40 results found
Rawson TM, Antcliffe D, Wilson R, et al., 2023, Management of bacterial and fungal infections in the ICU: diagnosis, treatment, and prevention recommendations, Infection and Drug Resistance, Vol: 16, Pages: 2709-2726, ISSN: 1178-6973
Bacterial and fungal infections are common issues for patients in the intensive care unit (ICU). Large, multinational point prevalence surveys have identified that up to 50% of ICU patients have a diagnosis of bacterial or fungal infection at any one time. Infection in the ICU is associated with its own challenges. Causative organisms often harbour intrinsic and acquired mechanisms of drug-resistance, making empiric and targeted antimicrobial selection challenging. Infection in the ICU is associated with worse clinical outcomes for patients. We review the epidemiology of bacterial and fungal infection in the ICU. We discuss risk factors for acquisition, approaches to diagnosis and management, and common strategies for the prevention of infection.
Warner B, Harry A, Wells M, et al., 2023, Escalation to intensive care for the older patient. An exploratory qualitative study of patients aged over 65 years and their next of kin during the COVID-19 pandemic: the ESCALATE study, Age and Ageing, Vol: 52, Pages: 1-13, ISSN: 0002-0729
Background: Older people comprise the majority of hospital medical inpatients so decision-making regarding admission of this cohort to the intensive care unit (ICU) is important. ICU can be perceived by clinicians as overly burdensome for patients and loved ones, and long-term impact on quality of life considered unacceptable, effecting potential bias against admitting older people to ICU. The COVID-19 pandemic highlighted the challenge of selecting those who could most benefit from ICU. Objective: This qualitative study aimed to explore the views and recollections of escalation to ICU from older patients (aged ≥65 years) and next of kin (NoK)who experienced a COVID-19 ICU admission. Setting: The main site was a large NHS Trust in London, which experienced a high burden of COVID-19 cases. Subjects: 30 participants, comprising 12 patients, 7 NoK of survivor and 11 NoK of deceased. Methods: Semi-structured interviews with thematic analysis using a framework approach. Results: There were five major themes: Inevitability, Disconnect, Acceptance, Implications for future decision making and Unique impact of the COVID-19 pandemic. Life was highly valued and ICU perceived to be the only option. Prior understanding of ICU and admission decision-making explanations were limited. Despite benefit of hindsight, having experienced an ICU admission and its consequences, most could not conceptualise thresholds for future acceptable treatment outcomes.Conclusions: In this study of patients ≥65 years and their NoK experiencing an acute ICU admission, survival was prioritised. Despite the ordeal of an ICU stay and its aftermath, the decision to admit and sequelae were considered acceptable.
Cleasby C, Marshall T, Gordon AC, et al., 2023, The effect of vasopressin and hydrocortisone on cytokine trajectories: exploratory analysis from the VANISH trial, Intensive Care Medicine, Vol: 49, Pages: 241-243, ISSN: 0342-4642
Antcliffe DB, Burnham KL, Al-Beidh F, et al., 2022, Transcriptomic Signatures in Sepsis and a Differential Response to Steroids. From the VANISH Randomized Trial(vol 199, pg 980 year 2019), AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, Vol: 206, Pages: 1572-1573, ISSN: 1073-449X
Gordon A, 2022, Erratum: transcriptomic signatures in sepsis and a differential response to steroids. from the VANISH randomized trial., American Journal of Respiratory and Critical Care Medicine, Vol: 206, Pages: 1572-1573, ISSN: 1073-449X
Komorowski M, Green A, Tatham KC, et al., 2022, Sepsis biomarkers and diagnostic tools with a focus on machine learning., EBioMedicine, Vol: 86, Pages: 1-10, ISSN: 2352-3964
Over the last years, there have been advances in the use of data-driven techniques to improve the definition, early recognition, subtypes characterisation, prognostication and treatment personalisation of sepsis. Some of those involve the discovery or evaluation of biomarkers or digital signatures of sepsis or sepsis sub-phenotypes. It is hoped that their identification may improve timeliness and accuracy of diagnosis, suggest physiological pathways and therapeutic targets, inform targeted recruitment into clinical trials, and optimise clinical management. Given the complexities of the sepsis response, panels of biomarkers or models combining biomarkers and clinical data are necessary, as well as specific data analysis methods, which broadly fall under the scope of machine learning. This narrative review gives a brief overview of the main machine learning techniques (mainly in the realms of supervised and unsupervised methods) and published applications that have been used to create sepsis diagnostic tools and identify biomarkers.
