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Original Articles
Nutrition
Effect of standard- versus high-protein enteral feeding on rectus femoris muscle mass in mechanically ventilated traumatic brain injury patients: a prospective randomized study in Egypt and the United States
Hanan Elkalawy, Pavan Sekhar, Mona Fayad, Mohamed Barrima, Mohammad Abdullah
Acute Crit Care. 2026;41(1):160-173.   Published online November 24, 2025
DOI: https://doi.org/10.4266/acc.001025
  • 1,045 View
  • 44 Download
AbstractAbstract PDF
Background
Critically ill patients with muscle wasting experience prolonged intensive care unit (ICU) stays, delayed weaning, and higher mortality. Trauma-induced stress disrupts protein metabolism, leading to immunosuppression and muscle loss. This study evaluates whether high-protein intake through enteral nutrition preserves muscle mass and improves clinical outcomes compared to standard protein intake. Methods: In our multicenter research, 102 critically ill, mechanically ventilated patients (age, 39±7; female, 51; body mass index, 30.3±1.8 kg/m2 ) were assigned randomly to receive either a high-protein (2.2 g/kg BW/day) or standard (1.5 g/kg BW/day) diet. Enteral nutrition was individualized based on energy expenditure. Ultrasound measured whether the rectus femoris muscle cross-sectional area (RFM-9 CSA) and pennation angle correlated with dietary intake. The data are presented as mean±standard deviation. Results: Protein intake was 1.8±0.2 vs. 1.2±0.4 g/kg/day in high-protein and standard groups, respectively. In the intervention and standard groups, the baseline RFM-CSA and Pennation angle were 11.43±0.87 mm vs. 11.3±0.91 mm and 9.1±0.58 mm vs. 8.91±1.04 mm (P>0.05). Days 5, 10, and 20 showed significant variations in RFM-CSA and pennation angle (P<0.001). The intervention group experienced a shorter ICU length of stay (47.0±19.5 vs. 56.3±26.9 days, P=0.001) and a shorter period of mechanical ventilation (33±3.5 vs. 33±2.3 days, P=0.001). Conclusions: Early high protein intake significantly preserves muscle mass, reducing the duration of stay in the ICU and the need for mechanical ventilation.
Neurosurgery
Cost-effectiveness of intracranial pressure monitoring in severe traumatic brain injury in Southern Thailand
Jidapa Jitchanvichai, Thara Tunthanathip
Acute Crit Care. 2025;40(1):69-78.   Published online February 21, 2025
DOI: https://doi.org/10.4266/acc.004080
  • 3,993 View
  • 140 Download
  • 3 Web of Science
  • 5 Crossref
AbstractAbstract PDFSupplementary Material
Background
Traumatic brain injury (TBI) is a leading cause of fatalities and disabilities in the public health domain, particularly in Thailand. Guidelines for TBI patients advise intracranial pressure monitoring (ICPm) for intensive care. However, information about the cost-effectiveness (CE) of ICPm in cases of severe TBI is lacking. This study assessed the CE of ICPm in severe TBI.
Methods
This was a retrospective cohort economic evaluation study from the perspective of the healthcare system. Direct costs were sourced from electronic medical records, and quality-adjusted life years (QALY) for each individual were computed using multiple linear regression with standardization. Incremental costs, incremental QALY, and the incremental CE ratio (ICER) were estimated, and the bootstrap method with 1,000 iterations was used in uncertainty analysis.
Results
The analysis included 821 individuals, with 4.1% undergoing intraparenchymal ICPm. The average cost of hospitalization was United States dollar ($)8,697.13 (±6,271.26) in both groups. The incremental cost and incremental QALY of the ICPm group compared with the non-ICPm group were $3,322.88 and –0.070, with the base-case ICER of $–47,504.08 per additional QALY. Results demonstrated that 0.007% of bootstrapped ICERs were below the willingness-to-pay (WTP) threshold of Thailand.
Conclusions
ICPm for severe TBI was not cost-effective compared with the WTP threshold of Thailand. Resource allocation for TBI prognosis requires further development of cost-effective treatment guidelines.

