as requiring oxygenation, intensive care, or death, were recorded during the hospital stay. Clinical characteristics and outcomes were compared. Results: Of the 1781 patients examined, 276 (15.5%) had a hyperinflammatory phenotype. They were older (51.8 ± 17.2 vs 40.3 ± 13.8 years, P <0.001), had a lower PCR cycle threshold (PCR cycle threshold value 19.3 ± 6.3 vs 22.7 ± 15.4, P = 0.025) at presentation, and more medical comorbidities. The hyperinflammatory phenotype was independently associated with adverse clinical outcomes, even after adjusting for age, medical history and viral load on multivariable analyses (adjusted odds ratio 5.78, 95% confidence interval 2.86-11.63). Conclusion: Even in non-severe COVID-19, there are distinct hyper- and hypoinflammatory phenotypes, with the hyperinflammatory phenotype strongly associated with adverse clinical outcomes, that could be distinguished with a simple biomarker.

Virtual patient with temporal evolution for mechanical ventilation trial studies: A stochastic model approach.

BACKGROUND AND OBJECTIVE: Healthcare datasets are plagued by issues of data scarcity and class imbalance. Clinically validated virtual patient (VP) models can provide accurate in-silico representations of real patients and thus a means for synthetic data generation in hospital critical care settings. This research presents a realistic, time-varying mechanically ventilated respiratory failure VP profile synthesised using a stochastic model. METHODS: A stochastic model was developed using respiratory elastance (Ers) data from two clinical cohorts and averaged over 30-minute time intervals. The stochastic model was used to generate future Ers data based on current Ers values with added normally distributed random noise. Self-validation of the VPs was performed via Monte Carlo simulation and retrospective Ers profile fitting. A stochastic VP cohort of temporal Ers evolution was synthesised and then compared to an independent retrospective patient cohort data in a virtual trial across several measured patient responses, where similarity of profiles validates the realism of stochastic model generated VP profiles. RESULTS: A total of 120,000 3-hour VPs for pressure control (PC) and volume control (VC) ventilation modes are generated using stochastic simulation. Optimisation of the stochastic simulation process yields an ideal noise percentage of 5-10% and simulation iteration of 200,000 iterations, allowing the simulation of a realistic and diverse set of Ers profiles. Results of self-validation show the retrospective Ers profiles were able to be recreated accurately with a mean squared error of only 0.099 [0.009-0.790]% for the PC cohort and 0.051 [0.030-0.126]% for the VC cohort. A virtual trial demonstrates the ability of the stochastic VP cohort to capture Ers trends within and beyond the retrospective patient cohort providing cohort-level validation. CONCLUSION: VPs capable of temporal evolution demonstrate feasibility for use in designing, developing, and optimising bedside MV guidance protocols through in-silico simulation and validation. Overall, the temporal VPs developed using stochastic simulation alleviate the need for lengthy, resource intensive, high cost clinical trials, while facilitating statistically robust virtual trials, ultimately leading to improved patient care and outcomes in mechanical ventilation.

Effect of Angiotensin-Converting Enzyme Inhibitor and Angiotensin Receptor Blocker Initiation on Organ Support-Free Days in Patients Hospitalized With COVID-19: A Randomized Clinical Trial.

IMPORTANCE: Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective: To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS: In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non-critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS: Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES: The primary outcome was organ support-free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS: On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support-free days among critically ill patients was 10 (-1 to 16) in the ACE inhibitor group (n = 231), 8 (-1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support-free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE: In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02735707.

Correction: Expanding the utility of the ROX index among patients with acute hypoxemic respiratory failure.

[This corrects the article DOI: 10.1371/journal.pone.0261234.].

Long-term (180-Day) Outcomes in Critically Ill Patients With COVID-19 in the REMAP-CAP Randomized Clinical Trial.

