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Athirah Abdul Razak,1 Asma Abu-Samah,2 Normy Norfiza Abdul Razak,1 Ummu Jamaludin,3 Fatanah Suhaimi,4 Azrina Ralib,5 Mohd Basri Mat Nor,6 Christopher Pretty,7 Jennifer Laura Knopp,7 James Geoffrey Chase7 1College of Engineering, Universiti Tenaga Nasional, Kajang, Malaysia; 2Department of Electrical, Electronics and Systems, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi, Malaysia; 3Department of Mechanical Engineering, Universiti Malaysia Pahang, Kuantan, Malaysia; 4Advanced Medical and Dental Institute, Universiti Sains Malaysia, Pulau Pinang, Malaysia; 5Department of Anesthesiology, International Islamic University Malaysia, Kuantan, Malaysia; 6Intensive Care Unit, International Islamic University Medical Centre, Kuantan, Malaysia; 7Department of Mechanical Engineering, University of Canterbury, Christchurch, New ZealandCorrespondence: Normy Norfiza Abdul Razak; Athirah Abdul Razak Email Normy@uniten.edu.my; athirahrazak@gmail.comPurpose: This paper presents an assessment of an automated and personalized stochastic targeted (STAR) glycemic control protocol compliance in Malaysian intensive care unit (ICU) patients to ensure an optimized usage.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.Keywords: compliance, glycemic control, diabetes, stochastic targeted prediction, model-based control

Asma Abu-Samah,1 Jennifer Launa Knopp,2 Normy Norfiza Abdul Razak,3 Athirah Abdul Razak,3 Ummu Kulthum Jamaludin,3 Fatanah Mohamad Suhaimi,4 Azrina Md Ralib,5 Mohd Basri Mat Nor,6 James Geoffrey Chase,2 Christopher Grant Pretty21Institute of Energy Infrastructure, Universiti Tenaga Nasional, Kajang, 43000, Malaysia; 2Department of Mechanical Engineering, University of Canterbury, Christchurch, 8041, New Zealand; 3College of Engineering, Universiti Tenaga Nasional, Kajang, 43000, Malaysia; 4Faculty of Mechanical Engineering, Universiti Malaysia Pahang, Pekan, 26600, Malaysia; 5Advanced Medical and Dental Institute, Universiti Sains Islam Malaysia, Kepala Batas, 13200, Malaysia; 6Kulliyah of Medicine, International Islamic University Malaysia, Kuantan, 25200, MalaysiaBackground: Stress-induced hyperglycemia is common in critically ill patients. A few forms of model-based glycemic control have been introduced to reduce this phenomena and among them is the automated STAR protocol which has been used in the Christchurch and Gyulá hospitals’ intensive care units (ICUs) since 2010.Methods: This article presents the pilot trial assessment of STAR protocol which has been implemented in the International Islamic University Malaysia Medical Centre (IIUMMC) Hospital ICU since December 2017. One hundred and forty-two patients who received STAR treatment for more than 20 hours were used in the assessment. The initial results are presented to discuss the ability to adopt and adapt the model-based control framework in a Malaysian environment by analyzing its performance and safety.Results: Overall, 60.7% of blood glucose measurements were in the target band. Only 0.78% and 0.02% of cohort measurements were below 4.0 mmol/L and 2.2 mmol/L (the limitsfor mild and severe hypoglycemia, respectively). Treatment preference-wise, the clinical staff were favorable of longer intervention options when available. However, 1 hourly treatments were still used in 73.7% of cases.Conclusion: The protocol succeeded in achieving patient-specific glycemic control while maintaining safety and was trusted by nurses to reduce workload. Its lower performance results, however, give the indication for modification in some of the control settings to better fit the Malaysian environment.Keywords: glycemic control, intensive care unit, model-based control, pilot trial, Malaysian hospital

INTRODUCTION: Psychological burden of frontliners increased during the COVID-19 pandemic, leading to psychiatric illnesses reducing productivity. Assessing their mental health status is vital in providing effective care. Our aim was to investigate the levels of depression, anxiety, stress, and associated factors among frontlines of International Islamic University Malaysia (IIUM), Sultan Ahmad Shah Medical Centre (SASMEC) and Kuantan-Campus during the recent COVID-19 pandemic. MATERIALS AND METHODS: Cross-sectional study among 261 SASMEC@IIUM and 125 Kuantan-campus IIUM frontliners from March 2021 to June 2022 using self-administered validated DASS-21 questionnaire. Descriptive statistics, Chi-Square and Fisher's Exact tests were used for data analysis. Frontliners with severe and very severe DASS scores were offered psychoeducational counselling for intervention. RESULTS: Out of 386 respondents, 82.1% were clinical frontliners, 65.8% were female, and 65.8% were married. The prevalence was 15.8%, 29.5% and 9.3% for depression, anxiety and stress, respectively. This study showed no statistical differences between the clinical and non-clinical, and between SASMEC@IIUM and Kuantan-campus frontliners on depression, anxiety and stress levels. Those with post-traumatic events had significant association with depression (p<0.001) and anxiety (p<0.001), while anxiety significantly associated with chronic diseases (p=0.034). CONCLUSION: Over one-fourth of frontline staff suffered from anxiety during the COVID-19 pandemic, whereas 9-15% experienced depression and stress. Frontliners with post-traumatic events or chronic diseases required additional support in coping with their mental health burden. No significant difference was found in anxiety, depression and stress levels between clinical and non-clinical or between hospitalbased and on-campus frontliners, suggesting a comprehensive mental health screening and timely intervention to all frontliners regardless of their post or area of service. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Accurate assessment of glomerular filtration rate (GFR) is important in the critically ill. Kinetic estimate of GFR (keGFR) considers the changes of creatinine, creatinine production rate, and volume of distribution hence postulated to be a more accurate estimate of GFR, where there are rapidly changing kidney functions. We evaluated the association of the estimated GFR by established equations and keGFR with creatinine clearance (CrCl) measurement. MATERIALS AND METHODS: This is a prospective observational study of critically ill patients. Inclusion criteria were patients older than 18 years old with sepsis (clinical infection and increase in SOFA score>2), and plasma procalcitonin>0.5ng/ml. Plasma creatinine and Cystatin C (CysC) were measured on admission and 4 hours later, and the eGFR was calculated by the Cockcroft Gault (CG), MDRD, CKD-EPI, and keGFR equations, and compared to the CrCl measurement. RESULTS: A total of 70 patients were recruited. eGFR by all 4 equations strongly correlates with CrCl. keGFR had the least bias depicted by the mean differences nearest to zero (-18ml/min). Similarly, keGFRCysC had less bias than eGFRCysC, with a mean difference of -21ml/min. eGFRCG had the greatest precision depicted by the narrower SD lines, however, the precision of both keGFR were not much different compared to those of eGFRCG. CONCLUSIONS: In critically ill patients with sepsis, keGFRCr and keGFRCysC had the least bias and fair precision when compared to creatinine clearance measurement. In the absence of creatinine clearance measurement, keGFR calculations are useful as a surrogate for kidney function. [ABSTRACT FROM AUTHOR]

