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Biomarcadores , Lesiones Traumáticas del Encéfalo , Humanos , Lesiones Traumáticas del Encéfalo/sangre , Lesiones Traumáticas del Encéfalo/diagnóstico , Biomarcadores/sangre , Pronóstico , Estudios Prospectivos , Estudios de Cohortes , Proteína Serina-Treonina Quinasas de Interacción con ReceptoresRESUMEN
Patients with traumatic brain injury (TBI) frequently exhibit concomitant immunosuppression. In this study, we evaluated the predictive values of soluble programmed death-1 (sPD-1) and soluble programmed death ligand-1 (sPD-L1) in patients with severe TBI. Peripheral blood sPD-1 and sPD-L1 levels were measured within 48 h of patient admission. A total of 20 healthy volunteers and 82 patients were enrolled in this study. The levels of sPD-1 and sPD-L1 were upregulated in patients with severe TBI (P < 0.001). They were significantly increased in the post-TBI severe pneumonia group and among non-survivors (P < 0.001). The area under the curves (AUCs) for sPD-1 and sPD-L1 levels to predict severe pneumonia were 0.714 and 0.696, respectively, and the AUCs to predict mortality were 0.758 and 0.735. The levels of sPD-1 and sPD-L1 are correlated with the GCS scores at admission, APACHE II scores, length of MV, and time elapsed to mortality. The levels of sPD-1 and sPD-L1 emerged as independent predictive factors for severe pneumonia and mortality. This study demonstrates that upregulation of sPD-1 and sPD-L1 in severe TBI patients is significantly associated with severe pneumonia and mortality, suggesting their potential as predictive biomarkers for these outcomes.
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Antígeno B7-H1 , Biomarcadores , Lesiones Traumáticas del Encéfalo , Receptor de Muerte Celular Programada 1 , Humanos , Lesiones Traumáticas del Encéfalo/sangre , Lesiones Traumáticas del Encéfalo/mortalidad , Lesiones Traumáticas del Encéfalo/diagnóstico , Masculino , Femenino , Persona de Mediana Edad , Pronóstico , Adulto , Antígeno B7-H1/sangre , Antígeno B7-H1/metabolismo , Receptor de Muerte Celular Programada 1/sangre , Receptor de Muerte Celular Programada 1/metabolismo , Biomarcadores/sangre , Anciano , Neumonía/sangreRESUMEN
OBJECTIVE: Pediatric traumatic brain injury (pTBI) is a heterogeneous condition requiring the development of clinical decision rules (CDRs) for the optimal management of these patients. Machine learning (ML) is a novel artificial intelligence (AI) predictive tool with various applications in modern neurosurgery, including the creation of CDRs for patients with pTBI. In the present study, we summarized the current literature on the applications of ML in pTBI. METHODS: A systematic review was conducted following the PRISMA guidelines. The literature search included PubMed/MEDLINE, SCOPUS, and ScienceDirect databases. We included observational or experimental studies focusing on the applications of ML in patients with pTBI under 18 years of age. RESULTS: A total of 18 articles were included in our systematic review. Of these articles, 16 were retrospective cohorts, 1 was a prospective cohort, and 1 was a case-control study. Of these articles, ten concerned ML applications in predicting the outcome of pTBI patients, while 8 reported applications of ML in predicting the need for CT scans. Artificial Neuronal Network (ANN) and Random Forest (RF) were the most commonly utilized models for the creation of predictive algorithms. The accuracy of the ML algorithms to predict the need for CT scan in pTBI cases ranged from 0.790 to 0.999, and the Area Under Curve (AUC) ranged from 0.411 (95%CI: 0.354-0.468) to 0.980 (95%CI: 0.950-1.00). The model with the maximum accuracy to predict the need for CT scan was a Deep ANN model, while the model with the maximum AUC was Ensemble Learning. The model with the maximum accuracy to predict the outcome (favorable vs. unfavorable) of patients with TBI was a support vector machine (SVM) model with 94.0% accuracy, whereas the model with the highest AUC was an ANN model with an AUC of 0.991. CONCLUSION: In the present systematic review, conventional and novel ML models were utilized to either predict the presence of intracranial trauma or the prognosis of children with pTBI. However, most of the reported ML algorithms have not been externally validated and are pending further research.
