Long term opioid use after burn injury: a retrospective cohort study.

BACKGROUND: Patients who have survive a burn injury might be at risk of opioid dependence after discharge. This study examined the use of opioids in patients who suffer burn injury and explored factors associated with persistent opioid use after hospital discharge. METHODS: This retrospective cohort study compared adults admitted with a burn injury from 2009 to 2019 with two matched comparison cohorts from the general population and adults with a diagnosis of acute pancreatitis. Pre-admission prescription opioid use was determined, and a multivariable negative binomial regression analysis used to explore post-discharge opioid use. RESULTS: A total of 7147 burn patients were matched with 6810 pancreatitis patients and with 28 184 individuals from the general population. Pre-admission opioid use was higher in the burn and pancreatitis cohorts (29% and 40%, respectively) compared with the general population (17%). Opioid use increased in both burn and pancreatitis cohorts after discharge (41% and 53%, respectively), although patients with pancreatitis were at even higher risk of increased opioid use in an adjusted analysis (incidence rate ratio 1.43). Female sex, lower socioeconomic status, ICU admission, pre-injury opioid use, and a history of excess alcohol use were all associated with an increase in opioid prescriptions after discharge. CONCLUSIONS: Opioid use is high in those admitted with a burn injury or acute pancreatitis when compared with the general population, increasing further after hospital discharge. Female sex and socioeconomic deprivation are among factors that make increased opioid use more likely, although this phenomenon seems even more pronounced in those with acute pancreatitis compared with burn injuries.

Anxiety and depression following critical illness: A comparison of the recovery trajectories of patients and caregivers.

BACKGROUND: Following critical illness, family members are often required to adopt caregiving responsibilities. Anxiety and depression are common long term problems for both patients and caregivers. However, at present, it is not known how the trajectories of these symptoms compare between patients and caregivers. OBJECTIVES: The aim of this study was to investigate and compare the trajectories of anxiety and depression in patients and caregivers in the first year following critical illness. METHODS: This study analyses data from a prospective multicentre cohort study of patients and caregivers who underwent a complex recovery intervention following critical illness. Paired patients and caregivers were recruited. The Hospital Anxiety and Depression Scale was used to evaluate symptoms of anxiety and depression at three timepoints: baseline; 3 months; and 12 months in both patient and caregivers. A linear mixed-effects regression model was used to evaluate the trajectories of these symptoms over the first year following critical illness. RESULTS: 115 paired patients and caregivers, who received the complex recovery intervention, were recruited. There was no significant difference in the relative trajectory of depressive symptoms between patients and caregivers in the first 12 months following critical illness (p = 0.08). There was, however, a significant difference in the trajectory of anxiety symptoms between patients and caregivers during this time period (p = 0.04), with caregivers seeing reduced resolution of symptoms in comparison to patients. CONCLUSIONS: Following critical illness, symptoms of anxiety and depression are common in both patients and caregivers. The trajectory of symptoms of depression was similar between caregivers and patients; however, there was a significantly different recovery trajectory in symptoms of anxiety. Further research is required to understand the recovery pathway of caregivers in order to design effective interventions.

The Structure of Clinical Ethical Decision-Making: A Hospital System Needs Assessment.

Bioethical dilemmas can emerge in research and clinical settings, from end-of-life decision-making to experimental therapies. The COVID-19 pandemic raised serious ethical challenges for healthcare organizations, highlighting the need to conduct needs assessments of the bioethics infrastructures of healthcare organizations. Clinical ethics committees (CECs) also create equitable policies, train staff on ethics issues, and play a consultative role in resolving the difficulty of complex individual cases. The main objective of this project was to conduct a needs assessment of the bioethics infrastructure within a comprehensive hospital system. A cross-sectional anonymous online survey, including quantitative and qualitative formatted questions. The survey was sent to five key leaders from the organization's hospitals. Survey questions focused on the composition, structure, function, and effectiveness of their facilities' bioethics infrastructure and ethics-related training and resources. Positive findings included that most facilities have active CECs with multidisciplinary membership; CECs address critical issues and encourage team members to express clinical ethics concerns. Areas of concern included uncertainty about how CECs function and the process for resolving clinical ethics dilemmas. Most reported no formal orientation process for CEC members, and many said there was no ongoing ethics education process. The authors conclude that if CECs are a critical institutional resource where the practice of medicine and mission intersect, having well-functioning ethics committees with trained and oriented members demonstrates an essential commitment to the mission. The survey revealed that more needs to be done to bolster the bioethics infrastructure of this institution.

