METHODS: A stochastic model of Ers is integrated into the VENT protocol from previous works to develop the SiVENT protocol, to account for both intra- and inter-patient variability. A cohort of 20 virtual MV patients based on retrospective patient data are used to validate the performance of this method for volume-controlled (VC) ventilation. A performance evaluation was conducted where the SiVENT and VENT protocols were implemented in 1080 instances each to compare the two protocols and evaluate the difference in reduction of possible MV settings achieved by each.
RESULTS: From an initial number of 189,000 possible MV setting combinations, the VENT protocol reduced this number to a median of 10,612, achieving a reduction of 94.4% across the cohort. With the integration of the stochastic model component, the SiVENT protocol reduced this number from 189,000 to a median of 9329, achieving a reduction of 95.1% across the cohort. The SiVENT protocol reduces the number of possible combinations provided to the user by more than 1000 combinations as compared to the VENT protocol.
CONCLUSIONS: Adding a stochastic model component into a model-based approach to selecting MV settings improves the ability of a decision support system to recommend patient-specific MV settings. It specifically considers inter- and intra-patient variability in respiratory elastance and eliminates potentially harmful settings based on clinically recommended pressure thresholds. Clinical input and local protocols can further reduce the number of safe setting combinations. The results for the SiVENT protocol justify further investigation of its prediction accuracy and clinical validation trials.
METHODS: Retrospective data from 210 patients were obtained from a general hospital in Malaysia from May 2014 until June 2015, where 123 patients were having comorbid diabetes mellitus. The comparison of blood glucose control protocol performance between both protocol simulations was conducted through blood glucose fitted with physiological modelling on top of virtual trial simulations, mean calculation of simulation error and several graphical comparisons using stochastic modelling.
RESULTS: Stochastic Targeted Blood Glucose Control Protocol reduces hyperglycaemia by 16% in diabetic and 9% in nondiabetic cohorts. The protocol helps to control blood glucose level in the targeted range of 4.0-10.0 mmol/L for 71.8% in diabetic and 82.7% in nondiabetic cohorts, besides minimising the treatment hour up to 71 h for 123 diabetic patients and 39 h for 87 nondiabetic patients.
CONCLUSION: It is concluded that Stochastic Targeted Blood Glucose Control Protocol is good in reducing hyperglycaemia as compared to the current blood glucose management protocol in the Malaysian intensive care unit. Hence, the current Malaysian intensive care unit protocols need to be modified to enhance their performance, especially in the integration of insulin and nutrition intervention in decreasing the hyperglycaemia incidences. Improvement in Stochastic Targeted Blood Glucose Control Protocol in terms of uen model is also a must to adapt with the diabetic cohort.
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.
METHODS: This was a two-centre randomised controlled trial of CI versus IB dosing of beta-lactam antibiotics, which enrolled critically ill participants with severe sepsis who were not on renal replacement therapy (RRT). The primary outcome was clinical cure at 14 days after antibiotic cessation. Secondary outcomes were PK/PD target attainment, ICU-free days and ventilator-free days at day 28 post-randomisation, 14- and 30-day survival, and time to white cell count normalisation.
RESULTS: A total of 140 participants were enrolled with 70 participants each allocated to CI and IB dosing. CI participants had higher clinical cure rates (56 versus 34 %, p = 0.011) and higher median ventilator-free days (22 versus 14 days, p MIC than the IB arm on day 1 (97 versus 70 %, p
Objectives: A cross-sectional survey was carried out and sent to a total of 868 specialists working primarily in the ICU. The aim of this study was to explore knowledge, perception, and the antibiotic prescribing practice among specialists and advanced trainees in Malaysian ICU.
Materials and Methods: A cross-sectional survey was used, consisted of three sections: knowledge, perception, and antibiotic prescribing practice in ICU. Three case vignettes on hospital-acquired pneumonia (HAP), infected necrotizing pancreatitis (INP), and catheter-related bloodstream infection (CRBSI) were used to explore antibiotic prescribing practice.
Results: A total of 868 eligible subjects were approached with 104 responded to the survey. Three hundred eighty-nine antibiotics were chosen from seven different classes in the case vignettes. All respondents acknowledged the importance of pharmacokinetic/pharmacodynamic (PK/PD) in antibiotic optimization and majority (97.2%) perceived that current dosing is inadequate to achieve optimal PK/PD target in ICU patients. Majority (85.6%) believed that antibiotic dose should be streamlined to the organisms' minimum inhibitory concentration (MIC). In terms of knowledge, only 64.4% provided the correct correlations between antibiotics and their respective PK/PD targets. Compliance rates in terms of antibiotic choices were at 79.8%, 77.8%, and 27.9% for HAI, INP, and CRBSI, respectively.
Conclusion: Malaysian physicians are receptive to use PK/PD approach to optimize antibiotic dosing in ICU patients. Nonetheless, there are still gaps in the knowledge of antibiotic PK/PD as well as its application in the critically ill, especially for β-lactams.
