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Article ; Online: Potential Aerosol Generation by Bronchoscopy And Intubation: Another Piece in the Puzzle.

Ling, Lowell / Gomersall, Charles David

2020 Volume 158, Issue 6, Page(s) 2251–2252

MeSH term(s)	Aerosols ; Bronchoscopy ; Humans ; Intubation, Intratracheal
Chemical Substances	Aerosols
Language	English
Publishing date	2020-11-05
Publishing country	United States
Document type	Editorial ; Comment
ZDB-ID	1032552-9
ISSN	1931-3543 ; 0012-3692
ISSN (online)	1931-3543
ISSN	0012-3692
DOI	10.1016/j.chest.2020.08.2089
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Article ; Online: Therapeutic drug monitoring of carbapenem antibiotics in critically ill patients: an overview of principles, recommended dosing regimens, and clinical outcomes.

Joynt, Gavin Matthew / Ling, Lowell / Wong, Wai Tat / Lipman, Jeffrey

Expert review of clinical pharmacology

2023 Volume 16, Issue 8, Page(s) 703–714

Abstract: Introduction: The importance of antibiotic treatment for sepsis in critically ill septic patients is well established. Consistently achieving the dose of antibiotics required to optimally kill bacteria, minimize the development of resistance, and avoid ... ...

Abstract	Introduction: The importance of antibiotic treatment for sepsis in critically ill septic patients is well established. Consistently achieving the dose of antibiotics required to optimally kill bacteria, minimize the development of resistance, and avoid toxicity is challenging. The increasing understanding of the pharmacokinetic and pharmacodynamic (PK/PD) characteristics of antibiotics, and the effects of critical illness on key PK/PD parameters, is gradually re-shaping how antibiotics are dosed in critically ill patients. Areas covered: The PK/PD characteristics of commonly used carbapenem antibiotics, the principles of the application of therapeutic drug monitoring (TDM), and current as well as future methods of utilizing TDM to optimally devise dosing regimens will be reviewed. The limitations and evidence-base supporting the use of carbapenem TDM to improve outcomes in critically ill patients will be examined. Expert opinion: It is important to understand the principles of TDM in order to correctly inform dosing regimens. Although the concept of TDM is attractive, and the ability to utilize PK software to optimize dosing in the near future is expected to rapidly increase clinicians' ability to meet pre-defined PK/PD targets more accurately, current evidence provides only limited support for the use of TDM to guide carbapenem dosing in critically ill patients.
MeSH term(s)	Humans ; Carbapenems/adverse effects ; Critical Illness/therapy ; Drug Monitoring ; Anti-Bacterial Agents ; Sepsis/drug therapy
Chemical Substances	Carbapenems ; Anti-Bacterial Agents
Language	English
Publishing date	2023-03-27
Publishing country	England
Document type	Journal Article
ISSN	1751-2441
ISSN (online)	1751-2441
DOI	10.1080/17512433.2023.2194629
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Article: A Narrative Review on the Approach to Antimicrobial Use in Ventilated Patients with Multidrug Resistant Organisms in Respiratory Samples-To Treat or Not to Treat? That Is the Question.

Ling, Lowell / Wong, Wai-Tat / Lipman, Jeffrey / Joynt, Gavin Matthew

Antibiotics (Basel, Switzerland)

2022 Volume 11, Issue 4

Abstract: Multidrug resistant organisms (MDRO) are commonly isolated in respiratory specimens taken from mechanically ventilated patients. The purpose of this narrative review is to discuss the approach to antimicrobial prescription in ventilated patients who have ...

