Acute and Critical Care

Original Article

Trauma
Comparison of admission GCS score to admission GCS-P and FOUR scores for prediction of outcomes among patients with traumatic brain injury in the intensive care unit in India: Nishant Agrawal, Shivakumar S Iyer, Vishwanath Patil, Sampada Kulkarni, Jignesh N Shah, Prashant Jedge; Acute Crit Care. 2023;38(2):226-233. Published online May 25, 2023; DOI: https://doi.org/10.4266/acc.2023.00570

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Abstract PDF: Background
Traumatic brain injury (TBI) is a major contributor to trauma-related mortality and morbidity. Various scoring models have been proposed to evaluate the level of consciousness. The primary objective of this study was to measure the ability of the Full Outline of Unresponsiveness (FOUR) score and the Glasgow Coma Scale Pupil (GCS-P) score in predicting outcomes among TBI patients in terms of the Glasgow Outcome Scale (GOS) at 1 month and 6 months of follow-up.
Methods
Our study was a prospective observational study carried out over a period of 15 months that enrolled 50 patients admitted with TBI to the intensive care unit who fulfilled our inclusion criteria. Pearson’s correlation coefficient was used to correlate coma scales and outcome measures, and the predictive value of these scales was established by receiver operating characteristic (ROC) curve by calculating the area under the ROC curve with 99% confidence interval. All hypotheses were constructed as two-tailed, and P<0.01 was considered significant.
Results
In the present study, the GCS-P and FOUR scores among all patients on admission as well as in the subset of patients who were mechanically ventilated were statistically significant and strongly correlated with patient outcomes. The correlation coefficient of the GCS score compared to GCS-P and FOUR scores was higher and statistically significant. The areas under the ROC curve for the GCS, GCS-P, and FOUR scores and the number of computed tomography abnormalities were 0.912, 0.905, 0.937, and 0.324, respectively.
Conclusions
The GCS, GCS-P, and FOUR scores are all excellent predictors with a strong positive linear correlation with final outcome prediction. In particular, the GCS score has the best correlation with final outcome.

Review Article

Neurosurgery
Target temperature management in traumatic brain injury with a focus on adverse events, recognition, and prevention: Kwang Wook Jo; Acute Crit Care. 2022;37(4):483-490. Published online November 10, 2022; DOI: https://doi.org/10.4266/acc.2022.01291

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Abstract PDF: Traumatic brain injury (TBI) is a critical cause of disability and death worldwide. Many studies have been conducted aimed at achieving favorable neurologic outcomes by reducing secondary brain injury in TBI patients. However, ground-breaking outcomes are still insufficient so far. Because mild-to-moderate hypothermia (32°C–35°C) has been confirmed to help neurological recovery for recovered patients after circulatory arrest, it has been recognized as a major neuroprotective treatment plan for TBI patients. Thereafter, many clinical studies about the effect of therapeutic hypothermia (TH) on severe TBI have been conducted. However, efficacy and safety have not been demonstrated in many large-scale randomized controlled studies. Rather, some studies have demonstrated an increase in mortality rate due to complications such as pneumonia, so it is not highly recommended for severe TBI patients. Recently, some studies have shown results suggesting TH may help reperfusion/ischemic injury prevention after surgery in the case of mass lesions, such as acute subdural hematoma, and it has also been shown to be effective in intracranial pressure control. In conclusion, TH is still at the center of neuroprotective therapeutic studies regarding TBI. If proper measures can be taken to mitigate the many adverse events that may occur during the course of treatment, more positive efficacy can be confirmed. In this review, we look into adverse events that may occur during the process of the induction, maintenance, and rewarming of targeted temperature management and consider ways to prevent and address them.