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Lesiones Traumáticas del Encéfalo , Aprendizaje Automático , Humanos , Lesiones Traumáticas del Encéfalo/diagnóstico , Niño , AdolescenteRESUMEN
Background At present, the relationship between the Triglyceride-glucose index (TyG index) and Acute kidney injury (AKI) in traumatic brain injury patients in the Intensive Care Unit (ICU) is still unclear. Currently, the relationship between TyG index and AKI occurred within 7 days in the ICU is a highly researched and trending topic. Objective In this study, we conducted in-depth exploration of the relationship between the development of AKI in traumatic brain injury (TBI) patients in the ICU and changes in TyG index, as well as its relevance. Methods A cross-sectional study was conducted with a total of 492 individuals enrolled in the Medical Information Mart for Intensive Care IV(MIMIC-IV) database. Multivariate model logistic regression, smoothed curve fitting and forest plots were utilized to confirm the study objectives. The predictive power of the TyG index for outcome indicators was assessed using subject work characteristics (ROC) curves. As well as comparing the Integrated Discriminant Improvement Index and the Net Reclassification Index of the traditional forecasting model with the addition of the TyG index. Results Of all eligible subjects, 55.9% were male and the incidence of AKI was 59.3%. There was a statistically significant difference in the incidence of AKI within 7 days in the ICU between the different TyG index groups. The difference between TyG index and the risk of AKI within 7 days in the ICU remained significant after adjustment for logistic multifactorial modeling (OR = 2.07, 95% CI = 1.41-3.05, P < 0.001). A similar pattern of associations was observed in subgroup analyses (P values for all interactions were greater than 0.05). The addition of TyG index to the traditional risk factor model improved the predictive power of the risk of AKI within 7 days in ICU (P < 0.05). Conclusion The findings of this study demonstrate a strong association between the TyG index and the occurrence of AKI within 7 days in ICU patients. The TyG index can potentially be used as a risk stratification tool for early identification and prevention of AKI. Implementing preventive strategies targeting patients with a high TyG index may help reduce the burden of AKI in the ICU. Further prospective studies are warranted to validate these findings and explore the clinical utility of the TyG index in AKI prevention.
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Lesión Renal Aguda , Glucemia , Lesiones Traumáticas del Encéfalo , Unidades de Cuidados Intensivos , Triglicéridos , Humanos , Lesión Renal Aguda/sangre , Lesión Renal Aguda/diagnóstico , Lesión Renal Aguda/etiología , Masculino , Femenino , Lesiones Traumáticas del Encéfalo/sangre , Lesiones Traumáticas del Encéfalo/complicaciones , Lesiones Traumáticas del Encéfalo/diagnóstico , Persona de Mediana Edad , Triglicéridos/sangre , Estudios Transversales , Adulto , Glucemia/análisis , Glucemia/metabolismo , Valor Predictivo de las Pruebas , Anciano , Incidencia , Curva ROC , Factores de RiesgoRESUMEN
Background: Although the optimization of brain oxygenation is thought to improve the prognosis, the effect of brain tissue oxygen pressure (PbtO2) for patients with severe traumatic brain injury (STBI) remains controversial. Therefore, the present study aimed to determine whether adding PbtO2 to intracranial pressure (ICP) monitoring improves clinical outcomes for patients with STBI. Methods: PubMed, Embase, Scopus and Cochrane Library were searched for eligible trials from their respective inception through April 10th, 2024. We included clinical trials contrasting the combined monitoring of PbtO2 and ICP versus isolated ICP monitoring among patients with STBI. The primary outcome was favorable neurological outcome at 6 months, and secondary outcomes including the in-hospital mortality, long-term mortality, length of stay in intensive care unit (ICU) and hospital. Results: A total of 16 studies (four randomized studies and 12 cohort studies) were included in the meta-analysis. Compared with isolated ICP monitoring, the combined monitoring was associated with a higher favorable neurological outcome rate at 6 months (RR 1.33, 95% CI [1.17-1.51], P < 0.0001, I2 = 0%), reduced long-term mortality (RR 0.72, 95% CI [0.59-0.87], P = 0.0008, I2 = 2%). No significant difference was identified in the in-hospital mortality (RR 0.81, 95% CI 0.66 to 1.01, P = 0.06, I2 = 32%), length of stay in ICU (MD 2.10, 95% CI [-0.37-4.56], P = 0.10, I2 = 78%) and hospital (MD 1.07, 95% CI [-2.54-4.67], P = 0.56, I2 = 49%) between two groups. However, the pooled results of randomized studies did not show beneficial effect of combined monitoring in favorable neurological outcome and long-term mortality. Conclusions: Currently, there is limited evidence to prove that the combined PbtO2 and ICP monitoring may contribute to improved neurological outcome and long-term mortality for patients with STBI. However, the benefit of combined monitoring should be further validated in more randomized studies.
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Lesiones Traumáticas del Encéfalo , Presión Intracraneal , Humanos , Lesiones Traumáticas del Encéfalo/mortalidad , Lesiones Traumáticas del Encéfalo/terapia , Lesiones Traumáticas del Encéfalo/fisiopatología , Lesiones Traumáticas del Encéfalo/diagnóstico , Presión Intracraneal/fisiología , Monitoreo Fisiológico/métodos , Oxígeno/metabolismo , Mortalidad Hospitalaria , Encéfalo/metabolismo , Encéfalo/fisiopatología , Tiempo de InternaciónRESUMEN
Traumatic brain injury (TBI) is the leading cause of traumatic death worldwide and is a public health problem associated with high mortality and morbidity rates, with a significant socioeconomic burden. The diagnosis of brain injury may be difficult in some cases or may leave diagnostic doubts, especially in mild trauma with insignificant pathological brain changes or in cases where instrumental tests are negative. Therefore, in recent years, an important area of research has been directed towards the study of new biomarkers, such as micro-RNAs (miRNAs), which can assist clinicians in the diagnosis, staging, and prognostic evaluation of TBI, as well as forensic pathologists in the assessment of TBI and in the estimation of additional relevant data, such as survival time. The aim of this study is to investigate the expression profiles (down- and upregulation) of a panel of miRNAs in subjects deceased with TBI in order to assess, verify, and define the role played by non-coding RNA molecules in the different pathophysiological mechanisms of brain damage. This study also aims to correlate the detected expression profiles with survival time, defined as the time elapsed between the traumatic event and death, and with the severity of the trauma. This study was conducted on 40 cases of subjects deceased with TBI (study group) and 10 cases of subjects deceased suddenly from non-traumatic causes (control group). The study group was stratified according to the survival time and the severity of the trauma. The selection of miRNAs to be examined was based on a thorough literature review. Analyses were performed on formalin-fixed, paraffin-embedded (FFPE) brain tissue samples, with a first step of total RNA extraction and a second step of quantification of the selected miRNAs of interest. This study showed higher expression levels in cases compared to controls for miR-16, miR-21, miR-130a, and miR-155. In contrast, lower expression levels were found in cases compared to controls for miR-23a-3p. There were no statistically significant differences in the expression levels between cases and controls for miR-19a. In cases with short survival, the expression levels of miR-16-5p and miR-21-5p were significantly higher. In cases with long survival, miR-21-5p was significantly lower. The expression levels of miR-130a were significantly higher in TBI cases with short and middle survival. In relation to TBI severity, miR-16-5p and miR-21-5p expression levels were significantly higher in the critical-fatal TBI subgroup. Conclusions: This study provides evidence for the potential of the investigated miRNAs as predictive biomarkers to discriminate between TBI cases and controls. These miRNAs could improve the postmortem diagnosis of TBI and also offer the possibility to define the survival time and the severity of the trauma. The analysis of miRNAs could become a key tool in forensic investigations, providing more precise and detailed information on the nature and extent of TBI and helping to define the circumstances of death.