Bolton W, Rawson T, Hernandez B, et al., 2022, Machine learning and synthetic outcome estimation for individualised antimicrobial cessation, Frontiers in Digital Health, Vol: 4, Pages: 1-12, ISSN: 2673-253X
The decision on when it is appropriate to stop antimicrobial treatment in an individual patient is complex and under-researched. Ceasing too early can drive treatment failure, while excessive treatment risks adverse events. Under- and over-treatment can promote the development of antimicrobial resistance (AMR). We extracted routinely collected electronic health record data from the MIMIC-IV database for 18,988 patients (22,845 unique stays) who received intravenous antibiotic treatment during an intensive care unit (ICU) admission. A model was developed that utilises a recurrent neural network autoencoder and a synthetic control-based approach to estimate patients’ ICU length of stay (LOS) and mortality outcomes for any given day, under the alternative scenarios of if they were to stop vs. continue antibiotic treatment. Control days where our model should reproduce labels demonstrated minimal difference for both stopping and continuing scenarios indicating estimations are reliable (LOS results of 0.24 and 0.42 days mean delta, 1.93 and 3.76 root mean squared error, respectively). Meanwhile, impact days where we assess the potential effect of the unobserved scenario showed that stopping antibiotic therapy earlier had a statistically significant shorter LOS (mean reduction 2.71 days, p-value <0.01). No impact on mortality was observed. In summary, we have developed a model to reliably estimate patient outcomes under the contrasting scenarios of stopping or continuing antibiotic treatment. Retrospective results are in line with previous clinical studies that demonstrate shorter antibiotic treatment durations are often non-inferior. With additional development into a clinical decision support system, this could be used to support individualised antimicrobial cessation decision-making, reduce the excessive use of antibiotics, and address the problem of AMR.
Cano-Gamez E, Burnham KL, Goh C, et al., 2022, An immune dysfunction score for stratification of patients with acute infection based on whole-blood gene expression., Science Translational Medicine, Vol: 14, Pages: 1-15, ISSN: 1946-6234
Dysregulated host responses to infection can lead to organ dysfunction and sepsis, causing millions of global deaths each year. To alleviate this burden, improved prognostication and biomarkers of response are urgently needed. We investigated the use of whole-blood transcriptomics for stratification of patients with severe infection by integrating data from 3149 samples from patients with sepsis due to community-acquired pneumonia or fecal peritonitis admitted to intensive care and healthy individuals into a gene expression reference map. We used this map to derive a quantitative sepsis response signature (SRSq) score reflective of immune dysfunction and predictive of clinical outcomes, which can be estimated using a 7- or 12-gene signature. Last, we built a machine learning framework, SepstratifieR, to deploy SRSq in adult and pediatric bacterial and viral sepsis, H1N1 influenza, and COVID-19, demonstrating clinically relevant stratification across diseases and revealing some of the physiological alterations linking immune dysregulation to mortality. Our method enables early identification of individuals with dysfunctional immune profiles, bringing us closer to precision medicine in infection.
Arkell P, Wilson R, Watkins K, et al., 2022, Application of therapeutic drug monitoring to the treatment of bacterial central nervous system infection: a scoping review, Journal of Antimicrobial Chemotherapy, Vol: 77, Pages: 3408-3413, ISSN: 0305-7453
BackgroundBacterial central nervous system (CNS) infection is challenging to treat and carries high risk of recurrence, morbidity, and mortality. Low CNS penetration of antibiotics may contribute to poor clinical outcomes from bacterial CNS infections. The current application of therapeutic drug monitoring (TDM) to management of bacterial CNS infection was reviewed.MethodsStudies were included if they described adults treated for a suspected/confirmed bacterial CNS infection and had antibiotic drug concentration(s) determined that affected individual treatment.ResultsOne-hundred-and-thirty-six citations were retrieved. Seventeen manuscripts were included describing management of 68 patients. TDM for vancomycin (58/68) and the beta-lactams (29/68) was most common. Timing of clinical sampling varied widely between studies and across different antibiotics. Methods for setting individual PK-PD targets, determining parameters and making treatment changes varied widely and were sometimes unclear.DiscussionDespite increasing observational data showing low CNS penetration of various antibiotics, there are few clinical studies describing practical implementation of TDM in management of CNS infection. Lack of consensus around clinically relevant CSF PK-PD targets and protocols for dose-adjustment may contribute. Standardised investigation of TDM as a tool to improve treatment is required, especially as innovative drug concentration-sensing and PK-PD modelling technologies are emerging. Data generated at different centres offering TDM should be open access and aggregated to enrich understanding and optimize application.