Evaluation of a health and social care programme to improve outcomes following critical illness: a multicentre study.

RATIONALE: At present, clinicians aiming to support patients through the challenges after critical care have limited evidence to base interventions. OBJECTIVES: Evaluate a multicentre integrated health and social care intervention for critical care survivors. A process evaluation assessed factors influencing the programme implementation. METHODS: This study evaluated the impact of the Intensive Care Syndrome: Promoting Independence and Return to Employment (InS:PIRE) programme. We compared patients who attended this programme with a usual care cohort from the same time period across nine hospital sites in Scotland. The primary outcome was health-related quality of life (HRQoL) measured via the EuroQol 5-dimension 5-level instrument, at 12 months post hospital discharge. Secondary outcome measures included self-efficacy, depression, anxiety and pain. RESULTS: 137 patients who received the InS:PIRE intervention completed outcome measures at 12 months. In the usual care cohort, 115 patients completed the measures. The two cohorts had similar baseline demographics. After adjustment, there was a significant absolute increase in HRQoL in the intervention cohort in relation to the usual care cohort (0.12, 95% CI 0.04 to 0.20, p=0.01). Patients in the InS:PIRE cohort also reported self-efficacy scores that were 7.7% higher (2.32 points higher, 95% CI 0.32 to 4.31, p=0.02), fewer symptoms of depression (OR 0.38, 95% CI 0.19 to 0.76, p=0.01) and similar symptoms of anxiety (OR 0.58, 95% CI 0.30 to 1.13, p=0.11). There was no significant difference in overall pain experience. Key facilitators for implementation were: integration with inpatient care, organisational engagement, flexibility to service inclusion; key barriers were: funding, staff availability and venue availability. CONCLUSIONS: This multicentre evaluation of a health and social care programme designed for survivors of critical illness appears to show benefit at 12 months following hospital discharge.

Factors Associated With New Analgesic Requirements Following Critical Illness.

BACKGROUND: Chronic opioid use represents a significant burden to global healthcare with adverse long-term outcomes. Elevated patient reported pain levels and analgesic prescriptions have been reported following discharge from critical care. We describe analgesic requirements following discharge from hospital and identify if a critical care admission is a significant factor for stronger analgesic prescriptions. METHODS: This retrospective observational cohort study identified patients in the UK Biobank with a registered admission to any UK hospital between January 1, 2010 and December 31, 2015 and information on prescriptions drawn both prior to and following hospital discharge. Two matched cohorts were created from the dataset: critical care patients and hospital patients admitted without a critical care encounter. Outcomes were analgesic requirements following hospital discharge and factors associated with increased analgesic prescriptions. Multivariable logistic regression was used to identify factors associated with prescriptions from higher steps on the World Health Organization (WHO) analgesic ladder. RESULTS: In total, 660 formed the total study population. Strong opioid prescriptions following discharge were significantly higher in the critical care cohort (P value <.001). Critical care admission (OR = 1.45) and increasing Townsend deprivation (OR = 1.04) index were significantly associated with increasing strength of analgesic prescriptions following discharge. CONCLUSIONS: Critical care patients require stronger analgesic prescriptions in the 12 months following hospital discharge. Patients from areas of high socioeconomic deprivation may also be associated with increased analgesic requirements. Multidisciplinary support is required for patients who may be at risk of chronic opioid use and could be delivered within critical care recovery programs.

ISCEV standard pattern reversal VEP development: paediatric reference limits from 649 healthy subjects.