Patients and Methods: STAR proposes 1-3 hours treatment based on individual insulin sensitivity variation and history of blood glucose, insulin, and nutrition. A total of 136 patients recorded data from STAR pilot trial in Malaysia (2017-quarter of 2019*) were used in the study to identify the gap between chosen administered insulin and nutrition intervention as recommended by STAR, and the real intervention performed.
Results: The results show the percentage of insulin compliance increased from 2017 to first quarter of 2019* and fluctuated in feed administrations. Overall compliance amounted to 98.8% and 97.7% for administered insulin and feed, respectively. There was higher average of 17 blood glucose measurements per day than in other centres that have been using STAR, but longer intervals were selected when recommended. Control safety and performance were similar for all periods showing no obvious correlation to compliance.
Conclusion: The results indicate that STAR, an automated model-based protocol is positively accepted among the Malaysian ICU clinicians to automate glycemic control and the usage can be extended to other hospitals already. Performance could be improved with several propositions.
DESIGN: This was a single-center prospective observational study that compared resting energy expenditure estimated by 15 commonly used predictive equations against resting energy expenditure measured by indirect calorimetry at different phases. Degree of agreement between resting energy expenditure calculated by predictive equations and resting energy expenditure measured by indirect calorimetry was analyzed using intraclass correlation coefficient and Bland-Altman analyses. Resting energy expenditure values calculated from predictive equations differing by ± 10% from resting energy expenditure measured by indirect calorimetry was used to assess accuracy. A score ranking method was developed to determine the best predictive equations.
SETTING: General Intensive Care Unit, University of Malaya Medical Centre.
PATIENTS: Mechanically ventilated critically ill patients.
INTERVENTIONS: None.
MEASUREMENTS AND MAIN RESULTS: Indirect calorimetry was measured thrice during acute, late, and chronic phases among 305, 180, and 91 ICU patients, respectively. There were significant differences (F= 3.447; p = 0.034) in mean resting energy expenditure measured by indirect calorimetry among the three phases. Pairwise comparison showed mean resting energy expenditure measured by indirect calorimetry in late phase (1,878 ± 517 kcal) was significantly higher than during acute phase (1,765 ± 456 kcal) (p = 0.037). The predictive equations with the best agreement and accuracy for acute phase was Swinamer (1990), for late phase was Brandi (1999) and Swinamer (1990), and for chronic phase was Swinamer (1990). None of the resting energy expenditure calculated from predictive equations showed very good agreement or accuracy.
CONCLUSIONS: Predictive equations tend to either over- or underestimate resting energy expenditure at different phases. Predictive equations with "dynamic" variables and respiratory data had better agreement with resting energy expenditure measured by indirect calorimetry compared with predictive equations developed for healthy adults or predictive equations based on "static" variables. Although none of the resting energy expenditure calculated from predictive equations had very good agreement, Swinamer (1990) appears to provide relatively good agreement across three phases and could be used to predict resting energy expenditure when indirect calorimetry is not available.
METHODS: Using indirect calorimetry, REE was measured at acute (≤5 days; n = 294) and late (≥6 days; n = 180) phases of intensive care unit admission. PEs were developed by multiple linear regression. A multi-fold cross-validation approach was used to validate the PEs. The best PEs were selected based on the highest coefficient of determination (R2), the lowest root mean square error (RMSE) and the lowest standard error of estimate (SEE). Two PEs developed from paired 168-patient data were compared with measured REE using mean absolute percentage difference.
RESULTS: Mean absolute percentage difference between predicted and measured REE was <20%, which is not clinically significant. Thus, a single PE was developed and validated from data of the larger sample size measured in the acute phase. The best PE for REE (kcal/day) was 891.6(Height) + 9.0(Weight) + 39.7(Minute Ventilation)-5.6(Age) - 354, with R2 = 0.442, RMSE = 348.3, SEE = 325.6 and mean absolute percentage difference with measured REE was: 15.1 ± 14.2% [acute], 15.0 ± 13.1% [late].
CONCLUSIONS: Separate PEs for acute and late phases may not be necessary. Thus, we have developed and validated a PE from acute phase data and demonstrated that it can provide optimal estimates of REE for patients in both acute and late phases.
TRIAL REGISTRATION: ClinicalTrials.gov NCT03319329.
METHODS: The Asia-Pacific and Middle East Working Group on Nutrition in the ICU has identified major areas of uncertainty in clinical practice for healthcare professionals providing nutrition therapy in Asia-Pacific and the Middle East and developed a series of consensus statements to guide nutrition therapy in the ICU in these regions.
RESULTS: Accordingly, consensus statements have been provided on nutrition risk assessment and parenteral and enteral feeding strategies in the ICU, monitoring adequacy of, and tolerance to, nutrition in the ICU and institutional processes for nutrition therapy in the ICU. Furthermore, the Working Group has noted areas requiring additional research, including the most appropriate use of hypocaloric feeding in the ICU.
CONCLUSIONS: The objective of the Working Group in formulating these statements is to guide healthcare professionals in practicing appropriate clinical nutrition in the ICU, with a focus on improving quality of care, which will translate into improved patient outcomes.
