Observational Data to Improve Clinical Decision Making in Acute Care

The premise of Big Data in acute medicine is to make medicine more efficient and effective. However, the translation of large observational data to knowledge is difficult. This thesis explores and discusses the three main types of research questions which can be asked from large observational data:1. What is current clinical practice?2. What is best practice?3. What patients need to be prioritised?This thesis will focus on traumatic brain injury and in-hospital cardiac arrest.<br/

Observational Data to Improve Clinical Decision Making in Acute Care

The premise of Big Data in acute medicine is to make medicine more efficient and effective. However, the translation of large observational data to knowledge is difficult. This thesis explores and discusses the three main types of research questions which can be asked from large observational data:1. What is current clinical practice?2. What is best practice?3. What patients need to be prioritised?This thesis will focus on traumatic brain injury and in-hospital cardiac arrest.<br/

How to Study the Brain While Anesthetizing It?!:A Scoping Review on Running Neuroanesthesiologic Studies and Trials That Include Neurosurgical Patients

This scoping review addresses the challenges of neuroanesthesiologic research: the population, the methods/treatment/exposure, and the outcome/results. These challenges are put into the context of a future research agenda for peri-/intraoperative anesthetic management, neurocritical care, and applied neurosciences. Finally, the opportunities of adaptive trial design in neuroanesthesiologic research are discussed.</p

Surgical prioritization based on decision model outcomes is not sensitive to differences between the health-related quality of life values estimates of physicians and citizens

Purpose: Decision models can be used to support allocation of scarce surgical resources. These models incorporate health-related quality of life (HRQoL) values that can be determined using physician panels. The predominant opinion is that one should use values obtained from citizens. We investigated whether physicians give different HRQoL values to citizens and evaluate whether such differences impact decision model outcomes. Methods: A two-round Delphi study was conducted. Citizens estimated HRQoL of pre- and post-operative health states for ten surgeries using a visual analogue scale. These values were compared using Bland–Altman analysis with HRQoL values previously obtained from physicians. Impact on decision model outcomes was evaluated by calculating the correlation between the rankings of surgeries established using the physicians’ and the citizens’ values.Results: A total of 71 citizens estimated HRQoL. Citizens’ values on the VAS scale were − 0.07 points (95% CI − 0.12 to − 0.01) lower than the physicians’ values. The correlation between the rankings of surgeries based on citizens’ and physicians’ values was 0.96 (p &lt; 0.001). Conclusion: Physicians put higher values on health states than citizens. However, these differences only result in switches between adjacent entries in the ranking. It would seem that HRQoL values obtained from physicians are adequate to inform decision models during crises.</p

The association of COVID-19 lockdowns with adverse birth and pregnancy outcomes in 28 high-income countries:a systematic review and meta-analysis

We conducted a systematic review and meta-analysis to review the association of lockdowns with adverse birth and pregnancy outcomes (ABPOs) and related inequalities, in high-income countries (HICs). Databases (EMBASE, MEDLINE/PubMed and Web of Science) were searched from 1 January 2019 to 22 June 2023 for original observational studies based in HICs that compared the rates of ABPOs, before and during lockdowns. The risk of bias was assessed using the Newcastle-Ottawa tool for cohort studies. We ran random-effects meta-analyses and subgroup analyses per region, lockdown period, ethnicity group and deprivation level and adjusted for underlying temporal trends. A total of 132 studies were meta-analysed from 28 HICs. Reduced rates of preterm birth (reported by 26 studies) were associated with the first lockdown (relative risk 0.96, 95% confidence interval 0.93-0.99), 11 studies adjusted for long-term trends and the association remained (0.97, 0.95-0.99), and subgroup analysis found that this association varied by continental region. Ten studies reported positive screening rates for possible depression antenatally, and lockdown was associated with increases in positive screening rates (1.37, 1.06-1.78). No other ABPOs were associated with lockdowns. Investigation of inequalities was limited due to data availability and heterogeneity; further research is warranted on the effect of lockdowns on health inequalities. This study was funded by the National Institute of Health Research, School of Primary Care Research and registered on PROSPERO (CRD42022327448).</p