Original Articles

Trauma
C-reactive protein-albumin ratio and procalcitonin in predicting intensive care unit mortality in traumatic brain injury: Canan Gürsoy, Güven Gürsoy, Semra Gümüş Demirbilek; Acute Crit Care. 2022;37(3):462-467. Published online August 5, 2022; DOI: https://doi.org/10.4266/acc.2022.00052

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Abstract PDF: Background
Prediction of intensive care unit (ICU) mortality in traumatic brain injury (TBI), which is a common cause of death in children and young adults, is important for injury management. Neuroinflammation is responsible for both primary and secondary brain injury, and C-reactive protein-albumin ratio (CAR) has allowed use of biomarkers such as procalcitonin (PCT) in predicting mortality. Here, we compared the performance of CAR and PCT in predicting ICU mortality in TBI.
Methods
Adults with TBI were enrolled in our study. The medical records of 82 isolated TBI patients were reviewed retrospectively.
Results
The mean patient age was 49.0 ± 22.69 years; 59 of all patients (72%) were discharged, and 23 (28%) died. There was a statistically significant difference between PCT and CAR values according to mortality (P<0.05). The area under the curve (AUC) was 0.646 with 0.071 standard error for PCT and 0.642 with 0.066 standard error for CAR. The PCT showed a similar AUC of the receiver operating characteristic to CAR.
Conclusions
This study shows that CAR and PCT are usable biomarkers to predict ICU mortality in TBI. When the determined cut-off values are used to predict the course of the disease, the CAR and PCT biomarkers will provide more effective information for treatment planning and for preparation of the family for the treatment process and to manage their outcome expectations.

Neurosurgery
Development and internal validation of a nomogram for predicting outcomes in children with traumatic subdural hematoma: Anukoon Kaewborisutsakul, Thara Tunthanathip; Acute Crit Care. 2022;37(3):429-437. Published online June 23, 2022; DOI: https://doi.org/10.4266/acc.2021.01795

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2 Citations

Abstract PDF

Background
A subdural hematoma (SDH) following a traumatic brain injury (TBI) in children can lead to unexpected death or disability. The nomogram is a clinical prediction tool used by physicians to provide prognosis advice to parents for making decisions regarding treatment. In the present study, a nomogram for predicting outcomes was developed and validated. In addition, the predictors associated with outcomes in children with traumatic SDH were determined.
Methods
In this retrospective study, 103 children with SDH after TBI were evaluated. According to the King’s Outcome Scale for Childhood Head Injury classification, the functional outcomes were assessed at hospital discharge and categorized into favorable and unfavorable. The predictors associated with the unfavorable outcomes were analyzed using binary logistic regression. Subsequently, a two-dimensional nomogram was developed for presentation of the predictive model.
Results
The predictive model with the lowest level of Akaike information criterion consisted of hypotension (odds ratio [OR], 9.4; 95% confidence interval [CI], 2.0–42.9), Glasgow coma scale scores of 3–8 (OR, 8.2; 95% CI, 1.7–38.9), fixed pupil in one eye (OR, 4.8; 95% CI, 2.6–8.8), and fixed pupils in both eyes (OR, 3.5; 95% CI, 1.6–7.1). A midline shift ≥5 mm (OR, 1.1; 95% CI, 0.62–10.73) and co-existing intraventricular hemorrhage (OR, 6.5; 95% CI, 0.003–26.1) were also included.
Conclusions
SDH in pediatric TBI can lead to mortality and disability. The predictability level of the nomogram in the present study was excellent, and external validation should be conducted to confirm the performance of the clinical prediction tool.

Citations

Citations to this article as recorded by

Development and internal validation of a nomogram to predict massive blood transfusions in neurosurgical operations
Kanisorn Sungkaro, Chin Taweesomboonyat, Anukoon Kaewborisutsakul
Journal of Neurosciences in Rural Practice.2022; 13: 711. CrossRef
Prediction of massive transfusions in neurosurgical operations using machine learning
Chin Taweesomboonyat, Anukoon Kaewborisutsakul, Kanisorn Sungkaro
Asian Journal of Transfusion Science.2022;[Epub] CrossRef

Case Report

Neurology
Myoclonic status epilepticus after severe hyperthermia in a patient with coronavirus disease 2019: Katherine A Hill, John J Peters, Sara M Schaefer; Received October 6, 2021 Accepted November 22, 2021 Published online March 24, 2022; DOI: https://doi.org/10.4266/acc.2021.01452 [Epub ahead of print]

