The predictive value of lymphocyte-to-monocyte ratio in the prognosis of acute coronary syndrome patients: a systematic review and meta-analysis

Src homology 2-B adapter protein 3 C784 T and Methylenetetrahydrofolate reductase C677 T Polymorphisms and Inflammation Markers in ST-segment Elevation Myocardial Infarction Patients

Neutrophil-lymphocyte (NLR), platelet-lymphocyte (PLR), eosinophil-lymphocyte (ELR), and monocyte-lymphocyte (MLR) ratios are systemic inflammatory markers related to myocardial infarction. The aim of this study is to investigate the association of Src homology 2-B adapter protein 3 (SH2B3) C784 T and methylenetetrahydrofolate reductase (MTHFR) C677 T polymorphisms (SNP) with systemic inflammatory markers and the severity of coronary artery disease (CAD) in 150 ST-elevation myocardial infarction (STEMI) patients. Single nucleotide polymorphisms were genotyped using the tetra-primer amplification refractory mutation system-polymerase chain reaction (T-ARMS-PCR) method. The inflammatory markers were calculated. An interventional cardiologist blinded to other data assessed the SYNTAX (SX) Score. Eosinophil and platelet counts were significantly higher in SH2B3 variants than in the wild type. Additionally, SH2B3 variants had significantly higher ELR than the wild type (.12 ± .19 vs .25 ± .34, p = .018). NLR, PLR, ELR, and MLR were considerably higher in MTHFR variants than in the wild type (p < .05). The SX score was significantly higher in both SH2B3 C784 T (21.24 ± 8.90 vs 15.29 ± 9.40, p = .00) and MTHFR C677 T (20.34 ± 10.21 vs 16.08 ± 8.39, p = .00) variants when compared with wild type. In conclusion, these polymorphisms are associated with several markers of systemic inflammation as well as the severity of CAD.

Platelet to albumin ratio: A risk factor related to prognosis in patients with non-ST-segment elevation acute coronary syndrome undergoing percutaneous coronary intervention

BACKGROUND

Atherosclerotic cardiovascular disease (ASCAD) is recognized as a chronic subclinical systemic inflammatory condition. The platelet-albumin ratio (PAR) has shown promise in prognosticating various inflammation-related disorders. Our study aimed to assess the connection between PAR and major adverse cardiovascular events (MACE) in percutaneous coronary intervention (PCI)-treated patients with non-ST-segment elevation acute coronary syndrome (NSTE-ACS).

METHODS

PAR, derived from platelet and albumin counts, categorized participants into four quartiles. The primary outcome was composite MACE, encompassing all-cause mortality, non-fatal myocardial infarction (MI), and ischemia-driven revascularization. Secondary outcomes comprised individual MACE components. Multivariate Cox regression evaluated PAR's independent impact on adverse events. The non-linear relationship between the PAR value and MACE was explored using a restricted cubic spline (RCS). Receiver operating characteristic (ROC) analysis was conducted and the area under the curve (AUC) was calculated. Subgroup analysis was used to determine the effect of PAR on MACE in different subgroups.

RESULTS

Enrolling 1391 NSTE-ACS patients, high PAR quartiles were correlated with elevated MACE rates (quartile 4 vs. quartile 1: 33.5% vs. 10.2%, p < 0.001). PAR was revealed to be independently related to an increased risk of MACE (quartile 4 vs. quartile 1: HR, 2.04 [95% CI, 1.34-3.08], p = 0.001). RCS indicated a positive PAR-MACE relationship. The AUC of PAR for the 3-year MACE was 0.659 (95% CI: 0.626-0.677, P<0.001). Subgroup analysis showed no significant interactions across subsets.

CONCLUSION

PAR independently predicted MACE risk in PCI-treated NSTE-ACS patients.