Citations

Citations to this article as recorded by  
  • Impact of Preoperative Hair Removal on Self-Esteem after Brain Tumor Surgery
    Thara Tunthanathip, Natthanee Pisitthaworakul
    Asian Journal of Neurosurgery.2026; 21(01): 147.     CrossRef
  • Deep learning-based model for detection of intracranial waveforms with poor brain compliance in southern Thailand
    Thara Tunthanathip, Avika Trakulpanitkit
    Acute and Critical Care.2025; 40(3): 473.     CrossRef
  • Feasibility comparison of deep learning image regressions to estimate intracranial pressure from cranial computed tomography in hydrocephalus
    Thara Tunthanathip, Rakkrit Duangsoithong, Sakchai Sae-Heng
    Journal of Neurosciences in Rural Practice.2025; 16: 606.     CrossRef
  • Risk factors and dose-response relationship of catheter-associated urinary tract infection in neurosurgical patients
    Thara Tunthanathip, Natthanee Pisitthaworakul
    International Journal of Nutrition, Pharmacology, Neurological Diseases.2025; 15(4): 451.     CrossRef
  • Prognosis of subarachnoid hemorrhage determined by intracranial pressure thresholds
    Thara Tunthanathip, Rakkrit Duangsoithong, Sakchai Sae-Heng
    Journal of Cerebrovascular and Endovascular Neurosurgery.2025; 27(4): 309.     CrossRef
Trauma
Bedside ultrasonographic evaluation of optic nerve sheath diameter for monitoring of intracranial pressure in traumatic brain injury patients: a cross sectional study in level II trauma care center in India
Sujit J. Kshirsagar, Anandkumar H. Pande, Sanyogita V. Naik, Alok Yadav, Ruchira M. Sakhala, Sangharsh M. Salve, Aysath Nuhaimah, Priyanka Desai
Acute Crit Care. 2024;39(1):155-161.   Published online February 23, 2024
DOI: https://doi.org/10.4266/acc.2023.01172
  • 15,688 View
  • 550 Download
  • 11 Web of Science
  • 11 Crossref
AbstractAbstract PDF
Background
Optic nerve sheath diameter (ONSD) is an emerging non-invasive, easily accessible, and possibly useful measurement for evaluating changes in intracranial pressure (ICP). The utilization of bedside ultrasonography (USG) to measure ONSD has garnered increased attention due to its portability, real-time capability, and lack of ionizing radiation. The primary aim of the study was to assess whether bedside USG-guided ONSD measurement can reliably predict increased ICP in traumatic brain injury (TBI) patients.
Methods
A total of 95 patients admitted to the trauma intensive care unit was included in this cross sectional study. Patient brain computed tomography (CT) scans and Glasgow Coma Scale (GCS) scores were assessed at the time of admission. Bedside USG-guided binocular ONSD was measured and the mean ONSD was noted. Microsoft Excel was used for statistical analysis.
Results
Patients with low GCS had higher mean ONSD values (6.4±1.0 mm). A highly significant association was found among the GCS, CT results, and ONSD measurements (P<0.001). Compared to CT scans, the bedside USG ONSD had 86.42% sensitivity and 64.29% specificity for detecting elevated ICP. The positive predictive value of ONSD to identify elevated ICP was 93.33%, and its negative predictive value was 45.00%. ONSD measurement accuracy was 83.16%.
Conclusions
Increased ICP can be accurately predicted by bedside USG measurement of ONSD and can be a valuable adjunctive tool in the management of TBI patients.