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Abstract PDF: Myoclonic status epilepticus (MSE) is a sign of severe neurologic injury in cardiac arrest patients. To our knowledge, MSE has not been described as a result of prolonged hyperpyrexia. A 56-yearold man with coronavirus disease 2019 presented with acute respiratory distress syndrome, septic/hypovolemic shock, and presumed community-acquired pneumonia. Five days after presentation, he developed a sustained fever of 42.1°C that did not respond to acetaminophen or ice water gastric lavage. After several hours, he was placed on surface cooling. Three hours after fever resolution, new multifocal myoclonus was noted in the patient’s arms and trunk. Electroencephalography showed midline spikes consistent with MSE, which resolved with 40 mg/kg of levetiracetam. This case demonstrates that severe hyperthermia can cause cortical injury significant enough to trigger MSE and should be treated emergently using the most aggressive measures available. Providers should have a low threshold for electroencephalography in intubated patients with a recent history of hyperpyrexia.

Original Articles

Basic science and research
A machine learning model for predicting favorable outcome in severe traumatic brain injury patients after 6 months: Mehdi Nourelahi, Fardad Dadboud, Hosseinali Khalili, Amin Niakan, Hossein Parsaei; Acute Crit Care. 2022;37(1):45-52. Published online January 21, 2022; DOI: https://doi.org/10.4266/acc.2021.00486

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2 Citations

Abstract PDF

Background
Traumatic brain injury (TBI), which occurs commonly worldwide, is among the more costly of health and socioeconomic problems. Accurate prediction of favorable outcomes in severe TBI patients could assist with optimizing treatment procedures, predicting clinical outcomes, and result in substantial economic savings. Methods: In this study, we examined the capability of a machine learning-based model in predicting “favorable” or “unfavorable” outcomes after 6 months in severe TBI patients using only parameters measured on admission. Three models were developed using logistic regression, random forest, and support vector machines trained on parameters recorded from 2,381 severe TBI patients admitted to the neuro-intensive care unit of Rajaee (Emtiaz) Hospital (Shiraz, Iran) between 2015 and 2017. Model performance was evaluated using three indices: sensitivity, specificity, and accuracy. A ten-fold cross-validation method was used to estimate these indices. Results: Overall, the developed models showed excellent performance with the area under the curve around 0.81, sensitivity and specificity of around 0.78. The top-three factors important in predicting 6-month post-trauma survival status in TBI patients are “Glasgow coma scale motor response,” “pupillary reactivity,” and “age.” Conclusions: Machine learning techniques might be used to predict the 6-month outcome in TBI patients using only the parameters measured on admission when the machine learning is trained using a large data set.

Citations

Citations to this article as recorded by

Science fiction or clinical reality: a review of the applications of artificial intelligence along the continuum of trauma care
Olivia F. Hunter, Frances Perry, Mina Salehi, Hubert Bandurski, Alan Hubbard, Chad G. Ball, S. Morad Hameed
World Journal of Emergency Surgery.2023;[Epub] CrossRef
Predicting Outcome in Patients with Brain Injury: Differences between Machine Learning versus Conventional Statistics
Antonio Cerasa, Gennaro Tartarisco, Roberta Bruschetta, Irene Ciancarelli, Giovanni Morone, Rocco Salvatore Calabrò, Giovanni Pioggia, Paolo Tonin, Marco Iosa
Biomedicines.2022; 10(9): 2267. CrossRef

Trauma
The association between the initial lactate level and need for massive transfusion in severe trauma patients with and without traumatic brain injury: Young Hoon Park, Dong Hyun Ryu, Byung Kook Lee, Dong Hun Lee; Acute Crit Care. 2019;34(4):255-262. Published online November 29, 2019; DOI: https://doi.org/10.4266/acc.2019.00640

