Effects of escitalopram on synaptic density in the healthy human brain: a randomized controlled trial.

Selective serotonin reuptake inhibitors (SSRIs) are widely used for treating neuropsychiatric disorders. However, the exact mechanism of action and why effects can take several weeks to manifest is not clear. The hypothesis of neuroplasticity is supported by preclinical studies, but the evidence in humans is limited. Here, we investigate the effects of the SSRI escitalopram on presynaptic density as a proxy for synaptic plasticity. In a double-blind placebo-controlled study (NCT04239339), 32 healthy participants with no history of psychiatric or cognitive disorders were randomized to receive daily oral dosing of either 20 mg escitalopram (n = 17) or a placebo (n = 15). After an intervention period of 3-5 weeks, participants underwent a [11C]UCB-J PET scan (29 with full arterial input function) to quantify synaptic vesicle glycoprotein 2A (SV2A) density in the hippocampus and the neocortex. Whereas we find no statistically significant group difference in SV2A binding after an average of 29 (range: 24-38) days of intervention, our secondary analyses show a time-dependent effect of escitalopram on cerebral SV2A binding with positive associations between [11C]UCB-J binding and duration of escitalopram intervention. Our findings suggest that brain synaptic plasticity evolves over 3-5 weeks in healthy humans following daily intake of escitalopram. This is the first in vivo evidence to support the hypothesis of neuroplasticity as a mechanism of action for SSRIs in humans and it offers a plausible biological explanation for the delayed treatment response commonly observed in patients treated with SSRIs. While replication is warranted, these results have important implications for the design of future clinical studies investigating the neurobiological effects of SSRIs.

Blood-brain barrier permeable ß-blockers linked to lower risk of Alzheimer's disease in hypertension.

Alzheimer's disease is a neurodegenerative disorder in which the pathological accumulation of amyloid-ß and tau begins years before symptom onset. Emerging evidence suggests that ß-blockers (ß-adrenergic antagonists) increase brain clearance of these metabolites by enhancing CSF flow. Our objective was to determine whether ß-blocker treatments that easily cross the blood-brain barrier reduce the risk of Alzheimer's disease compared to less permeable ß-blockers. Data from the Danish national registers were used to identify a retrospective cohort of individuals with hypertension, and those treated with ß-blockers were included in the analysis. People with indications for ß-blocker use other than hypertension (e.g. heart failure) were only retained in a sensitivity analysis. ß-blockers were divided into three permeability groups: low, moderate and high. We used multivariable cause-specific Cox regression to model the effect of ß-blocker blood-brain barrier permeability on time to dementia outcomes, adjusting for baseline comorbidities, demographics and socioeconomic variables. Death was modelled as a competing risk. The 10-year standardized absolute risk was estimated as the averaged person-specific risks per treatment. In a cohort of 69 081 (median age = 64.4 years, 64.8% female) people treated with ß-blockers for hypertension, highly blood-brain barrier-permeable ß-blockers were associated with reduced risk of Alzheimer's disease versus low permeability ß-blockers (-0.45%, P < 0.036). This effect was specific to Alzheimer's diagnoses and did not extend to dementia in general. Propensity score analysis matching high and low blood-brain barrier-permeable patients also detected a decreased Alzheimer's risk (-0.92%, P < 0.001) in the high permeability group compared to the low, as did a 1-year landmark analysis (-0.57%, P < 0.029) in which events within the first year of follow-up were ignored as likely unrelated to treatment. Our results suggest that amongst people taking ß-blockers for hypertension, treatment with highly blood-brain barrier permeable ß-blockers reduces the risk of Alzheimer's disease compared to low permeability drugs. Our findings support the hypothesis that highly permeable ß-blockers protect against Alzheimer's disease by promoting waste brain metabolite clearance.

Stress Hormone Dynamics Are Coupled to Brain Serotonin 4 Receptor Availability in Unmedicated Patients With Major Depressive Disorder: A NeuroPharm Study.