Naples Prognostic Score and Prediction of Left Ventricular Ejection Fraction in STEMI Patients

The Naples score is a new prognostic score developed according to inflammatory and nutritional status and frequently evaluated in cancer patients. The present study aimed to evaluate using the Naples prognostic score (NPS) to predict the development of decreased left ventricular ejection fraction (LVEF) after acute ST-segment elevation myocardial infarction (STEMI). The study has a multicenter and retrospective design and included 2280 patients with STEMI who underwent primary percutaneous coronary intervention (pPCI) between 2017 and 2022. All participants were divided into 2 groups according to their NPS. The relationship between these 2 groups and LVEF was evaluated. The low-Naples risk group (Group-1) included 799 patients, and the high-Naples risk group (Group-2) had 1481 patients. Hospital mortality, shock, and no-reflow rates were found to be higher in Group 2 compared with Group 1 (P < .001, P = .032, P = .004). The NPS was significantly inversely associated with discharge LVEF (B coefficient: -1.51, 95% CI-2.26; -.76, P = .001). NPS, a simple and easily calculated risk score, may help identify high-risk STEMI patients. To the best of our knowledge, the present study is the first to demonstrate the relationship between low LVEF and NPS in patients with STEMI.

The prognostic importance of the Naples prognostic score for in-hospital mortality in patients with ST-segment elevation myocardial infarction

BACKGROUND

The Naples prognostic score (NPS) is an effective inflammatory and nutritional scoring system widely applied as a prognostic factor in various cancers. However, the prognostic significance of NPS is unknown in ST-segment elevation myocardial infarction (STEMI). We aimed to analyze the prognostic value of the NPS in-hospital mortality in patients with STEMI.

METHODS

The study consisted of 3828 patients diagnosed with STEMI who underwent primer percutaneous coronary intervention. As the primary outcome, in-hospital mortality was defined as all-cause deaths during hospitalization. The included patients were categorized into three groups based on NPS (group 1:NPS = 0,1,2; group 2:NPS = 3; group 3:NPS = 4).

RESULTS

Increased NPS was associated with higher in-hospital mortality rates( P  < 0.001). In the multivariable logistic regression analysis, the relationship between NPS and in-hospital mortality continued after adjustment for age, male sex, diabetes, hypertension, Killip score, SBP, heart rate, left ventricular ejection fraction, myocardial infarction type and postprocedural no-reflow. A strong positive association was found between in-hospital mortality and NPS by multivariable logistic regression analysis [NPS 0-1-2 as a reference, OR = 1.73 (95% CI, 1.04-2.90) for NPS 3, OR = 2.83 (95% CI, 1.76-4.54) for NPS 4].

CONCLUSION

The present study demonstrates that the NPS could independently predict in-hospital mortality in STEMI. Prospective studies will be necessary to confirm the performance, clinical applicability and practicality of the NPS for in-hospital mortality in STEMI.

Impact of Naples Prognostic Score at Admission on In-Hospital and Follow-Up Outcomes Among Patients with ST-Segment Elevation Myocardial Infarction

The Naples prognostic score (NPS) consists of cholesterol level, albumin concentration, lymphocyte-to-monocyte and neutrophil-to-lymphocyte ratios and reflects systemic inflammation, malnutrition, and survival for various conditions. We investigated the relationship of NPS at admission with in-hospital and follow-up outcomes among ST-segment elevation myocardial infarction (STEMI) patients. This retrospective study included 1887 consecutive patients diagnosed with STEMI and who underwent primary percutaneous coronary intervention between March 2020 and May 2022. The study population was divided by NPS into 2; low (0-1-2) and high (3-4). In-hospital adverse events and all-cause mortality rates during follow-up were extracted from the registry. The Median follow-up time was 15 months. The overall mortality rate was 14.6%. The proportions of in-hospital events that included acute respiratory failure, acute kidney injury, malignant arrhythmia, and mortality were significantly higher in the high NPS group than in the low NPS group. Compared with the baseline model, in the full model of Cox regression analysis; NPS was an independent predictor of all-cause mortality (adjusted hazard ratio (aHR): 2.49, 95%CI, 1.75-3.50, P < .001), with a significant improvement in model performance (likelihood ratio χ2, P < .001) and better calibration. In conclusion, we found an association between NPS and in-hospital and follow-up outcomes in STEMI patients.