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Abstract PDF: Background
Exsanguination is a major cause of death in severe trauma patients. The purpose of this study was to analyze the prognostic impact of the initial lactate level for massive transfusion (MT) in severe trauma. We divided patients according to subgroups of traumatic brain injury (TBI) and non-TBI.
Methods
This single-institution retrospective study was conducted on patients who were admitted to hospital for severe trauma between January 2016 and December 2017. TBI was defined by a head Abbreviated Injury Scale ≥3. Receiver operating characteristic analysis was used to analyze the prognostic impact of the lactate level. Multivariate analyses were performed to evaluate the relationship between the MT and lactate level. The primary outcome was MT.
Results
Of the 553 patients, MT was performed in 62 patients (11.2%). The area under the curve (AUC) for the lactate level for predicting MT was 0.779 (95% confidence interval [CI], 0.742 to 0.813). The AUCs for lactate level in the TBI and non-TBI patients were 0.690 (95% CI, 0.627 to 0.747) and 0.842 (95% CI, 0.796 to 0.881), respectively. In multivariate analyses, the lactate level was independently associated with the MT (odds ratio [OR], 1.179; 95% CI, 1.070 to 1.299). The lactate level was independently associated with MT in non-TBI patients (OR, 1.469; 95% CI, 1.262 to 1.710), but not in TBI patients.
Conclusions
The initial lactate level may be a possible prognostic factor for MT in severe trauma. In TBI patients, however, the initial lactate level was not suitable for predicting MT.

The Relation between Neurologic Prognosis and Optic Nerve Sheath Diameter Measured in Initial Brain Computed Tomography of Cardiac Arrest and Hanging Patients: Kun Dong Kim, Hong Joon Ahn, Byul Nim Hee Cho, Sang Min Jeong, Joon Wan Lee, Yeon Ho You, In Sool Yoo, Won Joon Jeong; Korean J Crit Care Med. 2013;28(4):293-299.; DOI: https://doi.org/10.4266/kjccm.2013.28.4.293

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Abstract PDF: BACKGROUND
Early prediction of neurologic outcome is important to patients treated with therapeutic hypothermia after hypoxic brain injury. Hypoxic brain injury patients may have poor neurologic prognosis due to increased intracranial pressure. Increased intracranial pressure can be detected by optic nerve sheath diameter (ONSD) measurement in computed tomography (CT) or ultrasound. In this study, we evaluate the relation between neurologic prognosis and optic nerve sheath diameter measured in brain CT of hypoxic brain injury patients.
METHODS
We analyzed the patient clinical data by retrospective chart review. We measured the ONSD in initial brain CT. We also measured and calculated the gray white matter ratio (GWR) in CT scan. We split the patients into two groups based on neurologic outcome, and clinical data, ONSD, and GWR were compared in the two groups.
RESULTS
Twenty-four patients were included in this study (age: 52.6 +/- 18.3, 18 males). The mean ONSD of the poor neurologic outcome group was larger than that of the good neurologic outcome group (6.07 mm vs. 5.39 mm, p = 0.003). The GWR of the good neurologic outcome group was larger than that of the poor outcome group (1.09 vs. 1.28, p = 0.000). ONSD was a good predictor of neurologic outcome (area under curve: 0.848), and an ONSD cut off > or = 5.575 mm had a sensitivity of 86.7% and a specificity of 77.8%.
CONCLUSIONS
ONSD measured on the initial brain CT scan can predict the neurologic prognosis in cardiac arrest and hanging patients treated with therapeutic hypothermia.

Review

Management of Brain Injury after Post-cardiac Arrest Syndrome: Jong Ho Choi; Korean J Crit Care Med. 2009;24(1):1-3.; DOI: https://doi.org/10.4266/kjccm.2009.24.1.1

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Abstract PDF: In spite of improvement in cardiopulmonary resuscitation (CPR) techniques, post-CPR mortality and brain injury rates have not changed significantly. The post-cardiac arrest syndrome has been suggested to be the major reason for the high mortality rate after CPR. Post-cardiac arrest syndrome, including brain injury, myocardial dysfunction, and septic shock-like syndrome after CPR, result in complicated multiple organ failure. Physicians who work in the ICU should have a good understanding of thepathophysiology of post-cardiac arrest syndrome. Recently, therapeutic hypothermia treatment for protection of brain injuries has been applied as a therapeutic regimen in spite of various side effects during the hypothermic procedure. Finally, therapeutic hypothermic treatment to reduce brain injury in post-cardiac arrest syndrome patients is strongly recommended to physiciansmanaging CPR. I would like to briefly review the therapeutic hypothermic procedure for the management of post-cardiac arrest syndrome.

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