BACKGROUND: A prominent finding in major depressive disorder (MDD) is distorted stress hormone dynamics, which is regulated by serotonergic brain signaling. An interesting feature of the cerebral serotonin system is the serotonin 4 receptor (5-HT4R), which is lower in depressed relative to healthy individuals and also has been highlighted as a promising novel antidepressant target. Here, we test the novel hypothesis that brain 5-HT4R availability in untreated patients with MDD is correlated with cortisol dynamics, indexed by the cortisol awakening response (CAR). Further, we evaluate if CAR changes with antidepressant treatment, including a selective serotonin reuptake inhibitor, and if pretreatment CAR can predict treatment outcome. METHODS: Sixty-six patients (76% women) with a moderate to severe depressive episode underwent positron emission tomography imaging with [11C]SB207145 for quantification of brain 5-HT4R binding using BPND as outcome. Serial home sampling of saliva in the first hour from awakening was performed to assess CAR before and after 8 weeks of antidepressant treatment. Treatment outcome was measured by change in Hamilton Depression Rating Scale 6 items. RESULTS: In the unmedicated depressed state, prefrontal and anterior cingulate cortices 5-HT4R binding was positively associated with CAR. CAR remained unaltered after 8 weeks of antidepressant treatment, and pretreatment CAR did not significantly predict treatment outcome. CONCLUSIONS: Our findings highlight a link between serotonergic disturbances in MDD and cortisol dynamics, which likely is involved in disease and treatment mechanisms. Further, our data support 5-HT4R agonism as a promising precision target in patients with MDD and disturbed stress hormone dynamics.

Individualized Net Benefit estimation and meta-analysis using generalized pairwise comparisons in N-of-1 trials.

BACKGROUND: The Net Benefit (Δ) is a measure of the benefit-risk balance in clinical trials, based on generalized pairwise comparisons (GPC) using several prioritized outcomes and thresholds of clinical relevance. We extended Δ to N-of-1 trials, with a focus on patient-level and population-level Δ. METHODS: We developed a Δ estimator at the individual level as an extension of the stratum-specific Δ, and at the population-level as an extension of the stratified Δ. We performed a simulation study mimicking PROFIL, a series of 38 N-of-1 trials testing sildenafil in Raynaud's phenomenon, to assess the power for such an analysis with realistic data. We then reanalyzed PROFIL using GPC. This reanalysis was finally interpreted in the context of the main analysis of PROFIL which used Bayesian individual probabilities of efficacy. RESULTS: Simulations under the null showed good size of the test for both individual and population levels. The test lacked power when being simulated from the true PROFIL data, even when increasing the number of repetitions up to 140 days per patient. PROFIL individual-level estimated Δ were well correlated with the probabilities of efficacy from the Bayesian analysis while showing similarly wide confidence intervals. Population-level estimated Δ was not significantly different from zero, consistently with the previous Bayesian analysis. CONCLUSION: GPC can be used to estimate individual Δ which can then be aggregated in a meta-analytic way in N-of-1 trials. GPC ability to easily incorporate patient preferences allow for more personalized treatment evaluation, while needing much less computing time than Bayesian modeling.

Deep phenotyping towards precision psychiatry of first-episode depression - the Brain Drugs-Depression cohort.

BACKGROUND: Major Depressive Disorder (MDD) is a heterogenous brain disorder, with potentially multiple psychosocial and biological disease mechanisms. This is also a plausible explanation for why patients do not respond equally well to treatment with first- or second-line antidepressants, i.e., one-third to one-half of patients do not remit in response to first- or second-line treatment. To map MDD heterogeneity and markers of treatment response to enable a precision medicine approach, we will acquire several possible predictive markers across several domains, e.g., psychosocial, biochemical, and neuroimaging. METHODS: All patients are examined before receiving a standardised treatment package for adults aged 18-65 with first-episode depression in six public outpatient clinics in the Capital Region of Denmark. From this population, we will recruit a cohort of 800 patients for whom we will acquire clinical, cognitive, psychometric, and biological data. A subgroup (subcohort I, n = 600) will additionally provide neuroimaging data, i.e., Magnetic Resonance Imaging, and Electroencephalogram, and a subgroup of patients from subcohort I unmedicated at inclusion (subcohort II, n = 60) will also undergo a brain Positron Emission Tomography with the [11C]-UCB-J tracer binding to the presynaptic glycoprotein-SV2A. Subcohort allocation is based on eligibility and willingness to participate. The treatment package typically lasts six months. Depression severity is assessed with the Quick Inventory of Depressive Symptomatology (QIDS) at baseline, and 6, 12 and 18 months after treatment initiation. The primary outcome is remission (QIDS ≤ 5) and clinical improvement (≥ 50% reduction in QIDS) after 6 months. Secondary endpoints include remission at 12 and 18 months and %-change in QIDS, 10-item Symptom Checklist, 5-item WHO Well-Being Index, and modified Disability Scale from baseline through follow-up. We also assess psychotherapy and medication side-effects. We will use machine learning to determine a combination of characteristics that best predict treatment outcomes and statistical models to investigate the association between individual measures and clinical outcomes. We will assess associations between patient characteristics, treatment choices, and clinical outcomes using path analysis, enabling us to estimate the effect of treatment choices and timing on the clinical outcome. DISCUSSION: The BrainDrugs-Depression study is a real-world deep-phenotyping clinical cohort study of first-episode MDD patients. TRIAL REGISTRATION: Registered at clinicaltrials.gov November 15th, 2022 (NCT05616559).