Mi Y, Burnham KL, Charles PD, et al., 2022, High-throughput mass spectrometry maps the sepsis plasma proteome and differences in response
<jats:title>Summary</jats:title><jats:p>Sepsis, the dysregulated host response to infection causing life-threatening organ dysfunction, is an unmet global health challenge. Here we apply high-throughput tandem mass spectrometry to delineate the plasma proteome for sepsis and comparator groups (non-infected critical illness, post-operative inflammation and healthy volunteers) involving 2622 samples and 4553 liquid chromatography-mass spectrometry analyses in a single batch, at 100 samples/day. We show how this scale of data can establish shared and specific proteins, pathways and co-expression modules in sepsis, and be integrated with paired leukocyte transcriptomic data (n=837 samples) using matrix decomposition. We map the landscape of the host response in sepsis including changes over time, and identify features relating to etiology, clinical phenotypes and severity. This work reveals novel subphenotypes informative for sepsis response state, disease processes and outcome, highlights potential biomarkers, pathways and processes for drug targets, and advances a systems-based precision medicine approach to sepsis.</jats:p>
Antcliffe DB, Mi Y, Santhakumaran S, et al., 2022, Inflammatory sub-phenotypes in sepsis: relationship to outcomes, treatment effect and transcriptomic sub-phenotypes
<jats:title>Abstract</jats:title><jats:sec><jats:title>Rationale</jats:title><jats:p>Heterogeneity of sepsis limits discovery and targeting of treatments. Clustering approaches in critical illness have identified patient groups who may respond differently to therapies. These include in acute respiratory distress syndrome (ARDS) two inflammatory sub-phenotypes, using latent class analysis (LCA), and in sepsis two Sepsis Response Signatures (SRS), based on transcriptome profiling. It is unknown if inflammatory sub-phenotypes such as those identified in ARDS are present in sepsis and how sub-phenotypes defined with different techniques compare.</jats:p></jats:sec><jats:sec><jats:title>Objectives</jats:title><jats:p>To identify inflammatory sub-phenotypes in sepsis using LCA and assess if these show differential treatment responses. These sub-phenotypes were compared to hierarchical clusters based on inflammatory mediators and to SRS sub-phenotypes.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>LCA was applied to clinical and biomarker data from two septic shock randomized trials. VANISH compared norepinephrine to vasopressin and hydrocortisone to placebo and LeoPARDS compared levosimendan to placebo. Hierarchical cluster analysis (HCA) was applied to 65, 21 and 11 inflammatory mediators measured in patients from the GAinS (n=124), VANISH (n=155) and LeoPARDS (n=484) studies.</jats:p></jats:sec><jats:sec><jats:title>Measurements and Main Results</jats:title><jats:p>LCA and HCA identified a sub-phenotype of patients with high cytokine levels and worse organ dysfunction and survival, with no interaction between LCA classes and trial treatment responses. Comparison of inflammatory and transcriptomic sub-phenotypes revealed some similarities but without sufficient overlap that they are interchangeable.</jat
Hussain H, Vutipongsatorn K, Jimenez B, et al., 2022, Patient stratification in sepsis: Using metabolomics to detect clinical phenotypes, sub-phenotypes and therapeutic response, Metabolites, Vol: 12, Pages: 1-42, ISSN: 2218-1989
Infections are common and need minimal treatment; however, occasionally, due to inappropriate immune response, they can develop into a life-threatening condition known as sepsis. Sepsis is a global concern with high morbidity and mortality. There has been little advancement in the treatment of sepsis, outside of antibiotics and supportive measures. Some of the difficulty in identifying novel therapies is the heterogeneity of the condition. Metabolic phenotyping has great potential for gaining understanding of this heterogeneity and how the metabolic fingerprints of patients with sepsis differ based on survival, organ dysfunction, disease severity, type of infection, treatment or causative organism. Moreover, metabolomics offers potential for patient stratification as metabolic profiles obtained from analytical platforms can reflect human individuality and phenotypic variation. This article reviews the most relevant metabolomic studies in sepsis and aims to provide an overview of the metabolic derangements in sepsis and how metabolic phenotyping has been used to identify sub-groups of patients with this condition. Finally, we consider the new avenues that metabolomics could open, exploring novel phenotypes and untangling the heterogeneity of sepsis, by looking at advances made in the field with other -omics technologies.
