Predictors of outcomes in geriatric patients with moderate traumatic brain injury after ground level falls.

complications geriatric ground level fall prediction traumatic brain injury

Journal

Frontiers in medicine
ISSN: 2296-858X
Titre abrégé: Front Med (Lausanne)
Pays: Switzerland
ID NLM: 101648047

Informations de publication

Date de publication:
2023
Historique:
received: 07 09 2023
accepted: 02 11 2023
medline: 28 12 2023
pubmed: 28 12 2023
entrez: 28 12 2023
Statut: epublish

Résumé

The elderly population constitutes one of the fastest-growing demographic groups globally. Within this population, mild to moderate traumatic brain injuries (TBI) resulting from ground level falls (GLFs) are prevalent and pose significant challenges. Between 50 and 80% of TBIs in older individuals are due to GLFs. These incidents result in more severe outcomes and extended recovery periods for the elderly, even when controlling for injury severity. Given the increasing incidence of such injuries it becomes essential to identify the key factors that predict complications and in-hospital mortality. Therefore, the aim of this study was to pinpoint the top predictors of complications and in-hospital mortality in geriatric patients who have experienced a moderate TBI following a GLF. Data were obtained from the American College of Surgeons' Trauma Quality Improvement Program database. A moderate TBI was defined as a head AIS ≤ 3 with a Glasgow Coma Scale (GCS) 9-13, and an AIS ≤ 2 in all other body regions. Potential predictors of complications and in-hospital mortality were included in a logistic regression model and ranked using the permutation importance method. A total of 7,489 patients with a moderate TBI were included in the final analyses. 6.5% suffered a complication and 6.2% died prior to discharge. The top five predictors of complications were the need for neurosurgical intervention, the Revised Cardiac Risk Index, coagulopathy, the spine abbreviated injury severity scale (AIS), and the injury severity score. The top five predictors of mortality were head AIS, age, GCS on admission, the need for neurosurgical intervention, and chronic obstructive pulmonary disease. When predicting both complications and in-hospital mortality in geriatric patients who have suffered a moderate traumatic brain injury after a ground level fall, the most important factors to consider are the need for neurosurgical intervention, cardiac risk, and measures of injury severity. This may allow for better identification of at-risk patients, and at the same time resulting in a more equitable allocation of resources.

Identifiants

pubmed: 38152301
doi: 10.3389/fmed.2023.1290201
pmc: PMC10751787
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1290201

Informations de copyright

Copyright © 2023 Forssten, Ahl Hulme, Forssten, Ribeiro, Sarani and Mohseni.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Auteurs

Sebastian Peter Forssten (SP)

Division of Surgery, CLINTEC, Karolinska Institute, Stockholm, Sweden.
Department of Orthopedic Surgery, Örebro University Hospital, Örebro, Sweden.

Rebecka Ahl Hulme (R)

Division of Surgery, CLINTEC, Karolinska Institute, Stockholm, Sweden.
Division of Trauma and Emergency Surgery, Department of Surgery, Karolinska University Hospital, Stockholm, Sweden.

Maximilian Peter Forssten (MP)

Department of Orthopedic Surgery, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
School of Medical Sciences, Örebro University, Örebro, Sweden.

Marcelo A F Ribeiro (MAF)

Pontifical Catholic University of São Paulo, São Paulo, Brazil.
Khalifa University and Gulf Medical University, Abu Dhabi, United Arab Emirates.
Department of Surgery, Sheikh Shakhbout Medical City, Mayo Clinic, Abu Dhabi, United Arab Emirates.

Babak Sarani (B)

Division of Trauma and Acute Care Surgery, George Washington University School of Medicine and Health Sciences, Washington, DC, United States.

Shahin Mohseni (S)

School of Medical Sciences, Örebro University, Örebro, Sweden.
Department of Surgery, Sheikh Shakhbout Medical City, Mayo Clinic, Abu Dhabi, United Arab Emirates.

Classifications MeSH