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Lesiones Traumáticas del Encéfalo , MicroARNs , Humanos , Lesiones Traumáticas del Encéfalo/genética , Lesiones Traumáticas del Encéfalo/mortalidad , Lesiones Traumáticas del Encéfalo/metabolismo , Lesiones Traumáticas del Encéfalo/patología , Lesiones Traumáticas del Encéfalo/diagnóstico , MicroARNs/genética , Masculino , Femenino , Persona de Mediana Edad , Adulto , Perfilación de la Expresión Génica , Biomarcadores , Anciano , Pronóstico , TranscriptomaRESUMEN
The study by Ooi et al. (2022) systematically reviews the potential of Interleukin-6 (IL-6) as a prognostic biomarker for traumatic brain injury (TBI). By analyzing IL-6 levels in serum, cerebrospinal fluid (CSF), and brain parenchyma, the authors provide valuable insights into its role in predicting clinical outcomes. The study emphasizes the neuroinflammatory response and the mechanistic role of IL-6 in neuronal recovery, offering a strong rationale for its consideration as a biomarker. However, variability in IL-6 detection methods and timing of sample collection across studies highlights the need for standardization. Future research should focus on refining detection methods, exploring IL-6's temporal dynamics post-TBI, and accounting for interactions with other cytokines. Additionally, advanced statistical controls are recommended to better isolate IL-6's prognostic value. This research lays a solid foundation for future studies aimed at improving clinical prognostication in TBI.
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Biomarcadores , Lesiones Traumáticas del Encéfalo , Interleucina-6 , Humanos , Biomarcadores/sangre , Biomarcadores/líquido cefalorraquídeo , Lesiones Traumáticas del Encéfalo/sangre , Lesiones Traumáticas del Encéfalo/diagnóstico , Interleucina-6/sangre , Interleucina-6/líquido cefalorraquídeo , PronósticoRESUMEN
OBJECTIVE: To describe experiences and challenges when updating a living evidence-based review database of randomized controlled trials (RCTs) on mental health and behavioral disorders in moderate to severe traumatic brain injury (MSTBI). METHOD: This commentary derives from our experience developing an extensive database of RCTs on MSTBI that has been conceptualized as a living evidence-based review. Our working group focused on mental health and behavior RCTs and reflected upon their experiences and challenges using the living systematic approach. We discuss challenges associated with metrics of study quality, injury etiology and severity, time post-injury, country of origin, and variability in outcome measures. RESULTS: RCTs were conducted almost solely in high income countries, with smaller sample sizes, and most conducted in the chronic phase post-TBI. Issues related to lack of transparency, unclear and incomplete reporting of injury severity, etiology, and time post-injury remain a concern and can lead to challenges associated with interpretation of results, validity, and reliability of the data. There was significant heterogeneity regarding the use of outcome measures and constructs, underscoring the need for standardization. CONCLUSION: Lack of standardization and incomplete reporting of injury characteristics makes it difficult to compare data between RCTs of MSTBI, perform meta-analyses, and generate evidence-based clinical recommendations.
