Traumatic brain injury hospital incidence in Brazil: an analysis of the past 10 years

Carteri, Randhall Bruce; Silva, Ricardo Azevedo da

doi:10.5935/0103-507x.20210036

Cited by 12 publications

(6 citation statements)

References 22 publications

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“…Understanding the hospital costs of TBI is essential for public policy. According to a study published in the Brazilian Journal of Intensive Care, the average total annual costs of hospital expenses associated with TBI patients were approximately US$43,238,319.90, with an average cost per admission of US$327.68 (CARTERI et al, 2021). These costs are included in the National Cost Management Program (PNGC), which is an important public management tool created to address the lack of cost information in public health institutions (BRASIL, 2021(BRASIL, , 2000.…”

Section: Pupil Response Evaluationmentioning

confidence: 99%

Predictors of In-Hospital Mortality and Years of Life Lost in Patients with Severe Traumatic Brain Injury: A Retrospective Study in the Metropolitan Region of Vitória, Brazil

FILHO,

DE ALMEIDA,

GONÇALVES

et al. 2024

Preprint

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Traumatic Brain Injury (TBI) poses a notable incidence in both developed countries and emerging economies worldwide. Each year, approximately 70 million people are affected by TBI, and around 11% of these events are classified as severe. Data from the Global Burden of Disease (GBD) in 2019 revealed that Brazil accounts for 1.1% of all moderate/severe TBI incidents worldwide. Within this context, falls stand out as the primary cause, representing 67% of cases. Analyzing the statistics at the state level, it is observed that Espírito Santo is responsible for 14% of all TBI incidents in Brazil, with falls also being the main cause, at a percentile of 67%. The discovery of predictors of TBI mortality is crucial to support intervention and prognosis strategies, potentially guiding public health policies. Due to the scarcity of studies in this area, our objective was to identify predictors of mortality in severe TBI and analyze the burden of TBI in the metropolitan region of Vitória, Espírito Santo. We conducted a retrospective observational cohort study at a trauma reference hospital in the state, including all individuals diagnosed with severe TBI from 2019 to 2022. The dependent variable analyzed was the outcome of hospital mortality. After applying the inclusion criteria, 863 individuals were included in the study, of which 450 (52.14%) had a fatal outcome, and 413 (47.86%) survived. The mean age was 48.67 years, with 82.5% being male. Falls (55.56%) were the leading cause of death in the population. The final binomial logistic regression model indicated that age up to 59 years, time up to 10 days in orotracheal intubation (OTI), and the type of trauma from falls were variables with notable predictive power for severe TBI-related mortality in the population. The calculation of Years of Life Lost (YLLs) revealed that TBI had an accumulated impact of 10,870.23 years of life lost prematurely in the study population. This is the first retrospective study to analyze predictive variables and the burden of TBI in the Greater Vitória region. However, it is important to note that unanalyzed factors may influence outcomes, such as the sample restriction to patients from a single reference hospital in the region, potentially limiting the understanding of variations in epidemiological profiles and adjacent health services.

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Section: Pupil Response Evaluationmentioning

confidence: 99%

Predictors of In-Hospital Mortality and Years of Life Lost in Patients with Severe Traumatic Brain Injury: A Retrospective Study in the Metropolitan Region of Vitória, Brazil

FILHO,

DE ALMEIDA,

GONÇALVES

et al. 2024

Preprint

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“…Among the elderly, traumatic brain injury might increase mortality when associated with several comorbidities, such as falls, which can even contribute to the cause of trauma (64)(65)(66). A retrospective cohort study that analyzed data from 8,598 patients reported that most ICU admissions were male patients.…”

Section: Multivariate Binary Logistic Regression Analysismentioning

confidence: 99%

Epidemiological profile and risk factors associated with death in patients receiving invasive mechanical ventilation in an adult intensive care unit from Brazil: a retrospective study