Background: Reporting on the International Nosocomial Infection Control Consortium study results from 2015 to 2020, conducted in 630 intensive care units across 123 cities in 45 countries spanning Africa, Asia, Eastern Europe, Latin America, and the Middle East., Methods: Prospective intensive care unit patient data collected via International Nosocomial Infection Control Consortium Surveillance Online System. Centers for Disease Control and Prevention/National Health Care Safety Network definitions applied for device-associated health care-associated infections (DA-HAI)., Results: We gathered data from 204,770 patients, 1,480,620 patient days, 936,976 central line (CL)-days, 637,850 mechanical ventilators (MV)-days, and 1,005,589 urinary catheter (UC)-days. Our results showed 4,270 CL-associated bloodstream infections, 7,635 ventilator-associated pneumonia, and 3,005 UC-associated urinary tract infections. The combined rates of DA-HAIs were 7.28%, and 10.07 DA-HAIs per 1,000 patient days. CL-associated bloodstream infections occurred at 4.55 per 1,000 CL-days, ventilator-associated pneumonias at 11.96 per 1,000 MV-days, and UC-associated urinary tract infections at 2.91 per 1,000 UC days. In terms of resistance, Pseudomonas aeruginosa showed 50.73% resistance to imipenem, 44.99% to ceftazidime, 37.95% to ciprofloxacin, and 34.05% to amikacin. Meanwhile, Klebsiella spp had resistance rates of 48.29% to imipenem, 72.03% to ceftazidime, 61.78% to ciprofloxacin, and 40.32% to amikacin. Coagulase-negative Staphylococci and Staphylococcus aureus displayed oxacillin resistance in 81.33% and 53.83% of cases, respectively., Conclusions: The high rates of DA-HAI and bacterial resistance emphasize the ongoing need for continued efforts to control them., (Copyright © 2024 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.)

Background: Catheter-Associated Urinary Tract Infections (CAUTIs) frequently occur in the intensive care unit (ICU) and are correlated with a significant burden., Methods: We implemented a strategy involving a 9-element bundle, education, surveillance of CAUTI rates and clinical outcomes, monitoring compliance with bundle components, feedback of CAUTI rates and performance feedback. This was executed in 299 ICUs across 32 low- and middle-income countries. The dependent variable was CAUTI per 1,000 UC days, assessed at baseline and throughout the intervention, in the second month, third month, 4 to 15 months, 16 to 27 months, and 28 to 39 months. Comparisons were made using a 2-sample t test, and the exposure-outcome relationship was explored using a generalized linear mixed model with a Poisson distribution., Results: Over the course of 978,364 patient days, 150,258 patients utilized 652,053 UC-days. The rates of CAUTI per 1,000 UC days were measured. The rates decreased from 14.89 during the baseline period to 5.51 in the second month (risk ratio [RR] = 0.37; 95% confidence interval [CI] = 0.34-0.39; P < .001), 3.79 in the third month (RR = 0.25; 95% CI = 0.23-0.28; P < .001), 2.98 in the 4 to 15 months (RR = 0.21; 95% CI = 0.18-0.22; P < .001), 1.86 in the 16 to 27 months (RR = 0.12; 95% CI = 0.11-0.14; P < .001), and 1.71 in the 28 to 39 months (RR = 0.11; 95% CI = 0.09-0.13; P < .001)., Conclusions: Our intervention, without substantial costs or additional staffing, achieved an 89% reduction in CAUTI incidence in ICUs across 32 countries, demonstrating feasibility in ICUs of low- and middle-income countries., (Copyright © 2024 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.)

Background: The COVID-19 pandemic resulted in a large number of critical care admissions. While national reports have described the outcomes of patients with COVID-19, there is limited international data of the pandemic impact on non-COVID-19 patients requiring intensive care treatment., Methods: We conducted an international, retrospective cohort study using 2019 and 2020 data from 11 national clinical quality registries covering 15 countries. Non-COVID-19 admissions in 2020 were compared with all admissions in 2019, prepandemic. The primary outcome was intensive care unit (ICU) mortality. Secondary outcomes included in-hospital mortality and standardised mortality ratio (SMR). Analyses were stratified by the country income level(s) of each registry., Findings: Among 1 642 632 non-COVID-19 admissions, there was an increase in ICU mortality between 2019 (9.3%) and 2020 (10.4%), OR=1.15 (95% CI 1.14 to 1.17, p<0.001). Increased mortality was observed in middle-income countries (OR 1.25 95% CI 1.23 to 1.26), while mortality decreased in high-income countries (OR=0.96 95% CI 0.94 to 0.98). Hospital mortality and SMR trends for each registry were consistent with the observed ICU mortality findings. The burden of COVID-19 was highly variable, with COVID-19 ICU patient-days per bed ranging from 0.4 to 81.6 between registries. This alone did not explain the observed non-COVID-19 mortality changes., Interpretation: Increased ICU mortality occurred among non-COVID-19 patients during the pandemic, driven by increased mortality in middle-income countries, while mortality decreased in high-income countries. The causes for this inequity are likely multi-factorial, but healthcare spending, policy pandemic responses, and ICU strain may play significant roles., Competing Interests: Competing interests: DP and Dr EL are members of the Australian and New Zealand Intensive Care Society (ANZICS) Centre for Outcome and Resources Evaluation management committee. AB is funded by Wellcome. JS and MS are cofounders and shareholders of Epimed Solutions, a healthcare cloud-based analytics company. They are also supported in part by individual research grants from CNPq and FAPERJ. SB is the current chair, and MR is the past chair of the Finnish Intensive Care Consortium (both unpaid). DAD is unpaid chair of NICE foundation. NI's primary affiliation is the Department of Healthcare Quality Assessment, which is a social collaboration department at the University of Tokyo supported by National Clinical Database, Johnson & Johnson K.K., and Nipro corporation. BKTV is the National Coordinator for the Indian Registry of IntenSive care (IRIS) and is supported for 0.5 FTE by funding from the Wellcome Trust, UK. The remaining authors have no conflicts of interest to declare., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Infection prevention measures are the gold standard for preventing the spread of hospital-acquired infections (HAIs). COVID-19 pandemic caused major disruptions in infection prevention measures, and this has implications on the rate of HAIs. This study assessed the impact of COVID-19 pandemic on the rate and the types of HAIs at Sultan Ahmed Shah Hospital., Method: This is a retrospective cohort study that compared the rate of HAIs from April to October 2019 (pre COVID period) and April to October 2020 (during COVID period). Data was collected through the review of patients' electronic medical records., Results: There were a total of 578 patients included in the selected wards during the pre- and during the pandemic. Thirty-nine episodes (12.1%) of HAIs were report in the pre COVID period and 29 (11.3%) during COVID-19. In both periods, hospital-acquired pneumonia (HAP) was the most frequent HAI among the patients. There was a rise in catheter-associated bloodstream infections (CLABSI) (0.8%) and ventilator associated pneumonia (VAP) (1.1%) during the COVID-19 period. The most common bacteria were methicillin-resistant Staphylococcus aureus (MRSA) (28.2%) and Enterococcus faecalis (17.9%) in the Pre COVID-19 period, and Pseudomonas aeruginosa (27.6%) and Stenotrophomonas maltophilia (6.9%) during COVID-19., Conclusion: Our research concluded that the rates of HAIs during the COVID-19 pandemic were not significantly impacted by the improved in-hospital infection prevention efforts to control the pandemic. There is need for further efforts to promote adherence to preventive practices., (© 2023. The Author(s).)