Importance: The longer-term effects of therapies for the treatment of critically ill patients with COVID-19 are unknown. Objective: To determine the effect of multiple interventions for critically ill adults with COVID-19 on longer-term outcomes. Design, Setting, and Participants: Prespecified secondary analysis of an ongoing adaptive platform trial (REMAP-CAP) testing interventions within multiple therapeutic domains in which 4869 critically ill adult patients with COVID-19 were enrolled between March 9, 2020, and June 22, 2021, from 197 sites in 14 countries. The final 180-day follow-up was completed on March 2, 2022. Interventions: Patients were randomized to receive 1 or more interventions within 6 treatment domains: immune modulators (n = 2274), convalescent plasma (n = 2011), antiplatelet therapy (n = 1557), anticoagulation (n = 1033), antivirals (n = 726), and corticosteroids (n = 401). Main Outcomes and Measures: The main outcome was survival through day 180, analyzed using a bayesian piecewise exponential model. A hazard ratio (HR) less than 1 represented improved survival (superiority), while an HR greater than 1 represented worsened survival (harm); futility was represented by a relative improvement less than 20% in outcome, shown by an HR greater than 0.83. Results: Among 4869 randomized patients (mean age, 59.3 years; 1537 [32.1%] women), 4107 (84.3%) had known vital status and 2590 (63.1%) were alive at day 180. IL-6 receptor antagonists had a greater than 99.9% probability of improving 6-month survival (adjusted HR, 0.74 [95% credible interval {CrI}, 0.61-0.90]) and antiplatelet agents had a 95% probability of improving 6-month survival (adjusted HR, 0.85 [95% CrI, 0.71-1.03]) compared with the control, while the probability of trial-defined statistical futility (HR >0.83) was high for therapeutic anticoagulation (99.9%; HR, 1.13 [95% CrI, 0.93-1.42]), convalescent plasma (99.2%; HR, 0.99 [95% CrI, 0.86-1.14]), and lopinavir-ritonavir (96.6%; HR, 1.06 [95% CrI, 0.82-1.38]) and the probabilities of harm from hydroxychloroquine (96.9%; HR, 1.51 [95% CrI, 0.98-2.29]) and the combination of lopinavir-ritonavir and hydroxychloroquine (96.8%; HR, 1.61 [95% CrI, 0.97-2.67]) were high. The corticosteroid domain was stopped early prior to reaching a predefined statistical trigger; there was a 57.1% to 61.6% probability of improving 6-month survival across varying hydrocortisone dosing strategies. Conclusions and Relevance: Among critically ill patients with COVID-19 randomized to receive 1 or more therapeutic interventions, treatment with an IL-6 receptor antagonist had a greater than 99.9% probability of improved 180-day mortality compared with patients randomized to the control, and treatment with an antiplatelet had a 95.0% probability of improved 180-day mortality compared with patients randomized to the control. Overall, when considered with previously reported short-term results, the findings indicate that initial in-hospital treatment effects were consistent for most therapies through 6 months.

Predicting mechanically ventilated patients future respiratory system elastance - A stochastic modelling approach.

BACKGROUND AND OBJECTIVE: Respiratory mechanics of mechanically ventilated patients evolve significantly with time, disease state and mechanical ventilation (MV) treatment. Existing deterministic data prediction methods fail to comprehensively describe the multiple sources of heterogeneity of biological systems. This research presents two respiratory mechanics stochastic models with increased prediction accuracy and range, offering improved clinical utility in MV treatment. METHODS: Two stochastic models (SM2 and SM3) were developed using retrospective patient respiratory elastance (Ers) from two clinical cohorts which were averaged over time intervals of 10 and 30 min respectively. A stochastic model from a previous study (SM1) was used to benchmark performance. The stochastic models were clinically validated on an independent retrospective clinical cohort of 14 patients. Differences in predictive ability were evaluated using the difference in percentile lines and cumulative distribution density (CDD) curves. RESULTS: Clinical validation shows all three models captured more than 98% (median) of future Ers data within the 5th - 95th percentile range. Comparisons of stochastic model percentile lines reported a maximum mean absolute percentage difference of 5.2%. The absolute differences of CDD curves were less than 0.25 in the ranges of 5 < Ers (cmH2O/L) < 85, suggesting similar predictive capabilities within this clinically relevant Ers range. CONCLUSION: The new stochastic models significantly improve prediction, clinical utility, and thus feasibility for synchronisation with clinical interventions. Paired with other MV protocols, the stochastic models developed can potentially form part of decision support systems, providing guided, personalised, and safe MV treatment.

Virtual patient framework for the testing of mechanical ventilation airway pressure and flow settings protocol.

