Machine learning-based prediction of clinical outcomes after traumatic brain injury: Hidden information of early physiological time series.

AIMS: To assess the predictive value of early-stage physiological time-series (PTS) data and non-interrogative electronic health record (EHR) signals, collected within 24 h of ICU admission, for traumatic brain injury (TBI) patient outcomes. METHODS: Using data from TBI patients in the multi-center eICU database, we focused on in-hospital mortality, neurological status based on the Glasgow Coma Score (mGCS) motor subscore at discharge, and prolonged ICU stay (PLOS). Three machine learning (ML) models were developed, utilizing EHR features, PTS signals collected 24 h after ICU admission, and their combination. External validation was performed using the MIMIC III dataset, and interpretability was enhanced using the Shapley Additive Explanations (SHAP) algorithm. RESULTS: The analysis included 1085 TBI patients. Compared to individual models and existing scoring systems, the combination of EHR and PTS features demonstrated comparable or even superior performance in predicting in-hospital mortality (AUROC = 0.878), neurological outcomes (AUROC = 0.877), and PLOS (AUROC = 0.835). The model's performance was validated in the MIMIC III dataset, and SHAP algorithms identified six key intervention points for EHR features related to prognostic outcomes. Moreover, the EHR results (All AUROC >0.8) were translated into online tools for clinical use. CONCLUSION: Our study highlights the importance of early-stage PTS signals in predicting TBI patient outcomes. The integration of interpretable algorithms and simplified prediction tools can support treatment decision-making, contributing to the development of accurate prediction models and timely clinical intervention.

Explainable machine learning for predicting neurological outcome in hemorrhagic and ischemic stroke patients in critical care.

Aim: The objective of this study is to develop accurate machine learning (ML) models for predicting the neurological status at hospital discharge of critically ill patients with hemorrhagic and ischemic stroke and identify the risk factors associated with the neurological outcome of stroke, thereby providing healthcare professionals with enhanced clinical decision-making guidance. Materials and methods: Data of stroke patients were extracted from the eICU Collaborative Research Database (eICU-CRD) for training and testing sets and the Medical Information Mart for Intensive Care IV (MIMIC IV) database for external validation. Four machine learning models, namely gradient boosting classifier (GBC), logistic regression (LR), multi-layer perceptron (MLP), and random forest (RF), were used for prediction of neurological outcome. Furthermore, shapley additive explanations (SHAP) algorithm was applied to explain models visually. Results: A total of 1,216 hemorrhagic stroke patients and 954 ischemic stroke patients from eICU-CRD and 921 hemorrhagic stroke patients 902 ischemic stroke patients from MIMIC IV were included in this study. In the hemorrhagic stroke cohort, the LR model achieved the highest area under curve (AUC) of 0.887 in the test cohort, while in the ischemic stroke cohort, the RF model demonstrated the best performance with an AUC of 0.867 in the test cohort. Further analysis of risk factors was conducted using SHAP analysis and the results of this study were converted into an online prediction tool. Conclusion: ML models are reliable tools for predicting hemorrhagic and ischemic stroke neurological outcome and have the potential to improve critical care of stroke patients. The summarized risk factors obtained from SHAP enable a more nuanced understanding of the reasoning behind prediction outcomes and the optimization of the treatment strategy.

Macrophage ß2-AR activation amplifies inflammation in wound healing by upregulating Trem1 via the cAMP/PKA/CREB pathway.

BACKGROUND: Inflammation is an important part of the wound healing process. The stress hormone epinephrine has been demonstrated to modulate the inflammatory response via its interaction with ß2-adrenergic receptor (ß2-AR). However, the precise molecular mechanism through which ß2-AR exerts its influence on inflammation during the wound healing process remains an unresolved question. METHODS: Transcriptome datasets of wound and macrophages from the GEO database were reanalyzed using bioinformatics. The role of ß2-AR in wound healing was explored by a mouse hind paw plantar wound model, and histological analyses were performed to assess wound healing. In vivo and in vitro assays were performed to elucidate the role of ß2-AR on the inflammatory response. Triggering receptor expressed on myeloid cells 1 (Trem1) was knocked down with siRNA on RAW cells and western blot and qPCR assays were performed. RESULTS: Trem1 was upregulated within 24 h of wounding, and macrophage ß2-AR activation also upregulated Trem1. In vivo experiments demonstrated that ß2-AR agonists impaired wound healing, accompanied by upregulation of Trem1 and activation of cAMP/PKA/CREB pathway, as well as by a high level of pro-inflammatory cytokine production. In vitro experiments showed that macrophage ß2-AR activation amplified LPS-induced inflammation, and knockdown of Trem1 reversed this effect. Using activator and inhibitor of cAMP, macrophage ß2-AR activation was confirmed to upregulate Trem1 via the cAMP/PKA/CREB pathway. CONCLUSION: Our study found that ß2-AR agonists increase Trem1 expression in wounds, accompanied by amplification of the inflammatory response, impairing wound healing. ß2-AR activation in RAW cells induces Trem1 upregulation via the cAMP/PKA/CREB pathway and amplifies LPS-induced inflammatory responses.