Citations

Citations to this article as recorded by  
  • Comparison of the Effects of Conventional and Piezoelectric Osteotomy on Intracranial Pressure Changes in Rhinoplasty Using Ultrasonographic Measurement of Optic Nerve Sheath Diameter
    Akif Gunes, Elif Karali, Yusuf Ozgur Bicer, Isa Yildiz, Sıddıka Halicioglu, Nurcan Akbas Gunes
    Aesthetic Plastic Surgery.2026;[Epub]     CrossRef
  • Exploring the impact of electroconvulsive therapy on intracranial pressure: A study of optic nerve sheath diameter measurements
    Iram Fatima, Aung Khine Phyoe, Abhimanyu Sharma, Shubh Mehta, Sara Tabassum, Manjeet Singh, Rama Siddiqui, Shivendra Shah, Kirpa Kaur, Hend Makky, Aadil Mahmood Khan
    The International Journal of Psychiatry in Medicine.2026; 61(1): 39.     CrossRef
  • Personalized treatment approaches in neurocritical care
    Jae Hyun Kim, Chang-Hyun Kim, Hanwool Jeon, Hyun-Chul Jung, Seungjoo Lee
    Acute and Critical Care.2026; 41(1): 33.     CrossRef
  • Optic nerve changes detected with ocular ultrasonography during epiduroscopy: a narrative review
    İlker Çöven, Yasin Tire, Aydın Mermer, Abdullah Celep, Serhat Cömert
    Frontiers in Surgery.2026;[Epub]     CrossRef
  • Relationship between optic nerve sheath diameter, Glasgow Coma Scale, and the impact of PEEP in critically ill patients: a prospective observational study
    Merve İkbal Göncü, Engin İhsan Turan, Ezgi Aydın İnan, Oktay İnan, Ebru Kaya, Ayça Sultan Şahin
    Turkish Journal of Intensive Care.2026; 24(1): 21.     CrossRef
  • Pediatric Neurologic Emergencies in Resource-Limited Settings: A Clinical Framework and Guidance
    Mohammed Alsabri, Emma Cravo, Chibuike Daniel Onyejesi, Louna Abouainain, Eslam Abady, Vincent Tsoi, Ammarah TariQ, Sohaila Abdelbar
    Current Emergency and Hospital Medicine Reports.2026;[Epub]     CrossRef
  • Assessment of optic nerve sheath enlargement and Frisen classification in idiopathic intracranial hypertension: Implications for estimating intracranial pressure and grading chronic papilledema
    Raghda Shawky El-Gendy, Ahmad Shehata Abd ElHamid, Ayman ElSayed Ali Galhom, Nihal Adel Hassan, Ehab Mahmoud Ghoneim
    Taiwan Journal of Ophthalmology.2025; 15(4): 618.     CrossRef
  • Bedside Ultrasonographic Measurement of Optic Nerve Sheath Diameter for Assessing Increased Intracranial Pressure: An Observational Study
    Saurav Shekhar, Raj B Singh, Preeti Sharma, Swapna Lata, Nitin Kumar, Ranjeet Rana De, Amit Kumar
    Cureus.2025;[Epub]     CrossRef
  • Noninvasive Intracranial Pressure Prediction Using a Multimodal Ultrasound-Based Hemispheric Modeling Strategy: A Prospective Dual-Center Study
    Jun Qiu, Tong-Juan Zou, Dong-Mei Wang, Hai-Rong Luo, Hai-Tao Yu, Ling Lei, Wan-Hong Yin
    Neurocritical Care.2025; 43(3): 911.     CrossRef
  • Correlation of Optic Nerve Sheath Diameter With Severity and Outcome in Head Injury: Ultrasonographic and CT Evaluation
    Syed Ali Mehsam, Sarosh Alam, Zunaira Rizwan , Haris Hanif, Fatima Tariq, Saharish Mansoor Khan
    Cureus.2025;[Epub]     CrossRef
  • Measurement of Optic Nerve Sheath Diameter by Bedside Ultrasound in Patients With Traumatic Brain Injury Presenting to Emergency Department: A Review
    Preethy Koshy, Charuta Gadkari
    Cureus.2024;[Epub]     CrossRef
Review Article
Trauma
Mobilization phases in traumatic brain injury
Tommy Alfandy Nazwar, Ivan Triangto, Gutama Arya Pringga, Farhad Bal’afif, Donny Wisnu Wardana
Acute Crit Care. 2023;38(3):261-270.   Published online August 1, 2023
DOI: https://doi.org/10.4266/acc.2023.00640
  • 21,615 View
  • 550 Download
  • 7 Web of Science
  • 8 Crossref
AbstractAbstract PDF
Mobilization in traumatic brain injury (TBI) have shown the improvement of length of stay, infection, long term weakness, and disability. Primary damage as a result of trauma’s direct effect (skull fracture, hematoma, contusion, laceration, and nerve damage) and secondary damage caused by trauma’s indirect effect (microvasculature damage and pro-inflammatory cytokine) result in reduced tissue perfusion & edema. These can be facilitated through mobilization, but several precautions must be recognized as mobilization itself may further deteriorate patient’s condition. Very few studies have discussed in detail regarding mobilizing patients in TBI cases. Therefore, the scope of this review covers the detail of physiological effects, guideline, precautions, and technique of mobilization in patients with TBI.