Background: Improved access to healthcare in low- and middle-income countries (LMICs) has not equated to improved health outcomes. Absence or unsustained quality of care is partly to blame. Improving outcomes in intensive care units (ICUs) requires delivery of complex interventions by multiple specialties working in concert, and the simultaneous prevention of avoidable harms associated with the illness and the treatment interventions. Therefore, successful design and implementation of improvement interventions requires understanding of the behavioural, organisational, and external factors that determine care delivery and the likelihood of achieving sustained improvement. We aim to identify care processes that contribute to suboptimal clinical outcomes in ICUs located in LMICs and to establish barriers and enablers for improving the care processes., Methods: Using rapid evaluation methods, we will use four data collection methods: 1) registry embedded indicators to assess quality of care processes and their associated outcomes; 2) process mapping to provide a preliminary framework to understand gaps between current and desired care practices; 3) structured observations of processes of interest identified from the process mapping and; 4) focus group discussions with stakeholders to identify barriers and enablers influencing the gap between current and desired care practices. We will also collect self-assessments of readiness for quality improvement. Data collection and analysis will be led by local stakeholders, performed in parallel and through an iterative process across eight countries: Kenya, India, Malaysia, Nepal, Pakistan, South Africa, Uganda and Vietnam., Conclusions: The results of our study will provide essential information on where and how care processes can be improved to facilitate better quality of care to critically ill patients in LMICs; thus, reduce preventable mortality and morbidity in ICUs. Furthermore, understanding the rapid evaluation methods that will be used for this study will allow other researchers and healthcare professionals to carry out similar research in ICUs and other health services., Competing Interests: No competing interests were disclosed., (Copyright: © 2023 The Collaboration for Research, Implementation and Training in Critical Care in Asia and Africa (CCAA) et al.)

Background: The effect of conservative vs. liberal oxygen therapy on 90-day in-hospital mortality in adults who have nonhypoxic ischaemic encephalopathy acute brain injuries and conditions and are receiving invasive mechanical ventilation in the intensive care unit (ICU) is uncertain., 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)., (© 2023 The Author(s).)

Objective: To describe whether contemporary dosing of antifungal drugs achieves therapeutic exposures in critically ill patients that are associated with optimal outcomes. Adequate antifungal therapy is a key determinant of survival of critically ill patients with fungal infections. Critical illness can alter an antifungal agents' pharmacokinetics, increasing the risk of inappropriate antifungal exposure that may lead to treatment failure and/or toxicity., 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., Competing Interests: The authors declare that they have no competing interests., (© 2023 Published by Elsevier B.V. on behalf of College of Intensive Care Medicine of Australia and New Zealand.)

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 (E rs ) 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 E rs 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 < E rs (cmH 2 O/L) < 85, suggesting similar predictive capabilities within this clinically relevant E rs 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., Competing Interests: Declaration of competing interest None declared., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Introduction: Creatinine kinetics denotes that under steady-state conditions, creatinine production (G) will equal creatinine excretion rate (E). The glomerular filtration (GFR) is impaired when excretion is less than production. The kinetic estimate of GFR (keGFR) and E/G ratio were proposed as a more accurate estimate of GFR in acute settings with rapidly changing kidney function. We evaluated keGFR and E/G to diagnose AKI, predict recovery, death or dialysis., Methods: This is a prospective observational study of critically ill patients. Inclusion criteria were patients >18 years old with sepsis, defined as clinical infection with an increase in SOFA score >2, and plasma procalcitonin >0.5 ng/mL. Plasma creatinine and Cystatin C were measured on ICU admission and 4 h later, and their keGFR was calculated. Urine creatinine and urine output were measured over 4 h to calculate the E/G ratio., Results: A total of 70 patients were recruited, of which 49 (70%) had AKI. Of these, 33 recovered within 3 days, and 15 had a composite outcome of death or dialysis. Day 1 keGFR Cr and keGFR CysC discriminated AKI from non-AKI with AUCs of 0.85 (95% Confidence interval: 0.74-0.96), and 0.86 (0.76-0.97), respectively. The E/G ratio predicted AKI recovery (AUC: 0.81 (0.69-0.97)). The keGFRs were not predictive of death or dialysis, whereas E/G was predictive (AUC: 0.76 (0.63-0.89)., Conclusion: keGFR was strongly diagnostic of AKI. The E/G ratio predicted AKI recovery and a composite outcome of death and dialysis., Competing Interests: There are no conflicts of interest., (Copyright: © 2022 Indian Journal of Nephrology.)

Rationale: Directly comparative data on sepsis epidemiology and sepsis bundle implementation in countries of differing national wealth remain sparse. Objectives: To evaluate across countries/regions of differing income status in Asia 1 ) the prevalence, causes, and outcomes of sepsis as a reason for ICU admission and 2 ) sepsis bundle (antibiotic administration, blood culture, and lactate measurement) compliance and its association with hospital mortality. Methods: A prospective point prevalence study was conducted among 386 adult ICUs from 22 Asian countries/regions. Adult ICU participants admitted for sepsis on four separate days (representing the seasons of 2019) were recruited. Measurements and Main Results: The overall prevalence of sepsis in ICUs was 22.4% (20.9%, 24.5%, and 21.3% in low-income countries/regions [LICs]/lower middle-income countries/regions [LMICs], upper middle-income countries/regions, and high-income countries/regions [HICs], respectively; P  < 0.001). Patients were younger and had lower severity of illness in LICs/LMICs. Hospital mortality was 32.6% and marginally significantly higher in LICs/LMICs than HICs on multivariable generalized mixed model analysis (adjusted odds ratio, 1.84; 95% confidence interval, 1.00-3.37; P  = 0.049). Sepsis bundle compliance was 21.5% at 1 hour (26.0%, 22.1%, and 16.2% in LICs/LMICs, upper middle-income countries/regions, and HICs, respectively; P  < 0.001) and 36.6% at 3 hours (39.3%, 32.8%, and 38.5%, respectively; P  = 0.001). Delaying antibiotic administration beyond 3 hours was the only element independently associated with increased mortality (adjusted odds ratio, 2.53; 95% confidence interval, 2.07-3.08; P  < 0.001). Conclusions: Sepsis is a common cause of admission to Asian ICUs. Mortality remains high and is higher in LICs/LMICs after controlling for confounders. Sepsis bundle compliance remains low. Delaying antibiotic administration beyond 3 hours from diagnosis is associated with increased mortality. Clinical trial registered with www.ctri.nic.in (CTRI/2019/01/016898).