Abstract	Multidrug resistant organisms (MDRO) are commonly isolated in respiratory specimens taken from mechanically ventilated patients. The purpose of this narrative review is to discuss the approach to antimicrobial prescription in ventilated patients who have grown a new MDRO isolate in their respiratory specimen. A MEDLINE and PubMed literature search using keywords "multidrug resistant organisms", "ventilator-associated pneumonia" and "decision making", "treatment" or "strategy" was used to identify 329 references as background for this review. Lack of universally accepted diagnostic criteria for ventilator-associated pneumonia, or ventilator-associated tracheobronchitis complicates treatment decisions. Consideration of the clinical context including signs of respiratory infection or deterioration in respiratory or other organ function is essential. The higher the quality of respiratory specimens or the presence of bacteremia would suggest the MDRO is a true pathogen, rather than colonization, and warrants antimicrobial therapy. A patient with higher severity of illness has lower safety margins and may require initiation of antimicrobial therapy until an alternative diagnosis is established. A structured approach to the decision to treat with antimicrobial therapy is proposed.
Language	English
Publishing date	2022-03-27
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2681345-2
ISSN	2079-6382
ISSN	2079-6382
DOI	10.3390/antibiotics11040452
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Article ; Online: Deep reinforcement learning approaches for global public health strategies for COVID-19 pandemic.

Gloria Hyunjung Kwak / Lowell Ling / Pan Hui

PLoS ONE, Vol 16, Iss 5, p e

2021 Volume 0251550

Abstract: Background Unprecedented public health measures have been used during this coronavirus 2019 (COVID-19) pandemic to control the spread of SARS-CoV-2 virus. It is a challenge to implement timely and appropriate public health interventions. Methods and ... ...

Abstract	Background Unprecedented public health measures have been used during this coronavirus 2019 (COVID-19) pandemic to control the spread of SARS-CoV-2 virus. It is a challenge to implement timely and appropriate public health interventions. Methods and findings Population and COVID-19 epidemiological data between 21st January 2020 to 15th November 2020 from 216 countries and territories were included with the implemented public health interventions. We used deep reinforcement learning, and the algorithm was trained to enable agents to try to find optimal public health strategies that maximized total reward on controlling the spread of COVID-19. The results suggested by the algorithm were analyzed against the actual timing and intensity of lockdown and travel restrictions. Early implementations of the actual lockdown and travel restriction policies, usually at the time of local index case were associated with less burden of COVID-19. In contrast, our agent suggested to initiate at least minimal intensity of lockdown or travel restriction even before or on the day of the index case in each country and territory. In addition, the agent mostly recommended a combination of lockdown and travel restrictions and higher intensity policies than the policies implemented by governments, but did not always encourage rapid full lockdown and full border closures. The limitation of this study was that it was done with incomplete data due to the emerging COVID-19 epidemic, inconsistent testing and reporting. In addition, our research focuses only on population health benefits by controlling the spread of COVID-19 without balancing the negative impacts of economic and social consequences. Interpretation Compared to actual government implementation, our algorithm mostly recommended earlier intensity of lockdown and travel restrictions. Reinforcement learning may be used as a decision support tool for implementation of public health interventions during COVID-19 and future pandemics.
Keywords	Medicine ; R ; Science ; Q
Subject code	300
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Deep reinforcement learning approaches for global public health strategies for COVID-19 pandemic.

Kwak, Gloria Hyunjung / Ling, Lowell / Hui, Pan

PloS one

2021 Volume 16, Issue 5, Page(s) e0251550

Abstract: Background: Unprecedented public health measures have been used during this coronavirus 2019 (COVID-19) pandemic to control the spread of SARS-CoV-2 virus. It is a challenge to implement timely and appropriate public health interventions.: Methods and ...