Citations

Citations to this article as recorded by  
  • Benchmarking mobilization practice and functional outcomes in traumatic brain injury patients admitted to the intensive care unit: a three-year service evaluation
    Fiona Howroyd, James Hodson, Anne Preece, Tammy Lea, Samantha Rooney, Hon Sing Geoffrey Wu, Simran Rahania, Fang Gao Smith, Tonny Veenith, Niharika A. Duggal, Zubair Ahmed, Jonathan Weblin
    Frontiers in Neurology.2026;[Epub]     CrossRef
  • The Impact of a Prior Traumatic Brain Injury and Injury Characteristics on Frailty in the Canadian Longitudinal Study on Aging
    Molly K. Courish, Myles W. O’Brien, Madeline E. Shivgulam, Emily E. MacDonald, Said Mekari, Olga Theou
    Archives of Physical Medicine and Rehabilitation.2026;[Epub]     CrossRef
  • Reversing Persistent PTEN Activation after Traumatic Brain Injury Fuels Long‐Term Axonal Regeneration via Akt/mTORC1 Signaling Cascade
    Ziyu Shi, Leilei Mao, Shuning Chen, Zhuoying Du, Jiakun Xiang, Minghong Shi, Yana Wang, Yuqing Wang, Xingdong Chen, Zhi‐Xiang Xu, Yanqin Gao
    Advanced Science.2025;[Epub]     CrossRef
  • Falls in a single brain rehabilitation center: a 3-year retrospective chart review
    Yoo Jin Choo, Jun Sung Moon, Gun Woo Lee, Wook-Tae Park, Min Cheol Chang
    Frontiers in Neurology.2025;[Epub]     CrossRef
  • Effects of using conventional assistive devices on spatiotemporal gait parameters of adults with neurological disorders: A systematic review protocol
    Jordana de Paula Magalhães, Sheridan Ayessa Ferreira de Brito, Merrill Landers, Aline Alvim Scianni, Poliana do Amaral Yamaguchi Benfica, Carolina Luisa de Almeida Soares, Christina Danielli Coelho de Morais Faria, Anne E. Martin
    PLOS ONE.2025; 20(4): e0321019.     CrossRef
  • Impact of Early Mobilisation on the Clinical Outcomes of Patients With Traumatic Brain Injury
    Fei Xia, Caiyun Li, Yiwen Liu
    Nursing in Critical Care.2025;[Epub]     CrossRef
  • Acute orthostatic responses during early mobilisation of patients with acquired brain injury - Innowalk pro versus standing frame
    Matthijs F Wouda, Espen I Bengtson, Ellen Høyer, Alhed P Wesche, Vivien Jørgensen
    Journal of Rehabilitation and Assistive Technologies Engineering.2024;[Epub]     CrossRef
  • Aktuelle Aspekte der intensivmedizinischen Versorgung bei Schädel-Hirn-Trauma – Teil 2
    André Hagedorn, Helge Haberl, Michael Adamzik, Alexander Wolf, Matthias Unterberg
    AINS - Anästhesiologie · Intensivmedizin · Notfallmedizin · Schmerztherapie.2024; 59(07/08): 466.     CrossRef
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
  • 14,316 View
  • 325 Download
  • 8 Web of Science
  • 10 Crossref
AbstractAbstract PDF
Background
This study aimed to determine the predictive power of the Full Outline of Unresponsiveness (FOUR) score and the Glasgow Coma Scale Pupil (GCS-P) score in determining outcomes for traumatic brain injury (TBI) patients. The Glasgow Outcome Scale (GOS) was used to evaluate patients at 1 month and 6 months after the injury.
Methods
We conducted a 15-month prospective observational study. It included 50 TBI patients admitted to the ICU who met our inclusion criteria. We used Pearson’s correlation coefficient to relate coma scales and outcome measures. The predictive value of these scales was determined using the receiver operating characteristic (ROC) curve, calculating the area under the curve with a 99% confidence interval. All hypotheses were two-tailed, and significance was defined as P<0.01.
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.

Citations

Citations to this article as recorded by  
  • Association Between Glasgow Coma Scale Trajectory and In‐Hospital Mortality in Traumatic Brain Injury in the ICU: A Retrospective Cohort Study
    Yangchun Zhang, Feng Chen, Na Ma, Cairong Liu, Xufeng Chen, Xueli Ji
    Nursing in Critical Care.2025;[Epub]     CrossRef
  • Epidemiology and Outcome of Traumatic Brain Injuries: A Retrospective Study in a Tertiary Care Center
    Rudra N Shah, Yam B Roka, Ashish J Thapa, Alok Jha, Chandan N Sah
    Cureus.2025;[Epub]     CrossRef
  • Comparison of the Accuracy of the GCS and FOUR Scores in Predicting Mortality of Patients with Traumatic Brain Injury (TBI) Admitted to the Emergency Department: A Prospective Study in Khorramabad, Iran
    Amirhossein Pashaei, Soodabeh Zare, Peiman Bakhshi, Sara Fakhri
    Shiraz E-Medical Journal.2025;[Epub]     CrossRef
  • Dynamic assessment of the prognostic value of scoring systems FOUR, GCS and CRS-R in patients with chronic critical illness after acute brain injury
    L. B. Berikashvili, M. Ya. Yadgarov, D. V. Zhidilyaev, K. K. Kadantseva, E. M. Korolenok, A. A. Yakovlev, A. N. Kuzovlev, V. V. Likhvantsev
    Messenger of ANESTHESIOLOGY AND RESUSCITATION.2025; 22(6): 39.     CrossRef
  • ASSOCIATION OF AGE AND FOUR SCORE WITH ICU LENGTH OF STAY IN POST-CRANIOTOMY PATIENTS AT SAKINAH HOSPITAL MOJOKERTO
    Rudi Hariyono, Ika Ainur Rofi’ah
    International Journal of Nursing and Midwifery Science (IJNMS).2025; 9(3): 506.     CrossRef
  • Development of a Novel Neurological Score Combining GCS and FOUR Scales for Assessment of Neurosurgical Patients with Traumatic Brain Injury: GCS-FOUR Scale
    Ali Ansari, Sina Zoghi, Amirabbas Khoshbooei, Mohammad Amin Mosayebi, Maryam Feili, Omid Yousefi, Amin Niakan, Seyed Amin Kouhpayeh, Reza Taheri, Hosseinali Khalili
    World Neurosurgery.2024; 182: e866.     CrossRef
  • Comparison of Glasgow Coma Scale Full Outline of UnResponsiveness and Glasgow Coma Scale: Pupils Score for Predicting Outcome in Patients with Traumatic Brain Injury
    Indu Kapoor, Hemanshu Prabhakar, Arvind Chaturvedi, Charu Mahajan, Abraham L Chawnchhim, Tej P Sinha
    Indian Journal of Critical Care Medicine.2024; 28(3): 256.     CrossRef
  • Machine learning for the prediction of in-hospital mortality in patients with spontaneous intracerebral hemorrhage in intensive care unit
    Baojie Mao, Lichao Ling, Yuhang Pan, Rui Zhang, Wanning Zheng, Yanfei Shen, Wei Lu, Yuning Lu, Shanhu Xu, Jiong Wu, Ming Wang, Shu Wan
    Scientific Reports.2024;[Epub]     CrossRef
  • The assessment of consciousness status in primary brainstem hemorrhage (PBH) patients can be achieved by monitoring changes in basic vital signs
    Shiyi Zuo, Yuting Feng, Juan Sun, Guofang Liu, Hanxu Cai, Xiaolong Zhang, Zhian Hu, Yong Liu, Zhongxiang Yao
    Geriatric Nursing.2024; 59: 498.     CrossRef
  • Traumatic brain injury in companion animals: Pathophysiology and treatment
    Molly Wart, Thomas H. Edwards, Julie A. Rizzo, Geoffrey W. Peitz, Armi Pigott, Jonathan M. Levine, Nicholas D. Jeffery
    Topics in Companion Animal Medicine.2024; 63: 100927.     CrossRef
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
  • 16,288 View
  • 480 Download
  • 8 Web of Science
  • 9 Crossref
AbstractAbstract 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.