2023

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IntroductionUnderstanding the epidemiological profile and risk factors associated with invasive mechanical ventilation (IMV) is essential to manage the patients better and to improve health services. Therefore, our objective was to describe the epidemiological profile of adult patients in intensive care that required IMV in-hospital treatment. Also, to evaluate the risks associated with death and the influence of positive end-expiratory pressure (PEEP) and arterial oxygen pressure (PaO2) at admission in the clinical outcome.MethodsWe conducted an epidemiological study analyzing medical records of inpatients who received IMV from January 2016 to December 2019 prior to the Coronavirus Disease (COVID)-19 pandemic in Brazil. We considered the following characteristics in the statistical analysis: demographic data, diagnostic hypothesis, hospitalization data, and PEEP and PaO2 during IMV. We associated the patients’ features with the risk of death using a multivariate binary logistic regression analysis. We adopted an alpha error of 0.05.ResultsWe analyzed 1,443 medical records; out of those, 570 (39.5%) recorded the patients’ deaths. The binary logistic regression was significant in predicting the patients’ risk of death [X2(9) = 288.335; p < 0.001]. Among predictors, the most significant in relation to death risk were: age [elderly ≥65 years old; OR = 2.226 (95%CI = 1.728–2.867)]; male sex (OR = 0.754; 95%CI = 0.593–0.959); sepsis diagnosis (OR = 1.961; 95%CI = 1.481–2.595); need for elective surgery (OR = 0.469; 95%CI = 0.362–0.608); the presence of cerebrovascular accident (OR = 2.304; 95%CI = 1.502–3.534); time of hospital care (OR = 0.946; 95%CI = 0.935–0.956); hypoxemia at admission (OR = 1.635; 95%CI = 1.024–2.611), and PEEP >8 cmH2O at admission (OR = 2.153; 95%CI = 1.426–3.250).ConclusionThe death rate of the studied intensive care unit was equivalent to that of other similar units. Regarding risk predictors, several demographic and clinical characteristics were associated with enhanced mortality in intensive care unit patients under mechanical ventilation, such as diabetes mellitus, systemic arterial hypertension, and older age. The PEEP >8 cmH2O at admission was also associated with increased mortality since this value is a marker of initially severe hypoxia.

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“…Traumatic brain injury (TBI) is a major cause of death and disability worldwide, affecting mainly individuals of working age. It is a complex health condition with considerable economic and social costs and, therefore a public health problem, especially in developing countries [ 13 ]. The monitoring of intracranial pressure (ICP) is a cornerstone of the clinical management of severe TBI.…”

Section: Introductionmentioning

confidence: 99%

Can a new noninvasive method for assessment of intracranial pressure predict intracranial hypertension and prognosis?

et al. 2023

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Purpose Individuals with TBI are at risk of intracranial hypertension (ICH), and monitoring of intracranial pressure (ICP) is usually indicated. However, despite many new noninvasive devices, none is sufficiently accurate and effective for application in clinical practice, particularly in the management of TBIs. This study aimed to compare the noninvasive Brain4Care system (nICP) with invasive ICP (iICP) curve parameters in their ability to predict ICH and functional prognosis in severe TBI. Methods Observational, descriptive-analytical, and prospective study of 22 patients between 2018 and 2021, simultaneously monitored with nICP and iICP. The independent variables evaluated were the presence of ICH and functional prognoses. The dependent variables were the P2/P1 pressure ratio metrics, time to peak (TTP), and TTP × P2/P1. Results We found a good nonlinear correlation between iICP and nICP waveforms, despite a moderate Pearson’s linear correlation. The noninvasive parameters of P2/P1, P2/P1 × TTP, and TTP were not associated with outcomes or ICH. The nICP P2/P1 ratio showed sensitivity/specificity/accuracy (%) of 100/0/56.3, respectively for 1-month outcomes and 77.8/22.2/50 for 6-month outcomes. The nICP TTP ratio had values of 100/0/56.3 for 1-month and 99.9/42.9/72.2 for 6-month outcomes. The nICP P2/P1 × TTP values were 100/0/56.3 for 1-month outcomes and 81.8/28.6/61.1 for 6-month outcomes. Conclusion Brain4Care’s noninvasive method showed low specificity and accuracy and cannot be used as the sole means of monitoring ICP in patients with severe TBI. Future studies with a larger sample of patients with P2 > P1 and new nICP curve parameters are warranted. Supplementary Information The online version contains supplementary material available at 10.1007/s00701-023-05580-z.

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Traumatic brain injury hospital incidence in Brazil: an analysis of the past 10 years

Cited by 12 publications

References 22 publications

Predictors of In-Hospital Mortality and Years of Life Lost in Patients with Severe Traumatic Brain Injury: A Retrospective Study in the Metropolitan Region of Vitória, Brazil

Predictors of In-Hospital Mortality and Years of Life Lost in Patients with Severe Traumatic Brain Injury: A Retrospective Study in the Metropolitan Region of Vitória, Brazil

Epidemiological profile and risk factors associated with death in patients receiving invasive mechanical ventilation in an adult intensive care unit from Brazil: a retrospective study

Can a new noninvasive method for assessment of intracranial pressure predict intracranial hypertension and prognosis?

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