BACKGROUND AND OBJECTIVE: Model-based and personalised decision support systems are emerging to guide mechanical ventilation (MV) treatment for respiratory failure patients. However, model-based treatments require resource-intensive clinical trials prior to implementation. This research presents a framework for generating virtual patients for testing model-based decision support, and direct use in MV treatment. METHODS: The virtual MV patient framework consists of 3 stages: 1) Virtual patient generation, 2) Patient-level validation, and 3) Virtual clinical trials. The virtual patients are generated from retrospective MV patient data using a clinically validated respiratory mechanics model whose respiratory parameters (respiratory elastance and resistance) capture patient-specific pulmonary conditions and responses to MV care over time. Patient-level validation compares the predicted responses from the virtual patient to their retrospective results for clinically implemented MV settings and changes to care. Patient-level validated virtual patients create a platform to conduct virtual trials, where the safety of closed-loop model-based protocols can be evaluated. RESULTS: This research creates and presents a virtual patient platform of 100 virtual patients generated from retrospective data. Patient-level validation reported median errors of 3.26% for volume-control and 6.80% for pressure-control ventilation mode. A virtual trial on a model-based protocol demonstrates the potential efficacy of using virtual patients for prospective evaluation and testing of the protocol. CONCLUSION: The virtual patient framework shows the potential to safely and rapidly design, develop, and optimise new model-based MV decision support systems and protocols using clinically validated models and computer simulation, which could ultimately improve patient care and outcomes in MV.

Pre- and apnoeic high-flow oxygenation for rapid sequence intubation in the emergency department (the Pre-AeRATE trial): A multicentre randomised controlled trial.

INTRODUCTION: Evidence regarding the efficacy of high-flow nasal cannula (HFNC) oxygenation for preoxygenation and apnoeic oxygenation is conflicting. Our objective is to evaluate whether HFNC oxygenation for preoxygenation and apnoeic oxygenation maintains higher oxygen saturation (SpO2) during rapid sequence intubation (RSI) in ED patients compared to usual care. METHODS: This was a multicentre, open-label, randomised controlled trial in adult ED patients requiring RSI. Patients were randomly assigned 1:1 to either intervention (HFNC oxygenation at 60L/min) group or control (non-rebreather mask for preoxygenation and nasal prongs of at least 15L/min oxygen flow for apnoeic oxygenation) group. Primary outcome was lowest SpO2 during the first intubation attempt. Secondary outcomes included incidence of SpO2 falling below 90% and safe apnoea time. RESULTS: One hundred and ninety patients were included, with 97 in the intervention and 93 in the control group. Median lowest SpO2 during the first intubation attempt was 100% in both groups. Incidence of SpO2 falling below 90% was lower in the intervention group (15.5%) compared to the control group (22.6%) (adjusted relative risk=0.68, 95% confidence interval [CI] 0.37-1.25). Post hoc quantile regression analysis showed that the first quartile of lowest SpO2 during the first intubation attempt was greater by 5.46% (95% CI 1.48-9.45%, P=0.007) in the intervention group. CONCLUSION: Use of HFNC for preoxygenation and apnoeic oxygenation, when compared to usual care, did not improve lowest SpO2 during the first intubation attempt but may prolong safe apnoea time.

Expanding the utility of the ROX index among patients with acute hypoxemic respiratory failure.

BACKGROUND: Delaying intubation in patients who fail high-flow nasal cannula (HFNC) may result in increased mortality. The ROX index has been validated to predict HFNC failure among pneumonia patients with acute hypoxemic respiratory failure (AHRF), but little information is available for non-pneumonia causes. In this study, we validate the ROX index among AHRF patients due to both pneumonia or non-pneumonia causes, focusing on early prediction. METHODS: This was a retrospective observational study in eight Singapore intensive care units from 1 January 2015 to 30 September 2017. All patients >18 years who were treated with HFNC for AHRF were eligible and recruited. Clinical parameters and arterial blood gas values at HFNC initiation and one hour were recorded. HFNC failure was defined as requiring intubation post-HFNC initiation. RESULTS: HFNC was used in 483 patients with 185 (38.3%) failing HFNC. Among pneumonia patients, the ROX index was most discriminatory in pneumonia patients one hour after HFNC initiation [AUC 0.71 (95% CI 0.64-0.79)], with a threshold value of <6.06 at one hour predicting HFNC failure (sensitivity 51%, specificity 80%, positive predictive value 61%, negative predictive value 73%). The discriminatory power remained moderate among pneumonia patients upon HFNC initiation [AUC 0.65 (95% CI 0.57-0.72)], non-pneumonia patients at HFNC initiation [AUC 0.62 (95% CI 0.55-0.69)] and one hour later [AUC 0.63 (95% CI 0.56-0.70)]. CONCLUSION: The ROX index demonstrated moderate discriminatory power among patients with either pneumonia or non-pneumonia-related AHRF at HFNC initiation and one hour later.

Effect of Antiplatelet Therapy on Survival and Organ Support-Free Days in Critically Ill Patients With COVID-19: A Randomized Clinical Trial.

Importance: The efficacy of antiplatelet therapy in critically ill patients with COVID-19 is uncertain. Objective: To determine whether antiplatelet therapy improves outcomes for critically ill adults with COVID-19. Design, Setting, and Participants: In an ongoing adaptive platform trial (REMAP-CAP) testing multiple interventions within multiple therapeutic domains, 1557 critically ill adult patients with COVID-19 were enrolled between October 30, 2020, and June 23, 2021, from 105 sites in 8 countries and followed up for 90 days (final follow-up date: July 26, 2021). Interventions: Patients were randomized to receive either open-label aspirin (n = 565), a P2Y12 inhibitor (n = 455), or no antiplatelet therapy (control; n = 529). Interventions were continued in the hospital for a maximum of 14 days and were in addition to anticoagulation thromboprophylaxis. Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of intensive care unit-based respiratory or cardiovascular organ support) within 21 days, ranging from -1 for any death in hospital (censored at 90 days) to 22 for survivors with no organ support. There were 13 secondary outcomes, including survival to discharge and major bleeding to 14 days. The primary analysis was a bayesian cumulative logistic model. An odds ratio (OR) greater than 1 represented improved survival, more organ support-free days, or both. Efficacy was defined as greater than 99% posterior probability of an OR greater than 1. Futility was defined as greater than 95% posterior probability of an OR less than 1.2 vs control. Intervention equivalence was defined as greater than 90% probability that the OR (compared with each other) was between 1/1.2 and 1.2 for 2 noncontrol interventions. Results: The aspirin and P2Y12 inhibitor groups met the predefined criteria for equivalence at an adaptive analysis and were statistically pooled for further analysis. Enrollment was discontinued after the prespecified criterion for futility was met for the pooled antiplatelet group compared with control. Among the 1557 critically ill patients randomized, 8 patients withdrew consent and 1549 completed the trial (median age, 57 years; 521 [33.6%] female). The median for organ support-free days was 7 (IQR, -1 to 16) in both the antiplatelet and control groups (median-adjusted OR, 1.02 [95% credible interval {CrI}, 0.86-1.23]; 95.7% posterior probability of futility). The proportions of patients surviving to hospital discharge were 71.5% (723/1011) and 67.9% (354/521) in the antiplatelet and control groups, respectively (median-adjusted OR, 1.27 [95% CrI, 0.99-1.62]; adjusted absolute difference, 5% [95% CrI, -0.2% to 9.5%]; 97% posterior probability of efficacy). Among survivors, the median for organ support-free days was 14 in both groups. Major bleeding occurred in 2.1% and 0.4% of patients in the antiplatelet and control groups (adjusted OR, 2.97 [95% CrI, 1.23-8.28]; adjusted absolute risk increase, 0.8% [95% CrI, 0.1%-2.7%]; 99.4% probability of harm). Conclusions and Relevance: Among critically ill patients with COVID-19, treatment with an antiplatelet agent, compared with no antiplatelet agent, had a low likelihood of providing improvement in the number of organ support-free days within 21 days. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707.

Therapeutic drug monitoring of meropenem and piperacillin-tazobactam in the Singapore critically ill population - A prospective, multi-center, observational study (BLAST 1).

PURPOSE: To determine percentage of patients with sub-therapeutic beta-lactam exposure in our intensive care units (ICU) and to correlate target attainment with clinical outcomes. MATERIALS AND METHODS: Multi-centre, prospective, observational study was conducted in ICUs from three hospitals in Singapore from July 2016 to May 2018. Adult patients (≥21 years) receiving meropenem or piperacillin-tazobactam were included. Four blood samples were obtained during a dosing interval to measure and determine attainment of therapeutic targets: unbound beta-lactam concentration above (i) minimum inhibitory concentration (MIC) at 40% (meropenem) or 50% (piperacillin) of dosing interval (40-50%fT > MIC) and (ii) 5 × MIC at 100% of dosing interval (100%fT > 5 × MIC). Correlation to clinical outcomes was evaluated using Cox regression. RESULTS: Beta-lactam levels were highly variable among 61 patients, with trough meropenem and piperacillin levels at 21.5 ± 16.8 mg/L and 101.6 ± 81.1 mg/L respectively. Among 85 sets of blood samples, current dosing practices were able to achieve 94% success for 40-50%fT > MIC and 44% for 100%fT > 5 × MIC. Failure to achieve 40-50%fT > MIC within 48 h was significantly associated with all-cause mortality (HR: 9.0, 95% CI: 1.8-45.0), after adjustment for APACHE II score. Achievement of 100%fT > 5 × MIC within 48 h was significantly associated with shorter length of hospital stay. CONCLUSION: Current dosing practices may be suboptimal for ICU patients. Beta-lactam TDM may be useful.

