| 1. |
- Johnsson, Jesper, et al.
(författare)
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Artificial neural networks improve early outcome prediction and risk classification in out-of-hospital cardiac arrest patients admitted to intensive care
- 2020
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Ingår i: Critical Care. - : Springer Science and Business Media LLC. - 1364-8535. ; 24:1
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Pre-hospital circumstances, cardiac arrest characteristics, comorbidities and clinical status on admission are strongly associated with outcome after out-of-hospital cardiac arrest (OHCA). Early prediction of outcome may inform prognosis, tailor therapy and help in interpreting the intervention effect in heterogenous clinical trials. This study aimed to create a model for early prediction of outcome by artificial neural networks (ANN) and use this model to investigate intervention effects on classes of illness severity in cardiac arrest patients treated with targeted temperature management (TTM). METHODS: Using the cohort of the TTM trial, we performed a post hoc analysis of 932 unconscious patients from 36 centres with OHCA of a presumed cardiac cause. The patient outcome was the functional outcome, including survival at 180 days follow-up using a dichotomised Cerebral Performance Category (CPC) scale with good functional outcome defined as CPC 1-2 and poor functional outcome defined as CPC 3-5. Outcome prediction and severity class assignment were performed using a supervised machine learning model based on ANN. RESULTS: The outcome was predicted with an area under the receiver operating characteristic curve (AUC) of 0.891 using 54 clinical variables available on admission to hospital, categorised as background, pre-hospital and admission data. Corresponding models using background, pre-hospital or admission variables separately had inferior prediction performance. When comparing the ANN model with a logistic regression-based model on the same cohort, the ANN model performed significantly better (p = 0.029). A simplified ANN model showed promising performance with an AUC above 0.852 when using three variables only: age, time to ROSC and first monitored rhythm. The ANN-stratified analyses showed similar intervention effect of TTM to 33 °C or 36 °C in predefined classes with different risk of a poor outcome. CONCLUSION: A supervised machine learning model using ANN predicted neurological recovery, including survival excellently, and outperformed a conventional model based on logistic regression. Among the data available at the time of hospitalisation, factors related to the pre-hospital setting carried most information. ANN may be used to stratify a heterogenous trial population in risk classes and help determine intervention effects across subgroups.
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| 2. |
- Andersson, Peder, et al.
(författare)
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Predicting neurological outcome after out-of-hospital cardiac arrest with cumulative information; development and internal validation of an artificial neural network algorithm
- 2021
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Ingår i: Critical Care. - : Springer Science and Business Media LLC. - 1364-8535. ; 25:1
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundPrognostication of neurological outcome in patients who remain comatose after cardiac arrest resuscitation is complex. Clinical variables, as well as biomarkers of brain injury, cardiac injury, and systemic inflammation, all yield some prognostic value. We hypothesised that cumulative information obtained during the first three days of intensive care could produce a reliable model for predicting neurological outcome following out-of-hospital cardiac arrest (OHCA) using artificial neural network (ANN) with and without biomarkers.MethodsWe performed a post hoc analysis of 932 patients from the Target Temperature Management trial. We focused on comatose patients at 24, 48, and 72 h post-cardiac arrest and excluded patients who were awake or deceased at these time points. 80% of the patients were allocated for model development (training set) and 20% for internal validation (test set). To investigate the prognostic potential of different levels of biomarkers (clinically available and research-grade), patients' background information, and intensive care observation and treatment, we created three models for each time point: (1) clinical variables, (2) adding clinically accessible biomarkers, e.g., neuron-specific enolase (NSE) and (3) adding research-grade biomarkers, e.g., neurofilament light (NFL). Patient outcome was the dichotomised Cerebral Performance Category (CPC) at six months; a good outcome was defined as CPC 1-2 whilst a poor outcome was defined as CPC 3-5. The area under the receiver operating characteristic curve (AUROC) was calculated for all test sets.ResultsAUROC remained below 90% when using only clinical variables throughout the first three days in the ICU. Adding clinically accessible biomarkers such as NSE, AUROC increased from 82 to 94% (p<0.01). The prognostic accuracy remained excellent from day 1 to day 3 with an AUROC at approximately 95% when adding research-grade biomarkers. The models which included NSE after 72 h and NFL on any of the three days had a low risk of false-positive predictions while retaining a low number of false-negative predictions.ConclusionsIn this exploratory study, ANNs provided good to excellent prognostic accuracy in predicting neurological outcome in comatose patients post OHCA. The models which included NSE after 72 h and NFL on all days showed promising prognostic performance.