Impact of Naples Prognostic Score on midterm all-cause mortality in patients with decompensated heart failure

Aim: This work was designed to investigate the relationship between cardiac outcomes and Naples Prognostic Score (NPS) among heart failure (HF) patients. Materials & methods: This retrospective observational study enrolled 298 consecutive individuals hospitalized for New York Heart Association class 3-4 HF. The primary outcome was all-cause mortality. Secondary outcomes were rehospitalization and in-hospital death. Results: The high NPS group had a statistically greater rate of all-cause mortality (p < 0.001). In Cox regression analysis, integrating NPS considerably improved the performance of the full model over the baseline model (adjusted hazard ratio = 2.28; p = 0.004). Based on time-dependent receiver operating characteristic curve analysis, the NPS model outperformed the baseline and CONUT score models in discriminatory power in predicting the probability of survival. Conclusion: NPS was associated with short- and midterm mortality as well as rehospitalization.

Hematological parameters and early-onset coronary artery disease: a retrospective case-control study based on 3366 participants

Background

Thrombosis and inflammation are crucial elements in the pathogenesis of cardiovascular disease. Hematological parameters elucidate information involving the inflammatory and blood coagulation processes.

Objectives

The current study explored the association of hematological parameters with EOCAD to identify specific risk factors.

Design

A single-center retrospective case-control study was conducted with 1693 coronary artery disease patients and 1693 controls.

Methods

Hematological parameters were examined through an automated analyzer.

Results

The basophil percentage was significantly reduced in EOCAD (0.43 ± 0.26, p < 0.001) and MI (0.33 ± 0.24, p < 0.001) groups compared with controls (0.54 ± 0.28). The eosinophil percentage was also significantly lower in EOCAD (2.21 ± 1.71, p < 0.001) and MI (1.71 ± 2.44, p < 0.001) groups compared with controls (2.41 ± 1.75). The lymphocyte percentage in patients of EOCAD and MI and controls was 31.65 ± 7.93, 25.48 ± 9.43, and 34.82 ± 7.28, respectively. A significant difference was observed among the groups (p < 0.001). Except for the mean corpuscular hemoglobin (MCH), other red blood cell (RBC) parameters significantly differed between EOCAD patients and controls. The red blood cell distribution width (RDW), hematocrit (HCT), RBC count, mean corpuscular hemoglobin concentration (MCHC), mean corpuscular volume (MCV), and hemoglobin level were associated with EOCAD prevalence after adjusting for baseline differences. Platelet volume distribution width (PDW) also correlated with EOCAD prevalence (OR_adjust = 1.087, 95% CI: 1.044-1.131).

Conclusions

Hematological parameters are closely associated with EOCAD. Moreover, leukocyte parameters correlated with the presence and severity of the disease. In addition, erythrocyte parameters were associated with the disease presence but not with the disease severity. Among the platelet parameters, only PDW was related to the disease presence.

Lymphocyte-to-Monocyte Ratio Is Independently Associated with Progressive Infarction in Patients with Acute Ischemic Stroke

Methods

From April 2017 to December 2020, we retrospectively recruited 477 patients with acute ischemic stroke (within 48 hours after onset). Progressive infarction was defined as an increase of ≥1 point in motor power or ≥2 points on the total National Institutes of Health Stroke Scale (NIHSS) within 7 days after admission and extension of the original infarction were further confirmed by diffusion-weighted imaging. Demographic characteristics, clinical information, and neuroimaging characteristics were evaluated after admission. All blood draws and initial imaging were completed within 24 hours of admission.

Results

PI occurred in 147 (30.8%) patients. Univariate analysis comparing the two groups revealed that hypertension, initial NIHSS score, discharge NIHSS score, modified Rankin scale score at 90 days, monocyte level, creatinine level, fasting glucose level, LMR, monocyte-to-high-density lipoprotein ratio (MHR), and lesion location were significantly different (P < 0.05). Multivariate logistic regression analysis showed that the odds ratio of PI increased as the quartile of LMR increased, with the lowest quartile as the reference value. Subgroup analyses showed that a high LMR was an independent predictor of PI only in large artery atherosclerosis (LAA) patients. The receiver operating characteristic (ROC) curve was drawn to estimate the predictive value of LMR for PI. For all cases, the area under the curve was 0.583 (95% CI 0.526-0.641), and the best predictive cutoff value was 3.506, with a sensitivity of 53.1% and a specificity of 63.9%. In patients with LAA, the area under the curve was 0.585 (95% CI 0.505-0.665), and the best predictive cutoff value was 3.944, with a sensitivity of 48.7% and a specificity of 72.8%.