Cano-Gamez E, Burnham KL, Goh C, et al., 2022, An immune dysfunction score for stratification of patients with acute infection based on whole blood gene expression
<jats:title>Abstract</jats:title><jats:p>Dysregulated host responses to infection can lead to organ dysfunction and sepsis, causing millions of deaths globally each year. To alleviate this burden, improved prognostication and biomarkers of response are urgently needed. We investigated the use of whole blood transcriptomics for stratification of patients with severe infection by integrating data from 3,149 samples of sepsis patients and healthy individuals into a gene expression reference map. We used this map to derive a quantitative sepsis response signature (SRSq) score reflective of immune dysfunction and predictive of clinical outcomes, which can be estimated using a 19-gene signature. Finally, we built a machine learning framework, SepstratifieR, to deploy SRSq in sepsis, H1N1 influenza, and COVID-19, demonstrating clinically relevant stratification across diseases and revealing the physiological alterations linking immune dysregulation to mortality. Our method enables early identification of individuals with dysfunctional immune profiles, thus bringing us closer to precision medicine in infection.</jats:p>
Arkell P, Wilson R, Antcliffe DB, et al., 2022, A pilot observational study of CSF vancomycin therapeutic drug monitoring during the treatment of nosocomial ventriculitis., Journal of Infection, ISSN: 0163-4453
Warner B, Harry A, Brett S, et al., 2022, The end is just the beginning: involvement of bereaved next of kin in qualitative research, BMJ Supportive & Palliative Care, Vol: 12, ISSN: 2045-4368
Jones T, Janani L, Gordon A, et al., 2022, A novel role for cytochrome P450 epoxygenase metabolites in septic shock, Critical Care Explorations, Vol: 4, ISSN: 2639-8028
Objectives Oxylipins are oxidative breakdown products of cell membrane fatty acids. Animal models have demonstrated that oxylipins generated by the P450 epoxygenase pathway may be implicated in septic shock pathology. However, these mediators are relatively unexplored in humans with septic shock. We aimed to determine if there were patterns of oxylipins that were associated with 28-day septic shock mortality and organ dysfunction. Design Retrospective analysis of samples collected during the Vasopressin vs. Norepinephrine as Initial Therapy in Septic Shock trial.Setting Intensive Care Units in the United KingdomPatients Adults recruited within six hours of onset of septic shock. Interventions Trial interventions were not considered in this analysis.Measurements and Main Results Oxylipin profiling was performed on 404 serum samples from 152 patients using liquid chromatography-mass spectrometry. Non-survivors were found to have higher levels of 14,15-dihydroxyeicosatrienoic acid at baseline (DHET) than survivors (p=0.02). Patients with 14,15-DHET levels above the lower limit of quantification of the assay were more likely to die than patients with levels below this limit (Hazard Ratio 2.3, 95% CI 1.2-4.5). Patients with measurable 14,15-DHET had higher levels of organ dysfunction and fewer renal failure free days than those in whom it was unmeasurable. Considering samples collected over the first week of intensive care stay, measurable levels of DHET species were associated with higher daily SOFA scores which appeared to be accounted for predominantly by the liver component. Measurable 14,15-DHET showed positive correlation with bilirubin (rs=0.38, p<0.001) and lactate (rs=0.27, p=0.001).Conclusions The P450 epoxygenase-derived DHET species of oxylipins were associated with organ, particularly liver, dysfunction in septic shock and 14,15-DHET was associated with septic shock mortality. These results support further investigation into the role of the P450 epoxygena
Patel BV, Haar S, Handslip R, et al., 2021, Natural history, trajectory, and management of mechanically ventilated COVID-19 patients in the United Kingdom, Intensive Care Medicine, Vol: 47, Pages: 549-565, ISSN: 0342-4642