Citations

Citations to this article as recorded by  
  • Target temperature management in acute ischemic stroke
    Lan Gao, Ting Yang, Hong Chong, Longfei Wu, Jinming Han
    Frontiers in Molecular Biosciences.2026;[Epub]     CrossRef
  • Blood pressure variability and functional outcome after decompressive hemicraniectomy in malignant middle cerebral artery infarction
    Jae Wook Jung, Ilmo Kang, Jin Park, Sang‐Beom Jeon
    European Journal of Neurology.2025;[Epub]     CrossRef
  • State-of-the-art for automated machine learning predicts outcomes in poor-grade aneurysmal subarachnoid hemorrhage using routinely measured laboratory & radiological parameters: coagulation parameters and liver function as key prognosticators
    Ali Haider Bangash, Jayro Toledo, Muhammed Amir Essibayi, Neil Haranhalli, Rafael De la Garza Ramos, David J. Altschul, Stavropoula Tjoumakaris, Reza Yassari, Robert M. Starke, Redi Rahmani
    Neurosurgical Review.2025;[Epub]     CrossRef
  • Advancements in the application of multimodal monitoring and machine learning for the development of personalized therapeutic strategies in traumatic brain injury
    Zhijing Wei, Lingda Meng, Wei Chong
    Frontiers in Human Neuroscience.2025;[Epub]     CrossRef
  • Trends and hotspots in research of traumatic brain injury from 2000 to 2022: A bibliometric study
    Yan-rui Long, Kai Zhao, Fu-chi Zhang, Yu Li, Jun-wen Wang, Hong-quan Niu, Jin Lei
    Neurochemistry International.2024; 172: 105646.     CrossRef
  • Targeted temperature control following traumatic brain injury: ESICM/NACCS best practice consensus recommendations
    Andrea Lavinio, Jonathan P. Coles, Chiara Robba, Marcel Aries, Pierre Bouzat, Dara Chean, Shirin Frisvold, Laura Galarza, Raimund Helbok, Jeroen Hermanides, Mathieu van der Jagt, David K. Menon, Geert Meyfroidt, Jean-Francois Payen, Daniele Poole, Frank R
    Critical Care.2024;[Epub]     CrossRef
  • A review on targeted temperature management for cardiac arrest and traumatic brain injury
    Hiroshi Ito, Sanae Hosomi, Takeshi Nishida, Youhei Nakamura, Jiro Iba, Hiroshi Ogura, Jun Oda
    Frontiers in Neuroscience.2024;[Epub]     CrossRef
  • Intracranial pressure trends and clinical outcomes after decompressive hemicraniectomy in malignant middle cerebral artery infarction
    Jae Wook Jung, Ilmo Kang, Jin Park, Seungjoo Lee, Sang-Beom Jeon
    Annals of Intensive Care.2024;[Epub]     CrossRef
  • Severe traumatic brain injury in adults: a review of critical care management
    Siobhan McLernon
    British Journal of Neuroscience Nursing.2023; 19(6): 206.     CrossRef
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
  • 7,048 View
  • 205 Download
  • 10 Web of Science
  • 10 Crossref
AbstractAbstract 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.