Conclusions

LMR was an independent predictor for progressive infarction in patients with acute ischemic stroke, especially in LAA cerebral infarction patients.

NLRP3 Inflammasome May Be a Biomarker for Risk Stratification in Patients with Acute Coronary Syndrome

Purpose

Acute coronary syndrome (ACS) has a high incidence and mortality rate worldwide, which has a considerable negative impact on the global economy. This study aimed to identify a group of ACS patients at a high risk of recurrent adverse cardiac events using the plasma NLRP3 inflammasome.

Patients and methods

ACS patients admitted to Liaocheng People's Hospital between June 2021 and March 2022 were enrolled in this study. Patients were divided into low (levels < 3.84 ng/mL) and high (levels ≥ 3.84 ng/mL) groups based on the median NLRP3 inflammasome levels. The patients were divided into three groups according to the Thrombolysis in Myocardial Infarction Risk Score for Secondary Prevention (TRS-2P): low (scores ≤ 2 points), intermediate (scores = 3 points), and high (score ≥ 4 points) risk. We investigated the relationship between NLRP3 inflammasome and laboratory indicators. Additionally, we examined whether the NLRP3 inflammasome was an independent predictor of high TRS-2P and explored the applicability of the plasma NLRP3 inflammasome for predicting high TRS-2P.

Results

Logistic regression analysis revealed that NLRP3 inflammasome was an independent predictor of high TRS-2P (odds ratio [OR]:2.013; 95% confidence interval [CI]: 1.174-3.452). The area under the receiver operating characteristic curve value of the NLRP3 inflammasome was 0.674 (95% CI: 0.611-0.737; P < 0.001).

Conclusion

NLRP3 inflammasome levels are an independent predictive factor for high TRS-2P levels, which indicates that the NLRP3 inflammasome may help predict the prognosis of ACS patients.

Prognosis of systemic inflammation at an early stage of cirrhosis using the monocyte-to-lymphocyte ratio during malnutrition risk screening: a prospective cohort study

OBJECTIVE

To determine whether the monocyte-to-lymphocyte ratio (MLR), as a systemic inflammation index, predicts malnutrition risk during the early stages of cirrhosis.

METHODS

We conducted a single-center prospective cohort study, enrolling patients from June 2016 to September 2020. The patients underwent malnutrition risk assessments upon admission. The patients were classified into five clinical stages according to portal hypertension. The malnutrition risk was scored using the Royal Free Hospital-Nutritional Prioritizing Tool (RFH-NPT) and validated by the Nutritional Risk Screening 2002 (NRS-2002) or Liver Disease Undernutrition Screening Tool (LDUST). Routine clinical laboratory measurements were performed to calculate the MLR, Child-Turcotte-Pugh (CTP) class, and model for end-stage liver disease (MELD) score. The patients were followed up for 2 years.

RESULTS

Among the 154 patients with cirrhosis, 60 had compensated cirrhosis and 94 had decompensated cirrhosis. The optimal cutoff value of the MLR, >0.4, was effective in predicting malnutrition related to death or liver transplantation. Those with a high malnutrition risk defined by the NRS-2002 or RFH-NPT had a higher MLR than those with a low malnutrition risk. For patients with class A CTP cirrhosis or a MELD score of <10, an MLR cutoff of <0.4 significantly distinguished more patients with a low malnutrition risk than those with a high malnutrition risk. Both the RFH-NPT score and MLR increased significantly across the decompensated cirrhosis substages. Interestingly, the MLR exhibited a positive correlation with the RFH-NPT score until varices appeared, but the correlation was the highest at the substage of a history of variceal bleeding (r = 0.714, P = 0.009). Multivariable analysis demonstrated that an MLR of >0.4 was an independent factor for malnutrition risk by screening with the RFH-NPT, and this was confirmed using the LDUST and NRS-2002.