PURPOSE: To establish the extent of agreement for ISCEV standard reference pattern reversal VEPs (prVEPs) acquired at three European centres, to determine any effect of sex, and to establish reference intervals from birth to adolescence. METHODS: PrVEPs were recorded from healthy reference infants and children, aged 2 weeks to 16 years, from three centres using closely matched but non-identical protocols. Amplitudes and peak times were modelled with orthogonal quadratic and sigmoidal curves, respectively, and two-sided limits, 2.5th and 97.5th centiles, estimated using nonlinear quantile Bayesian regression. Data were compared by centre and by sex using median quantile confidence intervals. The 'critical age', i.e. age at which P100 peak time ceased to shorten, was calculated. RESULTS: Data from the three centres were adequately comparable. Sex differences were not clinically meaningful. The pooled data showed rapid drops in P100 peak time which stabilised by 27 and by 34 weeks for large and small check widths, respectively. Post-critical-age reference limits were 87-115 ms and 96-131 ms for large and small check widths, respectively. Amplitudes varied markedly and reference limits for all ages were 5-57 µV and 3.5-56 µV for large and small check widths, respectively. CONCLUSIONS: PrVEP reference data could be combined despite some methodology differences within the tolerances of the ISCEV VEP Standard, supporting the clinical benefit of ISCEV Standards. Comparison with historical data is hampered by lack of minimum reporting guidelines. The reference data presented here could be validated or transformed for use elsewhere.

A multicentre evaluation exploring the impact of an integrated health and social care intervention for the caregivers of ICU survivors.

BACKGROUND: Caregivers and family members of Intensive Care Unit (ICU) survivors can face emotional problems following patient discharge from hospital. We aimed to evaluate the impact of a multi-centre integrated health and social care intervention, on caregiver and family member outcomes. METHODS: This study evaluated the impact of the Intensive Care Syndrome: Promoting Independence and Return to Employment (InS:PIRE) programme across 9 sites in Scotland. InS:PIRE is an integrated health and social care intervention. We compared caregivers who attended this programme with a contemporary control group of ICU caregivers (usual care cohort), who did not attend. RESULTS: The primary outcome was anxiety measured via the Hospital Anxiety and Depression Scale at 12 months post-hospital discharge. Secondary outcome measures included depression, carer strain and clinical insomnia. A total of 170 caregivers had data available at 12 months for inclusion in this study; 81 caregivers attended the InS:PIRE intervention and completed outcome measures at 12 months post-hospital discharge. In the usual care cohort of caregivers, 89 completed measures. The two cohorts had similar baseline demographics. After adjustment, those caregivers who attended InS:PIRE demonstrated a significant improvement in symptoms of anxiety (OR: 0.42, 95% CI: 0.20-0.89, p = 0.02), carer strain (OR: 0.39; 95% CI: 0.16-0.98 p = 0.04) and clinical insomnia (OR: 0.40; 95% CI: 0.17-0.77 p < 0.001). There was no significant difference in symptoms of depression at 12 months. CONCLUSIONS: This multicentre evaluation has shown that caregivers who attended an integrated health and social care intervention reported improved emotional health and less symptoms of insomnia, 12 months after the delivery of the intervention.

Demystifying the Black Box: The Importance of Interpretability of Predictive Models in Neurocritical Care.

Neurocritical care patients are a complex patient population, and to aid clinical decision-making, many models and scoring systems have previously been developed. More recently, techniques from the field of machine learning have been applied to neurocritical care patient data to develop models with high levels of predictive accuracy. However, although these recent models appear clinically promising, their interpretability has often not been considered and they tend to be black box models, making it extremely difficult to understand how the model came to its conclusion. Interpretable machine learning methods have the potential to provide the means to overcome some of these issues but are largely unexplored within the neurocritical care domain. This article examines existing models used in neurocritical care from the perspective of interpretability. Further, the use of interpretable machine learning will be explored, in particular the potential benefits and drawbacks that the techniques may have when applied to neurocritical care data. Finding a solution to the lack of model explanation, transparency, and accountability is important because these issues have the potential to contribute to model trust and clinical acceptance, and, increasingly, regulation is stipulating a right to explanation for decisions made by models and algorithms. To ensure that the prospective gains from sophisticated predictive models to neurocritical care provision can be realized, it is imperative that interpretability of these models is fully considered.

Buprenorphine Compared with Methadone in Pregnancy: A Systematic Review and Meta-Analysis.