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Lesiones Traumáticas del Encéfalo , Trastornos Mentales , Humanos , Lesiones Traumáticas del Encéfalo/complicaciones , Lesiones Traumáticas del Encéfalo/diagnóstico , Lesiones Traumáticas del Encéfalo/terapia , Medicina Basada en la Evidencia , Trastornos Mentales/etiología , Trastornos Mentales/terapia , Ensayos Clínicos Controlados Aleatorios como Asunto , Índices de Gravedad del TraumaRESUMEN
This study examines the emerging role of biomarkers in the prognosis and management of severe traumatic brain injury (sTBI). Key findings highlight the significance of serum RIP-3, STC1, Nrf2, and cerebrospinal fluid galectin-3 and cytokines in predicting disease severity, mortality, and functional outcomes in sTBI patients. Elevated levels of RIP-3 and STC1 were linked to poor prognosis and increased mortality, with RIP-3 associated with necroptosis and inflammation, and STC1 with neuroprotective properties. Nrf2 was found to correlate with oxidative stress and adverse outcomes, while elevated CSF galectin-3 and IL-6 indicated neuroinflammation and neurodegeneration. These biomarkers show promise not only as prognostic tools but also as potential therapeutic targets. The study suggests further validation through multicenter research to enhance clinical applications and improve treatment strategies for sTBI.
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Biomarcadores , Lesiones Traumáticas del Encéfalo , Humanos , Biomarcadores/sangre , Biomarcadores/líquido cefalorraquídeo , Lesiones Traumáticas del Encéfalo/diagnóstico , Lesiones Traumáticas del Encéfalo/sangre , Lesiones Traumáticas del Encéfalo/terapia , PronósticoRESUMEN
BACKGROUND: Home monitoring systems utilising artificial intelligence hold promise for digitally enhanced healthcare in older adults. Their real-world use will depend on acceptability to the end user i.e. older adults and caregivers. We explored the experiences of adults over the age of 60 and their social and care networks with a home monitoring system installed on hospital discharge after sustaining a moderate/severe Traumatic Brain Injury (TBI), a growing public health concern. METHODS: A qualitative descriptive approach was taken to explore experiential data from older adults and their caregivers as part of a feasibility study. Semi-structured interviews were conducted with 6 patients and 6 caregivers (N = 12) at 6-month study exit. Data were analysed using Framework analysis. Potential factors affecting acceptability and barriers and facilitators to the use of home monitoring in clinical care and research were examined. RESULTS: Home monitoring was acceptable to older adults with TBI and their caregivers. Facilitators to the use of home monitoring were perceived need for greater support after hospital discharge, the absence of sound and video recording, and the peace of mind provided to care providers. Potential barriers to adoption were reliability, lack of confidence in technology and uncertainty at how data would be acted upon to improve safety at home. CONCLUSIONS: Remote monitoring approaches are likely to be acceptable, especially if patients and caregivers see direct benefit to their care. We identified key barriers and facilitators to the use of home monitoring in older adults who had sustained TBI, which can inform the development of home monitoring for research and clinical use. For sustained use in this demographic the technology should be developed in conjunction with older adults and their social and care networks.
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Lesiones Traumáticas del Encéfalo , Investigación Cualitativa , Humanos , Masculino , Anciano , Femenino , Lesiones Traumáticas del Encéfalo/terapia , Lesiones Traumáticas del Encéfalo/psicología , Lesiones Traumáticas del Encéfalo/diagnóstico , Persona de Mediana Edad , Anciano de 80 o más Años , Cuidadores/psicología , Servicios de Atención de Salud a Domicilio , Estudios de FactibilidadRESUMEN
In the presented clinical observation of complex therapy of severe combined trauma: severe brain contusion, subarachnoid hemorrhage, closed fracture of the occipital bone, closed compression fracture of ThVI-ThVIII vertebral bodies, contusion of the lungs and kidneys, blunt abdominal trauma and closed fracture of both bones of the right leg in lower third with displacement) in a teenager after an accident, the need for dynamic introscopic examination of the patient is shown for timely detection of abnormalities in the state of brain structures and correction of treatment up to surgical intervention. The effectiveness of the inclusion of Cytoflavin in complex treatment regimens was noted in the form of positive dynamics of the clinical and introscopic picture. The results obtained may serve as a basis for further research.
