Prehospital and Emergency Care in Adult Patients with Acute Traumatic Brain Injury

Traumatic brain injury (TBI) is a major healthcare problem and a major burden to society. The identification of a TBI can be challenging in the prehospital setting, particularly in elderly patients with unobserved falls. Errors in triage on scene cannot be ruled out based on limited clinical diagnostics. Potential new mobile diagnostics may decrease these errors. Prehospital care includes decision-making in clinical pathways, means of transport, and the degree of prehospital treatment. Emergency care at hospital admission includes the definitive diagnosis of TBI with, or without extracranial lesions, and triage to the appropriate receiving structure for definitive care. Early risk factors for an unfavorable outcome includes the severity of TBI, pupil reaction and age. These three variables are core variables, included in most predictive models for TBI, to predict short-term mortality. Additional early risk factors of mortality after severe TBI are hypotension and hypothermia. The extent and duration of these two risk factors may be decreased with optimal prehospital and emergency care. Potential new avenues of treatment are the early use of drugs with the capacity to decrease bleeding, and brain edema after TBI. There are still many uncertainties in prehospital and emergency care for TBI patients related to the complexity of TBI patterns.

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Critical Appraisal of Traumatic Brain Injury and Its Management

Indian Journal of Neurotrauma ◽

10.1055/s-0040-1713555 ◽

2020 ◽

Vol 17 (02) ◽

pp. 079-084

Author(s):

Subhas Konar ◽

Orlin Pavlov ◽

Yeider Durango-Espinosa ◽

Ezequiel Garcia-Ballestas ◽

Andrei Fernandes Joaquim ◽

...

Keyword(s):

Risk Factors ◽

Traumatic Brain Injury ◽

Brain Injury ◽

Critical Appraisal ◽

Prehospital Care ◽

Clinical Status ◽

Initial Assessment ◽

Surgical Approaches ◽

Research Groups ◽

Prophylactic Measures

AbstractCritical appraisal of traumatic brain injury (TBI) management has always been marred with a conflict of differential approaches, with claims and counterclaims of outcomes among the research groups. We performed this study to review the management of TBI from risk factors to outcomes including the comorbidities and final clinical status. In conjunction with the aforesaid stabilization of TBI cases, prophylactic and definitive surgical approaches and other supporting interventions will ultimately decide the final outcomes in the long run. Improvements in the quality of care for patients with severe TBI, with the reduction in mortality, have been demonstrated in high-income areas due to improvements in the health care system and not just in one isolated intervention. In the management of TBI, a fast and high index of suspicion is the key to success, from the initial assessment to the final rehabilitation of the cases, from the victim of risk factors to the victims of situation. The research groups feel that TBI prophylactic measures and primary care mitigation models are as important as definitive care, starting from prehospital care to dedicated care.

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The pathway to special education: The role of early risk factors in disability identification

PsycEXTRA Dataset ◽

10.1037/e569872014-001 ◽

2014 ◽

Author(s):

Whitney A. Leboeuf ◽

Benjamin Brumley ◽

John W. Fantuzzo ◽

Cody A. Hostutler

Keyword(s):

Risk Factors ◽

Special Education ◽

Early Risk ◽

Early Risk Factors ◽

Disability Identification

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A-126 Clinical Utility of Risk Factors to Predict Self-reported Neurobehavioral Outcome Following Traumatic Brain Injury: PTSD, Sleep, Resilience, and Lifetime Blast Exposure

Archives of Clinical Neuropsychology ◽

10.1093/arclin/acaa068.126 ◽

2020 ◽

Vol 35 (6) ◽

pp. 919-919

Author(s):

Lange R ◽

Lippa S ◽

Hungerford L ◽

Bailie J ◽

French L ◽

...