CONCLUSION

Immune-related inflammatory dysfunction predicts malnutrition risk during the early stages of cirrhosis.

Development and Validation of a Risk Nomogram Model for Predicting Recurrence in Patients with Atrial Fibrillation After Radiofrequency Catheter Ablation

Purpose

This study aimed to develop and validate a risk nomogram model for predicting the risk of atrial fibrillation recurrence after radiofrequency catheter ablation.

Patients and Methods

A retrospective observational study was conducted using data from 485 patients with atrial fibrillation who underwent the first radiofrequency ablation in our hospital from January 2018 to June 2021. All patients were randomized into training cohort (70%; n=340) and validation cohort (30%; n=145). Univariate and multivariate logistic regression analyses were used to identify independent risk factors. The predictive nomogram model was established by using R software. The nomogram was developed and evaluated based on differentiation, calibration, and clinical efficacy by concordance statistic (C-statistic), calibration plots, and decision curve analysis (DCA), respectively.

Results

The nomogram was established by four variables including left atrial diameter (OR 1.057, 95% CI 1.010–1.107, P=0.018), left ventricular ejection fraction (OR 0.943, 95% CI 0.905–0.982, P=0.005), type of atrial fibrillation (OR 2.164, 95% CI: 1.262–3.714), and systemic inflammation score (OR 1.905, 95% CI 1.408–2.577). The C-statistic of the nomogram was 0.741 (95% CI: 0.689–0.794) in the training cohort and 0.750 (95% CI: 0.670–0.831) in the validation cohort. The calibration plots showed good agreement between the predictions and observations in the training and validation cohorts. Decision curve analysis and clinical impact curves indicated the clinical utility of the predictive nomogram.

Conclusion

The nomogram model has good discrimination and accuracy, which can screen high-risk groups intuitively and individually, and has a certain predictive value for atrial fibrillation recurrence in patients after radiofrequency ablation.

Predicting major adverse cardiovascular events in acute coronary syndrome: A scoping review of machine learning approaches

BACKGROUND

Acute coronary syndrome is the topmost cause of death worldwide; therefore, it is necessary to predict major adverse cardiovascular events and cardiovascular deaths in patients with acute coronary syndrome to make correct and timely clinical decisions.

OBJECTIVE

The current review aimed to highlight algorithms and important predictor variables through examining those studies which used machine learning algorithms for predicting major adverse cardiovascular events in patients with acute coronary syndrome.

METHODS

In order to predict major adverse cardiovascular events in patients with acute coronary syndrome, the preferred reporting items for scoping reviews guidelines were used. PubMed, Embase, Web of Science, Scopus, Springer, and IEEE Xplore databases were searched for articles published between 2005 and 2021. The findings of the studies are presented in the form of a narrative synthesis of evidence.

RESULTS

According to the results, 14 (63.64%) studies did not perform external validation and only used registry data. The algorithms used in this study comprised, inter alia, Regression Logistic, Random Forest, Boosting Ensemble, Non-Boosting Ensemble, Decision Trees, and Naive Bayes. Multiple studies (N=20) achieved a high Area under the ROC Curve between 0.8 to 0.99 in predicting mortality and major adverse cardiovascular events. The predictor variables used in these studies were divided into demographic, clinical, and therapeutic features. However, no study reported the integration of machine learning model into clinical practice.

CONCLUSION

Machine learning algorithms rendered acceptable results to predict major adverse cardiovascular events and mortality outcomes in patients with acute coronary syndrome. However, these approaches have never been integrated into clinical practice. Further research is required to develop feasible and effective machine learning prediction models to measure their potentially important implications for optimizing the quality of care in patients with acute coronary syndrome.