Citations

Citations to this article as recorded by  
  • Performance and accuracy of blood glucose and neutrophil-lymphocyte ratio as predictors of mortality in children and adolescents with traumatic brain injury
    José Roberto Tude Melo, Caio Vinicius de Almeida Chaves, Cindy Kawano, Isabela Zampirolli Leal, Maria Antonia Coladeti Fernandes, Stephannie Monaco Bodra, Jean Gonçalves de Oliveira, José Carlos Esteves Veiga
    Child's Nervous System.2026;[Epub]     CrossRef
  • Prognostic value of CAR, FIB-4, and procalcitonin in subdural hematoma: associations with mortality and 90-day functional outcomes running title: CAR, FIB-4, and procalcitonin in SDH outcomes
    Tamer Tamdoğan, İlke Tamdoğan
    Journal of Health Sciences and Medicine.2026; 9(1): 19.     CrossRef
  • One-Year Mortality After Percutaneous Endoscopic Gastrostomy: The Prognostic Role of Nutritional Biomarkers and Care Settings
    Nermin Mutlu Bilgiç, Güldan Kahveci, Ekmel Burak Özşenel, Sema Basat
    Nutrients.2025; 17(5): 904.     CrossRef
  • Elevation of C-reactive protein and homocysteine levels as reliable biomarkers for assessing injury severity and prognosis in traumatic brain injury
    Zi-Yan Wang, Wei Du, Xian-Zhi Liu, Yuan Li, Jun Liu
    Scientific Reports.2025;[Epub]     CrossRef
  • Prognostic value of procalcitonin and IL-6 with a composite model in moderate-severe traumatic brain injury
    Xin-meng Li, Zi-wei Liu, Wei-yu Liu, Gao-jian Su, Xian-jian Huang
    Journal of Clinical Neuroscience.2025; 140: 111516.     CrossRef
  • Development and validation of a prediction model for pulmonary infection in elderly patients with traumatic brain injury
    Shuai Tian, Ali Shang, Wenqian Zhou, Zhen Xu, Yunpeng Kou, Zhenyu Guo, Fan Chen, Peigang Ji, Yulong Zhai, Wenjian Zhao, Yang Jiao, Zhipeng Song, Shunnan Ge, Yuan Wang, Liang Wang, Shaochun Guo
    Neurochirurgie.2025; 71(6): 101733.     CrossRef
  • Albuminemia as a Potential Predictor of Clinical Outcomes in Patients with Severe Traumatic Brain Injury (TBI)
    Luka Stepanovic, Usha Govindarajulu, George Agriantonis, Navin D. Bhatia, Jasmine Dave, Shalini Arora, Zahra Shafaee, Kate Twelker, Jennifer Whittington, Bharti Sharma
    Journal of Clinical Medicine.2025; 14(21): 7499.     CrossRef
  • Research Advances in CAR, NLR, and S100β for Assessing Neurological Functional Prognosis in Traumatic Brain Injury Patients
    明隆 陈
    Advances in Clinical Medicine.2025; 15(10): 2518.     CrossRef
  • Symptoms and Functional Outcomes Among Traumatic Brain Injury Patients 3- to 12-Months Post-Injury
    Kathryn S. Gerber, Gemayaret Alvarez, Arsham Alamian, Victoria Behar-Zusman, Charles A. Downs
    Journal of Trauma Nursing.2024; 31(2): 72.     CrossRef
  • Association of C-reactive protein/albumin ratio with mortality in patients with Traumatic Brain Injury: A systematic review and meta-analysis
    Yuyang Liu, Yaheng Tan, Jun Wan, Qiwen Chen, Yuxin Zheng, Wenhao Xu, Peng Wang, Weelic Chong, Xueying Yu, Yu Zhang
    Heliyon.2024; 10(13): e33460.     CrossRef
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
  • 5,719 View
  • 229 Download
  • 12 Web of Science
  • 14 Crossref
AbstractAbstract 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

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    Thara Tunthanathip, Natthanee Pisitthaworakul
    Asian Journal of Neurosurgery.2026; 21(01): 147.     CrossRef
  • The Prognostic Value of Immunonutritional Indexes in Pineal Region Tumor
    Suchada Supbumrung, Anukoon Kaewborisutsakul, Thara Tunthanathip
    Journal of Health and Allied Sciences NU.2025; 15(01): 109.     CrossRef
  • Dynamic nomogram for predicting long-term survival in patients with brain abscess
    Thara Tunthanathip, Rakkrit Duangsoithong, Waranyu Kittirojkasem, Akira Pongweat, Rattiyaphon Khongthep, Benchamat Sutchai, Assama Tohyunuh
    Chinese Neurosurgical Journal.2025;[Epub]     CrossRef
  • A nomogram for the prediction of traumatic intracranial abnormalities in the elderly: Development and validation
    Apisorn Jongjit, Thara Tunthanathip
    Chinese Journal of Traumatology.2025;[Epub]     CrossRef
  • Deep learning-based model for detection of intracranial waveforms with poor brain compliance in southern Thailand
    Thara Tunthanathip, Avika Trakulpanitkit
    Acute and Critical Care.2025; 40(3): 473.     CrossRef
  • Prognostic value of CT scoring systems and a simplified prediction model in pediatric moderate-to-severe traumatic brain injury
    Yangyang Diao, Ping Liang
    Chinese Journal of Traumatology.2025;[Epub]     CrossRef
  • Feasibility comparison of deep learning image regressions to estimate intracranial pressure from cranial computed tomography in hydrocephalus
    Thara Tunthanathip, Rakkrit Duangsoithong, Sakchai Sae-Heng
    Journal of Neurosciences in Rural Practice.2025; 16: 606.     CrossRef
  • Risk factors and dose-response relationship of catheter-associated urinary tract infection in neurosurgical patients
    Thara Tunthanathip, Natthanee Pisitthaworakul
    International Journal of Nutrition, Pharmacology, Neurological Diseases.2025; 15(4): 451.     CrossRef
  • Prognosis of subarachnoid hemorrhage determined by intracranial pressure thresholds
    Thara Tunthanathip, Rakkrit Duangsoithong, Sakchai Sae-Heng
    Journal of Cerebrovascular and Endovascular Neurosurgery.2025; 27(4): 309.     CrossRef
  • Prognostic factors and clinical nomogram for in-hospital mortality in traumatic brain injury
    Thara Tunthanathip, Nakornchai Phuenpathom, Apisorn Jongjit
    The American Journal of Emergency Medicine.2024; 77: 194.     CrossRef
  • Development of a Clinical Nomogram for Predicting Shunt-Dependent Hydrocephalus
    Avika Trakulpanitkit, Thara Tunthanathip
    Journal of Health and Allied Sciences NU.2024; 14(04): 516.     CrossRef
  • Prediction performance of the machine learning model in predicting mortality risk in patients with traumatic brain injuries: a systematic review and meta-analysis
    Jue Wang, Ming Jing Yin, Han Chun Wen
    BMC Medical Informatics and Decision Making.2023;[Epub]     CrossRef
  • 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
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
  • 10,456 View
  • 298 Download
  • 16 Web of Science
  • 18 Crossref
AbstractAbstract 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

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  • THE USE OF ARTIFICIAL INTELLIGENCE IN TRAUMATOLOGY: A SYSTEMATIC REVIEW AND RECOMMENDATIONS FOR CLINICAL PRACTICE
    V. V. Savgachev, L. B. Shubin
    Bulletin of Pirogov National Medical & Surgical Center.2026; 21(1): 127.     CrossRef
  • Development of web- and mobile-based shared decision-making tools in the neurological intensive care unit
    Winnie L. Liu, Lidan Zhang, Soussan Djamasbi, Bengisu Tulu, Susanne Muehlschlegel
    Neurotherapeutics.2025; 22(1): e00503.     CrossRef
  • Long-term survival prediction in patients with acute brain lesions using ensemble machine learning algorithms: a cohort study with combined national health insurance service and its self-run hospital database
    Dougho Park, Daeyoung Hong, Suntak Jin, Jong Hun Kim, Hyoung Seop Kim
    Journal of Big Data.2025;[Epub]     CrossRef
  • Predicting outcomes after moderate and severe traumatic brain injury using artificial intelligence: a systematic review
    Armaan K. Malhotra, Husain Shakil, Christopher W. Smith, Yu Qing Huang, Jethro C. C. Kwong, Kevin E. Thorpe, Christopher D. Witiw, Abhaya V. Kulkarni, Jefferson R. Wilson, Avery B. Nathens
    npj Digital Medicine.2025;[Epub]     CrossRef
  • Artificial intelligence in traumatic brain injury: Brain imaging analysis and outcome prediction: A mini review
    Luca Marino, Federico Bilotta
    World Journal of Critical Care Medicine.2025;[Epub]     CrossRef
  • Prediction of Clinically Significant Improvements During the Interdisciplinary Intensive Outpatient Program for Traumatic Brain Injury Using Machine Learning
    Rujirutana Srikanchana, David Samuel, Jacob Powell, Treven Pickett, Thomas DeGraba, Chandler Sours Rhodes
    Annals of Biomedical Engineering.2025; 53(11): 2845.     CrossRef
  • A practical approach to predicting long-term outcomes in traumatic brain injury: Enhancing clinical decision-making with machine learning
    Amirmohammad Farrokhi, Mahtab Jalali, Mohamed Sobhi Jabal, Saeed Abdollahifard, Reza Taheri, Omid Yousefi, Amin Niakan, Hosseinali Khalili
    Computers in Biology and Medicine.2025; 196: 110827.     CrossRef
  • The effect of extended early rehabilitation on the treatment outcome of patients with moderate and severe traumatic brain injury
    Nataša Keleman, Dragana Dragičević-Cvjetković, Aleksandra Mikov, Dragomir Radošević, Ðula Ðilvesi, Vladimir Mrđa, Rastislava Krasnik
    Frontiers in Human Neuroscience.2025;[Epub]     CrossRef
  • Artificial Intelligence in Traumatic Brain Injury: A Systematic Review of Prognostic, Diagnostic, and Monitoring Applications
    Anas E Ahmed, Rayan M Alyami, Fatimah H Al Ghazwi, Renad H Hamzi, Nawa K Alshammari, Fawziah M Jali, Abdullah A Al Alduwayh, Thikra M Almujami, Abdullah S Alamri, Jamal A Sabban, Ghadi F Alsum
    Cureus.2025;[Epub]     CrossRef
  • Enhancing hospital course and outcome prediction in patients with traumatic brain injury: A machine learning study
    Guangming Zhu, Burak B Ozkara, Hui Chen, Bo Zhou, Bin Jiang, Victoria Y Ding, Max Wintermark
    The Neuroradiology Journal.2024; 37(1): 74.     CrossRef
  • Machine Learning in Neuroimaging of Traumatic Brain Injury: Current Landscape, Research Gaps, and Future Directions
    Kevin Pierre, Jordan Turetsky, Abheek Raviprasad, Seyedeh Mehrsa Sadat Razavi, Michael Mathelier, Anjali Patel, Brandon Lucke-Wold
    Trauma Care.2024; 4(1): 31.     CrossRef
  • A Systematic Review of the Outcomes of Utilization of Artificial Intelligence Within the Healthcare Systems of the Middle East: A Thematic Analysis of Findings
    Mohsen Khosravi, Seyyed Morteza Mojtabaeian, Emine Kübra Dindar Demiray, Burak Sayar
    Health Science Reports.2024;[Epub]     CrossRef
  • 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
  • Gastrointestinal failure, big data and intensive care
    Pierre Singer, Eyal Robinson, Orit Raphaeli
    Current Opinion in Clinical Nutrition & Metabolic Care.2023; 26(5): 476.     CrossRef
  • Prediction performance of the machine learning model in predicting mortality risk in patients with traumatic brain injuries: a systematic review and meta-analysis
    Jue Wang, Ming Jing Yin, Han Chun Wen
    BMC Medical Informatics and Decision Making.2023;[Epub]     CrossRef
  • Predicting return to work after traumatic brain injury using machine learning and administrative data
    Helena Van Deynse, Wilfried Cools, Viktor-Jan De Deken, Bart Depreitere, Ives Hubloue, Eva Kimpe, Maarten Moens, Karen Pien, Ellen Tisseghem, Griet Van Belleghem, Koen Putman
    International Journal of Medical Informatics.2023; 178: 105201.     CrossRef
  • Fluid-Based Protein Biomarkers in Traumatic Brain Injury: The View from the Bedside
    Denes V. Agoston, Adel Helmy
    International Journal of Molecular Sciences.2023; 24(22): 16267.     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
  • 8,428 View
  • 149 Download
  • 8 Web of Science
  • 6 Crossref
AbstractAbstract 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.

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  • Near-Field Communications Sensor for Lactate Determination in Saliva and Sweat Using Organic Electrochemical Transistors (OECTs)
    Antonio Lazaro, Emma Rojas Rodriguez, Marc Lazaro, Ramon Villarino, Benito González, David Girbau
    IEEE Sensors Journal.2026; 26(3): 5037.     CrossRef
  • Agreement of point‐of‐care and laboratory lactate levels among trauma patients and association with transfusion
    Biswadev Mitra, Madison Essery, Abha Somesh, Carly Talarico, Alexander Olaussen, David Anderson, Benjamin Meadley
    Vox Sanguinis.2025; 120(2): 188.     CrossRef
  • A Combined Model of Vital Signs and Serum Biomarkers Outperforms Shock Index in the Prediction of Hemorrhage Control Interventions in Surgical Intensive Care Unit Patients
    John P. Forrester, Manuel Beltran Del Rio, Cristine H. Meyer, Samuel P. R. Paci, Ella R. Rastegar, Timmy Li, Maria G. Sfakianos, Eric N. Klein, Matthew E Bank, Daniel M. Rolston, Nathan A Christopherson, Daniel Jafari
    Journal of Intensive Care Medicine.2025; 40(6): 632.     CrossRef
  • Association of initial lactate levels and red blood cell transfusion strategy with outcomes after severe trauma: a post hoc analysis of the RESTRIC trial
    Yoshinori Kosaki, Takashi Hongo, Mineji Hayakawa, Daisuke Kudo, Shigeki Kushimoto, Takashi Tagami, Hiromichi Naito, Atsunori Nakao, Tetsuya Yumoto
    World Journal of Emergency Surgery.2024;[Epub]     CrossRef
  • Predictors of massive transfusion protocols activation in patients with trauma in Korea: a systematic review
    Dongmin Seo, Inhae Heo, Juhong Park, Junsik Kwon, Hye-min Sohn, Kyoungwon Jung
    Journal of Trauma and Injury.2024; 37(2): 97.     CrossRef
  • Prehospital Lactate Levels Obtained in the Ambulance and Prediction of 2-Day In-Hospital Mortality in Patients With Traumatic Brain Injury
    Francisco Martin-Rodriguez, Ancor Sanz-Garcia, Raul Lopez-Izquierdo, Juan F. Delgado Benito, Francisco T. Martínez Fernández, Santiago Otero de la Torre, Carlos Del Pozo Vegas
    Neurology.2024;[Epub]     CrossRef

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