Keyword(s):

Risk Factors ◽

Traumatic Brain Injury ◽

Risk Factor ◽

Brain Injury ◽

Clinical Utility ◽

Poor Sleep ◽

Post Injury ◽

Poor Outcome ◽

Blast Exposure ◽

Neurobehavioral Outcome

Abstract Objective To examine the clinical utility of PTSD, Sleep, Resilience, and Lifetime Blast Exposure as ‘Risk Factors’ for predicting poor neurobehavioral outcome following traumatic brain injury (TBI). Methods Participants were 993 service members/veterans evaluated following an uncomplicated mild TBI (MTBI), moderate–severe TBI (ModSevTBI), or injury without TBI (Injured Controls; IC); divided into three cohorts: (1) < 12 months post-injury, n = 237 [107 MTBI, 71 ModSevTBI, 59 IC]; (2) 3-years post-injury, n = 370 [162 MTBI, 80 ModSevTBI, 128 IC]; and (3) 10-years post-injury, n = 386 [182 MTBI, 85 ModSevTBI, 119 IC]. Participants completed a 2-hour neurobehavioral test battery. Odds Ratios (OR) were calculated to determine whether the ‘Risk Factors’ could predict ‘Poor Outcome’ in each cohort separately. Sixteen Risk Factors were examined using all possible combinations of the four risk factor variables. Poor Outcome was defined as three or more low scores (< 1SD) on five TBI-QOL scales (e.g., Fatigue, Depression). Results In all cohorts, the vast majority of risk factor combinations resulted in ORs that were ‘clinically meaningful’ (ORs > 3.00; range = 3.15 to 32.63, all p’s < .001). Risk factor combinations with the highest ORs in each cohort were PTSD (Cohort 1 & 2, ORs = 17.76 and 25.31), PTSD+Sleep (Cohort 1 & 2, ORs = 18.44 and 21.18), PTSD+Sleep+Resilience (Cohort 1, 2, & 3, ORs = 13.56, 14.04, and 20.08), Resilience (Cohort 3, OR = 32.63), and PTSD+Resilience (Cohort 3, OR = 24.74). Conclusions Singularly, or in combination, PTSD, Poor Sleep, and Low Resilience were strong predictors of poor outcome following TBI of all severities and injury without TBI. These variables may be valuable risk factors for targeted early interventions following injury.

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Early Risk Factors for Obesity in the First 1000 Days—Relationship with Body Fat and BMI at 2 Years

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18158179 ◽

2021 ◽

Vol 18 (15) ◽

pp. 8179

Author(s):

Mercedes Díaz-Rodríguez ◽

Celia Pérez-Muñoz ◽

Jesús Carretero-Bravo ◽

Catalina Ruíz-Ruíz ◽

Manuel Serrano-Santamaría ◽

...

Keyword(s):

Risk Factors ◽

Weight Gain ◽

Body Fat ◽

Early Pregnancy ◽

Body Fat Percentage ◽

Z Score ◽

Fat Percentage ◽

Early Risk ◽

Early Risk Factors ◽

Increased Risk

(1) Background: Obesity is defined as an excessive accumulation of body fat. Several early developmental factors have been identified which are associated with an increased risk of childhood obesity and increased adiposity in childhood. The primary objective of the present study is to analyse the effect of various early risk factors on Body Mass Index (BMI) and body fat percentage at 2 years of age. (2) Methods: A prospective cohort study design was used, with the sample consisting of 109 mother-child pairs from whom data were collected between early pregnancy and 2 years old. Adiposity was determined based on skinfold measurements using the Brooks and Siri formulae. Mean comparison tests (Student’s t-test and ANOVAs) and multiple linear regression models were used to analyse the relationship between early programming factors and dependent variables. (3) Results: Maternal excess weight during early pregnancy (β = 0.203, p = 0.026), gestational smoking (β = 0.192, p = 0.036), and accelerated weight gain in the first 2 years (β = − 0.269, p = 0.004) were significantly associated with high body fat percentage. Pre-pregnancy BMI and accelerated weight gain in the first 2 years were associated with high BMI z-score (β = 0.174, p = 0.047 and β = 0.417, p = 0.000 respectively). The cumulative effect of these variables resulted in high values compared to the baseline zero-factor group, with significant differences in BMI z-score (F = 8.640, p = 0.000) and body fat percentage (F = 5.402, p = 0.002) when three factors were present. (4) Conclusions: The presence of several early risk factors related to obesity in infancy was significantly associated with higher BMI z-score and body fat percentage at 2 years of age. The presence of more than one of these variables was also associated with higher adiposity at 2 years of age. Early prevention strategies should address as many of these factors as possible.

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