INTRODUCTION: Illicit opioid use in pregnancy is associated with adverse maternal, neonatal, and childhood outcomes. Opioid substitution is recommended, but whether methadone or buprenorphine is the optimal agent remains unclear. METHODS: We searched EMBASE, PubMed, Web of Science, Scopus, Open Gray, CINAHL and the Cochrane Central Registry of Controlled Trials (CENTRAL) from inception to April 2020 for randomized controlled trials (RCTs) and cohort studies comparing methadone and buprenorphine treatment for opioid-using mothers. Included studies assessed maternal and or neonatal outcomes. We used random-effects meta-analyses to estimate summary measures for outcomes and report these separately for RCTs and cohort studies. RESULTS: Of 408 abstracts screened, 20 papers were included (4 RCTs, 16 cohort, 223 and 7028 participants respectively). All RCTs (4/4) had a high risk of bias and median (IQR) Newcastle Ottawa Scale for cohort studies was 7.5 (6-9). In both RCTs and cohort studies, buprenorphine was associated with; greater offspring birth weight (weighted mean difference [WMD] 343 g (95% CI: 40-645 g) in RCT and 184 g (95% CI: 121-247 g) in cohort studies); body length at birth (WMD 2.28 cm (95% CI: 1.06-3.49 cm) in RCTs and 0.65 cm (95% CI: 0.31-0.98 cm) in cohort studies); and reduced risk of prematurity (risk ratio [RR] 0.41 (95% CI: 0.18-0.93) in RCTs and 0.63 [95% CI: 0.53-0.75] in cohort studies) when compared to methadone. All other clinical outcomes were comparable. CONCLUSIONS: Compared to methadone, buprenorphine was consistently associated with improved birthweight and gestational age, however given potential biases, results should be interpreted with caution.

Postoperative C-reactive protein concentrations to predict infective complications following gastrectomy for cancer.

BACKGROUND AND OBJECTIVES: Gastrectomy for gastric cancer is associated with significant infective postoperative complications. C-reactive protein (CRP) is a useful biomarker in the early detection of infective complications following major abdominal surgery. This single-centre retrospective study aimed to determine the relationship between postoperative CRP levels and development of postoperative infective complications after gastrectomy. METHODS: Daily postoperative CRP levels were analyzed to determine a CRP threshold associated with infective complications. ROC curve analysis was used to determine which postoperative day (POD) gave the optimal cutoff. Multivariate analysis was performed to determine significant factors associated with complications. RESULTS: One hundred and forty-four patients were included. A total of 61 patients (42%) had at least one infective complication. A CRP level of 220 mg/L was associated with the highest AUC (0.765) with a sensitivity of 70% and specificity of 76% (positive predictive value, 67%; negative predictive value, 78%). More patients with a CRP > 220 mg/L on POD 3 developed infective complications (67% vs. 21%, p < 0.001). CONCLUSIONS: A CRP of more than 220 mg/L on POD 3 may be useful to alert clinicians to the increased risk of a postoperative infective complication or enable earlier safe discharge from critical care for those with a lower value.

Influence of Patient Demographics on Optimal Cerebral Perfusion Pressure Following Traumatic Brain Injury.

The relationship between optimal cerebral perfusion pressure (CPPopt) and patient characteristics has yet to be defined but could have significant implications for future guidelines recommending cerebral perfusion pressure (CPP) targets.Data from 36 traumatic brain injured patients admitted to neurological intensive care were analysed retrospectively. Linear mixed effects (LME) analysis was performed using an unadjusted-adjusted approach.Clinical characteristics with p < 0.10 were included in the adjusted model. A second adjusted model which included all variables of interest was created. Model fit was assessed using the root-mean-square error (RMSE).The adjusted model included time from initiation of intracranial pressure (ICP) monitoring (estimate = 0.00292, p < 0.001), age (estimate = -0.211, p = 0.0750) and the presence of diffuse axonal injury (DAI) (estimate = -35.5, p < 0.001). The RMSE of this model was 8.11 mmHg. The RMSE of the model containing all variables was 8.09 mmHg.Time, age and the presence of DAI may be important predictors of CPPopt. The models were too inaccurate at predicting CPPopt for employment in clinical practice but warrant further investigation. CPPopt is a dynamic measurement influenced by many factors, supporting the utility of investigating the feasibility of CPPopt-guided therapy.

