Factors with the strongest prognostic value associated with in-hospital mortality rate among patients operated for acute subdural and epidural hematoma

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Abstract

Introduction

Traumatic brain injury (TBI) still remains a serious health problem and is called a “silent epidemic”. Each year in Europe 262 per 100,000 individuals suffer from TBI. The most common consequence of severe head injuries include acute subdural (SDH) and epidural hematomas (EDH), which usually require immediate surgically treatment. The aim of our study is to identify factors which have the strongest prognostic value in relation to in-hospital mortality rate among of patients undergoing surgery for EDH and SDH.

Patients and methods

Cohort included 128 patients with isolated craniocerebral injuries who underwent surgery for EDH (28 patients) and SDH (100 patients) in a single, tertiary care Department of Neurosurgery. The data were collected on admission of patients to the Emergency Department and retrospectively analyzed. The following factors were analyzed: demographic data, physiological parameters, laboratory variables, computed tomography scan characteristics and the time between trauma and surgery. Likewise, we have investigated the in-hospital mortality of patients at the time of discharge.

Results

We found that the factors with the strongest prognostic values were: the initial GCS score, respiratory rate, glycaemia, blood saturation, systolic blood pressure, midline shift and type of hematoma. Additionally, we proved that a drop by one point in the GCS score almost doubles the risk of in-hospital death while the presence of coagulopathy increases the risk of in-hospital death almost six times.

Conclusion

Most of the factors with the strongest prognostic value are factors that the emergency team can treat prior to the hospital admission. Coagulopathy, however that has the strongest influence on in-hospital death rate can only be efficiently treated in a hospital setting.

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Most cited references 74

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Estimating the global incidence of traumatic brain injury

Michael Dewan, Abbas Rattani, Saksham Gupta … (2018)

Traumatic brain injury (TBI)—the “silent epidemic”—contributes to worldwide death and disability more than any other traumatic insult. Yet, TBI incidence and distribution across regions and socioeconomic divides remain unknown. In an effort to promote advocacy, understanding, and targeted intervention, the authors sought to quantify the case burden of TBI across World Health Organization (WHO) regions and World Bank (WB) income groups. Open-source epidemiological data on road traffic injuries (RTIs) were used to model the incidence of TBI using literature-derived ratios. First, a systematic review on the proportion of RTIs resulting in TBI was conducted, and a meta-analysis of study-derived proportions was performed. Next, a separate systematic review identified primary source studies describing mechanisms of injury contributing to TBI, and an additional meta-analysis yielded a proportion of TBI that is secondary to the mechanism of RTI. Then, the incidence of RTI as published by the Global Burden of Disease Study 2015 was applied to these two ratios to generate the incidence and estimated case volume of TBI for each WHO region and WB income group. Relevant articles and registries were identified via systematic review; study quality was higher in the high-income countries (HICs) than in the low- and middle-income countries (LMICs). Sixty-nine million (95% CI 64–74 million) individuals worldwide are estimated to sustain a TBI each year. The proportion of TBIs resulting from road traffic collisions was greatest in Africa and Southeast Asia (both 56%) and lowest in North America (25%). The incidence of RTI was similar in Southeast Asia (1.5% of the population per year) and Europe (1.2%). The overall incidence of TBI per 100,000 people was greatest in North America (1299 cases, 95% CI 650–1947) and Europe (1012 cases, 95% CI 911–1113) and least in Africa (801 cases, 95% CI 732–871) and the Eastern Mediterranean (897 cases, 95% CI 771–1023). The LMICs experience nearly 3 times more cases of TBI proportionally than HICs. Sixty-nine million (95% CI 64–74 million) individuals are estimated to suffer TBI from all causes each year, with the Southeast Asian and Western Pacific regions experiencing the greatest overall burden of disease. Head injury following road traffic collision is more common in LMICs, and the proportion of TBIs secondary to road traffic collision is likewise greatest in these countries. Meanwhile, the estimated incidence of TBI is highest in regions with higher-quality data, specifically in North America and Europe.

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Predicting outcome after traumatic brain injury: practical prognostic models based on large cohort of international patients.

Pablo Perel, Miguel Arango, Tim Clayton … (2008)

To develop and validate practical prognostic models for death at 14 days and for death or severe disability six months after traumatic brain injury. Multivariable logistic regression to select variables that were independently associated with two patient outcomes. Two models designed: "basic" model (demographic and clinical variables only) and "CT" model (basic model plus results of computed tomography). The models were subsequently developed for high and low-middle income countries separately. Medical Research Council (MRC) CRASH Trial. 10,008 patients with traumatic brain injury. Models externally validated in a cohort of 8509. The basic model included four predictors: age, Glasgow coma scale, pupil reactivity, and the presence of major extracranial injury. The CT model also included the presence of petechial haemorrhages, obliteration of the third ventricle or basal cisterns, subarachnoid bleeding, midline shift, and non-evacuated haematoma. In the derivation sample the models showed excellent discrimination (C statistic above 0.80). The models showed good calibration graphically. The Hosmer-Lemeshow test also indicated good calibration, except for the CT model in low-middle income countries. External validation for unfavourable outcome at six months in high income countries showed that basic and CT models had good discrimination (C statistic 0.77 for both models) but poorer calibration. Simple prognostic models can be used to obtain valid predictions of relevant outcomes in patients with traumatic brain injury.