PurposeThe trajectory of mechanically ventilated patients with coronavirus disease 2019 (COVID-19) is essential for clinical decisions, yet the focus so far has been on admission characteristics without consideration of the dynamic course of the disease in the context of applied therapeutic interventions.MethodsWe included adult patients undergoing invasive mechanical ventilation (IMV) within 48 h of intensive care unit (ICU) admission with complete clinical data until ICU death or discharge. We examined the importance of factors associated with disease progression over the first week, implementation and responsiveness to interventions used in acute respiratory distress syndrome (ARDS), and ICU outcome. We used machine learning (ML) and Explainable Artificial Intelligence (XAI) methods to characterise the evolution of clinical parameters and our ICU data visualisation tool is available as a web-based widget (https://www.CovidUK.ICU).ResultsData for 633 adults with COVID-19 who underwent IMV between 01 March 2020 and 31 August 2020 were analysed. Overall mortality was 43.3% and highest with non-resolution of hypoxaemia [60.4% vs17.6%; P < 0.001; median PaO2/FiO2 on the day of death was 12.3(8.9–18.4) kPa] and non-response to proning (69.5% vs.31.1%; P < 0.001). Two ML models using weeklong data demonstrated an increased predictive accuracy for mortality compared to admission data (74.5% and 76.3% vs 60%, respectively). XAI models highlighted the increasing importance, over the first week, of PaO2/FiO2 in predicting mortality. Prone positioning improved oxygenation only in 45% of patients. A higher peak pressure (OR 1.42[1.06–1.91]; P < 0.05), raised respiratory component (OR 1.71[ 1.17–2.5]; P < 0.01) and cardiovascular component (OR 1.36 [1.04–1.75]; P < 0.05) of the sequential organ failure assessment (SOFA) score and raised lactate (OR 1.33 [0.99–1.79
Patel BV, Haar S, Handslip R, et al., 2020, Natural history, trajectory, and management of mechanically ventilated COVID-19 patients in the United Kingdom, Publisher: Cold Spring Harbor Laboratory
Background To date the description of mechanically ventilated patients with Coronavirus Disease 2019 (COVID-19) has focussed on admission characteristics with no consideration of the dynamic course of the disease. Here, we present a data-driven analysis of granular, daily data from a representative proportion of patients undergoing invasive mechanical ventilation (IMV) within the United Kingdom (UK) to evaluate the complete natural history of COVID-19.Methods We included adult patients undergoing IMV within 48 hours of ICU admission with complete clinical data until death or ICU discharge. We examined factors and trajectories that determined disease progression and responsiveness to ARDS interventions. Our data visualisation tool is available as a web-based widget (https://www.CovidUK.ICU).Findings Data for 623 adults with COVID-19 who were mechanically ventilated between 01 March 2020 and 31 August 2020 were analysed. Mortality, intensity of mechanical ventilation and severity of organ injury increased with severity of hypoxaemia. Median tidal volume per kg across all mandatory breaths was 5.6 [IQR 4.7-6.6] mL/kg based on reported body weight, but 7.0 [IQR 6.0-8.4] mL/kg based on calculated ideal body weight. Non-resolution of hypoxaemia over the first week of IMV was associated with higher ICU mortality (59.4% versus 16.3%; P<0.001). Of patients ventilated in prone position only 44% showed a positive oxygenation response. Non-responders to prone position show higher D-Dimers, troponin, cardiovascular SOFA, and higher ICU mortality (68.9% versus 29.7%; P<0.001). Multivariate analysis showed prone non-responsiveness being independently associated with higher lactate (hazard ratio 1.41, 95% CI 1.03–1.93), respiratory SOFA (hazard ratio 3.59, 95% CI 1.83–7.04); and cardiovascular SOFA score (hazard ratio 1.37, 95% CI 1.05–1.80).Interpretation A sizeable proportion of patients with progressive worsening of hypoxaemia were also refractory to evid
Antcliffe DB, Gordon AC, 2019, Why Understanding Sepsis Endotypes Is Important for Steroid Trials in Septic Shock, Critical Care Medicine, Vol: 47, Pages: 1782-1784, ISSN: 0090-3493
Antcliffe DB, Santhakumaran S, Orme RML, et al., 2019, Levosimendan in septic shock in patients with biochemical evidence of cardiac dysfunction: a subgroup analysis of the LeoPARDS randomised trial, Intensive Care Medicine, Vol: 45, Pages: 1392-1400, ISSN: 0342-4642
PurposeMyocardial dysfunction is common in sepsis but optimal treatment strategies are unclear. The inodilator, levosimendan was suggested as a possible therapy; however, the levosimendan to prevent acute organ dysfunction in Sepsis (LeoPARDS) trial found it to have no benefit in reducing organ dysfunction in septic shock. In this study we evaluated the effects of levosimendan in patients with and without biochemical cardiac dysfunction and examined its non-inotropic effects.MethodsTwo cardiac biomarkers, troponin I (cTnI) and N-terminal prohormone of brain natriuretic peptide (NT-proBNP), and five inflammatory mediators were measured in plasma from patients recruited to the LeoPARDS trial at baseline and over the first 6 days. Mean total Sequential Organ Failure Assessment (SOFA) score and 28-day mortality were compared between patients with normal and raised cTnI and NT-proBNP values, and between patients above and below median values.ResultsLevosimendan produced no benefit in SOFA score or 28-day mortality in patients with cardiac dysfunction. There was a statistically significant treatment by subgroup interaction (p = 0.04) in patients with NT-proBNP above or below the median value. Those with NT-proBNP values above the median receiving levosimendan had higher SOFA scores than those receiving placebo (mean daily total SOFA score 7.64 (4.41) vs 6.09 (3.88), mean difference 1.55, 95% CI 0.43–2.68). Levosimendan had no effect on the rate of decline of inflammatory biomarkers.ConclusionAdding levosimendan to standard care in septic shock was not associated with less severe organ dysfunction nor lower mortality in patients with biochemical evidence of cardiac dysfunction.
Antcliffe D, Burnham K, Al-Beidh F, et al., 2019, Transcriptomic signatures in sepsis and a differential response to steroids: from the VANISH randomized trial, American Journal of Respiratory and Critical Care Medicine, Vol: 199, Pages: 980-986, ISSN: 1073-449X
Rationale: There remains uncertainty about the role of corticosteroids in sepsis with clear beneficial effects on shock duration but conflicting survival effects. Two transcriptomic sepsis response signatures (SRS) have been identified. SRS1 is relatively immunosuppressed whilst SRS2 is relatively immunocompetent. Objectives: We aimed to categorized patients based on SRS endotypes to determine if these profiles influenced response to either norepinephrine or vasopressin, or to corticosteroids in septic shock. Methods: A post-hoc analysis was performed of a double-blind randomized clinical trial in septic shock (VANISH). Patients were included within 6 hours of onset of shock and were randomized to receive norepinephrine or vasopressin followed by hydrocortisone or placebo. Genome-wide gene expression profiling was performed and SRS endotype was determined using a previously established model using seven discriminant genes. Measurements and Main Results: Samples were available from 176 patients, 83 SRS1 and 93 SRS2. There was no significant interaction between SRS group and vasopressor assignment (p=0·50). However, there was an interaction between assignment to hydrocortisone or placebo, and SRS endotype (p=0·02). Hydrocortisone use was associated with increased mortality in those with an SRS2 phenotype (OR 7·9, 95%CI 1·6-39·9). Conclusions: Transcriptomic profile at onset of septic shock was associated with response to corticosteroids. Those with the immuno-competent SRS2 endotype had significantly higher mortality when given corticosteroids compared to placebo. Clinical trial registration available at www.isrctn.com, ID ISRCTN20769191.
Fiorini F, Antcliffe D, Al-Beidh F, et al., 2018, Analysis of lipoproteins in septic shock, European Society of Intensive Care Medicine Congress, Publisher: SpringerOpen, ISSN: 2197-425X
Antcliffe D, Ward J, Marshall T, et al., 2018, Multivariate analysis of cytokines in septic shock predicts outcome, European Society of Intensive Care Medicine Congress, Publisher: SpringerOpen, ISSN: 2197-425X
Antcliffe D, Al-Beidh F, Gordon A, 2018, Metabolic profiles in sepsis evolve over time, European Society of Intensive Care Medicine Congress, Publisher: SpringerOpen, ISSN: 2197-425X
O'Callaghan D, Antcliffe D, 2018, Vasodilators and antihypertensives, Oh's Intensive Care Manual, Editors: Bersten, Handy, Publisher: Elsevier, ISBN: 9780702072215
This bestselling manual covers all aspects of intensive care in sufficient detail for daily practice while keeping you up to date with the latest innovations in the field.