Psilocybin modulation of time-varying functional connectivity is associated with plasma psilocin and subjective effects.

BACKGROUND: Psilocin, the neuroactive metabolite of psilocybin, is a serotonergic psychedelic that induces an acute altered state of consciousness, evokes lasting changes in mood and personality in healthy individuals, and has potential as an antidepressant treatment. Examining the acute effects of psilocin on resting-state time-varying functional connectivity implicates network-level connectivity motifs that may underlie acute and lasting behavioral and clinical effects. AIM: Evaluate the association between resting-state time-varying functional connectivity (tvFC) characteristics and plasma psilocin level (PPL) and subjective drug intensity (SDI) before and right after intake of a psychedelic dose of psilocybin in healthy humans. METHODS: Fifteen healthy individuals completed the study. Before and at multiple time points after psilocybin intake, we acquired 10-minute resting-state blood-oxygen-level-dependent functional magnetic resonance imaging scans. Leading Eigenvector Dynamics Analysis (LEiDA) and diametrical clustering were applied to estimate discrete, sequentially active brain states. We evaluated associations between the fractional occurrence of brain states during a scan session and PPL and SDI using linear mixed-effects models. We examined associations between brain state dwell time and PPL and SDI using frailty Cox proportional hazards survival analysis. RESULTS: Fractional occurrences for two brain states characterized by lateral frontoparietal and medial fronto-parietal-cingulate coherence were statistically significantly negatively associated with PPL and SDI. Dwell time for these brain states was negatively associated with SDI and, to a lesser extent, PPL. Conversely, fractional occurrence and dwell time of a fully connected brain state partly associated with motion was positively associated with PPL and SDI. CONCLUSION: Our findings suggest that the acute perceptual psychedelic effects induced by psilocybin may stem from drug-level associated decreases in the occurrence and duration of lateral and medial frontoparietal connectivity motifs. We apply and argue for a modified approach to modeling eigenvectors produced by LEiDA that more fully acknowledges their underlying structure. Together these findings contribute to a more comprehensive neurobiological framework underlying acute effects of serotonergic psychedelics.

Brain serotonin transporter is associated with cognitive-affective biases in healthy individuals.

Cognitive affective biases describe the tendency to process negative information or positive information over the other. These biases can be modulated by changing extracellular serotonin (5-HT) levels in the brain, for example, by pharmacologically blocking and downregulating the 5-HT transporter (5-HTT), which remediates negative affective bias. This suggests that higher levels of 5-HTT are linked to a priority of negative information over positive, but this link remains to be tested in vivo in healthy individuals. We, therefore, evaluated the association between 5-HTT levels, as measured with [11 C]DASB positron emission tomography (PET), and affective biases, hypothesising that higher 5-HTT levels are associated with a more negative bias. We included 98 healthy individuals with measures of [11 C]DASB binding potential (BPND ) and affective biases using The Emotional Faces Identification Task by subtracting the per cent hit rate for happy from that of sad faces (EFITAB ). We evaluated the association between [11 C]DASB BPND and EFITAB in a linear latent variable model, with the latent variable (5-HTTLV ) modelled from [11 C]DASB BPND in the fronto-striatal and fronto-limbic networks implicated in affective cognition. We observed an inverse association between 5-HTTLV and EFITAB (ß = -8% EFITAB per unit 5-HTTLV , CI = -14% to -3%, p = .002). These findings show that higher 5-HTT levels are linked to a more negative bias in healthy individuals. High 5-HTT supposedly leads to high clearance of 5-HT, and thus, a negative bias could result from low extracellular 5-HT. Future studies must reveal if a similar inverse association exists in individuals with affective disorders.