Primary versus early secondary referral to a specialized neurotrauma center in patients with moderate/severe traumatic brain injury : a CENTER TBI study

Publisher Copyright: © 2021, The Author(s).Background: Prehospital care for patients with traumatic brain injury (TBI) varies with some emergency medical systems recommending direct transport of patients with moderate to severe TBI to hospitals with specialist neurotrauma care (SNCs). The aim of this study is to assess variation in levels of early secondary referral within European SNCs and to compare the outcomes of directly admitted and secondarily transferred patients. Methods: Patients with moderate and severe TBI (Glasgow Coma Scale < 13) from the prospective European CENTER-TBI study were included in this study. All participating hospitals were specialist neuroscience centers. First, adjusted between-country differences were analysed using random effects logistic regression where early secondary referral was the dependent variable, and a random intercept for country was included. Second, the adjusted effect of early secondary referral on survival to hospital discharge and functional outcome [6 months Glasgow Outcome Scale Extended (GOSE)] was estimated using logistic and ordinal mixed effects models, respectively. Results: A total of 1347 moderate/severe TBI patients from 53 SNCs in 18 European countries were included. Of these 1347 patients, 195 (14.5%) were admitted after early secondary referral. Secondarily referred moderate/severe TBI patients presented more often with a CT abnormality: mass lesion (52% vs. 34%), midline shift (54% vs. 36%) and acute subdural hematoma (77% vs. 65%). After adjusting for case-mix, there was a large European variation in early secondary referral, with a median OR of 1.69 between countries. Early secondary referral was not associated with functional outcome (adjusted OR 1.07, 95% CI 0.78–1.69), nor with survival at discharge (1.05, 0.58–1.90). Conclusions: Across Europe, substantial practice variation exists in the proportion of secondarily referred TBI patients at SNCs that is not explained by case mix. Within SNCs early secondary referral does not seem to impact functional outcome and survival after stabilisation in a non-specialised hospital. Future research should identify which patients with TBI truly benefit from direct transportation.Peer reviewe

Tracheal intubation in traumatic brain injury : a multicentre prospective observational study

Background: We aimed to study the associations between pre- and in-hospital tracheal intubation and outcomes in traumatic brain injury (TBI), and whether the association varied according to injury severity. Methods: Data from the international prospective pan-European cohort study, Collaborative European NeuroTrauma Effectiveness Research for TBI (CENTER-TBI), were used (n=4509). For prehospital intubation, we excluded selfpresenters. For in-hospital intubation, patients whose tracheas were intubated on-scene were excluded. The association between intubation and outcome was analysed with ordinal regression with adjustment for the International Mission for Prognosis and Analysis of Clinical Trials in TBI variables and extracranial injury. We assessed whether the effect of intubation varied by injury severity by testing the added value of an interaction term with likelihood ratio tests. Results: In the prehospital analysis, 890/3736 (24%) patients had their tracheas intubated at scene. In the in-hospital analysis, 460/2930 (16%) patients had their tracheas intubated in the emergency department. There was no adjusted overall effect on functional outcome of prehospital intubation (odds ratio=1.01; 95% confidence interval, 0.79-1.28; P=0.96), and the adjusted overall effect of in-hospital intubation was not significant (odds ratio=0.86; 95% confidence interval, 0.65-1.13; P=0.28). However, prehospital intubation was associated with better functional outcome in patients with higher thorax and abdominal Abbreviated Injury Scale scores (P=0.009 and P=0.02, respectively), whereas inhospital intubation was associated with better outcome in patients with lower Glasgow Coma Scale scores (P=0.01): inhospital intubation was associated with better functional outcome in patients with Glasgow Coma Scale scores of 10 or lower. Conclusion: The benefits and harms of tracheal intubation should be carefully evaluated in patients with TBI to optimise benefit. This study suggests that extracranial injury should influence the decision in the prehospital setting, and level of consciousness in the in-hospital setting.Peer reviewe

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury.Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma ScaleResults: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study.Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations. (C) 2020 The Authors. Published by Elsevier Inc.</p