Death after discharge: prognostic model of 1-year mortality in traumatic brain injury patients undergoing decompressive craniectomy

Cui, Wenxing; Ge, Shunnan; Shi, Yingwu; Wu, Xun; Luo, Jianing; Lui, Haixiao; Zhu, Gang; Guo, Hao; Feng, Dayun; Qu, Yan

doi:10.1186/s41016-021-00242-4

Cited by 3 publications

(2 citation statements)

References 36 publications

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“…In an era of disruptive technology, various clinical prediction tools have been developed and used for prognosis in various conditions including TBI [10], oncology [11], and surgical complications [12]. A nomogram is a prediction instrument used for outcome prediction, especially TBI.…”

Section: Introductionmentioning

confidence: 99%

“…The tool had an area under the receiver operating characteristic curve (AUC) of 0.71. Cui et al [10] developed a nomogram for predicting prognosis in TBI patients after decompressive craniectomy and showed an AUC of 0.83. Furthermore, Parmontree et al [14] proposed a nomogram for prediction of early posttraumatic seizure, with an AUC of 0.77.…”

Section: Introductionmentioning

confidence: 99%

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Development and internal validation of a nomogram for predicting outcomes in children with traumatic subdural hematoma

Kaewborisutsakul

Tunthanathip

2022

Acute Crit Care

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Background: A subdural hematoma (SDH) following a traumatic brain injury (TBI) in children can lead to unexpected death or disability. The nomogram is a clinical prediction tool used by physicians to provide prognosis advice to parents for making decisions regarding treatment. In the present study, a nomogram for predicting outcomes was developed and validated. In addition, the predictors associated with outcomes in children with traumatic SDH were determined. Methods: In this retrospective study, 103 children with SDH after TBI were evaluated. According to the King's Outcome Scale for Childhood Head Injury classification, the functional outcomes were assessed at hospital discharge and categorized into favorable and unfavorable. The predictors associated with the unfavorable outcomes were analyzed using binary logistic regression. Subsequently, a two-dimensional nomogram was developed for presentation of the predictive model. Results:The predictive model with the lowest level of Akaike information criterion consisted of hypotension (odds ratio [OR], 9.4; 95% confidence interval [CI], 2.0-42.9), Glasgow coma scale scores of 3-8 (OR, 8.2; 95% CI, 1.7-38.9), fixed pupil in one eye (OR, 4.8; 95% CI, 2.6-8.8), and fixed pupils in both eyes (OR, 3.5; 95% CI, 1.6-7.1). A midline shift ≥5 mm (OR, 1.1; 95% CI, 0.62-10.73) and co-existing intraventricular hemorrhage (OR, 6.5; 95% CI, 0.003-26.1) were also included. Conclusions: SDH in pediatric TBI can lead to mortality and disability. The predictability level of the nomogram in the present study was excellent, and external validation should be conducted to confirm the performance of the clinical prediction tool.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Development and internal validation of a nomogram for predicting outcomes in children with traumatic subdural hematoma

Kaewborisutsakul

Tunthanathip

2022

Acute Crit Care

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Mortality and Risk Factors in Isolated Traumatic Brain Injury Patients: A Prospective Cohort Study

Bansal¹,

Patil²,

Faria³

et al. 2022

Journal of Surgical Research

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Predictors of Mortality Due to Severe Traumatic Brain Injury: a Prospective Observational Cohort Study With 1-year Analyses

Gonçalves,

Lirio,

Nascimento

et al. 2023

Preprint

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Background Many predictors are associated with higher risks of hospital mortality due to severe Traumatic Brain Injury (TBI). The identification of these predictive factors is important for reducing morbimortality. Thus, the aim of this study was to identify predictors of mortality due to severe TBI in a trauma referral hospital in Brazil. Methods A prospective observational cohort study was carried out at a trauma referral hospital. All individuals > 18 years old with severe TBI diagnosis were included. Binomial logistic regression analysis was performed for each variable individually to identify possible predictors of in-hospital mortality and death 12 after hospital discharge. Variables considered statistically significant were analyzed in a final binomial logistic regression model and the magnitude of the association was measured by the odds ratio (OR). Results After applying the enrollment criteria, 383 patients were included. Of these, 211 (55%) died, 172 (45%) survived hospitalization and 22 (15%) died within the first year. The mean age was 49 ± 19 years, 309 (81%) individuals were male, and fall (46.5%) was the main cause of injury. Most individuals had Injury Severity Score ≥ 25 (85.2%). On the final binomial logistic regression model, age greater than 65 years (OR = 6.60 95%CI 2.515–17.354) and pupillary changes such as anisocoria (OR = 2.440 95%CI 1.098–5.465) and mydriasis (6.906 95%CI 2.758- 17,293) were independent variables associated with a higher risk of hospital mortality. High respiratory rate (OR = 1.127 95%CI 1.025–1.240) and body temperature (OR = 0.758 0.606–0.949) collected on admission to the emergency room were also predictors of mortality. A higher risk of mortality was associated with values > 25 on the Injury Severity Score (OR = 3.69395%CI 1.556–8.766) and the performance of decompressive craniectomy (OR = 2.644 95%CI 1.343–5.204). Conclusions This study demonstrated higher mortality rate of patients with TBI when compared to other trauma centers in both high-income countries (HICs) and low- and middle-income countries (LMICs). Early clinical factors such as pupillary changes, high values in the ISS, the performance of decompressive craniectomy, increased respiratory rate and low body temperature were associated with a higher risk of hospital mortality. The study highlights the importance of accounting for regional disparities when developing and implementing TBI management strategies worldwide.

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Death after discharge: prognostic model of 1-year mortality in traumatic brain injury patients undergoing decompressive craniectomy

Cited by 3 publications

References 36 publications

Development and internal validation of a nomogram for predicting outcomes in children with traumatic subdural hematoma

Development and internal validation of a nomogram for predicting outcomes in children with traumatic subdural hematoma

Mortality and Risk Factors in Isolated Traumatic Brain Injury Patients: A Prospective Cohort Study

Predictors of Mortality Due to Severe Traumatic Brain Injury: a Prospective Observational Cohort Study With 1-year Analyses

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