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| 3. |
- Chew, Michelle S., et al.
(författare)
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Identification of myocardial injury using perioperative troponin surveillance in major noncardiac surgery and net benefit over the Revised Cardiac Risk Index
- 2022
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Ingår i: British Journal of Anaesthesia. - : Elsevier. - 0007-0912 .- 1471-6771. ; 128:1, s. 26-36
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Patients with perioperative myocardial injury are at risk of death and major adverse cardiovascular and cerebrovascular events (MACCE). The primary aim of this study was to determine optimal thresholds of preoperative and perioperative changes in high-sensitivity cardiac troponin T (hs-cTnT) to predict MACCE and mortality.METHODS: Prospective, observational, cohort study in patients ≥50 yr of age undergoing elective major noncardiac surgery at seven hospitals in Sweden. The exposures were hs-cTnT measured before and days 0-3 after surgery. Two previously published thresholds for myocardial injury and two thresholds identified using receiver operating characteristic analyses were evaluated using multivariable logistic regression models and externally validated. The weighted comparison net benefit method was applied to determine the additional value of hs-cTnT thresholds when compared with the Revised Cardiac Risk Index (RCRI). The primary outcome was a composite of 30-day all-cause mortality and MACCE.RESULTS: We included 1291 patients between April 2017 and December 2020. The primary outcome occurred in 124 patients (9.6%). Perioperative increase in hs-cTnT ≥14 ng L-1 above preoperative values provided statistically optimal model performance and was associated with the highest risk for the primary outcome (adjusted odds ratio 2.9, 95% confidence interval 1.8-4.7). Validation in an independent, external cohort confirmed these findings. A net benefit over RCRI was demonstrated across a range of clinical thresholds.CONCLUSIONS: Perioperative increases in hsTnT ≥14 ng L-1 above baseline values identifies acute perioperative myocardial injury and provides a net prognostic benefit when added to RCRI for the identification of patients at high risk of death and MACCE.CLINICAL TRIAL REGISTRATION: NCT03436238.
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| 4. |
- Farha, Munavara, 1995, et al.
(författare)
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Assessment of experimental methods for measurements of the horizontal flow of fluidized solids under bubbling conditions
- 2023
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Ingår i: Fuel. - 0016-2361. ; 348
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Tidskriftsartikel (refereegranskat)abstract
- Dual fluidized bed systems are indispensable for future energy systems that require solids cycling between different atmospheres. However, controlling the residence time of solids in the reactor, which is crucial for controlling the heat and mass transfer of the fuel, is a significant challenge. This study investigates four experimental techniques to quantify the horizontal flow of solids fluidized under bubbling conditions: integral mass accumulation; differential mass accumulation; thermal tracing; and magnetic solids tracing. Integral mass accumulation entails collecting bed material using a defluidized box within a given time period. Differential mass accumulation measures the material accumulation rate in a section of the bed that is monitored using pressure measurements. Thermal tracing calculates the solids flow rate by solving the heat balance to match the temperature field captured by a thermographic camera. Magnetic solids tracing involves injecting a batch of magnetic tracer solids into the reactor and then measuring the residence time distribution using impedance coils. The experiments were conducted under down-scaled conditions that resemble large-scale operations with a length scaling factor of 0.12. For this study, three operational parameters were varied: the fixed bed height; the volumetric flow rate of the conveying air; and the fluidization velocity in the bed. The horizontal solids circulation rates achieved ranged from 1.7×10−4 to 10 kg/m·s, corresponding to 1.2×10−3 to 70 kg/m·s on a hot up-scaled basis, which is a relevant range to indirect biomass gasification in an industrial setting. The three selected operational parameters led to increases in the horizontal solids flow. While all four methods replicated the trends, quantitative variations in the measured circulation rates occurred due to the inherent characteristics of the methods. High circulation rates resulted in a continuous decrease in the solids inventory, leading to an underestimation of the circulation rate when using the integral mass accumulation method. The accuracy of the differential mass accumulation method relied on transient pressure measurements, which were less-effective at low solids flow rates. Conversely, the accumulation time required for pressure measurements was reduced at high circulation rates, resulting in uncertainties in the analysis. The accuracy of the thermal tracing method decreased drastically with higher solids circulation, resulting in an overestimation of the circulation rate. Moreover, low circulation rates adversely affected the accuracy of the magnetic solids tracing by producing barely discernible tracer concentration gradients.