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Lesiones Traumáticas del Encéfalo , Fosa Craneal Posterior , Combinación de Medicamentos , Mononucleótido de Flavina , Inosina Difosfato , Humanos , Adolescente , Lesiones Traumáticas del Encéfalo/complicaciones , Lesiones Traumáticas del Encéfalo/diagnóstico , Lesiones Traumáticas del Encéfalo/diagnóstico por imagen , Masculino , Fosa Craneal Posterior/lesiones , Fosa Craneal Posterior/diagnóstico por imagen , Mononucleótido de Flavina/uso terapéutico , Inosina Difosfato/uso terapéutico , Niacinamida/uso terapéutico , Succinatos/uso terapéutico , Resultado del Tratamiento , Traumatismo MúltipleRESUMEN
BACKGROUND: The inflammatory response in patients with traumatic brain injury (TBI) offers opportunities for stratification and intervention. Previous unselected approaches to immunomodulation in patients with TBI have not improved patient outcomes. METHODS: Serum and plasma samples from two prospective, multi-centre observational studies of patients with TBI were used to discover (Collaborative European NeuroTrauma Effectiveness Research [CENTER-TBI], Europe) and validate (Transforming Research and Clinical Knowledge in Traumatic Brain Injury [TRACK-TBI] Pilot, USA) individual variations in the immune response using a multiplex panel of 30 inflammatory mediators. Mediators that were associated with unfavourable outcomes (Glasgow outcome score-extended [GOS-E] ≤ 4) were used for hierarchical clustering to identify patients with similar signatures. FINDINGS: Two clusters were identified in both the discovery and validation cohorts, termed early-inflammatory and pauci-inflammatory. The early-inflammatory phenotype had higher concentrations of interleukin-6 (IL-6), IL-15, and monocyte chemoattractant protein 1 (MCP1). Patients with the early-inflammatory phenotype were older and more likely to have an unfavourable GOS-E at 6 months. There were no differences in the baseline injury severity scores between patients in each phenotype. A combined IL-15 and MCP1 signature identified patients with the early-inflammatory phenotype in both cohorts. Inflammatory processes mediated outcomes in older patients with moderate-severe TBI. INTERPRETATION: Our findings offer a precision medicine approach for future clinical trials of immunomodulation in patients with TBI, by using inflammatory signatures to stratify patients. FUNDING: CENTER-TBI study was supported by the European Union 7th Framework Programme. TRACK-TBI is supported by the National Institute of Neurological Disorders and Stroke.
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Biomarcadores , Lesiones Traumáticas del Encéfalo , Humanos , Lesiones Traumáticas del Encéfalo/inmunología , Lesiones Traumáticas del Encéfalo/sangre , Lesiones Traumáticas del Encéfalo/diagnóstico , Masculino , Femenino , Persona de Mediana Edad , Adulto , Anciano , Fenotipo , Mediadores de Inflamación/sangre , Mediadores de Inflamación/metabolismo , Estudios Prospectivos , Pronóstico , Citocinas/sangre , Citocinas/metabolismoRESUMEN
The development of an optical interface to directly distinguish the brain tissue's biochemistry is the next step in understanding traumatic brain injury (TBI) pathophysiology and the best and most appropriate treatment in cases where in-hospital intracranial access is required. Despite TBI being a globally leading cause of morbidity and mortality in patients under 40, there is still a lack of objective diagnostical tools. Further, given its pathophysiological complexity the majority of treatments provided are purely symptomatic without standardized therapeutic targets. Our tailor-engineered prototype of the intracranial Raman spectroscopy probe (Intra-RSP) is designed to bridge the gap and provide real-time spectroscopic insights to monitor TBI and its evolution as well as identify patient-specific molecular targets for timely intervention. Raman spectroscopy being rapid, label-free and non-destructive, renders it an ideal portable diagnostics tool. In combination with our in-house developed software, using machine learning algorithms for multivariate analysis, the Intra-RSP is shown to accurately differentiate simulated TBI conditions in rat brains from the healthy controls, directly from the brain surface as well as through the rat's skull. Using clinically pre-established methods of cranial entry, the Intra-RSP can be inserted into a 2-piece optimised cranial bolt with integrated focussing and correctly identify a sample in real-life conditions with an accuracy >80 %. To further validate the Intra-RSP's efficiency as a TBI monitoring device, rat brains mildly damaged from inflicted spinal cord injury were found to be correctly classified with 94.5 % accuracy. Through optimization and rigorous in-vivo validation, the Intra-RSP prototype is envisioned to seamlessly integrate into existing standards of neurological care, serving as a minimally invasive, in-situ neuromonitoring tool. This transformative approach has the potential to revolutionize the landscape of neurological care by providing clinicians with unprecedented insights into the nature of brain injuries and fostering targeted, timely and effective therapeutic interventions.
