Dataset Information

The Impact of Medical Complications in Predicting the Rehabilitation Outcome of Patients With Disorders of Consciousness After Severe Traumatic Brain Injury.

ABSTRACT: In this study, we sought to assess the predictors of outcome in patients with disorders of consciousness (DOC) after severe traumatic brain injury (TBI) during neurorehabilitation stay. In total, 96 patients with DOC (vegetative state, minimally conscious state, or emergence from minimally conscious state) were enrolled (69 males; mean age 43.6 ± 20.8 years) and the improvement of the degree of disability, as assessed by the Disability Rating Scale, was considered the main outcome measure. To define the best predictor, a series of demographical and clinical factors were modeled using a twofold approach: (1) logistic regression to evaluate a possible causal effect among variables; and (2) machine learning algorithms (ML), to define the best predictive model. Univariate analysis demonstrated that disability in DOC patients statistically decreased at the discharge with respect to admission. Genitourinary was the most frequent medical complication (MC) emerging during the neurorehabilitation period. The logistic model revealed that the total amount of MCs is a risk factor for lack of functional improvement. ML discloses that the most important prognostic factors are the respiratory and hepatic complications together with the presence of the upper gastrointestinal comorbidities. Our study provides new evidence on the most adverse short-term factors predicting a functional recovery in DOC patients after severe TBI. The occurrence of medical complications during neurorehabilitation stay should be considered to avoid poor outcomes.

SUBMITTER: Lucca LF

PROVIDER: S-EPMC7641612 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The Impact of Medical Complications in Predicting the Rehabilitation Outcome of Patients With Disorders of Consciousness After Severe Traumatic Brain Injury.

Lucca Lucia Francesca LF Lofaro Danilo D Leto Elio E Ursino Maria M Rogano Stefania S Pileggi Antonio A Vulcano Serafino S Conforti Domenico D Tonin Paolo P Cerasa Antonio A

Frontiers in human neuroscience 20201021

In this study, we sought to assess the predictors of outcome in patients with disorders of consciousness (DOC) after severe traumatic brain injury (TBI) during neurorehabilitation stay. In total, 96 patients with DOC (vegetative state, minimally conscious state, or emergence from minimally conscious state) were enrolled (69 males; mean age 43.6 ± 20.8 years) and the improvement of the degree of disability, as assessed by the Disability Rating Scale, was considered the main outcome measure. To de ...[more]

PMID: 33192402

Similar Datasets

Project description:Patients with severe acquired brain injury and prolonged disorders of consciousness (pDoC) are characterized by high clinical complexity and high risk to develop medical complications. The present multi-center longitudinal study aimed at investigating the impact of medical complications on the prediction of clinical outcome by means of machine learning models. Patients with pDoC were consecutively enrolled at admission in 23 intensive neurorehabilitation units (IRU) and followed-up at 6 months from onset via the Glasgow Outcome Scale-Extended (GOSE). Demographic and clinical data at study entry and medical complications developed within 3 months from admission were collected. Machine learning models were developed, targeting neurological outcomes at 6 months from brain injury using data collected at admission. Then, after concatenating predictions of such models to the medical complications collected within 3 months, a cascade model was developed. One hundred seventy six patients with pDoC (M: 123, median age 60.2 years) were included in the analysis. At admission, the best performing solution (k-Nearest Neighbors regression, KNN) resulted in a median validation error of 0.59 points [IQR 0.14] and a classification accuracy of dichotomized GOS-E of 88.6%. Coherently, at 3 months, the best model resulted in a median validation error of 0.49 points [IQR 0.11] and a classification accuracy of 92.6%. Interpreting the admission KNN showed how the negative effect of older age is strengthened when patients' communication levels are high and ameliorated when no communication is present. The model trained at 3 months showed appropriate adaptation of the admission prediction according to the severity of the developed medical complexity in the first 3 months. In this work, we developed and cross-validated an interpretable decision support tool capable of distinguishing patients which will reach sufficient independence levels at 6 months (GOS-E > 4). Furthermore, we provide an updated prediction at 3 months, keeping in consideration the rehabilitative path and the risen medical complexity.

