Connectivity of Soft Random Geometric Graphs Over Annuli

Nodes are randomly distributed within an annulus (and then a shell) to form a point pattern of communication terminals which are linked stochastically according to the Rayleigh fading of radio-frequency data signals. We then present analytic formulas for the connection probability of these spatially embedded graphs, describing the connectivity behaviour as a dense-network limit is approached. This extends recent work modelling ad hoc networks in non-convex domains.Comment: 12 pages, 6 figure

Comparison of four clinical risk scores in comatose patients after out-of-hospital cardiac arrest.

BACKGROUND AND AIMS Several different scoring systems for early risk stratification after out-of-hospital cardiac arrest have been developed, but few have been validated in large datasets. The aim of the present study was to compare the well-validated Out-of-hospital Cardiac Arrest (OHCA) and Cardiac Arrest Hospital Prognosis (CAHP)-scores to the less complex MIRACLE2- and Target Temperature Management (TTM)-scores. METHODS This was a post-hoc analysis of the Targeted Hypothermia versus Targeted Normothermia after Out-of-Hospital Cardiac Arrest (TTM2) trial. Missing data were handled by multiple imputation. The primary outcome was discriminatory performance assessed as the area under the receiver operating characteristics-curve (AUROC), with the outcome of interest being poor functional outcome or death (modified Rankin Scale 4-6) at 6 months after OHCA. RESULTS Data on functional outcome at 6 months were available for 1829 cases, which constituted the study population. The pooled AUROC for the MIRACLE2-score was 0.810 (95% CI 0.790 - 0.828), 0.835 (95% CI 0.816 - 0.852) for the TTM-score, 0.820 (95% CI 0.800 - 0.839) for the CAHP-score and 0.770 (95% CI 0.748 - 0.791) for the OHCA-score. At the cut-offs needed to achieve specificities >95%, sensitivities were <40 % for all four scoring systems. CONCLUSIONS The TTM-, MIRACLE2- and CAHP-scores are all capable of providing objective risk estimates accurate enough to be used as part of a holistic patient assessment after OHCA of a suspected cardiac origin. Due to its simplicity, the MIRACLE2-score could be a practical solution for both clinical application and risk stratification within trials

Auditory discrimination improvement predicts awakening of postanoxic comatose patients treated with targeted temperature management at 36°C.

Outcome prognostication in postanoxic comatose patients is more accurate in predicting poor than good recovery. Using electroencephalography recordings in patients treated with targeted temperature management at 33°C (TTM 33), we have previously shown that improvement in auditory discrimination over the first days of coma predicted awakening. Given the increased application of a 36°C temperature target (TTM 36), here we aimed at validating the predictive value of auditory discrimination in the TTM 36 setting. In this prospective multicenter study, we analyzed the EEG responses to auditory stimuli from 60 consecutive patients from the first and second coma day. A semiautomatic decoding analysis was applied to single patient data to quantify discrimination performance between frequently repeated and deviant sounds. The decoding change from the first to second day was used for predicting patient outcome. We observed an increase in auditory discrimination in 25 out of 60 patients. Among them, 17 awoke from coma (68% positive predictive value; 95% confidence interval: 0.46-0.85). By excluding patients with electroencephalographic epileptiform features, 15 of 18 exhibited improvement in auditory discrimination (83% positive predictive value; 95% confidence interval: 0.59-0.96). Specificity of good outcome prediction increased after adding auditory discrimination to EEG reactivity. These results suggest that tracking of auditory discrimination over time is informative of good recovery independent of the temperature target. This quantitative test provides complementary information to existing clinical tools by identifying patients with high chances of recovery and encouraging the maintenance of life support

Somatosensory and auditory deviance detection for outcome prediction during postanoxic coma.

Prominent research in patients with disorders of consciousness investigated the electrophysiological correlates of auditory deviance detection as a marker of consciousness recovery. Here, we extend previous studies by investigating whether somatosensory deviance detection provides an added value for outcome prediction in postanoxic comatose patients. Electroencephalography responses to frequent and rare stimuli were obtained from 66 patients on the first and second day after coma onset. Multivariate decoding analysis revealed an above chance-level auditory discrimination in 25 patients on the first day and in 31 patients on the second day. Tactile discrimination was significant in 16 patients on the first day and in 23 patients on the second day. Single-day sensory discrimination was unrelated to patients' outcome in both modalities. However, improvement of auditory discrimination from first to the second day was predictive of good outcome with a positive predictive power (PPV) of 0.73 (CI = 0.52-0.88). Analyses considering the improvement of tactile, auditory and tactile, or either auditory or tactile discrimination showed no significant prediction of good outcome (PPVs = 0.58-0.68). Our results show that in the acute phase of coma deviance detection is largely preserved for both auditory and tactile modalities. However, we found no evidence for an added value of somatosensory to auditory deviance detection function for coma-outcome prediction

Speed of cooling after cardiac arrest in relation to the intervention effect: a sub-study from the TTM2-trial