Acute Traumatic Stress Screening Can Identify Patients and Their Partners at Risk for Posttraumatic Stress Disorder Symptoms After a Cardiac Arrest: A Multicenter Prospective Cohort Study.

BACKGROUND: Posttraumatic stress disorder (PTSD) is prevalent in patients who have had a cardiac arrest and their partners. Accordingly, acute traumatic stress screening is recommended, but its association with later PTSD symptoms has never been addressed in postresuscitation settings. OBJECTIVE: The aim of this study was to examine whether acute traumatic stress is associated with PTSD symptoms in patients who have had a cardiac arrest and their partners. METHODS: This multicenter longitudinal study of 141 patients and 97 partners measures acute traumatic stress at 3 weeks and PTSD symptoms at 3 months and 1 year after resuscitation, using the Impact of Event Scale. Linear regression models were used to evaluate the association between severity of acute traumatic stress and PTSD symptoms and post hoc to explore effects of group (patients/partners), age, and sex on acute traumatic stress severity. We categorized Impact of Event Scale scores higher than 26 at 3 months and 1 year as clinical severe PTSD symptoms . RESULTS: Higher acute traumatic stress severity is significantly positively associated with higher PTSD symptom severity at 3 months (patients and partners: P < .001) and 1 year (patients and partners: P < .001) postresuscitation, with the strongest association for women compared with men ( P = .03). Acute traumatic stress was higher in women compared with men across groups ( P = .02). Clinical severe PTSD symptoms were present in 26% to 28% of patients and 45% to 48% of partners. CONCLUSION: Experiencing a cardiac arrest may elicit clinical severe PTSD symptoms in patients, but particularly in their partners. Screening patients and partners for acute traumatic stress postresuscitation is warranted to identify those at increased risk of long-term PTSD symptoms.

Net benefit in the presence of correlated prioritized outcomes using generalized pairwise comparisons: A simulation study.

BACKGROUND: The prioritized net benefit (Δ) is a measure of the benefit-risk balance in clinical trials, based on generalized pairwise comparisons (GPC) using several prioritized outcomes. Its estimation requires the classification as Wins or Losses of all possible pairs of patients, one from the experimental treatment (E) group and one from the control treatment (C) group. In this simulation study, we assessed the impact of the correlation between prioritized outcomes on Δ, its estimate, bias, size, and power. METHODS: The theoretical Δ value was derived for the specific case of two correlated binary outcomes when a normal copula is used. Focusing on one efficacy and one toxicity outcome, two situations frequently met in practice were simulated: binary efficacy outcome with binary toxicity outcome, or time to event efficacy outcome with categorical toxicity outcome. Several scenarios of efficacy and toxicity were generated, with various levels of correlation. RESULTS: When E was more effective than C, positive correlations were mainly associated with a decrease in the proportion of Losses, while negative correlations were associated with a decrease in the proportion of Wins on the toxicity outcome. This resulted in an increase of Δ^ with the intensity of the positive correlation without adding any bias. Results were similar whatever the type of outcomes generated but led to power alteration. CONCLUSION: Correlations between outcomes analyzed with GPC led to substantial but predictable modifications of Δ and its estimate. Correlations should be taken into consideration when performing sample size estimations in clinical trials.

Correcting the bias of the net benefit estimator due to right-censored observations.

Generalized pairwise comparisons (GPCs) are a statistical method used in randomized clinical trials to simultaneously analyze several prioritized outcomes. This procedure estimates the net benefit (Δ). Δ may be interpreted as the probability for a random patient in the treatment group to have a better overall outcome than a random patient in the control group, minus the probability of the opposite situation. However, the presence of right censoring introduces uninformative pairs that will typically bias the estimate of Δ toward 0. We propose a correction to GPCs that estimates the contribution of each uninformative pair based on the average contribution of the informative pairs. The correction can be applied to the analysis of several prioritized outcomes. We perform a simulation study to evaluate the bias associated with this correction. When only one time-to-event outcome was generated, the corrected estimates were unbiased except in the presence of very heavy censoring. The correction had no effect on the power or type-1 error of the tests based on the Δ. Finally, we illustrate the impact of the correction using data from two randomized trials. The illustrative datasets showed that the correction had limited impact when the proportion of censored observations was around 20% and was most useful when this proportion was close to 70%. Overall, we propose an estimator for the net benefit that is minimally affected by censoring under the assumption that uninformative pairs are exchangeable with informative pairs.