Quantification of respiratory effort magnitude in spontaneous breathing patients using Convolutional Autoencoders.

BACKGROUND: Spontaneous breathing (SB) effort during mechanical ventilation (MV) is an important metric of respiratory drive. However, SB effort varies due to a variety of factors, including evolving pathology and sedation levels. Therefore, assessment of SB efforts needs to be continuous and non-invasive. This is important to prevent both over- and under-assistance with MV. In this study, a machine learning model, Convolutional Autoencoder (CAE) is developed to quantify the magnitude of SB effort using only bedside MV airway pressure and flow waveform. METHOD: The CAE model was trained using 12,170,655 simulated SB flow and normal flow data (NB). The paired SB and NB flow data were simulated using a Gaussian Effort Model (GEM) with 5 basis functions. When the CAE model is given a SB flow input, it is capable of predicting a corresponding NB flow for the SB flow input. The magnitude of SB effort (SBEMag) is then quantified as the difference between the SB and NB flows. The CAE model was used to evaluate the SBEMag of 9 pressure control/ support datasets. Results were validated using a mean squared error (MSE) fitting between clinical and training SB flows. RESULTS: The CAE model was able to produce NB flows from the clinical SB flows with the median SBEMag of the 9 datasets being 25.39% [IQR: 21.87-25.57%]. The absolute error in SBEMag using MSE validation yields a median of 4.77% [IQR: 3.77-8.56%] amongst the cohort. This shows the ability of the GEM to capture the intrinsic details present in SB flow waveforms. Analysis also shows both intra-patient and inter-patient variability in SBEMag. CONCLUSION: A Convolutional Autoencoder model was developed with simulated SB and NB flow data and is capable of quantifying the magnitude of patient spontaneous breathing effort. This provides potential application for real-time monitoring of patient respiratory drive for better management of patient-ventilator interaction.

Protocol conception for safe selection of mechanical ventilation settings for respiratory failure Patients.

BACKGROUND AND OBJECTIVE: Mechanical ventilation is the primary form of care provided to respiratory failure patients. Limited guidelines and conflicting results from major clinical trials means selection of mechanical ventilation settings relies heavily on clinician experience and intuition. Determining optimal mechanical ventilation settings is therefore difficult, where non-optimal mechanical ventilation can be deleterious. To overcome these difficulties, this research proposes a model-based method to manage the wide range of possible mechanical ventilation settings, while also considering patient-specific conditions and responses. 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.

High-flow nasal cannula therapy: A multicentred survey of the practices among physicians and respiratory therapists in Singapore.

BACKGROUND: Use of high-flow nasal cannula (HFNC) has become a regular intervention in the intensive care units especially in patients coming in with hypoxaemic respiratory failure. Clinical practices may differ from published literature. OBJECTIVES: The objective of this study was to determine the clinical practices of physicians and respiratory therapists (RTs) on the use of HFNC. METHODS: A retrospective observational study looking at medical records on HFNC usage from January 2015 to September 2017 was performed and was followed by a series of questions related to HFNC practices. The survey involved physicians and RTs in intensive care units from multiple centres in Singapore from January to April 2018. Indications and thresholds for HFNC usage with titration and weaning practices were compared with the retrospective observational study data. RESULTS: One hundred twenty-three recipients (69.9%) responded to the survey and reported postextubation (87.8%), pneumonia in nonimmunocompromised (65.9%), and pneumonia in immunocompromised (61.8%) patients as the top three indications for HFNC. Of all, 39.8% of respondents wanted to use HFNC for palliative intent. Similar practices were observed in the retrospective study with the large cohort of 63% patients (483 of the total 768 patients) where HFNC was used for acute hypoxaemic respiratory failure and 274 (35.7%) patients to facilitate extubation. The survey suggested that respondents would initiate HFNC at a lower fraction of inspired oxygen (FiO2), higher partial pressure of oxygen to FiO2 ratio, and higher oxygen saturation to FiO2 ratio for nonpneumonia patients than patients with pneumonia. RTs were less likely to start HFNC for patients suffering from pneumonia and interstitial lung disease than physicians. RTs also preferred adjustment of FiO2 to improve oxygen saturations and noninvasive ventilation for rescue. CONCLUSIONS: Among the different intensive care units surveyed, the indications and thresholds for the initiation of HFNC differed in the clinical practices of physicians and RTs.