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| 5. |
- Fogelholm, Jesper, 1986-, et al.
(författare)
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CREBBP and WDR 24 Identified as Candidate Genes for Quantitative Variation in Red-Brown Plumage Colouration in the Chicken
- 2020
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Ingår i: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- Plumage colouration in birds is important for a plethora of reasons, ranging from camouflage, sexual signalling, and species recognition. The genes underlying colour variation have been vital in understanding how genes can affect a phenotype. Multiple genes have been identified that affect plumage variation, but research has principally focused on major-effect genes (such as those causing albinism, barring, and the like), rather than the smaller effect modifier loci that more subtly influence colour. By utilising a domestic × wild advanced intercross with a combination of classical QTL mapping of red colouration as a quantitative trait and a targeted genetical genomics approach, we have identified five separate candidate genes (CREBBP, WDR24, ARL8A, PHLDA3, LAD1) that putatively influence quantitative variation in red-brown colouration in chickens. By treating colour as a quantitative rather than qualitative trait, we have identified both QTL and genes of small effect. Such small effect loci are potentially far more prevalent in wild populations, and can therefore potentially be highly relevant to colour evolution.
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| 6. |
- Henriksen, Rie, et al.
(författare)
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Intra-Individual Behavioural Variability: A Trait under Genetic Control
- 2020
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Ingår i: International Journal of Molecular Sciences. - : MDPI. - 1661-6596 .- 1422-0067. ; 21:21
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Tidskriftsartikel (refereegranskat)abstract
- When individuals are measured more than once in the same context they do not behave in exactly the same way each time. The degree of predictability differs between individuals, with some individuals showing low levels of variation around their behavioural mean while others show high levels of variation. This intra-individual variability in behaviour has received much less attention than between-individual variability in behaviour, and very little is known about the underlying mechanisms that affect this potentially large but understudied component of behavioural variation. In this study, we combine standardized behavioural tests in a chicken intercross to estimate intra-individual behavioural variability with a large-scale genomics analysis to identify genes affecting intra-individual behavioural variability in an avian population. We used a variety of different anxiety-related behavioural phenotypes for this purpose. Our study shows that intra-individual variability in behaviour has a direct genetic basis that is largely unique compared to the genetic architecture for the standard behavioural measures they are based on (at least in the detected quantitative trait locus). We identify six suggestive candidate genes that may underpin differences in intra-individual behavioural variability, with several of these candidates having previously been linked to behaviour and mental health. These findings demonstrate that intra-individual variability in behaviour appears to be a heritable trait in and of itself on which evolution can act.
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| 7. |
- Höglund, Andrey, 1985-, et al.
(författare)
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The methylation landscape and its role in domestication and gene regulation in the chicken
- 2020
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Ingår i: Nature Ecology & Evolution. - : Springer Nature. - 2397-334X. ; 4, s. 1713-1724
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Tidskriftsartikel (refereegranskat)abstract
- Domestication is one of the strongest examples of artificial selection and has produced some of the most extreme within-species phenotypic variation known. In the case of the chicken, it has been hypothesized that DNA methylation may play a mechanistic role in the domestication response. By inter-crossing wild-derived red junglefowl with domestic chickens, we mapped quantitative trait loci for hypothalamic methylation (methQTL), gene expression (eQTL) and behaviour. We find large, stable methylation differences, with 6,179 cis and 2,973 trans methQTL identified. Over 46% of the trans effects were genotypically controlled by five loci, mainly associated with increased methylation in the junglefowl genotype. In a third of eQTL, we find that there is a correlation between gene expression and methylation, while statistical causality analysis reveals multiple instances where methylation is driving gene expression, as well as the reverse. We also show that methylation is correlated with some aspects of behavioural variation in the inter-cross. In conclusion, our data suggest a role for methylation in the regulation of gene expression underlying the domesticated phenotype of the chicken.