A new measure of treatment effect in clinical trials involving competing risks based on generalized pairwise comparisons.

In survival analysis with competing risks, the treatment effect is typically expressed using cause-specific or subdistribution hazard ratios, both relying on proportional hazards assumptions. This paper proposes a nonparametric approach to analyze competing risks data based on generalized pairwise comparisons (GPC). GPC estimate the net benefit, defined as the probability that a patient from the treatment group has a better outcome than a patient from the control group minus the probability of the opposite situation, by comparing all pairs of patients taking one patient from each group. GPC allow using clinically relevant thresholds and simultaneously analyzing multiple prioritized endpoints. We show that under proportional subdistribution hazards, the net benefit for competing risks settings can be expressed as a decreasing function of the subdistribution hazard ratio, taking a value 0 when the latter equals 1. We propose four net benefit estimators dealing differently with censoring. Among them, the Péron estimator uses the Aalen-Johansen estimator of the cumulative incidence functions to classify the pairs for which the patient with the best outcome could not be determined due to censoring. We use simulations to study the bias of these estimators and the size and power of the tests based on the net benefit. The Péron estimator was approximately unbiased when the sample size was large and the censoring distribution's support sufficiently wide. With one endpoint, our approach showed a comparable power to a proportional subdistribution hazards model even under proportional subdistribution hazards. An application of the methodology in oncology is provided.

A Single Dose of Psilocybin Increases Synaptic Density and Decreases 5-HT2A Receptor Density in the Pig Brain.

A single dose of psilocybin, a psychedelic and serotonin 2A receptor (5-HT2AR) agonist, may be associated with antidepressant effects. The mechanism behind its antidepressive action is unknown but could be linked to increased synaptogenesis and down-regulation of cerebral 5-HT2AR. Here, we investigate if a single psychedelic dose of psilocybin changes synaptic vesicle protein 2A (SV2A) and 5-HT2AR density in the pig brain. Twenty-four awake pigs received either 0.08 mg/kg psilocybin or saline intravenously. Twelve pigs (n = 6/intervention) were euthanized one day post-injection, while the remaining twelve pigs were euthanized seven days post-injection (n = 6/intervention). We performed autoradiography on hippocampus and prefrontal cortex (PFC) sections with [3H]UCB-J (SV2A), [3H]MDL100907 (5-HT2AR antagonist) and [3H]Cimbi-36 (5-HT2AR agonist). One day post psilocybin injection, we observed 4.42% higher hippocampal SV2A density and lowered hippocampal and PFC 5-HT2AR density (-15.21% to -50.19%). These differences were statistically significant in the hippocampus for all radioligands and in the PFC for [3H]Cimbi-36 only. Seven days post-intervention, there was still significantly higher SV2A density in the hippocampus (+9.24%) and the PFC (+6.10%), whereas there were no longer any differences in 5-HT2AR density. Our findings suggest that psilocybin causes increased persistent synaptogenesis and an acute decrease in 5-HT2AR density, which may play a role in psilocybin's antidepressive effects.

The structure of the serotonin system: A PET imaging study.

The human brain atlas of the serotonin (5-HT) system does not conform with commonly used parcellations of neocortex, since the spatial distribution of homogeneous 5-HT receptors and transporter is not aligned with such brain regions. This discrepancy indicates that a neocortical parcellation specific to the 5-HT system is needed. We first outline issues with an existing parcellation of the 5-HT system, and present an alternative parcellation derived from brain MR- and high-resolution PET images of five different 5-HT targets from 210 healthy controls. We then explore how well this new 5-HT parcellation can explain mRNA levels of all 5-HT genes. The parcellation derived here represents a characterization of the 5-HT system which is more stable and explains the underlying 5-HT molecular imaging data better than other atlases, and may hence be more sensitive to capture region-specific changes modulated by 5-HT.

Common HTR2A variants and 5-HTTLPR are not associated with human in vivo serotonin 2A receptor levels.