Abstract	Background: Unprecedented public health measures have been used during this coronavirus 2019 (COVID-19) pandemic to control the spread of SARS-CoV-2 virus. It is a challenge to implement timely and appropriate public health interventions. Methods and findings: Population and COVID-19 epidemiological data between 21st January 2020 to 15th November 2020 from 216 countries and territories were included with the implemented public health interventions. We used deep reinforcement learning, and the algorithm was trained to enable agents to try to find optimal public health strategies that maximized total reward on controlling the spread of COVID-19. The results suggested by the algorithm were analyzed against the actual timing and intensity of lockdown and travel restrictions. Early implementations of the actual lockdown and travel restriction policies, usually at the time of local index case were associated with less burden of COVID-19. In contrast, our agent suggested to initiate at least minimal intensity of lockdown or travel restriction even before or on the day of the index case in each country and territory. In addition, the agent mostly recommended a combination of lockdown and travel restrictions and higher intensity policies than the policies implemented by governments, but did not always encourage rapid full lockdown and full border closures. The limitation of this study was that it was done with incomplete data due to the emerging COVID-19 epidemic, inconsistent testing and reporting. In addition, our research focuses only on population health benefits by controlling the spread of COVID-19 without balancing the negative impacts of economic and social consequences. Interpretation: Compared to actual government implementation, our algorithm mostly recommended earlier intensity of lockdown and travel restrictions. Reinforcement learning may be used as a decision support tool for implementation of public health interventions during COVID-19 and future pandemics.
MeSH term(s)	COVID-19/epidemiology ; COVID-19/prevention & control ; Communicable Disease Control ; Deep Learning ; Global Health ; Humans ; Pandemics ; Public Health ; SARS-CoV-2/isolation & purification
Language	English
Publishing date	2021-05-13
Publishing country	United States
Document type	Journal Article
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0251550
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Article ; Online: A narrative review on antimicrobial therapy in septic shock: updates and controversies.

Ling, Lowell / Joynt, Gavin Matthew / Lipman, Jeffrey

Current opinion in anaesthesiology

2020 Volume 34, Issue 2, Page(s) 92–98

Abstract: Purpose of review: Antibiotics are an essential treatment for septic shock. This review provides an overview of the key issues in antimicrobial therapy for septic shock. We include a summary of available evidence with an emphasis on data published in ... ...

Abstract	Purpose of review: Antibiotics are an essential treatment for septic shock. This review provides an overview of the key issues in antimicrobial therapy for septic shock. We include a summary of available evidence with an emphasis on data published in the last few years. Recent findings: We examine apparently contradictory data supporting the importance of minimizing time to antimicrobial therapy in sepsis, discuss approaches to choosing appropriate antibiotics, and review the importance and challenges presented by antimicrobial dosing. Lastly, we evaluate the evolving concepts of de-escalation, and optimization of the duration of antimicrobials. Summary: The topics discussed in this review provide background to key clinical decisions in antimicrobial therapy for septic shock: timing, antibiotic choice, dosage, de-escalation, and duration. Although acknowledging some controversy, antimicrobial therapy in septic shock should be delivered early, be of the adequate spectrum, appropriately and individually dosed, rationalized when possible, and of minimal effective duration.
MeSH term(s)	Anti-Bacterial Agents/therapeutic use ; Humans ; Shock, Septic/drug therapy
Chemical Substances	Anti-Bacterial Agents
Language	English
Publishing date	2020-11-26
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	645203-6
ISSN	1473-6500 ; 0952-7907
ISSN (online)	1473-6500
ISSN	0952-7907
DOI	10.1097/ACO.0000000000000954
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Zs.A 2564: Show issues

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Article ; Online: Predicting the Need For Vasopressors in the Intensive Care Unit Using an Attention Based Deep Learning Model.

Kwak, Gloria Hyunjung / Ling, Lowell / Hui, Pan

Shock (Augusta, Ga.)

2020 Volume 56, Issue 1, Page(s) 73–79

Abstract: Background: Previous models on prediction of shock mostly focused on septic shock and often required laboratory results in their models. The purpose of this study was to use deep learning approaches to predict vasopressor requirement for critically ill ... ...