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| 8. |
- Johnsson, Anna-Karin, et al.
(författare)
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COX-1 dependent biosynthesis of 15-hydroxyeicosatetraenoic acid in human mast cells
- 2021
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Ingår i: Biochimica et Biophysica Acta - Molecular and Cell Biology of Lipids. - : Elsevier. - 1388-1981 .- 1879-2618. ; 1866:5
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Tidskriftsartikel (refereegranskat)abstract
- 15-hydroxyeicosatetraenoic acid (15-HETE) is an arachidonic acid derived lipid mediator which can originate both from 15-lipoxygenase (15-LOX) activity and cyclooxygenase (COX) activity. The enzymatic source determines the enantiomeric profile of the 15-HETE formed. 15-HETE is the most abundant arachidonic acid metabolite in the human lung and has been suggested to influence the pathophysiology of asthma. Mast cells are central effectors in asthma, but there are contradictory reports on whether 15-HETE originates from 15-LOX or COX in human mast cells. This prompted the current study where the pathway of 15-HETE biosynthesis was examined in three human mast cell models; the cell line LAD2, cord blood derived mast cells (CBMC) and tissue isolated human lung mast cells (HLMC). Levels and enantiomeric profiles of 15-HETE and levels of the downstream metabolite 15-KETE, were analyzed by UPLC-MS/MS after stimulation with anti-IgE or calcium ionophore A23187 in the presence and absence of inhibitors of COX isoenzymes. We found that 15-HETE was produced by COX-1 in human mast cells under these experimental conditions. Unexpectedly, chiral analysis showed that the 15(R) isomer was predominant and gradually accumulated, whereas the 15(S) isomer was metabolized by the 15hydroxyprostaglandin dehydrogenase. We conclude that during physiological conditions, i.e., without addition of exogenous arachidonic acid, both enantiomers of 15-HETE are produced by COX-1 in human mast cells but that the 15(S) isomer is selectively depleted by undergoing further metabolism. The study highlights that 15-HETE cannot be used as an indicator of 15-LOX activity for cellular studies, unless chirality and sensitivity to pharmacologic inhibition is determined.
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| 9. |
- Johnsson, Jesper, et al.
(författare)
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Functional outcomes associated with varying levels of targeted temperature management after out-of-hospital cardiac arrest — An INTCAR2 registry analysis
- 2020
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Ingår i: Resuscitation. - : Elsevier BV. - 0300-9572 .- 1873-1570. ; 146, s. 229-236
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Targeted temperature management (TTM) after out-of-hospital cardiac arrest (OHCA) has been recommended in international guidelines since 2005. The TTM-trial published in 2013 showed no difference in survival or neurological outcome for patients randomised to 33 °C or 36 °C, and many hospitals have changed practice. The optimal utilization of TTM is still debated. This study aimed to analyse if a difference in temperature goal was associated with outcome in an unselected international registry population. Methods: This is a retrospective observational study based on a prospective registry — the International Cardiac Arrest Registry 2. Patients were categorized as receiving TTM in the lower range at 32–34 °C (TTM-low) or at 35–37 °C (TTM-high). Primary outcome was good functional status defined as cerebral performance category (CPC) of 1–2 at hospital discharge and secondary outcome was adverse events related to TTM. A logistic regression model was created to evaluate the independent effect of temperature by correcting for clinical and demographic factors associated with outcome. Results: Of 1710 patients included, 1242 (72,6%) received TTM-low and 468 (27,4%) TTM-high. In patients receiving TTM-low, 31.3% survived with good outcome compared to 28.8% in the TTM-high group. There was no significant association between temperature and outcome (p = 0.352). In analyses adjusted for baseline differences the OR for a good outcome with TTM-low was 1.27, 95% CI (0.94–1.73). Haemodynamic instability leading to discontinuation of TTM was more common in TTM-low. Conclusions: No significant difference in functional outcome at hospital discharge was found in patients receiving lower- versus higher targeted temperature management.
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| 10. |
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