Models to predict expansive intracranial hematomas occurrence for adult traumatic brain injury patients presenting at Accident and Emergency Department at Mulago National referral Hospital in Uganda

Authors

  • Larrey Kasereka Kamabu 1. Department of Surgery, Neurosurgery, College of Medicine, Makerere University, College of Health Sciences, Kampala, Uganda 2. Department of Neurosurgery, New deal SARL hospitals CIMAK & Faculty of Medicine, Université Catholique du Graben, Democratic Republic of the Congo
  • Ronald Oboth 1. Department of Surgery, Neurosurgery, College of Medicine, Makerere University, College of Health Sciences, Kampala, Uganda
  • Godfrey S. Bbosa Department of Pharmacology & Therapeutics, Makerere University College of Health Sciences, Kampala, Uganda
  • Anthony T. Fuller Duke Global Neurology Neurosurgery, Duke University, Durham, USA
  • Daniel Deng Duke Global Neurology Neurosurgery, Duke University, Durham, USA
  • Hervé Monka Lekuya Department of Surgery, Neurosurgery, College of Medicine, Makerere University, College of Health Sciences, Kampala, Uganda
  • John Baptist Ssenyondwa Department of Surgery, Neurosurgery, College of Medicine, Makerere University, College of Health Sciences, Kampala, Uganda
  • Juliet Nalwanga Sekabunga Department of Surgery, Neurosurgery, College of Medicine, Makerere University, College of Health Sciences, Kampala, Uganda
  • Louange Maha Kataka Department of Neurosurgery, New deal SARL hospitals CIMAK & Faculty of Medicine, Université Catholique du Graben, Democratic Republic of the Congo
  • Martin N. Kaddumukasa Department of Medicine, School of Medicine, College of Health Sciences, Makerere University, P.O. Box 7072, Kampala, Uganda
  • Doomwin Oscar Deogratius Obiga Department of Surgery, Neurosurgery, College of Medicine, Makerere University, College of Health Sciences, Kampala, Uganda
  • Joel Kiryabwire Department of Surgery, Neurosurgery, College of Medicine, Makerere University, College of Health Sciences, Kampala, Uganda
  • Moses Galukande Department of Surgery, Neurosurgery, College of Medicine, Makerere University, College of Health Sciences, Kampala, Uganda
  • Martha Sajatovic Neurological and Behavioral Outcomes Center, University Hospitals Cleveland Medical Center & Case Western Reserve University School of Medicine, 11100 Euclid Avenue, Cleveland, OH 44106, USA.
  • Mark Kaddumukasa Department of Medicine, School of Medicine, College of Health Sciences, Makerere University, P.O. Box 7072, Kampala, Uganda
  • David Kitya Department of Neurosurgery, Mbarara Regional Referral Teaching Hospital, Mbarara University of Science and Technology, Mbarara
  • Michael M. Haglund Duke Global Neurology Neurosurgery, Duke University, Durham, USA

DOI:

https://doi.org/10.51437/jgns.v4i1.465

Keywords:

Global Neurosurgery, Traumatic Brain Injury, TBI, LMIC

Abstract

Intracranial hemorrhage (EIH) in traumatic brain injury (TBI) patients is a critical issue in clinical practice, particularly in resource-limited settings. This study aimed to identify predictive models for EIH occurrence among TBI patients in Uganda. A cross-sectional study included adult TBI patients with intracranial hematomas undergoing surgical evacuation from June 16, 2021, to December 17, 2022. Patients were categorized by EIH presence, determined by changes in hematoma volume. Logistic regression analyzed factors influencing EIH, including demographics, neurological assessment, hematological parameters, and neuroimaging.

Out of 324 patients, 59.3% (n=192) developed EIH. The final model included age, systolic and diastolic blood pressure, subdural hematoma (SDH), diffuse axonal injury (DAI), skull fracture, and an interaction between skull fracture and SDH. Each unit increase in systolic blood pressure raised EIH odds by 1.045, while each unit increase in diastolic blood pressure lowered odds to 0.942. SDH increased odds by 6.286, and DAI by 4.024. In cases of skull fracture, SDH reduced odds to 0.0676. The model’s five-fold cross-validated average area under the receiver operating curve (AUC) was 0.722, with 64.5% accuracy.

EIH is prevalent among TBI patients in Uganda, with a rate of 59.3%. The identified predictive factors can inform policy and interventions to anticipate and manage EIH, enhancing patient outcomes.

 

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Published

2024-06-29