Abstract	Background: Previous models on prediction of shock mostly focused on septic shock and often required laboratory results in their models. The purpose of this study was to use deep learning approaches to predict vasopressor requirement for critically ill patients within 24 h of intensive care unit (ICU) admission using only vital signs. Methods: We used data from the Medical Information Mart for Intensive Care III database and the eICU Collaborative Research Database to develop a vasopressor prediction model. We performed systematic data preprocessing using matching of cohorts, oversampling, and imputation to control for bias, class imbalance, and missing data. Bidirectional long short-term memory (Bi-LSTM), a multivariate time series model, was used to predict the need for vasopressor therapy using serial physiological data collected 21 h prior to prediction time. Results: Using data from 10,941 critically ill patients from 209 ICUs, our model achieved an initial area under the curve of 0.96 (95% CI 0.96-0.96) to predict the need for vasopressor therapy in 2 h within the first day of ICU admission. After matching to control class imbalance, the Bi-LSTM model had area under the curve of 0.83 (95% CI 0.82-0.83). Heart rate, respiratory rate, and mean arterial pressure contributed most to the model. Conclusions: We used Bi-LSTM to develop a model to predict the need for vasopressor for critically ill patients for the first 24 h of ICU admission. With attention mechanism, respiratory rate, mean arterial pressure, and heart rate were identified as key sequential determinants of vasopressor requirements.
MeSH term(s)	Aged ; Cohort Studies ; Critical Illness/therapy ; Deep Learning ; Female ; Humans ; Intensive Care Units ; Male ; Middle Aged ; Models, Theoretical ; Needs Assessment ; Retrospective Studies ; Vasoconstrictor Agents/therapeutic use ; Vital Signs
Chemical Substances	Vasoconstrictor Agents
Language	English
Publishing date	2020-11-30
Publishing country	United States
Document type	Journal Article ; Multicenter Study
ZDB-ID	1185432-7
ISSN	1540-0514 ; 1073-2322
ISSN (online)	1540-0514
ISSN	1073-2322
DOI	10.1097/SHK.0000000000001692
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Zs.A 3985: Show issues

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Article ; Online: Weaning adult patients with cardiogenic shock on veno-arterial extracorporeal membrane oxygenation by pump-controlled retrograde trial off.

Ling, Lowell / Chan, Kai Man

Perfusion

2018 Volume 33, Issue 5, Page(s) 339–345

Abstract: Background: There is a lack of consensus on the timing of veno-arterial extracorporeal membrane oxygenation (VA-ECMO) liberation. VA-ECMO weaning usually consists of serial decrements until an idling flow is achieved, supported by echocardiographic and ... ...

Abstract	Background: There is a lack of consensus on the timing of veno-arterial extracorporeal membrane oxygenation (VA-ECMO) liberation. VA-ECMO weaning usually consists of serial decrements until an idling flow is achieved, supported by echocardiographic and haemodynamic assessments. Even with minimal idling flow, right ventricular (RV) preload is reduced and, hence, right heart function is not fully tested under adequate loading conditions. Following the use of a novel technique called Pump Controlled Retrograde Trial Off (PCRTO) in neonate VA-ECMO weaning, we report the use of this technique in seven adult patients on VA-ECMO. Methods: We retrospectively reviewed all adult VA-ECMO patients treated at a tertiary teaching hospital in Hong Kong since 2010. Clinical data, including diagnosis, echocardiography findings, ECMO configuration, PCRTO settings, survival after veno-arterial ECMO (SAVE) score and outcomes, were collected. Mortality and death due to cardiac failure was compared between PCRTO and conventional weaning. Results: Seven patients underwent PCRTO, with a mean SAVE score of -4.4 ± 5.9. All seven patients were successfully decannulated without haemodynamic deterioration. In all cases, no clots or fibrin deposits were found in the circuit after the trial. There was no difference in mean SAVE scores among the seven patients in PCRTO and the 23 patients in the conventional group (-3.6, 95% CI -8.8 to 1.5). The number of deaths due to cardiac failure in the PCRTO group and the conventional group were 0 and 3, respectively (0% vs. 13%, p=0.99). Mortality after decannulation for PCRTO was 42.9% vs. conventional weaning 34.8% (p=0.99). Conclusion: Our study suggests that PCRTO is a simple, safe and reversible alternative weaning method. It may have a particular role in the assessment of patients who have marginal recovery and right heart failure. Prospective controlled studies are needed to establish the potential role of PCRTO in the liberation of patients from VA-ECMO support.
MeSH term(s)	Adult ; Aged ; Catheterization/adverse effects ; Catheterization/instrumentation ; Catheterization/methods ; Catheterization/mortality ; Equipment Design ; Extracorporeal Membrane Oxygenation/adverse effects ; Extracorporeal Membrane Oxygenation/instrumentation ; Extracorporeal Membrane Oxygenation/methods ; Extracorporeal Membrane Oxygenation/mortality ; Female ; Heart Failure/etiology ; Heart Failure/mortality ; Hemodynamics ; Hospital Mortality ; Humans ; Male ; Middle Aged ; Retrospective Studies ; Shock, Cardiogenic/complications ; Shock, Cardiogenic/mortality ; Shock, Cardiogenic/physiopathology ; Shock, Cardiogenic/therapy
Language	English
Publishing date	2018-02-07
Publishing country	England
Document type	Clinical Trial ; Journal Article
ZDB-ID	645038-6
ISSN	1477-111X ; 0267-6591
ISSN (online)	1477-111X
ISSN	0267-6591
DOI	10.1177/0267659118755888
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Article: Blood microbial signatures associated with mortality in patients with sepsis: A pilot study.