Evaluation of Software for Automated Measurement of Adherence to ICP-Monitoring Threshold Guideline.

Challenges inherent in clinical guideline development include a long time lag between the key results and incorporation into best practice and the qualitative nature of adherence measurement, meaning it will have no directly measurable impact. To address these issues, a framework has been developed to automatically measure adherence by clinicians in neurological intensive care units to the Brain Trauma Foundation's intracranial pressure (ICP)-monitoring guidelines for severe traumatic brain injury (TBI).The framework processes physiological and treatment data taken from the bedside, standardises the data as a set of process models, then compares these models against similar process models constructed from published guidelines. A similarity metric (i.e. adherence measure) between the two models is calculated, composed of duration and scale of non-adherence.In a pilot clinical validation test, the framework was applied to physiological/treatment data from three TBI patients exhibiting ICP secondary insults at a local neuro-centre where clinical experts coded key clinical interventions/decisions about patient management.The framework identified non-adherence with respect to drug administration in one patient, with a spike in non-adherence due to an inappropriately high dosage; a second patient showed a high severity of guideline non-adherence; and a third patient showed non-adherence due to a low number of associated events and treatment annotations.

Time Series Analysis and Prediction of Intracranial Pressure Using Time-Varying Dynamic Linear Models.

Intracranial pressure (ICP) monitoring is a key clinical tool in the assessment and treatment of patients in a neuro-intensive care unit (neuro-ICU). As such, a deeper understanding of how an individual patient's ICP can be influenced by therapeutic interventions could improve clinical decision-making. A pilot application of a time-varying dynamic linear model was conducted using the BrainIT dataset, a multi-centre European dataset containing temporaneous treatment and vital-sign recordings. The study included 106 patients with a minimum of 27 h of ICP monitoring. The model was trained on the first 24 h of each patient's ICU stay, and then the next 2 h of ICP was forecast. The algorithm enabled switching between three interventional states: analgesia, osmotic therapy and paralysis, with the inclusion of arterial blood pressure, age and gender as exogenous regressors. The overall median absolute error was 2.98 (2.41-5.24) mmHg calculated using all 106 2-h forecasts. This is a novel technique which shows some promise for forecasting ICP with an adequate accuracy of approximately 3 mmHg. Further optimisation is required for the algorithm to become a usable clinical tool.

Use of Direct Intracranial Pressure and Brain Tissue Oxygen Monitoring in Perioperative Management of Patients with Moyamoya Disease.

Intracranial pressure monitoring and brain tissue oxygen monitoring are commonly used in head injury for goal-directed therapies, but there may be more indications for its use. Moyamoya disease involves progressive stenosis of the arterial circulation and formation of collateral vessels that are at risk of hemorrhage. The risk of ischemic events during revascularization surgery and postoperatively is high. Impaired cerebral autoregulation may be one of the factors that are implicated. We present our experience with monitoring of cerebral oxygenation and autoregulation in the pathological hemisphere during the perioperative period in four patients with moyamoya disease.

Telemetric Intracranial Pressure: A Snapshot Does not Give the Full Story.

Telemetric intracranial pressure (ICP) monitors are useful tools in the management of complex hydrocephalus and idiopathic intracranial hypertension (IIH). Clinicians may use them as a "snapshot" screening tool to assess shunt function or ICP. We compared "snapshot" telemetric ICP recordings with extended, in-patient periods of monitoring to determine whether this practice is safe and useful for clinical decision making.

Transcranial bioimpedance measurement in horses: a pilot study.