Background: Whilst timely clinical characterisation of infections caused by novel SARS-CoV-2 variants is necessary for evidence-based policy response, individual-level data on infecting variants are typically only available for a minority of patients and settings., Methods: Here, we propose an innovative approach to study changes in COVID-19 hospital presentation and outcomes after the Omicron variant emergence using publicly available population-level data on variant relative frequency to infer SARS-CoV-2 variants likely responsible for clinical cases. We apply this method to data collected by a large international clinical consortium before and after the emergence of the Omicron variant in different countries., Results: Our analysis, that includes more than 100,000 patients from 28 countries, suggests that in many settings patients hospitalised with Omicron variant infection less often presented with commonly reported symptoms compared to patients infected with pre-Omicron variants. Patients with COVID-19 admitted to hospital after Omicron variant emergence had lower mortality compared to patients admitted during the period when Omicron variant was responsible for only a minority of infections (odds ratio in a mixed-effects logistic regression adjusted for likely confounders, 0.67 [95% confidence interval 0.61-0.75]). Qualitatively similar findings were observed in sensitivity analyses with different assumptions on population-level Omicron variant relative frequencies, and in analyses using available individual-level data on infecting variant for a subset of the study population., Conclusions: Although clinical studies with matching viral genomic information should remain a priority, our approach combining publicly available data on variant frequency and a multi-country clinical characterisation dataset with more than 100,000 records allowed analysis of data from a wide range of settings and novel insights on real-world heterogeneity of COVID-19 presentation and clinical outcome., Funding: Bronner P. Gonçalves, Peter Horby, Gail Carson, Piero L. Olliaro, Valeria Balan, Barbara Wanjiru Citarella, and research costs were supported by the UK Foreign, Commonwealth and Development Office (FCDO) and Wellcome [215091/Z/18/Z, 222410/Z/21/Z, 225288/Z/22/Z]; and Janice Caoili and Madiha Hashmi were supported by the UK FCDO and Wellcome [222048/Z/20/Z]. Peter Horby, Gail Carson, Piero L. Olliaro, Kalynn Kennon and Joaquin Baruch were supported by the Bill & Melinda Gates Foundation [OPP1209135]; Laura Merson was supported by University of Oxford's COVID-19 Research Response Fund - with thanks to its donors for their philanthropic support. Matthew Hall was supported by a Li Ka Shing Foundation award to Christophe Fraser. Moritz U.G. Kraemer was supported by the Branco Weiss Fellowship, Google.org, the Oxford Martin School, the Rockefeller Foundation, and the European Union Horizon 2020 project MOOD (#874850). The contents of this publication are the sole responsibility of the authors and do not necessarily reflect the views of the European Commission. Contributions from Srinivas Murthy, Asgar Rishu, Rob Fowler, James Joshua Douglas, François Martin Carrier were supported by CIHR Coronavirus Rapid Research Funding Opportunity OV2170359 and coordinated out of Sunnybrook Research Institute. Contributions from Evert-Jan Wils and David S.Y. Ong were supported by a grant from foundation Bevordering Onderzoek Franciscus; and Andrea Angheben by the Italian Ministry of Health "Fondi Ricerca corrente-L1P6" to IRCCS Ospedale Sacro Cuore-Don Calabria. The data contributions of J.Kenneth Baillie, Malcolm G. Semple, and Ewen M. Harrison were supported by grants from the National Institute for Health Research (NIHR; award CO-CIN-01), the Medical Research Council (MRC; grant MC&#95;PC&#95;19059), and by the NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool in partnership with Public Health England (PHE) (award 200907), NIHR HPRU in Respiratory Infections at Imperial College London with PHE (award 200927), Liverpool Experimental Cancer Medicine Centre (grant C18616/A25153), NIHR Biomedical Research Centre at Imperial College London (award IS-BRC-1215-20013), and NIHR Clinical Research Network providing infrastructure support. All funders of the ISARIC Clinical Characterisation Group are listed in the appendix., Competing Interests: BG, MH, WJ, VB, CK, AR, JB, LR, AD, JD, BC, MP, US, JB, DA, YA, AR, JC, EH, CF, MM, YC, XW, SB, ST, LS, AR, RR, DO, MH, GC, JD, MK, EW, PH, LM, PO No competing interests declared, SM declares receiving salary support from the Health Research Foundation and Innovative Medicines Canada Chair in Pandemic Preparedness Research, MS reports grants from DHSC National Institute of Health Research UK, from the Medical Research Council UK, and from the Health Protection Research Unit in Emerging & Zoonotic Infections, University of Liverpool, supporting the conduct of the study; other interest in Integrum Scientific LLC, Greensboro, NC, USA, outside the submitted work, AM declares consulting fees for Gilead and MSD, presentation fees for GILEAD, Pfizer and MSD, support for attending ECCMID from Gilead, and advisory board fees for MSD and Gilead, AA declares support from Italian Ministry of Health - "Fondi Ricerca Corrente" Line1 Project 5 to IRCCS Sacro Cuore - Don Calabria Hospital, FC declares a grant from the Canadian Institute of Health Research, JG declares support by Pfizer, Angelini and MSD to attend meetings (registration to meetings only), JD declares personal fees from lectures from Sunovion and Merck and consulting fees from Pfizer, AS has been an investigator in COVID-19 clinical trials by Algernon Pharmaceuticals, Atea Pharmaceuticals, Regeneron Pharmaceuticals, Diffusion Pharmaceuticals, Celltrion, Inc and Atriva Therapeutics, outside the scope of the submitted work, RF declares a peer reviewed research grant from the Canadian Institutes of Health Research, See Appendix 1 for competing interests for group author members, (© 2022, Gonçalves et al.)

Background: The association between interleukin-6 (IL-6) and serum albumin (ALB) with mortality in critically ill elderly patients, either as stand-alone biomarkers or in combination, has been scarcely reported. We, therefore, aimed to investigate the prognostic value of the IL-6-to-albumin ratio in this special population., Patients and Methods: This was a cross-sectional study conducted in the mixed intensive care unit (ICU) of two university-affiliated hospitals in Malaysia. Consecutive elderly patients (aged above or equal to 60 years) admitted to the ICU, who underwent simultaneous measurement of plasma IL-6 and serum ALB, were recruited. The prognostic value of the IL-6-to-albumin ratio was assessed by analysis of the receiver-operating characteristic (ROC) curve., Results: A total of 112 critically ill elderly patients were recruited. The outcome of all-cause ICU mortality was 22.3%. The calculated IL-6-to-albumin ratio was significantly higher in the non-survivors compared to the survivors {14.1 [interquartile range (IQR), 6.5-26.7] vs 2.5 [(IQR, 0.6-9.2) pg/mL, p <0.001]}. The area under the curve (AUC) of IL-6-to-albumin ratio for discrimination of ICU mortality was 0.766 [95% confidence interval (CI), 0.667-0.865, p <0.001] which was slightly higher than that of IL-6 and albumin alone. The ideal cut-off value of the IL-6-to-albumin ratio was above 5.7 with a sensitivity of 80.0% and specificity of 64.4%. After adjusting for severity of illness, the IL-6-to-albumin ratio remained as an independent predictor of ICU mortality with an adjusted odd ratio of 0.975 (95% CI, 0.952-0.999, p = 0.039)., Conclusion: The IL-6-to-albumin ratio offers a slight improvement in mortality prediction than either of its constituent individual biomarkers and as such, it may be a potential tool to aid in the prognostication of critically ill elderly patients although this requires further validation in a larger prospective study., How to Cite This Article: Lim KY, Shukeri WFWM, Hassan WMNW, Mat-Nor MB, Hanafi MH. The Combined Use of Interleukin-6 with Serum Albumin for Mortality Prediction in Critically Ill Elderly Patients: The Interleukin-6-to-albumin Ratio. Indian J Crit Care Med 2022;26(10):1126-1130., Competing Interests: Source of support: Ministry of Higher Education Malaysia through Fundamental Research Grant Scheme (Reference Code: FRGS/1/2020/SKK01/USM/03/1). Conflict of interest: None, (Copyright © 2022; Jaypee Brothers Medical Publishers (P) Ltd.)