Chen, Huarong / Liu, Weixin / Coker, Olabisi Oluwabukola / Qin, Na / Chen, Hongyan / Wang, Yifei / Liu, Xiaodong / Zhang, Lin / Choi, Gordon Y S / Wong, Wai Tat / Leung, Czarina C H / Ling, Lowell / Hui, Mamie / Gin, Tony / Wong, Sunny Hei / Chan, Matthew Tak Vai / Wu, William Ka Kei

Heliyon

2024 Volume 10, Issue 8, Page(s) e29572

Abstract: Sepsis is a life-threatening illness caused by the dysregulated host response to infection. Nevertheless, our current knowledge of the microbial landscape in the blood of septic patients is still limited. Next-generation sequencing (NGS) is a sensitive ... ...

Abstract	Sepsis is a life-threatening illness caused by the dysregulated host response to infection. Nevertheless, our current knowledge of the microbial landscape in the blood of septic patients is still limited. Next-generation sequencing (NGS) is a sensitive method to quantitatively characterize microbiomes at various sites of the human body. In this study, we analyzed the blood microbial DNA of 22 adult patients with sepsis and 3 healthy subjects. The presence of non-human DNA was identified in both healthy and septic subjects. Septic patients had a markedly altered microbial DNA profile compared to healthy subjects over α- and β-diversity. Unexpectedly, the patients could be further divided into two subgroups (C1 and C2) based on β-diversity analysis. C1 patients showed much higher bacteria, viruses, fungi, and archaea abundance, and a higher level of α-diversity (Chao1, Observed and Shannon index) than both C2 patients and healthy subjects. The most striking difference was seen in the case of
Language	English
Publishing date	2024-04-20
Publishing country	England
Document type	Journal Article
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2024.e29572
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Article ; Online: Predicting the need for intubation in the first 24 h after critical care admission using machine learning approaches.

Siu, Benjamin Ming Kit / Kwak, Gloria Hyunjung / Ling, Lowell / Hui, Pan

Scientific reports

2020 Volume 10, Issue 1, Page(s) 20931

Abstract: Early and accurate prediction of the need for intubation may provide more time for preparation and increase safety margins by avoiding high risk late intubation. This study evaluates whether machine learning can predict the need for intubation within 24 ... ...

Abstract	Early and accurate prediction of the need for intubation may provide more time for preparation and increase safety margins by avoiding high risk late intubation. This study evaluates whether machine learning can predict the need for intubation within 24 h using commonly available bedside and laboratory parameters taken at critical care admission. We extracted data from 2 large critical care databases (MIMIC-III and eICU-CRD). Missing variables were imputed using autoencoder. Machine learning classifiers using logistic regression and random forest were trained using 60% of the data and tested using the remaining 40% of the data. We compared the performance of logistic regression and random forest models to predict intubation in critically ill patients. After excluding patients with limitations of therapy and missing data, we included 17,616 critically ill patients in this retrospective cohort. Within 24 h of admission, 2,292 patients required intubation, whilst 15,324 patients were not intubated. Blood gas parameters (P
MeSH term(s)	Aged ; Algorithms ; Calibration ; Cohort Studies ; Critical Care ; Female ; Hospitalization ; Humans ; Intubation, Intratracheal ; Machine Learning ; Male ; Middle Aged ; ROC Curve
Language	English
Publishing date	2020-12-01
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-020-77893-3
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