Project description:Severe traumatic brain injury (TBI) may result in a disorder of consciousness (DoC) and lead to substantial long-term disability. While level of independence with activities of daily living, especially for persons who recover consciousness during inpatient rehabilitation, generally improves over time, the degree of change in participation remains unknown. We determined level of participation among persons with TBI between 2005 and 2017 who were admitted to inpatient rehabilitation unable to follow commands and subsequently enrolled in the TBI Model Systems National Database. Participation on the Participation Assessment with Recombined Tools-Objective (PART-O) Productivity, Social Relations, and Out and About subscales was evaluated at 1-5 years post-injury. We used a mixed-effects model to longitudinally compare participation between persons who did and did not regain command-following during inpatient rehabilitation. We further explored the level of participation associated with increasing levels of functional independence (FIM). The analysis included 333 persons (229 recovered command-following during rehabilitation, mean age = 35.46 years, 74.9% male). Participation across groups, at all follow-up time points, on all PART-O subscales, was remarkably low (mean range = 0.021-1.91, maximum possible score = 5). Performance was highest on the Social Relations subscale and lowest on the Productivity subscale. Longitudinal analyses revealed no difference in level of participation or change in participation across time for persons who regained command-following during rehabilitation compared to those who did not. While productivity increased over time, social participation did not and participation outside the home increased more for younger than for older persons. Across all three PART-O subscales, FIM Motor scores positively predicted participation. FIM Cognitive scores positively predicted level of participation on the Productivity and Social Relations subscales. Exploratory analyses revealed that even persons who achieved independence on the FIM Motor and Cognitive subscales had low levels of participation across domains and follow-up years. In summary, persons with severe TBI who were admitted to inpatient rehabilitation unable to follow commands were found to be unlikely to participate in productive tasks, social endeavors, or activities outside of the home up to 5 years post-injury, even if functional independence was recovered.

Project description:See Schiff (doi:10.1093/awx209) for a scientific commentary on this article. Patients with acute severe traumatic brain injury may recover consciousness before self-expression. Without behavioural evidence of consciousness at the bedside, clinicians may render an inaccurate prognosis, increasing the likelihood of withholding life-sustaining therapies or denying rehabilitative services. Task-based functional magnetic resonance imaging and electroencephalography techniques have revealed covert consciousness in the chronic setting, but these techniques have not been tested in the intensive care unit. We prospectively enrolled 16 patients admitted to the intensive care unit for acute severe traumatic brain injury to test two hypotheses: (i) in patients who lack behavioural evidence of language expression and comprehension, functional magnetic resonance imaging and electroencephalography detect command-following during a motor imagery task (i.e. cognitive motor dissociation) and association cortex responses during language and music stimuli (i.e. higher-order cortex motor dissociation); and (ii) early responses to these paradigms are associated with better 6-month outcomes on the Glasgow Outcome Scale-Extended. Patients underwent functional magnetic resonance imaging on post-injury Day 9.2 ± 5.0 and electroencephalography on Day 9.8 ± 4.6. At the time of imaging, behavioural evaluation with the Coma Recovery Scale-Revised indicated coma (n = 2), vegetative state (n = 3), minimally conscious state without language (n = 3), minimally conscious state with language (n = 4) or post-traumatic confusional state (n = 4). Cognitive motor dissociation was identified in four patients, including three whose behavioural diagnosis suggested a vegetative state. Higher-order cortex motor dissociation was identified in two additional patients. Complete absence of responses to language, music and motor imagery was only observed in coma patients. In patients with behavioural evidence of language function, responses to language and music were more frequently observed than responses to motor imagery (62.5-80% versus 33.3-42.9%). Similarly, in 16 matched healthy subjects, responses to language and music were more frequently observed than responses to motor imagery (87.5-100% versus 68.8-75.0%). Except for one patient who died in the intensive care unit, all patients with cognitive motor dissociation and higher-order cortex motor dissociation recovered beyond a confusional state by 6 months. However, 6-month outcomes were not associated with early functional magnetic resonance imaging and electroencephalography responses for the entire cohort. These observations suggest that functional magnetic resonance imaging and electroencephalography can detect command-following and higher-order cortical function in patients with acute severe traumatic brain injury. Early detection of covert consciousness and cortical responses in the intensive care unit could alter time-sensitive decisions about withholding life-sustaining therapies.

Project description:Integrity of the default mode network (DMN) is believed to be essential for human consciousness. However, the effects of acute severe traumatic brain injury (TBI) on DMN functional connectivity are poorly understood. Furthermore, the temporal dynamics of DMN reemergence during recovery of consciousness have not been studied longitudinally in patients with acute severe TBI. We performed resting-state functional magnetic resonance imaging (rs-fMRI) to measure DMN connectivity in 17 patients admitted to the intensive care unit (ICU) with acute severe TBI and in 16 healthy control subjects. Eight patients returned for follow-up rs-fMRI and behavioral assessment six months post-injury. At each time point, we analyzed DMN connectivity by measuring intra-network correlations (i.e. positive correlations between DMN nodes) and inter-network anticorrelations (i.e. negative correlations between the DMN and other resting-state networks). All patients were comatose upon arrival to the ICU and had a disorder of consciousness (DoC) at the time of acute rs-fMRI (9.2 ± 4.6 days post-injury): 2 coma, 4 unresponsive wakefulness syndrome, 7 minimally conscious state, and 4 post-traumatic confusional state. We found that, while DMN anticorrelations were absent in patients with acute DoC, patients who recovered from coma to a minimally conscious or confusional state while in the ICU showed partially preserved DMN correlations. Patients who remained in coma or unresponsive wakefulness syndrome in the ICU showed no DMN correlations. All eight patients assessed longitudinally recovered beyond the confusional state by 6 months post-injury and showed normal DMN correlations and anticorrelations, indistinguishable from those of healthy subjects. Collectively, these findings suggest that recovery of consciousness after acute severe TBI is associated with partial preservation of DMN correlations in the ICU, followed by long-term normalization of DMN correlations and anticorrelations. Both intra-network DMN correlations and inter-network DMN anticorrelations may be necessary for full recovery of consciousness after acute severe TBI.