DESIGN SETTING AND PARTICIPANTS: This international, multicentre, observational pharmacokinetic study will comprise adult critically ill patients prescribed antifungal agents including fluconazole, voriconazole, posaconazole, isavuconazole, caspofungin, micafungin, anidulafungin, and amphotericin B for the treatment or prophylaxis of invasive fungal disease. A minimum of 12 patients are targeted for enrolment for each antifungal agent, across 12 countries and 30 intensive care units to perform descriptive pharmacokinetics. Pharmacokinetic sampling will occur during two dosing intervals (occasions): firstly, between days 1 and 3, and secondly, between days 4 and 7 of the antifungal course, collecting three samples per occasion. Patients' demographic and clinical data will be collected.
MAIN OUTCOME MEASURES: The primary endpoint of the study is attainment of pharmacokinetic/pharmacodynamic target exposures that are associated with optimal efficacy. Thirty-day mortality will also be measured.
RESULTS AND CONCLUSIONS: This study will describe whether contemporary antifungal drug dosing achieves drug exposures associated with optimal outcomes. Data will also be used for the development of antifungal dosing algorithms for critically ill patients. Optimised drug dosing should be considered a priority for improving clinical outcomes for critically ill patients with fungal infections.
DESIGN: Cross-sectional observational study.
SETTING: Twenty-three Asian countries and regions, covering 92.1% of the continent's population.
PARTICIPANTS: Ten low-income and lower-middle-income economies, five upper-middle-income economies, and eight high-income economies according to the World Bank classification.
INTERVENTIONS: Data closest to 2017 on critical care beds, including ICU and intermediate care unit beds, were obtained through multiple means, including government sources, national critical care societies, colleges, or registries, personal contacts, and extrapolation of data.
MEASUREMENTS AND MAIN RESULTS: Cumulatively, there were 3.6 critical care beds per 100,000 population. The median number of critical care beds per 100,000 population per country and region was significantly lower in low- and lower-middle-income economies (2.3; interquartile range, 1.4-2.7) than in upper-middle-income economies (4.6; interquartile range, 3.5-15.9) and high-income economies (12.3; interquartile range, 8.1-20.8) (p = 0.001), with a large variation even across countries and regions of the same World Bank income classification. This number was independently predicted by the World Bank income classification on multivariable analysis, and significantly correlated with the number of acute hospital beds per 100,000 population (r = 0.19; p = 0.047), the universal health coverage service coverage index (r = 0.35; p = 0.003), and the Human Development Index (r = 0.40; p = 0.001) on univariable analysis.
CONCLUSIONS: Critical care bed capacity varies widely across Asia and is significantly lower in low- and lower-middle-income than in upper-middle-income and high-income countries and regions.
MAIN BODY: Although the first Asian intensive care units (ICUs) surfaced in the 1960s and the 1970s and specialisation started in the 1990s, multiple challenges still exist, including the lack of intensivists, critical care nurses, and respiratory therapists in many countries. This is aggravated by the brain drain of skilled ICU staff to high-income countries. Critical care societies have been integral to the development of the discipline and have increasingly contributed to critical care education, although critical care research is only just starting to take off through collaboration across groups. Sepsis, increasingly aggravated by multidrug resistance, contributes to a significant burden of critical illness, while epidemics and pandemics continue to haunt the continent intermittently. In particular, the coronavirus disease 2019 (COVID-19) has highlighted the central role of critical care in pandemic response. Accessibility to critical care is affected by lack of ICU beds and high costs, and quality of critical care is affected by limited capability for investigations and treatment in low- and middle-income countries. Meanwhile, there are clear cultural differences across countries, with considerable variations in end-of-life care. Demand for critical care will rise across the continent due to ageing populations and rising comorbidity burdens. Even as countries respond by increasing critical care capacity, the critical care community must continue to focus on training for ICU healthcare workers, processes anchored on evidence-based medicine, technology guided by feasibility and impact, research applicable to Asian and local settings, and rallying of governments for support for the specialty.
CONCLUSIONS: Critical care in Asia has progressed through the years, but multiple challenges remain. These challenges should be addressed through a collaborative approach across disciplines, ICUs, hospitals, societies, governments, and countries.
OBJECTIVE: The objective of this study was to summarise the protocol and statistical analysis plan for the Mega-ROX Brains trial.
DESIGN SETTING AND PARTICIPANTS: Mega-ROX Brains is an international randomised clinical trial, which will be conducted within an overarching 40,000-participant, registry-embedded clinical trial comparing conservative and liberal ICU oxygen therapy regimens. We expect to enrol between 7500 and 9500 participants with nonhypoxic ischaemic encephalopathy acute brain injuries and conditions who are receiving unplanned invasive mechanical ventilation in the ICU.
MAIN OUTCOME MEASURES: The primary outcome is in-hospital all-cause mortality up to 90 d from the date of randomisation. Secondary outcomes include duration of survival, duration of mechanical ventilation, ICU length of stay, hospital length of stay, and the proportion of participants discharged home.
RESULTS AND CONCLUSIONS: Mega-ROX Brains will compare the effect of conservative vs. liberal oxygen therapy regimens on 90-day in-hospital mortality in adults in the ICU with acute brain injuries and conditions. The protocol and planned analyses are reported here to mitigate analysis bias.
TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry (ACTRN 12620000391976).