Machine Learning-Based Screening of Risk Factors and Prediction of Deep Vein Thrombosis and Pulmonary Embolism After Hip Arthroplasty.

Prophylactic anticoagulation is a standard strategy for patients undergoing total hip arthroplasty (THA) to prevent deep venous thromboembolism (DVT) and pulmonary embolism (PE). Nevertheless, some patients still experience these complications during their hospital stay. Current risk assessment methods like the Caprini and Geneva scores are not specifically designed for THA and may not accurately predict DVT or PE postoperatively. This study used machine learning techniques to establish models for early diagnosis of DVT and PE in patients undergoing THA. Data were collected from 1481 patients who received perioperative prophylactic anticoagulation. Model establishment and parameter tuning were performed using a training set and evaluated using a test set. Among the models, extreme gradient boosting (XGBoost) performed the best, with an area under the receiver operating characteristic curve (AUC) of 0.982, sensitivity of 0.913, and specificity of 0.998. The main features used in the XGBoost model were direct and indirect bilirubin, partial activation prothrombin time, prealbumin, creatinine, D-dimer, and C-reactive protein. Shapley Additive Explanations analysis was conducted to further analyze these features. This study presents a model for early diagnosis DVT or PE after THA and demonstrates bilirubin could be a potential predictor in the assessment of DVT or PE. Compared to traditional risk assessment, XGBoost has a high sensitivity and specificity to predict DVT and PE in the clinical setting. Furthermore, the results of this study were converted into a web calculator that can be used in clinical practice.

Improvement of sleep quality in isolated metastatic patients with spinal cord compression after surgery.

BACKGROUND: This study aimed to assess changes in quality of sleep (QoS) in isolated metastatic patients with spinal cord compression following two different surgical treatments and identify potential contributing factors associated with QoS improvement. METHODS: We reviewed 49 patients with isolated spinal metastasis at our spinal tumor center between December 2017 and May 2021. Total en bloc spondylectomy (TES) and palliative surgery with postoperative stereotactic radiosurgery (PSRS) were performed on 26 and 23 patients, respectively. We employed univariate and multivariate analyses to identify the potential prognostic factors affecting QoS. RESULTS: The total Pittsburgh Sleep Quality Index (PSQI) score improved significantly 6 months after surgery. Univariate analysis indicated that age, pain worsening at night, decrease in visual analog scale (VAS), increase in Eastern Cooperative Oncology Group performance score (ECOG-PS), artificial implant in focus, and decrease in epidural spinal cord compression (ESCC) scale values were potential contributing factors for QoS. Multivariate analysis indicated that the ESCC scale score decreased as an independent prognostic factor. CONCLUSIONS: Patients with spinal cord compression caused by the metastatic disease had significantly improved QoS after TES and PSRS treatment. Moreover, a decrease in ESCC scale value of > 1 was identified as a favorable contributing factor associated with PSQI improvement. In addition, TES and PSRS can prevent recurrence by achieving efficient local tumor control to improve indirect sleep. Accordingly, timely and effective surgical decompression and recurrence control are critical for improving sleep quality.

Prognosis and pain dissection of novel signatures in kidney renal clear cell carcinoma based on fatty acid metabolism-related genes.

Renal cell carcinoma (RCC) is a malignant tumor that is characterized by the accumulation of intracellular lipid droplets. The prognostic value of fatty acid metabolism-related genes (FMGs) in RCC remains unclear. Alongside this insight, we collected data from three RCC cohorts, namely, The Cancer Genome Atlas (TCGA), E-MTAB-1980, and GSE22541 cohorts, and identified a total of 309 FMGs that could be associated with RCC prognosis. First, we determined the copy number variation and expression levels of these FMGs, and identified 52 overall survival (OS)-related FMGs of the TCGA-KIRC and the E-MTAB-1980 cohort data. Next, 10 of these genes-FASN, ACOT9, MID1IP1, CYP2C9, ABCD1, CPT2, CRAT, TP53INP2, FAAH2, and PTPRG-were identified as pivotal OS-related FMGs based on least absolute shrinkage and selection operator and Cox regression analyses. The expression of some of these genes was confirmed in patients with RCC by immunohistochemical analyses. Kaplan-Meier analysis showed that the identified FMGs were effective in predicting the prognosis of RCC. Moreover, an optimal nomogram was constructed based on FMG-based risk scores and clinical factors, and its robustness was verified by time-dependent receiver operating characteristic analysis, calibration curve analysis, and decision curve analysis. We have also described the biological processes and the tumor immune microenvironment based on FMG-based risk score classification. Given the close association between fatty acid metabolism and cancer-related pain, our 10-FMG signature may also serve as a potential therapeutic target with dual effects on ccRCC prognosis and cancer pain and, therefore, warrants further investigation.

Huc-MSCs-derived exosomes attenuate inflammatory pain by regulating microglia pyroptosis and autophagy via the miR-146a-5p/TRAF6 axis.