Project description:ObjectivesTo investigate functional outcomes and state of consciousness at 1 year and ≥2 years postinjury in children who sustained a traumatic brain injury and were in a disorder of consciousness (DOC), either vegetative state (VS) or minimally conscious state (MCS), upon admission to inpatient rehabilitation.DesignRetrospective chart review.SettingPediatric inpatient rehabilitation unit.ParticipantsChildren aged 2-18 years (N=37) who were admitted to inpatient rehabilitation with admission scores <30 on the Cognitive and Linguistic Scale (CALS).InterventionsNot applicable.Main outcome measuresGlasgow Outcome Scale- Extended, Pediatric Revision (GOS-E Peds), and state of consciousness based on previously established guidelines.ResultsAt admission, 16 children were in VS (43.2%) and 21 (56.8%) were in MCS. Children admitted in VS had a significantly longer time from injury to inpatient rehabilitation admission, lower CALS admission scores, were more likely to be in a DOC ≥28 days, and had greater disability at both follow-up time points. At the 1-year follow-up, 3 patients were in VS, 7 were in MCS, and 27 had emerged from MCS. By the time of the most recent follow-up (≥2y), 2 more patients had emerged from MCS. Across the cohort, GOS-E Peds scores at 1 year ranged from VS (GOS-E Peds, 7) to upper moderate disability (GOS-E Peds, 3). Most patients were functioning in the lower severe disability category (GOS-E Peds, 6) at 1 year (43.2%) and at the time of the most recent follow-up (43.2%). Twenty-seven patients (73.0%) showed stable GOS-E Peds scores between the 2 time points, 6 (16.2%) improved, and 4 (10.8%) were deceased.ConclusionsAlthough a majority of patients emerged from a DOC by 1 year postinjury, most continued to demonstrate notable functional impairment at the 1-year follow-up that persisted to the most recent follow-up. A small subset demonstrated important improvements between 1 year and the most recent follow-up (2 patients emerged, 6 patients showed improvement in GOS-E Peds scores).

Project description:Background/objectiveBehavioral examinations may fail to detect language function in patients with severe traumatic brain injury (TBI) due to confounds such as having an endotracheal tube. We investigated whether resting and stimulus-evoked electroencephalography (EEG) methods detect the presence of language function in patients with severe TBI.MethodsFour EEG measures were assessed: (1) resting background (applying Forgacs' criteria), (2) reactivity to speech, (3) background and reactivity (applying Synek's criteria); and (4) an automated support vector machine (classifier for speech versus rest). Cohen's kappa measured agreement between the four EEG measures and evidence of language function on a behavioral coma recovery scale-revised (CRS-R) and composite (CRS-R or functional MRI) reference standard. Sensitivity and specificity of each EEG measure were calculated against the reference standards.ResultsWe enrolled 17 adult patients with severe TBI (mean ± SD age 27.0 ± 7.0 years; median [range] 11.5 [2-1173] days post-injury) and 16 healthy subjects (age 28.5 ± 7.8 years). The classifier, followed by Forgacs' criteria for resting background, demonstrated the highest agreement with the behavioral reference standard. Only Synek's criteria for background and reactivity showed significant agreement with the composite reference standard. The classifier and resting background showed balanced sensitivity and specificity for behavioral (sensitivity = 84.6% and 80.8%; specificity = 57.1% for both) and composite reference standards (sensitivity = 79.3% and 75.9%, specificity = 50% for both).ConclusionsMethods applying an automated classifier, resting background, or resting background with reactivity may identify severe TBI patients with preserved language function. Automated classifier methods may enable unbiased and efficient assessment of larger populations or serial timepoints, while qualitative visual methods may be practical in community settings.

Dataset Information

The Impact of Medical Complications in Predicting the Rehabilitation Outcome of Patients With Disorders of Consciousness After Severe Traumatic Brain Injury.

Publications

The Impact of Medical Complications in Predicting the Rehabilitation Outcome of Patients With Disorders of Consciousness After Severe Traumatic Brain Injury.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets