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Comparison of Prognostic Computed Tomography Scores in Geriatric Patients with Traumatic Brain Injury: A Retrospective Study

Yıl 2022, Cilt 12, Sayı 2, 177 - 181, 15.03.2022
https://doi.org/10.16899/jcm.1009858

Öz

Aim This study aimed to compare the Rotterdam and Helsinki computed tomography (CT) scoring systems for predicting the 30-day mortality after traumatic brain injury (TBI) in the geriatric population. Materials and Methods Patients aged ≥65 years presenting to the emergency department with trauma-related complaints were retrospectively scanned using International Classification of Disease codes, and patients with isolated head trauma examined using brain CT were included. Demographic data including age, gender, trauma mechanisms, Glasgow Coma Scale (GCS) score at the time of admission, light reflex information, intubation, and surgery status, and emergency department outcomes were recorded. Brain CT images were investigated to calculate the Rotterdam and Helsinki CT scores and the relationship between them was examined. Results Of the 890 included patients, 403 (45.3%) were male. Overall, 683 patients fell from a height of <1 m and 195 suffered injuries by hitting or direct impact. Further, the 30-day mortality rate was examined, revealing that 868 patients were alive and 22 patients died. Mortality rate was 3.7% for males and 1.4% for females. The Rotterdam and Helsinki CT scores and 30-day mortality was analyzed using receiver operating characteristic curve analysis, and the area under the curve was found as 0.564 and 0.603, respectively. The specificity of Rotterdam and Helsinki CT scoring systems in predicting 30-day mortality was 99.08% and 99.19%, respectively. Conclusion The use of CT scoring systems such as Rotterdam and Helsinki in the geriatric population presenting with TBI allows us to predict 30-day mortality.

Kaynakça

  • CDC. TBI-Related Emergency Department Visits, Hospitalizations, and Deaths (EDHDs). (2019). Available online at: https://www.cdc.gov/traumaticbraininjury/data/tbi-edhd.html (accessed 1, october 2021).
  • Garza N, Toussi A, Wilson M, Shahlaie K, Martin R. The Increasing Age of TBI Patients at a Single Level 1 Trauma Center and the Discordance Between GCS and CT Rotterdam Scores in the Elderly. Front Neurol. 2020;11:112. Published 2020 Feb 20. doi:10.3389/fneur.2020.00112
  • In-Suk Bae, Hyoung-Joon Chun, Hyeong-Joong Yi, Kyu-Sun Choi. Using components of the Glasgow coma scale and Rotterdam CT scores for mortality risk stratification in adult patients with traumatic brain injury: A preliminary study. Clin Neurol Neurosurg. 2020;188:105599. doi:10.1016/j.clineuro.2019.105599
  • Brazinova A, Rehorcikova V, Taylor MS, et al. Epidemiology of Traumatic Brain Injury in Europe: A Living Systematic Review. J Neurotrauma. 2021;38(10):1411-1440. doi:10.1089/neu.2015.4126
  • Karibe H, Hayashi T, Narisawa A, Kameyama M, Nakagawa A, Tominaga T. Clinical Characteristics and Outcome in Elderly Patients with Traumatic Brain Injury: For Establishment of Management Strategy. Neurol Med Chir (Tokyo). 2017;57(8):418-425. doi:10.2176/n.
  • Abio A, Bovet P, Valentin B, et al. Changes in Mortality Related to Traumatic Brain Injuries in the Seychelles from 1989 to 2018. Front Neurol. 2021;12:720434. Published 2021 Aug 27. doi:10.3389/fneur.2021.720434
  • Mata-Mbemba D, Mugikura S, Nakagawa A, et al. Early CT findings to predict early death in patients with traumatic brain injury: Marshall and Rotterdam CT scoring systems compared in the major academic tertiary care hospital in northeastern Japan. Acad Radiol. 2014;21(5):605-611. doi:10.1016/j.acra.2014.01.017
  • Maas AI, Hukkelhoven CW, Marshall LF, Steyerberg EW. Prediction of outcome in traumatic brain injury with computed tomographic characteristics: a comparison between the computed tomographic classification and combinations of computed tomographic predictors. Neurosurgery. 2005;57(6):1173-1182. doi:10.1227/01.neu.0000186013.63046.6b
  • Raj, R., Siironen, J., Skrifvars, M. B., Hernesniemi, J., & Kivisaari, R. (2014). Predicting Outcome in Traumatic Brain Injury. Neurosurgery, 75(6), 632–647. doi:10.1227/neu.00000000000005.
  • Katar S, Aydin Ozturk P, Ozel M, et al. The Use of Rotterdam CT Score for Prediction of Outcomes in Pediatric Traumatic Brain Injury Patients Admitted to Emergency Service. Pediatr Neurosurg. 2020;55(5):237-243. doi:10.1159/000510016
  • Summaka, M., Zein, H., Elias, E., Naim, I., Fares, Y., & Nasser, Z. (2020). Prediction of quality of life by Helsinki computed tomography scoring system in patients with traumatic brain injury. Brain Injury, 1–8. doi:10.1080/02699052.2020.1799435 .
  • Pargaonkar R, Kumar V, Menon G, Hegde A. Comparative study of computed tomographic scoring systems and predictors of early mortality in severe traumatic brain injury. J Clin Neurosci. 2019;66:100-106. doi:10.1016/j.jocn.2019.05.011
  • Reith FCM, Lingsma HF, Gabbe BJ, Lecky FE, Roberts I, Maas AIR. Differential effects of the Glasgow Coma Scale Score and its Components: An analysis of 54,069 patients with traumatic brain injury. Injury. 2017;48(9):1932-1943. doi:10.1016/j.injury.2017.05. Zuercher, M., Ummenhofer, W., Baltussen, A., & Walder, B. (2009). The use of Glasgow Coma Scale in injury assessment: A critical review. Brain Injury, 23(5), 371–384. doi:10.1080/02699050902926267 .
  • Thelin EP, Nelson DW, Vehviläinen J, et al. Evaluation of novel computerized tomography scoring systems in human traumatic brain injury: An observational, multicenter study. PLoS Med. 2017;14(8):e1002368. Published 2017 Aug 3. doi:10.1371/journal.pmed.100.
  • Posti JP, Takala RSK, Raj R, et al. Admission Levels of Interleukin 10 and Amyloid β 1-40 Improve the Outcome Prediction Performance of the Helsinki Computed Tomography Score in Traumatic Brain Injury. Front Neurol. 2020;11:549527. Published 2020 Oct 30. doi:10.3389/fneur.2020.549527
  • Gardner RC, Dams-O'Connor K, Morrissey MR, Manley GT. Geriatric Traumatic Brain Injury: Epidemiology, Outcomes, Knowledge Gaps, and Future Directions. J Neurotrauma. 2018;35(7):889-906. doi:10.1089/neu.2017.5371.
  • Shimoda K, Maeda T, Tado M, Yoshino A, Katayama Y, Bullock MR. Outcome and surgical management for geriatric traumatic brain injury: analysis of 888 cases registered in the Japan Neurotrauma Data Bank. World Neurosurg. 2014;82(6):1300-1306. doi:10.1016/j.
  • Zeng X, Pan S, Hu Z. Geriatric Traumatic Brain Injury in China. Curr Transl Geriatr Exp Gerontol Rep. 2012;1(3):167-170. Published 2012 Jun 19. doi:10.1007/s13670-012-0018-1

Travmatik Beyin Hasarı olan yaşlı hastalarda Prognostik Bilgisayarlı Tomografi Skorları karşılaştırması: Retrospektif bir çalışma

Yıl 2022, Cilt 12, Sayı 2, 177 - 181, 15.03.2022
https://doi.org/10.16899/jcm.1009858

Öz

Giriş Rotterdam Bilgisayarlı Tomografi (BT) skorlama ve Helsinki BT skorlama sisteminin geriatrik popülasyonda TBH (travmatik beyin hasarı) sonrası 30 günlük mortaliteyi tahmin etme yeteneklerinin karşılaştırmasını sağlamayı amaçlamaktadır. Metod Acil servise travma ilişkili şikayetlerle başvuran 65 yaş ve üstü hastalar ICD kodları üzerinden retrospektif olarak tarandı ve izole kafa travması mevcut olup beyin BT ile tetkik edilmiş olan hastalar çalışmaya dahil edildi. Hastaların yaş, cinsiyet gibi demografik verileri, travma mekanizmaları, geliş muayenesinde Glasgow Koma Skalası (GKS), ışık refleksi bilgileri, entübe olup olmadığı ve opere olup olmadığı, acil servis sonlanım bilgisi taranarak kaydedildi. Hastaların beyin BT görüntüleri incelenerek Rotterdam ve Helsinki BT skorları hesaplandı ve bunlar arasındaki ilişkiye bakıldı. Bulgular Çalışmamıza dahil edilen 890 hastanın 403 (%45.3) erkekti. Çalışmamızda 683 hastanın 1 metreden daha düşük yükseklikten düştüğü, 195 tanesinin çarpma veya direkt darbe alma şeklinde olduğu görüldü. Hastaların bir aylık mortalite bilgisine bakıldığında 22 hastanın öldüğü ve 868 hastanın sağ olduğu saptandı. Erkek hastalarda ölüm oranı %3,7 iken kadın hastalarda bu oran %1,4 olarak bulunmuş olup mortalite açısından cinsiyetler arasında anlamlı fark saptandı. Hastaların Rotterdam ve Helsinki BT Skorları ve bir aylık mortaliteleri ROC analizi ile incelendiğinde Rotterdam BT Skoru için eğri altında kalan alan sırasıyla 0.564 ve 0.603 olarak bulundu. Hastaların Rotterdam BT Skoru ve Helsinki BT skoru 1 aylık mortaliteyi tahmin etmede spesifitesi sırayla %99,08 ve %99,19 olarak hesaplandı. Sonuç TBH ile başvuran geriatrik popülasyonda Rotterdam ve Helsinki gibi BT skorlamalarının kullanımı bize 30 günlük mortaliteyi tahmin etmemizi olanak sağlamaktadır.

Kaynakça

  • CDC. TBI-Related Emergency Department Visits, Hospitalizations, and Deaths (EDHDs). (2019). Available online at: https://www.cdc.gov/traumaticbraininjury/data/tbi-edhd.html (accessed 1, october 2021).
  • Garza N, Toussi A, Wilson M, Shahlaie K, Martin R. The Increasing Age of TBI Patients at a Single Level 1 Trauma Center and the Discordance Between GCS and CT Rotterdam Scores in the Elderly. Front Neurol. 2020;11:112. Published 2020 Feb 20. doi:10.3389/fneur.2020.00112
  • In-Suk Bae, Hyoung-Joon Chun, Hyeong-Joong Yi, Kyu-Sun Choi. Using components of the Glasgow coma scale and Rotterdam CT scores for mortality risk stratification in adult patients with traumatic brain injury: A preliminary study. Clin Neurol Neurosurg. 2020;188:105599. doi:10.1016/j.clineuro.2019.105599
  • Brazinova A, Rehorcikova V, Taylor MS, et al. Epidemiology of Traumatic Brain Injury in Europe: A Living Systematic Review. J Neurotrauma. 2021;38(10):1411-1440. doi:10.1089/neu.2015.4126
  • Karibe H, Hayashi T, Narisawa A, Kameyama M, Nakagawa A, Tominaga T. Clinical Characteristics and Outcome in Elderly Patients with Traumatic Brain Injury: For Establishment of Management Strategy. Neurol Med Chir (Tokyo). 2017;57(8):418-425. doi:10.2176/n.
  • Abio A, Bovet P, Valentin B, et al. Changes in Mortality Related to Traumatic Brain Injuries in the Seychelles from 1989 to 2018. Front Neurol. 2021;12:720434. Published 2021 Aug 27. doi:10.3389/fneur.2021.720434
  • Mata-Mbemba D, Mugikura S, Nakagawa A, et al. Early CT findings to predict early death in patients with traumatic brain injury: Marshall and Rotterdam CT scoring systems compared in the major academic tertiary care hospital in northeastern Japan. Acad Radiol. 2014;21(5):605-611. doi:10.1016/j.acra.2014.01.017
  • Maas AI, Hukkelhoven CW, Marshall LF, Steyerberg EW. Prediction of outcome in traumatic brain injury with computed tomographic characteristics: a comparison between the computed tomographic classification and combinations of computed tomographic predictors. Neurosurgery. 2005;57(6):1173-1182. doi:10.1227/01.neu.0000186013.63046.6b
  • Raj, R., Siironen, J., Skrifvars, M. B., Hernesniemi, J., & Kivisaari, R. (2014). Predicting Outcome in Traumatic Brain Injury. Neurosurgery, 75(6), 632–647. doi:10.1227/neu.00000000000005.
  • Katar S, Aydin Ozturk P, Ozel M, et al. The Use of Rotterdam CT Score for Prediction of Outcomes in Pediatric Traumatic Brain Injury Patients Admitted to Emergency Service. Pediatr Neurosurg. 2020;55(5):237-243. doi:10.1159/000510016
  • Summaka, M., Zein, H., Elias, E., Naim, I., Fares, Y., & Nasser, Z. (2020). Prediction of quality of life by Helsinki computed tomography scoring system in patients with traumatic brain injury. Brain Injury, 1–8. doi:10.1080/02699052.2020.1799435 .
  • Pargaonkar R, Kumar V, Menon G, Hegde A. Comparative study of computed tomographic scoring systems and predictors of early mortality in severe traumatic brain injury. J Clin Neurosci. 2019;66:100-106. doi:10.1016/j.jocn.2019.05.011
  • Reith FCM, Lingsma HF, Gabbe BJ, Lecky FE, Roberts I, Maas AIR. Differential effects of the Glasgow Coma Scale Score and its Components: An analysis of 54,069 patients with traumatic brain injury. Injury. 2017;48(9):1932-1943. doi:10.1016/j.injury.2017.05. Zuercher, M., Ummenhofer, W., Baltussen, A., & Walder, B. (2009). The use of Glasgow Coma Scale in injury assessment: A critical review. Brain Injury, 23(5), 371–384. doi:10.1080/02699050902926267 .
  • Thelin EP, Nelson DW, Vehviläinen J, et al. Evaluation of novel computerized tomography scoring systems in human traumatic brain injury: An observational, multicenter study. PLoS Med. 2017;14(8):e1002368. Published 2017 Aug 3. doi:10.1371/journal.pmed.100.
  • Posti JP, Takala RSK, Raj R, et al. Admission Levels of Interleukin 10 and Amyloid β 1-40 Improve the Outcome Prediction Performance of the Helsinki Computed Tomography Score in Traumatic Brain Injury. Front Neurol. 2020;11:549527. Published 2020 Oct 30. doi:10.3389/fneur.2020.549527
  • Gardner RC, Dams-O'Connor K, Morrissey MR, Manley GT. Geriatric Traumatic Brain Injury: Epidemiology, Outcomes, Knowledge Gaps, and Future Directions. J Neurotrauma. 2018;35(7):889-906. doi:10.1089/neu.2017.5371.
  • Shimoda K, Maeda T, Tado M, Yoshino A, Katayama Y, Bullock MR. Outcome and surgical management for geriatric traumatic brain injury: analysis of 888 cases registered in the Japan Neurotrauma Data Bank. World Neurosurg. 2014;82(6):1300-1306. doi:10.1016/j.
  • Zeng X, Pan S, Hu Z. Geriatric Traumatic Brain Injury in China. Curr Transl Geriatr Exp Gerontol Rep. 2012;1(3):167-170. Published 2012 Jun 19. doi:10.1007/s13670-012-0018-1

Ayrıntılar

Birincil Dil İngilizce
Konular Sağlık Bilimleri ve Hizmetleri
Bölüm Orjinal Araştırma
Yazarlar

Öner BOZAN (Sorumlu Yazar)
Prof. Dr. Cemil Taşçıoğlu City Hospital
0000-0002-4195-2601
Türkiye


İbrahim ALTUNOK
UNIVERSITY OF HEALTH SCIENCES, İSTANBUL ÜMRANİYE HEALTH RESEARCH CENTER
0000-0002-9312-1025
Türkiye

Destekleyen Kurum Yok
Erken Görünüm Tarihi 1 Ocak 2022
Yayımlanma Tarihi 15 Mart 2022
Kabul Tarihi 17 Kasım 2021
Yayınlandığı Sayı Yıl 2022, Cilt 12, Sayı 2

Kaynak Göster

AMA Bozan Ö. , Altunok İ. Comparison of Prognostic Computed Tomography Scores in Geriatric Patients with Traumatic Brain Injury: A Retrospective Study. J Contemp Med. 2022; 12(2): 177-181.