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Early coagulopathy predicts mortality in trauma.

Jana B. A. MacLeod, Mauricio Lynn, Mark McKenney … (2003)

Coagulopathy and hemorrhage are known contributors to trauma mortality; however, the actual relationship of prothrombin time (PT) and partial thromboplastin time (PTT) to mortality is unknown. Our objective was to measure the predictive value of the initial coagulopathy profile for trauma-related mortality. We reviewed prospectively collected data on trauma patients presenting to a Level I trauma center. A logistic regression analysis was performed of PT, PTT, platelet count, and confounders to determine whether coagulopathy is a predictor of all-cause mortality. From a trauma registry cohort of 20103 patients, 14397 had complete disposition data for initial analysis and 7638 had complete data for all variables in the final analysis. The total cohort was 76.2% male, the mean age was 38 years (range, 1-108 years), and the median Injury Severity Score was 9. There were 1276 deaths (all-cause mortality, 8.9%). The prevalence of coagulopathy early in the postinjury period was substantial, with 28% of patients having an abnormal PT (2994 of 10790) and 8% of patients having an abnormal PTT (826 of 10453) on arrival at the trauma bay. In patients with disposition data and a normal PT, 489 of 7796 died, as compared with 579 of 2994 with an abnormal PT (6.3% vs. 19.3%; chi2 = 414.1, p < 0.001). Univariate analysis generated an odds ratio of 3.6 (95% confidence interval [CI], 3.15-4.08; p < 0.0001) for death with abnormal PT and 7.81 (95% CI, 6.65-9.17; p < 0.001) for deaths with an abnormal PTT. The PT and PTT remained independent predictors of mortality in a multiple regression model, whereas platelet count did not. The model also included the independent risk factors age, Injury Severity Score, scene and trauma-bay blood pressure, hematocrit, base deficit, and head injury. The model generated an adjusted odds ratio of 1.35 for PT (95% CI, 1.11-1.68; p < 0.001) and 4.26 for PTT (95% CI, 3.23-5.63; p < 0.001). The incidence of coagulation abnormalities, early after trauma, is high and they are independent predictors of mortality even in the presence of other risk factors. An initial abnormal PT increases the adjusted odds of dying by 35% and an initial abnormal PTT increases the adjusted odds of dying by 326%.

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Author and article information

Contributors

Bartłomiej Kulesza:

ORCID: http://orcid.org/0000-0002-9973-9571

kuleszabartek88@gmail.com

Marek Mazurek: marekmazurek@hotmail.com

Adam Nogalski:

ORCID: http://orcid.org/0000-0003-0720-4690

chirurgiaurazowalublin@tlen.pl

Radosław Rola: rola.radoslaw@gmail.com

Journal

Journal ID (nlm-ta): Eur J Trauma Emerg Surg

Journal ID (iso-abbrev): Eur J Trauma Emerg Surg

Title: European Journal of Trauma and Emergency Surgery

Publisher: Springer Berlin Heidelberg (Berlin/Heidelberg )

ISSN (Print): 1863-9933

ISSN (Electronic): 1863-9941

Publication date (Electronic): 10 August 2020

Publication date PMC-release: 10 August 2020

Publication date (Print): 2021

Volume: 47

Issue: 5

Pages: 1517-1525

Affiliations

[1 ]GRID grid.411484.c, ISNI 0000 0001 1033 7158, Chair and Department of Neurosurgery and Paediatric Neurosurgery, , Medical University in Lublin, Independent Public Clinical Hospital No. 4 in Lublin, ; Jaczewskiego 8, 20-954 Lublin, Poland

[2 ]GRID grid.411484.c, ISNI 0000 0001 1033 7158, Chair and Department of Trauma Surgery and Emergency Medicine, , Medical University in Lublin, Independent Public Clinical Hospital No. 1 in Lublin Poland, ; Stanisława Sztaszica 16, 20-400 Lublin, Poland

Author information

Bartłomiej Kulesza http://orcid.org/0000-0002-9973-9571

Adam Nogalski http://orcid.org/0000-0003-0720-4690

Article

Publisher ID: 1460

DOI: 10.1007/s00068-020-01460-8

PMC ID: 8476473

PubMed ID: 32776246

SO-VID: bc87a91c-3ff5-4cac-92c8-69c43e108216

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 13 June 2020

Date accepted : 5 August 2020

Custom metadata

ScienceOpen disciplines: Emergency medicine & Trauma

Keywords: traumatic brain injury,epidural hematoma,subdural hematoma,in-hospital mortality rate

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ScienceOpen disciplines: Emergency medicine & Trauma

Keywords: traumatic brain injury, epidural hematoma, subdural hematoma, in-hospital mortality rate

Factors with the strongest prognostic value associated with in-hospital mortality rate among patients operated for acute subdural and epidural hematoma

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Abstract

Introduction

Patients and methods

Results

Conclusion

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Irish Journal of Paramedicine

Most cited references 74

Estimating the global incidence of traumatic brain injury

Predicting outcome after traumatic brain injury: practical prognostic models based on large cohort of international patients.

Early coagulopathy predicts mortality in trauma.

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