BACKGROUND: Chronic inflammatory pain significantly reduces the quality of life and lacks effective interventions. In recent years, human umbilical cord mesenchymal stem cells (huc-MSCs)-derived exosomes have been used to relieve neuropathic pain and other inflammatory diseases as a promising cell-free therapeutic strategy. However, the therapeutic value of huc-MSCs-derived exosomes in complete Freund's adjuvant (CFA)-induced inflammatory pain remains to be confirmed. In this study, we investigated the therapeutic effect and related mechanisms of huc-MSCs-derived exosomes in a chronic inflammatory pain model. METHODS: C57BL/6J male mice were used to establish a CFA-induced inflammatory pain model, and huc-MSCs-derived exosomes were intrathecally injected for 4 consecutive days. BV2 microglia cells were stimulated with lipopolysaccharide (LPS) plus adenosine triphosphate (ATP) to investigate the effect of huc-MSCs-derived exosomes on pyroptosis and autophagy. Bioinformatic analysis and rescue experiments were used to demonstrate the role of miR-146a-5p/ TRAF6 in regulating pyroptosis and autophagy. Western blotting, RT-qPCR, small interfering RNA and Yo-Pro-1 dye staining were performed to investigate the related mechanisms. RESULTS: Huc-MSCs-derived exosomes alleviated mechanical allodynia and thermal hyperalgesia in CFA-induced inflammatory pain. Furthermore, huc-MSCs-derived exosomes attenuated neuroinflammation by increasing the expression of autophagy-related proteins (LC3-II and beclin1) and inhibiting the activation of NLRP3 inflammasomes in the spinal cord dorsal horn. In vitro, NLRP3 inflammasome components (NLRP3, caspase1-p20, ASC) and gasdermin D (GSDMD-F, GSDMD-N) were inhibited in BV2 cells pretreated with huc-MSCs-derived exosomes. Western blot and Yo-Pro-1 dye staining demonstrated that 3-MA, an autophagy inhibitor, weakened the protective effect of huc-MSCs-derived exosomes on BV2 cell pyroptosis. Importantly, huc-MSCs-derived exosomes transfected with miR-146a-5p mimic promoted autophagy and inhibited BV2 cell pyroptosis. TRAF6, as a target gene of miR-146a-5p, was knocked down via small-interfering RNA, which increased pyroptosis and inhibited autophagy. CONCLUSION: Huc-MSCs-derived exosomes attenuated inflammatory pain via miR-146a-5p/TRAF6, which increased the level of autophagy and inhibited pyroptosis.

Glycometabolism Reprogramming of Glial Cells in Central Nervous System: Novel Target for Neuropathic Pain.

Neuropathic pain is characterized by hyperalgesia and allodynia. Inflammatory response is conducive to tissue recovery upon nerve injury, but persistent and exaggerated inflammation is detrimental and participates in neuropathic pain. Synaptic transmission in the nociceptive pathway, and particularly the balance between facilitation and inhibition, could be affected by inflammation, which in turn is regulated by glial cells. Importantly, glycometabolism exerts a vital role in the inflammatory process. Glycometabolism reprogramming of inflammatory cells in neuropathic pain is characterized by impaired oxidative phosphorylation in mitochondria and enhanced glycolysis. These changes induce phenotypic transition of inflammatory cells to promote neural inflammation and oxidative stress in peripheral and central nervous system. Accumulation of lactate in synaptic microenvironment also contributes to synaptic remodeling and central sensitization. Previous studies mainly focused on the glycometabolism reprogramming in peripheral inflammatory cells such as macrophage or lymphocyte, little attention was paid to the regulation effects of glycometabolism reprogramming on the inflammatory responses in glial cells. This review summarizes the evidences for glycometabolism reprogramming in peripheral inflammatory cells, and presents a small quantity of present studies on glycometabolism in glial cells, expecting to promote the exploration in glycometabolism in glial cells of neuropathic pain.

The synergistic effects of opioid and neuropeptide B/W in rat acute inflammatory and neuropathic pain models.

The use of morphine is controversial due to the incidence of rewarding behavior, respiratory depression, and tolerance, leading to increased drug dose requirements, advancing to morphine addiction. To overcome these barriers, strategies have been taken to combine morphine with other analgesics. Neuropeptide B23 and neuropeptide W23 (NPB23 and NPW23) are commonly used to relieve inflammatory pain and neuropathic pain. As NPB23 and NPW23 system shares similar anatomical basis with opioid system at least in the spinal cord we hypothesized that NPB23 or NPW23 and morphine may synergistically relieve inflammatory pain and neuropathic pain. To test this hypothesis, we demonstrated that µ opioid receptor and NPBW1 receptor (receptor of NPB23 and NPW23) are colocalized in the superficial dorsal horn of the spinal cord. Secondly, co-administration of morphine witheitherNPB23 or NPW23 synergistically attenuated inflammatory and neuropathic pain. Furthermore, either NPB23 or NPW23 significantly reduced morphine-induced conditioned place preference (CPP) and constipation. We also found that phosphorylation of extracellular-regulated protein kinase (ERK1/2) following morphine was profoundly potentiated by the application of NPB23 or NPW23. Hence, combination of morphine with either NPB23 or NPW23 reduced dose of morphine required for pain relief in inflammatory and neuropathic pain, while effectively prevented some side-effects of morphine.