ASSESSMENT OF COMA AND IMPAIRED CONSCIOUSNESS: A Practical Scale
Abstract
A clinical scale has been evolved for assessing the depth and duration of impaired consciousness and coma. Three aspects of behaviour are independently measured—motor responsiveness, verbal performance, and eye opening. These can be evaluated consistently by doctors and nurses and recorded on a simple chart which has proved practical both in a neurosurgical unit and in a general hospital. The scale facilitates consultations between general and special units in cases of recent brain damage, and is useful also in defining the duration of prolonged coma.
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Cited by (10138)
Intoxication and Glasgow coma scale scores in patients with head trauma
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In this retrospective chart review study, data were extracted from The Pennsylvania Trauma Systems Foundation Data Base Collection System. Eligible subjects included trauma patients aged 18 years and older, with head trauma, who presented between January 2019 and August 2023. Subjects were matched to controls who did not test positive for drugs or alcohol, matched by Injury Severity Score (ISS) category.
Among 1088 subjects, the mean age was 63 (95% CI 62–64). The mean Injury Severity Score was 21 (95% CI 21–22). The median GCS among all subjects was 14 (IQR 6–15). Cases with alcohol or drug use were matched to controls without alcohol or drug use, and were matched by categories of Injury Severity Score. Cases with alcohol or drug use had lower GCS (median 13; IQR 3–15), compared to cases without alcohol or drug use (median 15; IQR 13–15) (p < 0.0001, Wilcoxon Rank Sum Test).
Among patients with head trauma, intoxicated patients had statistically significant lower GCS scores as compared to matched patients with similar Injury Severity Scores.
A review of brain injury at multiple time scales and its clinicopathological correlation through in silico modeling
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Statement of Significance: The connection between clinical observations and brain pathology is crucial for managing brain injuries. Brain injuries result in brain damage via diverse factors across scales, from neurons to organs, from initial trauma to neurodegeneration. However, limited direct evidence linking injury mechanisms to long-term human tissue damage hinders clinicopathological connections. In silico modeling, a cost-effective approach utilizing physics and machine learning-based principles, can aid clinicians in uncovering injury pathways. A comprehensive, multimodal, and multiphysics model is vital for understanding complex brain tissue damage. This study categorizes modeling strategies, reviews damage mechanisms across scales, and recommends comprehensive biomechanical models for personalized treatment.
ABO blood type and thromboembolic complications after intracerebral hemorrhage: An exploratory analysis
2024, Journal of Stroke and Cerebrovascular DiseasesNon-O blood types are known to be associated with thromboembolic complications (TECs) in population-based studies. TECs are known drivers of morbidity and mortality in intracerebral hemorrhage (ICH) patients, yet the relationships of blood type on TECs in this patient population are unknown. We sought to explore the relationships between ABO blood type and TECs in ICH patients.
Consecutive adult ICH patients enrolled into a prospective observational cohort study with available ABO blood type data were analyzed. Patients with cancer history, prior thromboembolism, and baseline laboratory evidence of coagulopathy were excluded. The primary exposure variable was blood type (non-O versus O). The primary outcome was composite TEC, defined as pulmonary embolism, deep venous thrombosis, ischemic stroke or myocardial infarction, during the hospital stay. Relationships between blood type, TECs and clinical outcomes were separately assessed using logistic regression models after adjusting for sex, ethnicity and ICH score.
Of 301 ICH patients included for analysis, 44% were non-O blood type. Non-O blood type was associated with higher admission GCS and lower ICH score on baseline comparisons. We identified TECs in 11.6% of our overall patient cohort. . Although TECs were identified in 9.9% of non-O blood type patients compared to 13.0% in O blood type patients, we did not identify a significant relationship of non-O blood type with TECs (adjusted OR=0.776, 95%CI: 0.348-1.733, p=0.537). The prevalence of specific TECs were also comparable in unadjusted and adjusted analyses between the two cohorts. In additional analyses, we identified that TECs were associated with poor 90-day mRS (adjusted OR=3.452, 95% CI: 1.001-11.903, p=0.050). We did not identify relationships between ABO blood type and poor 90-day mRS (adjusted OR=0.994, 95% CI:0.465-2.128, p=0.988).
We identified that TECs were associated with worse ICH outcomes. However, we did not identify relationships in ABO blood type and TECs. Further work is required to assess best diagnostic and prophylactic and treatment strategies for TECs to improve ICH outcomes.
Trauma Bay Evaluation and Resuscitative Decision-Making
2024, Surgical Clinics of North AmericaPredicting time-to-intubation after critical care admission using machine learning and cured fraction information
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Nutritional risk and morbidity and mortality in intensive care unit patients with Coronavirus disease 2019
2024, Clinical Nutrition ESPENThe Coronavirus disease 2019 (COVID-19) spread rapidly, with 37 million cases and more than 699,000 deaths. Among intensive care unit (ICU) patients with COVID-19, a high incidence of acute kidney injury (AKI) has been observed, ranging from 50 to 80%; furthermore, 85.9% were calculated to have high nutritional risk, which doubled their odds of death. The aim of the present study was to evaluate possible associations between nutritional risk, acute kidney injury, and morbidity and mortality in patients with COVID-19 admitted to an ICU.
Retrospective cohort study of adult and older-adult patients hospitalized for >24 h in an ICU. The exposure was diagnosis of COVID-19, while the outcomes were mortality, acute kidney injury, dialysis, mechanical ventilation, and vasopressor use. The association of nutritional risk with outcomes was evaluated. The sample consisted of two secondary datasets. Individuals aged <18 years, those with dialytic chronic kidney disease, pregnant women, and those diagnosed with brain death were excluded.
The sample consisted of 192 patients: 101 in the exposure group (positive for COVID-19) and 91 in the control group (no COVID-19 diagnosis). The COVID-19 and non-COVID-19 groups differed significantly in the variables weight, body mass index (BMI), nutritional risk, mNUTRIC-S score, and length of ICU stay. Our results suggest that the optimal mNUTRIC-S score cutoff to predict nutritional risk is <5 points.
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