Sepsis is an important cause of morbidity and mortality in elderly patients, but there is a scarcity of data on sepsis in this specific cohort. We performed this study to review the impact of sepsis on outcomes in elderly patients admitted to our local intensive care unit (ICU). This was a secondary analysis of prospectively collected data of 159 consecutive adult patients with sepsis admitted to an ICU of a tertiary hospital in Malaysia over a three-year period. Of the 159 patients analysed, elderly patients constituted 18.9% of the cohort. Fifty percent of the older patients died within 30 days, compared to 24% of younger patients ( P = 0.005). On multivariate analysis, old age was found to be independently predictive of 30-day mortality with an adjusted odds ratio (OR) of 2.5 (95% confidence interval [CI]: 1.05, 6.01) compared to younger patients ( P = 0.021). In a Kaplan-Meier analysis, survival probability was significantly lower in patients of an older age compared to younger patients ( P = 0.015). In conclusion, mortality from sepsis is considerably higher in elderly patients, with age as an independent risk factor for mortality., Competing Interests: Conflict of Interest None., (© Penerbit Universiti Sains Malaysia, 2022.)

Background: Predictive equations (PEs) for estimating resting energy expenditure (REE) that have been developed from acute phase data may not be applicable in the late phase and vice versa. This study aimed to assess whether separate PEs are needed for acute and late phases of critical illness and to develop and validate PE(s) based on the results of this assessment., 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 (R 2 ), 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 R 2  = 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., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

Background and Objective: Mechanical ventilation (MV) is the primary form of care for respiratory failure patients. MV settings are based on general clinical guidelines, intuition, and experience. This approach is not patient-specific and patients may thus experience suboptimal, potentially harmful MV care. This study presents the Stochastic integrated VENT (SiVENT) protocol which combines model-based approaches of the VENT protocol from previous works, with stochastic modelling to take the variation of patient respiratory elastance over time into consideration., Methods: A stochastic model of E rs 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., (© 2022. The Author(s).)

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] cmH 2 O 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., Competing Interests: Declaration of Competing Interest The authors declare that they do not have conflict of interest., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Respiratory system modelling can assist clinicians in making clinical decisions during mechanical ventilation (MV) management in intensive care. However, there are some cases where the MV patients produce asynchronous breathing (asynchrony events) due to the spontaneous breathing (SB) effort even though they are fully sedated. Currently, most of the developed models are only suitable for fully sedated patients, which means they cannot be implemented for patients who produce asynchrony in their breathing. This leads to an incorrect measurement of the actual underlying mechanics in these patients. As a result, there is a need to develop a model that can detect asynchrony in real-time and at the bedside throughout the ventilated days. This paper demonstrates the asynchronous event detection of MV patients in the ICU of a hospital by applying a developed extended time-varying elastance model. Data from 10 mechanically ventilated respiratory failure patients admitted at the International Islamic University Malaysia (IIUM) Hospital were collected. The results showed that the model-based technique precisely detected asynchrony events (AEs) throughout the ventilation days. The patients showed an increase in AEs during the ventilation period within the same ventilation mode. SIMV mode produced much higher asynchrony compared to SPONT mode ( p < 0.05). The link between AEs and the lung elastance (AUC&nbsp;Edrs)&nbsp;was also investigated. It was found that when the AEs increased, the AUC&nbsp;Edrs&nbsp;decreased and vice versa based on the results obtained in this research. The information of AEs and AUC&nbsp;Edrs&nbsp;provides the true underlying lung mechanics of the MV patients. Hence, this model-based method is capable of detecting the AEs in fully sedated MV patients and providing information that can potentially guide clinicians in selecting the optimal ventilation mode of MV, allowing for precise monitoring of respiratory mechanics in MV patients.

While lung protective mechanical ventilation (MV) guidelines have been developed to avoid ventilator-induced lung injury (VILI), a one-size-fits-all approach cannot benefit every individual patient. Hence, there is significant need for the ability to provide patient-specific MV settings to ensure safety, and optimise patient care. Model-based approaches enable patient-specific care by identifying time-varying patient-specific parameters, such as respiratory elastance, E rs , to capture inter- and intra-patient variability. However, patient-specific parameters evolve with time, as a function of disease progression and patient condition, making predicting their future values crucial for recommending patient-specific MV settings. This study employs stochastic modelling to predict future E rs values using retrospective patient data to develop and validate a model indicating future intra-patient variability of E rs . Cross validation results show stochastic modelling can predict future elastance ranges with 92.59 and 68.56% of predicted values within the 5-95% and the 25-75% range, respectively. This range can be used to ensure patients receive adequate minute ventilation should elastance rise and minimise the risk of VILI should elastance fall. The results show the potential for model-based protocols using stochastic model prediction of future E rs values to provide safe and patient-specific MV. These results warrant further investigation to validate its clinical utility., (© 2021. Biomedical Engineering Society.)

Background: Asia has more critically ill people than any other part of our planet. The aim of this article is to review the development of critical care as a specialty, critical care societies and education and research, the epidemiology of critical illness as well as epidemics and pandemics, accessibility and cost and quality of critical care, culture and end-of-life care, and future directions for critical care in Asia., 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., (© 2021. The Author(s).)

Introduction: Accurate assessment of glomerular filtration rate (GFR) is very important for diagnostic and therapeutic intervention. Clinically, GFR is estimated from plasma creatinine using equations such as Cockcroft-Gault, Modification of Diet in Renal Disease, and Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) equations. However, these were developed in the Western population. To the best of our knowledge, there was no equation that has been developed specifically in our population., Objectives: We developed a new equation based on the gold standard of 99m Tc-DTPA imaging measured GFR. We then performed an internal validation by comparing the bias, precision, and accuracy of the new equation and the other equations with the gold standard of 99m Tc-DTPA imaging measured GFR., Methods: This was a cross-sectional study using the existing record of patients who were referred for 99m Tc-DTPA imaging at the Nuclear Medicine Centre, International Islamic University Malaysia. As this is a retrospective study utilising routinely collected data from the existing pool of data, the ethical committee has waived the need for informed consent., Results: Data of 187 patients were analysed from January 2016 to March 2021. Of these, 94 were randomised to the development cohort and 93 to the validation cohort. A new equation of eGFR was determined as 16.637 ∗ 0.9935 Age  ∗ (SCr/23.473) -0.45159 . In the validation cohort, both CKD-EPI and the new equation had the highest correlation to 99m Tc-DTPA with a correlation coefficient of 0.81 ( p < 0.0001). However, the new equation had the least bias and was the most precise (mean bias of -3.58 ± 12.01) and accurate (P30 of 64.5% and P50 of 84.9%) compared to the other equations., Conclusion: The new equation which was developed specifically using our local data population was the most accurate and precise, with less bias compared to the other equations. Further study validating this equation in the perioperative and intensive care patients is needed., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2021 Azrina Md Ralib et al.)

Background: The optimal dosing of antibiotics in critically ill patients receiving renal replacement therapy (RRT) remains unclear. In this study, we describe the variability in RRT techniques and antibiotic dosing in critically ill patients receiving RRT and relate observed trough antibiotic concentrations to optimal targets., Methods: We performed a prospective, observational, multinational, pharmacokinetic study in 29 intensive care units from 14 countries. We collected demographic, clinical, and RRT data. We measured trough antibiotic concentrations of meropenem, piperacillin-tazobactam, and vancomycin and related them to high- and low-target trough concentrations., Results: We studied 381 patients and obtained 508 trough antibiotic concentrations. There was wide variability (4-8-fold) in antibiotic dosing regimens, RRT prescription, and estimated endogenous renal function. The overall median estimated total renal clearance (eTRCL) was 50 mL/minute (interquartile range [IQR], 35-65) and higher eTRCL was associated with lower trough concentrations for all antibiotics (P < .05). The median (IQR) trough concentration for meropenem was 12.1 mg/L (7.9-18.8), piperacillin was 78.6 mg/L (49.5-127.3), tazobactam was 9.5 mg/L (6.3-14.2), and vancomycin was 14.3 mg/L (11.6-21.8). Trough concentrations failed to meet optimal higher limits in 26%, 36%, and 72% and optimal lower limits in 4%, 4%, and 55% of patients for meropenem, piperacillin, and vancomycin, respectively., Conclusions: In critically ill patients treated with RRT, antibiotic dosing regimens, RRT prescription, and eTRCL varied markedly and resulted in highly variable antibiotic concentrations that failed to meet therapeutic targets in many patients., (© The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Introduction: Approach to managing infection in the intensive care unit (ICU) often varies between institutions and not many readily adapt to available local guidelines despite it was constructed to suite local clinical scenario. Malaysia already has two published guidelines on managing infection in the ICU but data on its compliance are largely unknown., 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., Competing Interests: There are no conflicts of interest., (Copyright: © 2020 Journal of Pharmacy and Bioallied Sciences.)

Objective: To assess the number of adult critical care beds in Asian countries and regions in relation to population size., 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.

Objectives: Several predictive equations have been developed for estimation of resting energy expenditure, but no study has been done to compare predictive equations against indirect calorimetry among critically ill patients at different phases of critical illness. This study aimed to determine the degree of agreement and accuracy of predictive equations among ICU patients during acute phase (≤ 5 d), late phase (6-10 d), and chronic phase (≥ 11 d)., 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.

Introduction: Acute kidney injury (AKI) is common in the intensive care unit (ICU) with a high risk of morbidity and mortality. The high incidence of AKI in our population may be attributed to sepsis. We investigated the incidence, risk factors, and outcome of AKI in four tertiary Malaysian ICUs. We also evaluated its association with sepsis., Materials and Methods: This retrospective cohort study extracted de-identified data from the Malaysian Registry of Intensive Care in four Malaysian tertiary ICUs between January 2010 and December 2014. The study was registered under the NMRR and approved by the ethics committee. AKI was defined as twice the baseline creatinine or urine output <0.5 ml/kg/h for 12 h., Results: Of 26,663 patients, 24.2% had AKI within 24 h of admission. Patients with AKI were older and had higher severity of illness compared to those without AKI. AKI patients had a longer duration of mechanical ventilation, length of ICU, and hospital stay. Age, Simplified Acute Physiological II Score, and the presence of sepsis and preexisting hypertension, chronic cardiovascular disease independently associated with AKI. About 32.3% had sepsis. Patients with both AKI and sepsis had the highest risk of mortality (relative risk 3.43 [3.34-3.53])., Conclusions: AKI is common in our ICU, with higher morbidity and mortality. Independent risk factors of AKI include age, the severity of illness, sepsis and preexisting hypertension, and chronic cardiovascular disease. AKI independently contributes to mortality. The presence of AKI and sepsis increased the risk of mortality by three times., Competing Interests: There are no conflicts of interest.

Background and Objective: Blood glucose variability is common in healthcare and it is not related or influenced by diabetes mellitus. To minimise the risk of high blood glucose in critically ill patients, Stochastic Targeted Blood Glucose Control Protocol is used in intensive care unit at hospitals worldwide. Thus, this study focuses on the performance of stochastic modelling protocol in comparison to the current blood glucose management protocols in the Malaysian intensive care unit. Also, this study is to assess the effectiveness of Stochastic Targeted Blood Glucose Control Protocol when it is applied to a cohort of diabetic patients., 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 u en model is also a must to adapt with the diabetic cohort., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Background and Aims: Currently, there is a lack of real-time metric with high sensitivity and specificity to diagnose sepsis. Insulin sensitivity (SI) may be determined in real-time using mathematical glucose-insulin models; however, its effectiveness as a diagnostic test of sepsis is unknown. Our aims were to determine the levels and diagnostic value of model-based SI for identification of sepsis in critically ill patients., Materials and Methods: In this retrospective, cohort study, we analyzed SI levels in septic ( n = 18) and nonseptic ( n = 20) patients at 1 (baseline), 4, 8, 12, 16, 20, and 24 h of their Intensive Care Unit admission. Patients with diabetes mellitus Type I or Type II were excluded from the study. The SI levels were derived by fitting the blood glucose levels, insulin infusion and glucose input rates into the Intensive Control of Insulin-Nutrition-Glucose model., Results: The median SI levels were significantly lower in the sepsis than in the nonsepsis at all follow-up time points. The areas under the receiver operating characteristic curve of the model-based SI at baseline for discriminating sepsis from nonsepsis was 0.814 (95% confidence interval, 0.675-0.953). The optimal cutoff point of the SI test was 1.573 × 10 -4 L/mu/min. At this cutoff point, the sensitivity was 77.8%, specificity was 75%, positive predictive value was 73.7%, and negative predictive value was 78.9%., Conclusions: Model-based SI ruled in and ruled out sepsis with fairly high sensitivity and specificity in our critically ill nondiabetic patients. These findings can be used as a foundation for further, prospective investigation in this area., Competing Interests: There are no conflicts of interest.

Background and Objective: Respiratory mechanics estimation can be used to guide mechanical ventilation (MV) but is severely compromised when asynchronous breathing occurs. In addition, asynchrony during MV is often not monitored and little is known about the impact or magnitude of asynchronous breathing towards recovery. Thus, it is important to monitor and quantify asynchronous breathing over every breath in an automated fashion, enabling the ability to overcome the limitations of model-based respiratory mechanics estimation during asynchronous breathing ventilation., Methods: An iterative airway pressure reconstruction (IPR) method is used to reconstruct asynchronous airway pressure waveforms to better match passive breathing airway waveforms using a single compartment model. The reconstructed pressure enables estimation of respiratory mechanics of airway pressure waveform essentially free from asynchrony. Reconstruction enables real-time breath-to-breath monitoring and quantification of the magnitude of the asynchrony (M Asyn )., Results and Discussion: Over 100,000 breathing cycles from MV patients with known asynchronous breathing were analyzed. The IPR was able to reconstruct different types of asynchronous breathing. The resulting respiratory mechanics estimated using pressure reconstruction were more consistent with smaller interquartile range (IQR) compared to respiratory mechanics estimated using asynchronous pressure. Comparing reconstructed pressure with asynchronous pressure waveforms quantifies the magnitude of asynchronous breathing, which has a median value M Asyn for the entire dataset of 3.8%., Conclusion: The iterative pressure reconstruction method is capable of identifying asynchronous breaths and improving respiratory mechanics estimation consistency compared to conventional model-based methods. It provides an opportunity to automate real-time quantification of asynchronous breathing frequency and magnitude that was previously limited to invasively method only., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Background & Aims: Guidance on managing the nutritional requirements of critically ill patients in the intensive care unit (ICU) has been issued by several international bodies. While these guidelines are consulted in ICUs across the Asia-Pacific and Middle East regions, there is little guidance available that is tailored to the unique healthcare environments and demographics across these regions. Furthermore, the lack of consistent data from randomized controlled clinical trials, reliance on expert consensus, and differing recommendations in international guidelines necessitate further expert guidance on regional best practice when providing nutrition therapy for critically ill patients in ICUs in Asia-Pacific and the Middle East., 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., (Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Purpose: To derive a prediction equation for 30-day mortality in sepsis using a multi-marker approach and compare its performance to the Sequential Organ Failure Assessment (SOFA) score., Methods: This study included 159 septic patients admitted to an intensive care unit. Leukocytes count, procalcitonin (PCT), interleukin-6 (IL-6), and paraoxonase (PON) and arylesterase (ARE) activities of PON-1 were assayed from blood obtained on ICU presentation. Logistic regression was used to derive sepsis mortality score (SMS), a prediction equation describing the relationship between biomarkers and 30-day mortality., Results: The 30-day mortality rate was 28.9%. The SMS was [еlogit(p)/(1+еlogit(p))]×100; logit(p)=0.74+(0.004×PCT)+(0.001×IL-6)-(0.025×ARE)-(0.059×leukocytes count). The SMC had higher area under the receiver operating characteristic curve (95% Cl) than SOFA score [0.814 (0.736-0.892) vs. 0.767 (0.677-0.857)], but is not statistically significant. When the SMS was added to the SOFA score, prediction of 30-day mortality improved compared to SOFA score used alone [0.845 (0.777-0.899), p=0.022]., Conclusions: A sepsis mortality score using baseline leukocytes count, PCT, IL-6 and ARE was derived, which predicted 30-day mortality with very good performance and added significant prognostic information to SOFA score., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Background and Objectives: Refeeding hypophosphataemia (RH) is characterized by an acute electrolyte derangement following nutrition therapy. Complications associated include heart failure, respiratory failure, paraesthesia, seizure and death. We aim to assess its incidence, risk factors, and outcome in our local intensive care unit (ICU)., Methods and Study Design: A prospective observational cohort study was conducted at the mixed medical- surgical of a tertiary ICU in Kuantan, Malaysia. The study was registered under the National Medical Research Register (NMRR-14-803-19813) and has received ethical approval. Inclusion criteria include adult admission longer than 48 hours who were started on enteral feeding. Chronic renal failure patients and those receiving dialysis were excluded. RH was defined as plasma phosphate less than 0.65 mmol/L and a drop of more than 0.16 mmol/L following feeding., Results: A total of 109 patients were recruited, of which 44 (42.6%) had RH. Patients with RH had higher SOFA score compared to those without (p=0.04). There were no differences in the APACHE II and NUTRIC scores. Serum albumin was lower in those with RH (p=0.04). After refeeding, patients with RH had lower serum phosphate, magnesium and albumin, and higher supplementation of phosphate, potassium and calcium. There were no differences in mortality, length of hospital or ICU stay., Conclusions: Refeeding hypophosphataemia occurs in almost half of ICU admission. Risk factors for refeeding include high organ failure score and low albumin. Refeeding was associated with imbalances in phosphate, magnesium, potassium and calcium. Future larger study may further investigate these risk factors and long-term outcomes.

Aim: Sepsis is the leading cause of intensive care unit (ICU) admission. Plasma Neutrophil Gelatinase Associated-Lipocalin (NGAL) is a promising biomarker for acute kidney injury (AKI) detection; however, it is also increased with inflammation and few studies have been conducted in non-Caucasian populations and/or in developing economies. Therefore, we evaluated plasma NGAL's diagnostic performance in the presence of sepsis and systemic inflammatory response syndrome (SIRS) in a Malaysian ICU cohort., Methods: This is a prospective observational study on patients with SIRS. Plasma creatinine (pCr) and NGAL were measured on ICU admission. Patients were classified according to the occurrence of AKI and sepsis., Results: Of 225 patients recruited, 129 (57%) had sepsis of whom 67 (52%) also had AKI. 96 patients (43%) had non-infectious SIRS, of whom 20 (21%) also had AKI. NGAL concentrations were higher in AKI patients within both the sepsis and non-infectious SIRS cohorts (both P < 0.0001). The diagnostic area under curve for AKI was 0.81 (95%CI: 0.74 to 0.87). The optimal cut-off was higher in sepsis compared to non-infectious SIRS patients (454 versus 176 ng/mL). Addition of NGAL to a clinical model comprising age, pCr, medical admission category and SAPS II score increased the mean risk of those with AKI by 4% and reduced the mean risk of those without AKI by 3%., Conclusions: Acute kidney injury is more common with sepsis than non-infectious SIRS. Plasma NGAL was diagnostic of AKI in both subgroups. The optimal cut-off for diagnosing AKI was higher in sepsis than in non-infectious SIRS. Addition of plasma NGAL improved the clinical model used to diagnose AKI., (© 2016 Asian Pacific Society of Nephrology.)

Background and Aims: About 50% of patients admitted to the Intensive Care Unit have systemic inflammatory response syndrome (SIRS), and about 10%-20% of them died. Early risk stratification is important to reduce mortality. Plasma neutrophil gelatinase-associated lipocalin (NGAL) is increased by inflammation and infection. Its ability to predict mortality in SIRS patients is of interest. We evaluated the ability of serial measurement of NGAL for the prediction of mortality in critically ill patients with SIRS., Materials and Methods: This is a secondary analysis of a single-center, prospective, observational study. Patients who fulfill the SIRS criteria were recruited in the study. Delta NGAL at 24 and 48 h (ΔNGAL-24 and ΔNGAL-48) was defined as 24 and 48 h NGAL minus day 1 NGAL; NGAL clearance (NGALc) was defined as percentage of ΔNGAL over day 1 NGAL. The primary outcome of the study is in-hospital mortality., Results: A total of 151 patients were analyzed, of which 53 (35%) died. Nonsurvivors were older (51 vs. 45, P = 0.03) and had higher Sequential Organ Failure Assessment (9 ± 7 vs. 7 ± 4, P = 0.02) and Simplified Acute Physiology Score II (47 ± 15 vs. 40 ± 15, P = 0.01) scores as compared to survivors. NGAL concentrations over 3 days were higher in nonsurvivors compared to survivors (repeated measures analysis of variance, P = 0.02). Day 1 NGAL, ΔNGAL-24, and NGALc-24 were not independently predictive of mortality. However, day 3 NGAL, ΔNGAL-48, and NGALc-48 were predictive after adjusted for age and severity of illness (odds ratio 9.1 [1.97-41.7])., Conclusions: NGAL dynamics over 48 h independently predicted mortality in critically ill patients with SIRS. This could assist clinicians in risk stratification of this group of high-risk patients., Competing Interests: There are no conflicts of interest.

Purpose: This study aims to determine if continuous infusion (CI) is associated with better clinical and pharmacokinetic/pharmacodynamic (PK/PD) outcomes compared to intermittent bolus (IB) dosing in critically ill patients with severe sepsis., 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 < 0.043) than IB participants. PK/PD target attainment rates were higher in the CI arm at 100 % fT >MIC than the IB arm on day 1 (97 versus 70 %, p < 0.001) and day 3 (97 versus 68 %, p < 0.001) post-randomisation. There was no difference in 14-day or 30-day survival between the treatment arms., Conclusions: In critically ill patients with severe sepsis not receiving RRT, CI demonstrated higher clinical cure rates and had better PK/PD target attainment compared to IB dosing of beta-lactam antibiotics. Continuous beta-lactam infusion may be mostly advantageous for critically ill patients with high levels of illness severity and not receiving RRT. Malaysian National Medical Research Register ID: NMRR-12-1013-14017.

Hypoxemia in severe leptospirosis-associated pulmonary hemorrhage syndrome (LPHS) is a challenging clinical scenario not usually responsive to maximal support on mechanical ventilation. We described the efficacy and safety of high frequency oscillatory ventilation (HFOV) as rescue therapy in acute respiratory failure secondary to LPHS. This is a retrospective case study of five patients with diagnosis of severe LPHS, who were admitted to Intensive Care Unit from October 2014 to January 2015. They developed refractory hypoxemia on conventional mechanical ventilation and rescue therapy was indicated. All patients responded rapidly by showing improvements in oxygen index and PaO2/FiO2 ratio within first 72 h of therapy. Despite severity of illness evidenced by high Simplified Acute Physiological II and Sequential Organ Failure Assessment scores, all patients were discharged from hospital alive. In view of the rapid onset and extent of hemorrhage which may culminate quickly into asphyxiation and death, HFOV may indeed be lifesaving in severe LPHS.

Purpose: The purpose of the study was to quantify the ability of procalcitonin (PCT) and interleukin-6 (IL-6) to differentiate noninfectious systemic inflammatory response syndrome (SIRS) and sepsis and to predict hospital mortality., Materials: We recruited consecutively adult patients with SIRS admitted to an intensive care unit. They were divided into sepsis and noninfectious SIRS based on clinical assessment with or without positive cultures. Concentrations of PCT and IL-6 were measured daily over the first 3 days., Results: A total of 239 patients were recruited, 164 (68.6%) had sepsis, and 68 (28.5%) died in hospital. The PCT levels were higher in sepsis compared with noninfectious SIRS throughout the 3-day period (P < .0001). On admission, PCT concentration was diagnostic of sepsis (area under the curve of 0.63 [0.55-0.71]), and IL-6 was predictive of mortality, (area under the curve of 0.70 [0.62-0.78]). Peak IL-6 concentration improved the risk assessment of Sequential Organ Failure Assessment (SOFA) score for prediction of mortality among those who went on to die by an average of 5% and who did not die by 2%, Conclusions: Procalcitonin measured on intensive care unit admission was diagnostic of sepsis, and IL-6 was predictive of mortality. Addition of IL-6 concentration to SOFA score improved risk assessment for prediction of mortality. Future studies should include clinical indices, for example, SOFA score, for prognostic evaluation of biomarkers., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Doripenem has been recently introduced in Malaysia and is used for severe infections in the intensive care unit. However, limited data currently exist to guide optimal dosing in this scenario. We aimed to describe the population pharmacokinetics of doripenem in Malaysian critically ill patients with sepsis and use Monte Carlo dosing simulations to develop clinically relevant dosing guidelines for these patients. In this pharmacokinetic study, 12 critically ill adult patients with sepsis receiving 500 mg of doripenem every 8 h as a 1-hour infusion were enrolled. Serial blood samples were collected on 2 different days, and population pharmacokinetic analysis was performed using a nonlinear mixed-effects modeling approach. A two-compartment linear model with between-subject and between-occasion variability on clearance was adequate in describing the data. The typical volume of distribution and clearance of doripenem in this cohort were 0.47 liters/kg and 0.14 liters/kg/h, respectively. Doripenem clearance was significantly influenced by patients' creatinine clearance (CL(CR)), such that a 30-ml/min increase in the estimated CL(CR) would increase doripenem CL by 52%. Monte Carlo dosing simulations suggested that, for pathogens with a MIC of 8 mg/liter, a dose of 1,000 mg every 8 h as a 4-h infusion is optimal for patients with a CL(CR) of 30 to 100 ml/min, while a dose of 2,000 mg every 8 h as a 4-h infusion is best for patients manifesting a CL(CR) of >100 ml/min. Findings from this study suggest that, for doripenem usage in Malaysian critically ill patients, an alternative dosing approach may be meritorious, particularly when multidrug resistance pathogens are involved., (Copyright © 2015, American Society for Microbiology. All Rights Reserved.)

Here we describe the pharmacokinetics of piperacillin administered by continuous infusion (CI) versus intermittent bolus (IB) dosing in critically ill patients receiving continuous venovenous haemofiltration (CVVH) and compare the frequency of pharmacodynamic/pharmacokinetic (PK/PD) target attainment with each dosing strategy. This was a prospective pharmacokinetic trial in 16 critically ill patients with severe sepsis or septic shock undergoing CVVH and randomised to receive either CI or IB administration of a standard daily dose of piperacillin/tazobactam (11.25g/day on Day 1 followed by 9g/day). Serial blood samples were measured on two occasions. Piperacillin pharmacokinetics were calculated using a non-compartmental approach. Blood concentrations were compared with established PK/PD targets. On occasion 1 (Days 1-3 of therapy), IB administration resulted in significantly higher piperacillin peak concentrations (169 vs. 89mg/L; P=0.002), whereas significantly higher steady-state concentrations were observed in CI patients (83 vs. 57mg/L; P=0.04). Total clearance and clearance not mediated by CVVH were significantly higher with CI administration [median (interquartile range), 1.0 (0.7-1.1) and 0.8 (0.6-1.0)mL/kg/min; P=0.001 and 0.001, respectively]. The estimated unbound piperacillin concentrations were four times above the target susceptibility breakpoint (16mg/L) for the entire dosing interval (100%fT>4xMIC) in 87.5% of patients receiving CI administration (sampling occasion 1), compared with 62.5% of IB patients achieving the desired target (50%fT>4xMIC). Compared with IB dosing, and despite similar CVVH settings, CI administration of piperacillin results in a pharmacokinetic profile that may optimise outcomes for less susceptible pathogens., (Copyright © 2015 Elsevier B.V. and the International Society of Chemotherapy. All rights reserved.)