Background: Targeted temperature management (TTM) is recommended following cardiac arrest; however, time to target temperature varies in clinical practice. We hypothesised the effects of a target temperature of 33 °C when compared to normothermia would differ based on average time to hypothermia and those patients achieving hypothermia fastest would have more favorable outcomes. Methods: In this post-hoc analysis of the TTM-2 trial, patients after out of hospital cardiac arrest were randomized to targeted hypothermia (33 °C), followed by controlled re-warming, or normothermia with early treatment of fever (body temperature, ≥ 37.8 °C). The average temperature at 4 h (240 min) after return of spontaneous circulation (ROSC) was calculated for participating sites. Primary outcome was death from any cause at 6 months. Secondary outcome was poor functional outcome at 6 months (score of 4-6 on modified Rankin scale). Results: A total of 1592 participants were evaluated for the primary outcome. We found no evidence of heterogeneity of intervention effect based on the average time to target temperature on mortality (p = 0.17). Of patients allocated to hypothermia at the fastest sites, 71 of 145 (49%) had died compared to 68 of 148 (46%) of the normothermia group (relative risk with hypothermia, 1.07; 95% confidence interval 0.84-1.36). Poor functional outcome was reported in 74/144 (51%) patients in the hypothermia group, and 75/147 (51%) patients in the normothermia group (relative risk with hypothermia 1.01 (95% CI 0.80-1.26). Conclusions: Using a hospital's average time to hypothermia did not significantly alter the effect of TTM of 33 °C compared to normothermia and early treatment of fever. Keywords: Hypothermia; Out of hospital cardiac arrest; Temperature management; Time to target temperature

EEG for good outcome prediction after cardiac arrest: a multicentre cohort study.

AIM Assess the prognostic ability of a non-highly malignant and reactive EEG to predict good outcome after cardiac arrest (CA). METHODS Prospective observational multicentre substudy of the "Targeted Hypothermia versus Targeted Normothermia after Out-of-hospital Cardiac Arrest Trial", also known as the TTM2-trial. Presence or absence of highly malignant EEG patterns and EEG reactivity to external stimuli were prospectively assessed and reported by the trial sites. Highly malignant patterns were defined as burst-suppression or suppression with or without superimposed periodic discharges. Multimodal prognostication was performed 96 hours after CA. Good outcome at 6 months was defined as a modified Rankin Scale score of 0-3. RESULTS 873 comatose patients at 59 sites had an EEG assessment during the hospital stay. Of these, 283 (32%) had good outcome. EEG was recorded at a median of 69 hours (IQR 47-91) after CA. Absence of highly malignant EEG patterns was seen in 543 patients of whom 255 (29% of the cohort) had preserved EEG reactivity. A non-highly malignant and reactive EEG had 56% (CI 50-61) sensitivity and 83% (CI 80-86) specificity to predict good outcome. Presence of EEG reactivity contributed (p<0.001) to the specificity of EEG to predict good outcome compared to only assessing background pattern without taking reactivity into account. CONCLUSION Nearly one-third of comatose patients resuscitated after CA had a non-highly malignant and reactive EEG that was associated with a good long-term outcome. Reactivity testing should be routinely performed since preserved EEG reactivity contributed to prognostic performance

Recalibration of the delirium prediction model for ICU patients (PRE-DELIRIC): a multinational observational study

Purpose Recalibration and determining discriminative power, internationally, of the existing delirium prediction model (PRE-DELIRIC) for intensive care patients. Methods A prospective multicenter cohort study was performed in eight intensive care units (ICUs) in six countries. The ten predictors (age, APACHE-II, urgent and admission category, infection, coma, sedation, morphine use, urea level, metabolic acidosis) were collected within 24 h after ICU admission. The confusion assessment method for the intensive care unit (CAM-ICU) was used to identify ICU delirium. CAM-ICU screening compliance and inter-rater reliability measurements were used to secure the quality of the data. Results A total of 2,852 adult ICU patients were screened of which 1,824 (64 %) were eligible for the study. Main reasons for exclusion were length of stay <1 day (19.1 %) and sustained coma (4.1 %). CAM-ICU compliance was mean (SD) 82 ± 16 % and inter-rater reliability 0.87 ± 0.17. The median delirium incidence was 22.5 % (IQR 12.8–36.6 %). Although the incidence of all ten predictors differed significantly between centers, the area under the receiver operating characteristic (AUROC) curve of the eight participating centers remained good: 0.77 (95 % CI 0.74–0.79). The linear predictor and intercept of the prediction rule were adjusted and resulted in improved re-calibration of the PRE-DELIRIC model. Conclusions In this multinational study, we recalibrated the PRE-DELIRIC model. Despite differences in the incidence of predictors between the centers in the different countries, the performance of the PRE-DELIRIC-model remained good. Following validation of the PRE-DELIRIC model, it may facilitate implementation of strategies to prevent delirium and aid improvements in delirium management of ICU patients