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Lesiones Traumáticas del Encéfalo , Espectrometría Raman , Lesiones Traumáticas del Encéfalo/diagnóstico , Lesiones Traumáticas del Encéfalo/clasificación , Animales , Ratas , Espectrometría Raman/métodos , Ratas Sprague-Dawley , Masculino , Encéfalo/metabolismoRESUMEN
BACKGROUND: Traumatic brain injury (TBI) remains a major concern for global health. Recent studies have suggested the role of NOD-like receptor pyrin domain-containing protein 3 (NLRP3), an inflammatory marker, in the cerebrospinal fluid (CSF) and serum as potential indicators of TBI prognosis. The objective of the study was to characterize NLRP3 as a clinically applicable tool for predicting the outcomes of TBI patients. METHODS: A total of 270 patients with moderate to severe TBI were included in this retrospective analysis. Serum and CSF samples were collected at 1-, 3-, 7-, and 21-day post-injury to measure NLRP3 levels. The prognosis of patients was evaluated after 3 months using the Glasgow Outcome Scale (GOS). Patients were categorized into good prognosis (GOS score >3) and poor prognosis (GOS score ≤3) groups. The relationship between NLRP3 levels and prognosis was analyzed. RESULTS: Patients with poor prognosis had significantly elevated NLRP3 levels in their serum on days 1 and 3 post-injury compared with those with a good prognosis. The difference was more pronounced during these early days compared with days 7 and 21. However, NLRP3 levels in CSF consistently showed a large difference between the two groups throughout the observation period. Receiver operating characteristic analysis revealed that the level of NLRP3 in the CSF on day 3 post-injury had the highest predictive value for prognosis, with an area under the curve of 0.83, followed by the level of NLRP3 in the serum on day 3 post-injury. CONCLUSIONS: The levels of NLRP3, especially in the CSF on day 3 post-injury, can serve as a potential biomarker for predicting prognosis in moderate to severe TBI patients. Early measurement of NLRP3 levels can provide valuable insights into patient outcomes and guide therapeutic strategies.
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Lesiones Traumáticas del Encéfalo , Proteína con Dominio Pirina 3 de la Familia NLR , Humanos , Proteína con Dominio Pirina 3 de la Familia NLR/sangre , Proteína con Dominio Pirina 3 de la Familia NLR/líquido cefalorraquídeo , Lesiones Traumáticas del Encéfalo/líquido cefalorraquídeo , Lesiones Traumáticas del Encéfalo/sangre , Lesiones Traumáticas del Encéfalo/diagnóstico , Masculino , Femenino , Persona de Mediana Edad , Adulto , Pronóstico , Estudios Retrospectivos , Valor Predictivo de las Pruebas , Biomarcadores/sangre , Biomarcadores/líquido cefalorraquídeo , Escala de Consecuencias de Glasgow , Anciano , Adulto Joven , AdolescenteRESUMEN
Background: Currently, the treatment and care of patients with traumatic brain injury (TBI) are intractable health problems worldwide and greatly increase the medical burden in society. However, machine learning-based algorithms and the use of a large amount of data accumulated in the clinic in the past can predict the hospitalization time of patients with brain injury in advance, so as to design a reasonable arrangement of resources and effectively reduce the medical burden of society. Especially in China, where medical resources are so tight, this method has important application value. Objective: We aimed to develop a system based on a machine learning model for predicting the length of hospitalization of patients with TBI, which is available to patients, nurses, and physicians. Methods: We collected information on 1128 patients who received treatment at the Neurosurgery Center of the Second Affiliated Hospital of Anhui Medical University from May 2017 to May 2022, and we trained and tested the machine learning model using 5 cross-validations to avoid overfitting; 28 types of independent variables were used as input variables in the machine learning model, and the length of hospitalization was used as the output variables. Once the models were trained, we obtained the error and goodness of fit (R2) of each machine learning model from the 5 rounds of cross-validation and compared them to select the best predictive model