The serotonin 2A receptor (5-HT2AR) is implicated in the pathophysiology and treatment of various psychiatric disorders. [18 F]altanserin and [11 C]Cimbi-36 positron emission tomography (PET) allow for high-resolution imaging of 5-HT2AR in the living human brain. Cerebral 5-HT2AR binding is strongly genetically determined, though the impact of specific variants is poorly understood. Candidate gene studies suggest that HTR2A single nucleotide polymorphisms including rs6311/rs6313, rs6314, and rs7997012 may influence risk for psychiatric disorders and mediate treatment response. Although known to impact in vitro expression of 5-HT2AR or other serotonin (5-HT) proteins, their effect on human in vivo brain 5-HT2AR binding has as of yet been insufficiently studied. We thus assessed the extent to which these variants and the commonly studied 5-HTTLPR predict neocortex in vivo 5-HT2AR binding in healthy adult humans. We used linear regression analyses and likelihood ratio tests in 197 subjects scanned with [18 F]altanserin or [11 C]Cimbi-36 PET. Although we observed genotype group differences in 5-HT2AR binding of up to ~10%, no genetic variants were statistically significantly predictive of 5-HT2AR binding in what is the largest human in vivo 5-HT2AR imaging genetics study to date. Thus, in vitro and post mortem results suggesting effects on 5-HT2AR expression did not carry over to the in vivo setting. To any extent these variants might affect clinical risk, our findings do not support that 5-HT2AR binding mediates such effects. Our observations indicate that these individual variants do not significantly contribute to genetic load on human in vivo 5-HT2AR binding.

Visual stimuli induce serotonin release in occipital cortex: A simultaneous positron emission tomography/magnetic resonance imaging study.

Endogenous serotonin (5-HT) release can be measured noninvasively using positron emission tomography (PET) imaging in combination with certain serotonergic radiotracers. This allows us to investigate effects of pharmacological and nonpharmacological interventions on brain 5-HT levels in living humans. Here, we study the neural responses to a visual stimulus using simultaneous PET/MRI. In a cross-over design, 11 healthy individuals were PET/MRI scanned with the 5-HT1B receptor radioligand [11 C]AZ10419369, which is sensitive to changes in endogenous 5-HT. During the last part of the scan, participants either viewed autobiographical images with positive valence (n = 11) or kept their eyes closed (n = 7). The visual stimuli increased cerebral blood flow (CBF) in the occipital cortex, as measured with pseudo-continuous arterial spin labeling. Simultaneously, we found decreased 5-HT1B receptor binding in the occipital cortex (-3.6 ± 3.6%), indicating synaptic 5-HT release. Using a linear regression model, we found that the change in 5-HT1B receptor binding was significantly negatively associated with change in CBF in the occipital cortex (p = .004). For the first time, we here demonstrate how cerebral 5-HT levels change in response to nonpharmacological stimuli in humans, as measured with PET. Our findings more directly support a link between 5-HT signaling and visual processing and/or visual attention.

Evaluation of inferential methods for the net benefit and win ratio statistics.

General Pairwise Comparison (GPC) statistics, such as the net benefit and the win ratio, have been applied in clinical trial data analysis and design. In the literature, inferential methods based on re-sampling, asymptotic or exact methods have been proposed for these GPC statistics, but they have not been compared to each other. In this paper, the small sample bias of the variance estimation, Type I error control and 95% confidence interval coverage of the GPC inferential methods are evaluated using simulations. The exact permutation and bootstrap tests perform best in all evaluated aspects for the net benefit, while the exact bootstrap test performs best for the win ratio.

On the estimation of average treatment effects with right-censored time to event outcome and competing risks.

We are interested in the estimation of average treatment effects based on right-censored data of an observational study. We focus on causal inference of differences between t-year absolute event risks in a situation with competing risks. We derive doubly robust estimation equations and implement estimators for the nuisance parameters based on working regression models for the outcome, censoring, and treatment distribution conditional on auxiliary baseline covariates. We use the functional delta method to show that these estimators are regular asymptotically linear estimators and estimate their variances based on estimates of their influence functions. In empirical studies, we assess the robustness of the estimators and the coverage of confidence intervals. The methods are further illustrated using data from a Danish registry study.

Individualized quantification of the benefit from reperfusion therapy using stroke predictive models.