Antcliffe D, Wolfer A, O'Dea K, et al., 2018, Profiling inflammatory markers in patients with pneumonia on intensive care, Scientific Reports, Vol: 8, ISSN: 2045-2322
Clinical investigations lack predictive value when diagnosing pneumonia, especially when patients are ventilated and develop ventilator associated pneumonia (VAP). New tools to aid diagnosis are important to improve outcomes. This pilot study examines the potential for a panel of inflammatory mediators to aid in the diagnosis. Forty-four ventilated patients, 17 with pneumonia and 27 with brain injuries, eight of whom developed VAP, were recruited. 51 inflammatory mediators, including cytokines and oxylipins, were measured in patients’ serum using flow cytometry and mass spectrometry. The mediators could separate patients admitted to ICU with pneumonia compared to brain injury with an area under the receiver operating characteristic curve (AUROC) 0.75 (0.61–0.90). Changes in inflammatory mediators were similar in both groups over the course of ICU stay with 5,6-dihydroxyeicosatrienoic and 8,9-dihydroxyeicosatrienoic acids increasing over time and interleukin-6 decreasing. However, brain injured patients who developed VAP maintained inflammatory profiles similar to those at admission. A multivariate model containing 5,6-dihydroxyeicosatrienoic acid, 8,9-dihydroxyeicosatrienoic acid, intercellular adhesion molecule-1, interleukin-6, and interleukin-8, could differentiate patients with VAP from brain injured patients without infection (AUROC 0.94 (0.80–1.00)). The use of a selected group of markers showed promise to aid the diagnosis of VAP especially when combined with clinical data.
Antcliffe D, Fiorini F, Gordon A, 2018, Lessons from the ICU: choosing the right vasopressor, Hemodynamic Monitoring, Editors: Pinsky, Teboul, Vincent, Publisher: Springer, ISBN: 9783319692692
This book, part of the European Society of Intensive Care Medicine textbook series, teaches readers how to use hemodynamic monitoring, an essential skill for today’s intensivists.
Antcliffe D, Jimenez B, Veselkov K, et al., 2017, Metabolic profiling in patients with pneumonia on intensive care, EBioMedicine, Vol: 18, Pages: 244-253, ISSN: 2352-3964
Clinical features and investigations lack predictive value when diagnosing pneumonia, especially when patients are ventilated and when patients develop ventilator associated pneumonia (VAP). New tools to aid diagnosis are important to improve outcomes. This pilot study examines the potential for metabolic profiling to aid the diagnosis in critical care.In this prospective observational study ventilated patients with brain injuries or pneumonia were recruited in the intensive care unit and serum samples were collected soon after the start of ventilation. Metabolic profiles were produced using 1D 1H NMR spectra. Metabolic data were compared using multivariate statistical techniques including Principal Component Analysis (PCA) and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA).We recruited 15 patients with pneumonia and 26 with brain injuries, seven of whom went on to develop VAP. Comparison of metabolic profiles using OPLS-DA differentiated those with pneumonia from those with brain injuries (R2Y = 0.91, Q2Y = 0.28, p = 0.02) and those with VAP from those without (R2Y = 0.94, Q2Y = 0.27, p = 0.05). Metabolites that differentiated patients with pneumonia included lipid species, amino acids and glycoproteins.Metabolic profiling shows promise to aid in the diagnosis of pneumonia in ventilated patients and may allow a more timely diagnosis and better use of antibiotics.
Antcliffe D, Gordon AC, 2016, Metabonomics and Intensive Care, Annual Update in Intensive Care and Emergency Medicine 2016, Editors: Vincent, Publisher: Springer, Pages: 353-364, ISBN: 978-3-319-27348-8
Gordon AC, Antcliffe D, 2016, Metabonomics and intensive care, Critical Care, Vol: 20, ISSN: 1364-8535
This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency medicine 2016. Other selected articles can be found online at http://www.biomedcentral.com/collections/annualupdate2016. Further information about the Annual Update in Intensive Care and Emergency Medicine is available from http://www.springer.com/series/8901.
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