OBJECTIVE: This pilot study aimed to evaluate the feasibility of transcranial bioimpedance (TCBI) measurement and variability of TCBI values in healthy conscious horses and to study effects of body position and time on TCBI in anaesthetized horses. STUDY DESIGN: Prospective, observational study. ANIMALS: A total of four research horses and 16 client-owned horses presented for surgery. METHODS: After establishing optimal electrode position using computed tomography scans of cadaver heads, TCBI [described using impedance at zero frequency, R0, (Ω)] was measured in four conscious, resting horses to investigate the feasibility and changes in TCBI over time (80 minutes). Data were compared using a paired t test. TCBI was then measured throughout anaesthesia (duration 92 ± 28 minutes) in 16 horses in dorsal and lateral recumbency. Data were analysed using a general linear model; gamma regression was chosen as a model of characteristic impedance [Zc; (Ω)] against time. Data are presented as mean ± standard deviation. RESULTS: No change in R0 was seen in conscious horses (age = 15.3 ± 7.3 years, body mass = 512 ± 38 kg) over 80 minutes. The technique was well tolerated and caused no apparent adverse effects. In 16 horses (age = 7.4 ± 4.7 years; body mass = 479 ± 134 kg) anaesthetized for 92 ± 28 minutes, Zc fell during anaesthesia, decreasing more in horses in lateral recumbency than in horses in dorsal recumbency (p = 0.008). There was no relationship between Zc and body mass or age. CONCLUSIONS AND CLINICAL RELEVANCE: TCBI is readily measured in horses. TCBI did not change with time in conscious horses, but decreased with time in anaesthetized horses; this change was greater in horses in lateral recumbency, indicating that TCBI changes in anaesthetized horses may be related to the effects of recumbency, general anaesthesia, surgery or a combination of these factors.

Transcranial Bioimpedance Measurement as a Non-invasive Estimate of Intracranial Pressure.

OBJECTIVES: We have previously demonstrated a relationship between transcranial bioimpedance (TCB) measurements and intracranial pressure (ICP) in an animal model of raised ICP. The primary objective of this study was to explore the relationship between non-invasive bioelectrical impedance measurements of the brain and skull and ICP in traumatic brain injury (TBI) patients. MATERIALS AND METHODS: Included patients were adults admitted to the Neurological Intensive Care Unit with TBI and undergoing invasive ICP monitoring as part of their routine clinical care. Multi-frequency TCB measurements were performed hourly through bi-temporal electrodes. The bioimpedance parameters of Z c (impedance at the characteristic frequency) and R 0 (resistance to a direct current) were then modelled against ICP using unadjusted and adjusted linear models. RESULTS: One hundred and sixty-eight TCB measurements were available from ten study participants. Using an unadjusted linear modelling approach, there was no significant relationship between measured ICP and Zc or R0. The most significant relationship between ICP and TCB parameters was found by adjusting for multiple patient specific variables and using Zc and R0 normalised per patient (p < 0.0001, r 2 = 0.32). CONCLUSIONS: These pilot results confirm some degree of relationship between TCB parameters and invasively measured ICP. The magnitude of this relationship is small and, on the basis of the current study, TCB is unlikely to provide a clinically useful estimate of ICP in patients admitted with TBI.

Medical Waveform Format Encoding Rules Representation of Neurointensive Care Waveform Data.

OBJECTIVE: Technology in neurointensive care units can collect and store vast amounts of complex patient data. The CHART-ADAPT project is aimed at developing technology that will allow for the collection, analysis and use of these big data at the patient's bedside in neurointensive care units. A requirement of this project is to automatically extract and transfer high-frequency waveform data (e.g. ICP) from monitoring equipment to high performance computing infrastructure for analysis. Currently, no agreed data standard exists in neurointensive care for the description of this type of data. In this pilot study, we investigated the use of Medical Waveform Format Encoding Rules (MFER- www.mfer.org-ISO 11073-92001) as a possible data standard for neurointensive care waveform data. MATERIALS AND METHODS: Several waveform formats were explored (e.g. XML, DICOM waveform) and evaluated for suitability given existing computing infrastructure constraints, e.g. NHS network capacity and the processing capabilities of existing integration software. Key requirements of the format included a compact data size and the use of a recognised standard. The MFER waveform format (ISO/TS 11073-92001) met both requirements. To evaluate the practicality of the MFER waveform format, seven waveform signals (ICP, ECG, ART, CVP, EtCO2, Pleth, Resp) collected over a period of 8 h from a patient at the Institute of Neurological Sciences in Glasgow were converted into MFER waveform format. RESULTS: The MFER waveform format has two main components: sampling information and frame information. Sampling information describes the frequency of the data sampling and the resolution of the data. Frame information describes the data itself; it consists of three elements: data block (the actual data), channel (each type of waveform data occupies a channel) and sequence (the repetition of the data). All seven waveform signals were automatically and successfully converted into the MFER waveform format. One MFER file was created for each minute of data (total of 479 files, 181 KB each). CONCLUSIONS: The MFER waveform format has potential as a lightweight standard for representing high-frequency neurointensive care waveform data. Further work will include a comparison with other waveform data formats and a live trial of using the MFER waveform format to stream patient data over a longer period.