PURPOSE: Recent imaging developments have shown the potential of voxel-based models in assessing infarct growth after stroke. Many models have been proposed but their relevance in predicting the benefit of a reperfusion therapy remains unclear. We searched for a predictive model whose volumetric predictions would identify stroke patients who are to benefit from tissue plasminogen activator (t-PA)-induced reperfusion. MATERIAL AND METHODS: Forty-five cases were used to study retrospectively stroke progression from admission to end of follow-up. Predictive approaches based on various statistical models, predictive variables and spatial filtering methods were compared. The optimal approach was chosen according to the area under the precision-recall curve (AUPRC). The final lesion volume was then predicted assuming that the patient would or would not reperfuse. Patients, with an acute lesion of ≤50 ml and a predicted reduction in the presence of reperfusion >6 ml and >25% of the acute lesion, were classified as responders. RESULTS: The optimal model was a logistic regression using the voxel distance to the acute lesion, the volume of the acute lesion and Gaussian-filtered MRI contrast parameters as predictive variables. The predictions gave a median AUPRC of 0.655, a median AUC of 0.976 and a median volumetric error of 8.29 ml. Nineteen patients matched the responder profile. A non-significant trend of improved reduction in NIHSS score (-42.8%, p = .09) and in lesion volume (-78.1%, p = 0.21) following reperfusion was observed for responder patients. CONCLUSION: Despite limited volumetric accuracy, predictive stroke models can be used to quantify the benefit of reperfusion therapies.

Comparison of classification methods for tissue outcome after ischaemic stroke.

In acute ischaemic stroke, identifying brain tissue at high risk of infarction is important for clinical decision-making. This tissue may be identified with suitable classification methods from magnetic resonance imaging data. The aim of the present study was to assess and compare the performance of five popular classification methods (adaptive boosting, logistic regression, artificial neural networks, random forest and support vector machine) in identifying tissue at high risk of infarction on human voxel-based brain imaging data. The classification methods were used with eight MRI parameters, including diffusion-weighted imaging and perfusion-weighted imaging obtained in 55 patients. The five criteria used to assess the performance of the methods were the area under the receiver operating curve (AUCroc ), the area under the precision-recall curve (AUCpr ), sensitivity, specificity and the Dice coefficient. The methods performed equally in terms of sensitivity and specificity, while the results of AUCroc and the Dice coefficient were significantly better for adaptive boosting, logistic regression, artificial neural networks and random forest. However, there was no statistically significant difference between the performances of these five classification methods regarding AUCpr , which was the main comparison metric. Machine learning methods can provide valuable prognostic information using multimodal imaging data in acute ischaemic stroke, which in turn can assist in developing personalized treatment decision for clinicians after a thorough validation of methods with an independent data set.

Resumption of oral anticoagulation following traumatic injury and risk of stroke and bleeding in patients with atrial fibrillation: a nationwide cohort study.

Aims: We examined the risks of all-cause mortality, stroke, major bleeding, and recurrent traumatic injury associated with resumption of vitamin K antagonists (VKAs) and non-VKAs oral anticoagulants (NOACs) following traumatic injury in atrial fibrillation (AF) patients. Methods and results: This was a Danish nationwide registry-based study (2005-16), including 4541 oral anticoagulant (OAC)-treated AF patients experiencing traumatic injury (defined as traumatic brain injury, hip fracture, or traumatic torso or abdominal injury). Within 90 days following discharge from traumatic injury, 60.6% resumed VKA (median age = 80, CHA2DS2-VASc = 4, HAS-BLED = 2), 16.7% resumed NOAC (median age = 81, CHA2DS2-VASc = 4, HAS-BLED = 2), and 22.7% did not resume OAC treatment (median age = 81, CHA2DS2-VASc = 4, HAS-BLED = 3). Switch from VKA to NOAC occurred among 9.5%. Since 2009, the trend in OAC resumption increased (P-value <0.0001), in particular with NOACs (P-value <0.0001). Follow-up started 90 days after discharge, and time-varying multiple Cox regression analyses were used for comparisons. Compared with non-resumption, VKA and NOAC resumption were associated with lower hazard [95% confidence interval (CI)] of all-cause mortality [hazard ratio (HR) 0.48 (0.42-0.53) and HR 0.55 (0.47-0.66), respectively] and ischaemic stroke [HR 0.56 (0.43-0.72) and HR 0.54 (0.35-0.82), respectively], increased major bleeding hazard [HR 1.30 (1.03-1.64) and HR 1.15 (0.81-1.63), respectively], and similar hazard of recurrent traumatic injury [HR 0.93 (0.73-1.18) and HR 0.87 (0.60-1.27), respectively]. Conclusion: AF patients resuming VKA and NOAC treatment following traumatic injury have lower hazard of all-cause mortality and ischaemic stroke, increased hazard of major bleeding but without additional hazards of recurrent traumatic injury. Withholding OAC following a traumatic injury in AF patients may not be warranted.