to be encapsulated in the developed system. In addition, we externally tested the models using clinical data related to patients treated at the First Affiliated Hospital of Anhui Medical University from June 2021 to February 2022. Results: Six machine learning models were built, including support vector regression machine, convolutional neural network, back propagation neural network, random forest, logistic regression, and multilayer perceptron. Among them, the support vector regression has the smallest error of 10.22% on the test set, the highest goodness of fit of 90.4%, and all performances are the best among the 6 models. In addition, we used external datasets to verify the experimental results of these 6 models in order to avoid experimental chance, and the support vector regression machine eventually performed the best in the external datasets. Therefore, we chose to encapsulate the support vector regression machine into our system for predicting the length of stay of patients with traumatic brain trauma. Finally, we made the developed system available to patients, nurses, and physicians, and the satisfaction questionnaire showed that patients, nurses, and physicians agreed that the system was effective in providing clinical decisions to help patients, nurses, and physicians. Conclusions: This study shows that the support vector regression machine model developed using machine learning methods can accurately predict the length of hospitalization of patients with TBI, and the developed prediction system has strong clinical use.
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Algoritmos , Lesiones Traumáticas del Encéfalo , Aprendizaje Automático , Humanos , Lesiones Traumáticas del Encéfalo/terapia , Lesiones Traumáticas del Encéfalo/diagnóstico , Masculino , Adulto , Femenino , Persona de Mediana Edad , Hospitalización/estadística & datos numéricos , China , Tiempo de Internación/estadística & datos numéricos , AncianoRESUMEN
INTRODUCTION: Multimodal monitoring is the use of data from multiple physiological sensors combined in a way to provide individualized patient management. It is becoming commonplace in the civilian care of traumatic brain-injured patients. We hypothesized we could bring the technology to the battlefield using a noninvasive sensor suite and an artificial intelligence-based patient management guidance system. METHODS: Working with military medical personnel, we gathered requirements for a hand-held system that would adapt to the rapidly evolving field of neurocritical care. To select the optimal sensors, we developed a method to evaluate both the value of the sensor's measurement in managing brain injury and the burden to deploy that sensor in the battlefield. We called this the Value-Burden Analysis which resulted in a score weighted by the Role of Care. The Value was assessed using 7 criteria, 1 of which was the clinical value as assessed by a consensus of clinicians. The Burden was assessed using 16 factors such as size, weight, and ease of use. We evaluated and scored 17 sensors to test the assessment methodology. In addition, we developed a design for the guidance system, built a prototype, and tested the feasibility. RESULTS: The resulting architecture of the system was modular, requiring the development of an interoperable description of each component including sensors, guideline steps, medications, analytics, resources, and the context of care. A Knowledge Base was created to describe the interactions of the modules. A prototype test set-up demonstrated the feasibility of the system in that simulated physiological inputs would mimic the guidance provided by the current Clinical Practice Guidelines for Traumatic Brain Injury in Prolonged Care (CPG ID:63). The Value-Burden analysis yielded a ranking of sensors as well as sensor metadata useful in the Knowledge Base. CONCLUSION: We developed a design and tested the feasibility of a system that would allow the use of physiological biomarkers as a management tool in forward care. A key feature is the modular design that allows the system to adapt to changes in sensors, resources, and context as well as to updates in guidelines as they are developed. Continued work consists of further validation of the concept with simulated scenarios.