Investigation of the Relationship Between the Burden of Raised ICP and the Length of Stay in a Neuro-Intensive Care Unit.

OBJECTIVES: Raised intracranial pressure (ICP) is well known to be indicative of a poor outcome in traumatic brain injury (TBI). This phenomenon was quantified using a pressure time index (PTI) model of raised ICP burden in a paediatric population. Using the PTI methodology, this pilot study is aimed at investigating the relationship between raised ICP and length of stay (LOS) in adults admitted to a neurological intensive care unit (neuro-ICU). MATERIALS AND METHODS: In 10 patients admitted to the neuro-ICU following TBI, ICP was measured and data from the first 24 h were analysed. The PTI is a bounded area under the curve, where the bound is the threshold limit of interest for the signal. The upper bound of 20 mmHg for ICP is commonly used in clinical practice. To fully investigate the relationship between ICP and LOS, further bounds from 1 to 40 mmHg were used during the PTI calculations. A backwards step Poisson regression model with a log link function was used to find the important thresholds for the prediction of full LOS, measured in hours, in the neuro-ICU. RESULTS: The fit was assessed using a Chi-squared deviance goodness of fit method, which showed a non-significant p value of 0.97, indicating a correctly specified model. The backwards step strategy, minimising the model's Akaike information criteria (AIC) at each change, found that levels 13-16, 18 and 20-21 combined were the most predictive. From this model it can be shown that for every 1 mmHg/h increase in burden, as measured by the PTI, the LOS has a base exponential increase of approximately 2 h, with the largest increases in the LOS given at the 20-mmHg threshold level. CONCLUSIONS: This model demonstrates that increased duration of raised ICP in the early monitoring period is associated with a prolonged LOS in the neuro-ICU. Further validation of the PTI model in a larger cohort is currently underway as part of the CHART-ADAPT project. Second, further adjustment with known predictors of outcome, such as severity of injury, would help to improve the fit and validate the current combination of predictors.

Quantification of free sugars, fructan, pungency and sweetness indices in onion populations by FT-MIR spectroscopy.

BACKGROUND: To facilitate faster phenotyping of onions (Allium cepa L.), Fourier-transform mid infrared (FT-MIR) spectroscopy with partial least squares (PLS) regression modelling was evaluated for the determination of pungency (pyruvate), sweetness (free sugars) and fructan in juice samples (n = 605) expressed from bulbs from breeding populations. RESULTS: Fourier-transform infrared (FTIR) spectra (range 1700-900 cm-1 ) were obtained from droplets (30 µL) of unprocessed juice. Goodness-of-fit (r2 ) and prediction errors (standard error of cross validation) for optimal PLS models were: soluble solids (0.997, 0.1 °Brix), pyruvate [0.825, 0.8 µmol g-1 fresh weight (FW)], fructan (0.98, 1.9 mg g-1 FW), glucose (0.941, 1.1 mg g-1 FW), fructose (0.967, 1.0 mg g-1 FW) and sucrose (0.919, 1.7 mg g-1 FW). FTIR models for industry sweetness indices based on glucose or sucrose equivalents were also developed. Because of its very low concentration (0.8-12 µmol g-1 FW) relative to other compounds, pyruvate was the weakest model developed. Fructan could be determined spectroscopically without the need for enzymatic digestion. CONCLUSIONS: All of the chemometric models developed are acceptable for screening purposes. Those for soluble solids, fructan and fructose are also suitable for routine analysis. FT-MIR can therefore be utilised for the simultaneous determination of pungency, sweetness and fructan in this crop. © 2018 Society of Chemical Industry.