Monocyte-to-Lymphocyte Ratio as a Predictor of Worse Long-Term Survival after Off-Pump Surgical Revascularization-Initial Report

Background and objective: Coronary artery disease is one of the leading causes of deaths nowadays and the trends in diagnosis and revascularization are still in plateau despite well-known factors. Simple whole blood count parameters may be used to measure inflammatory reactions that are involved in processes of atherosclerosis progression. The aim of our study was to analyse the association between simply available hematologic indices and long-term mortality following off-pump coronary artery bypass grafting (OPCAB). Material and Methods: The study group comprised 129 consecutive patients (16 females and 113 males, mean age 66 ± 6 years) who underwent surgical revascularization with off-pump technique between January 2014 and September 2019. The mean follow-up was 4.7 +/−1.9 years. A receiver operating characteristics curve was applied to estimate demographical and perioperative parameters including MLR for mortality. Results: Cox regression analysis revealed chronic pulmonary obstructive disease (HR = 2.86, 95%CI 1.05–7.78), MLR (HR = 3.81, 95%CI 1.45–10.06) and right coronary artery blood flow (HR = 1.06, 95%CI 1.00–1.10) as significant factors predicting increased mortality risk. In the presented model, the MLR > 1.44 on 1st postoperative day was a significant predictor of late mortality after the OPCAB procedure (HR = 3.82, 95%CI 1.45–10.06). Conclusions: Pronounced inflammatory reaction after off-pump surgery measured by MLR > 1.44 can be regarded as a worse long-term prognostic factor.

Association of monocyte-lymphocyte ratio with in-hospital mortality in cardiac intensive care unit patients

BACKGROUND

Inflammatory cell plays a very important part in the occurrence and development of cardiovascular disease. As a combination of lymphocyte and monocyte, monocyte-lymphocyte ratio (MLR) was proved to be related to the severity and prognosis of cardiovascular diseases. Our objective was to explore the association between MLR and in-hospital mortality in cardiac intensive care unit (CICU) patients.

METHOD

MLR was obtained by dividing monocyte percentage by lymphocyte percentage. All patients were grouped by MLR quartiles. Primary outcome was in-hospital mortality. Binary logistic regression analysis was performed to determine the independent effect of MLR.

RESULT

5512 CICU patients were included. In-hospital mortality increased as MLR quartiles increased (Quartile 4 vs Quartile 1: 16.3 vs 7.8, P < 0.001). After adjusting for confounding variables, MLR was proved to be independently associated with increased risk of in-hospital mortality (Quartile 4 vs Quartile 1: OR, 95% CI: 1.87, 1.38-2.56, P < 0.001, P for trend < 0.001). Subgroup analysis revealed that patients with low Acute Physiology and Chronic Health Evaluation IV (APACHE IV) or with less comorbidities had higher risk of mortality for MLR. As MLR quartiles increased, length of CICU stay (Quartile 4 vs Quartile 1: 2.8, 1.7-5.4 vs 2.1, 1.2-3.7, P < 0.001) and hospital stay (Quartile 4 vs Quartile 1: 8.3, 4.8-11.1 vs 5.3, 3.1-9.3, P < 0.001) were prolonged.

CONCLUSION

MLR was independently correlated with in-hospital mortality in CICU patients.

Association of the lymphocyte-to-monocyte ratio, mean diameter of coronary arteries, and uric acid level with coronary slow flow in isolated coronary artery ectasia

Background

The pathophysiology of isolated coronary artery ectasia (CAE) with the coronary slow flow (CSF) phenomenon is still unclear. The purpose of this study was to investigate the risk factors for isolated CAE complicated with CSF.

Methods

A total of 126 patients with isolated CAE were selected retrospectively. The patients were grouped into the no CSF (NCSF) group (n = 55) and the CSF group (n = 71) according to the corrected thrombolysis in myocardial infarction (TIMI) frame count (CTFC). Data on demographics, laboratory measurements, left ventricular ejection fraction (LVEF), left ventricular end-diastolic diameter (LVEDd), CTFC and diameters of three coronary arteries were collected.

Results

The proportions of males (84.5% vs. 61.8%, p = 0.004) and patients with a smoking history (63.4% vs. 43.6%, p = 0.021) were higher in the CSF group than in the NCSF group. The neutrophil-to-lymphocyte ratio (NLR) (2.08(1.68–3.21) vs. 1.89 ± 0.58, p = 0.001), mean diameter of coronary arteries (mean D) (5.50 ± 0.85 vs. 5.18 ± 0.91, p < 0.001), and uric acid (URIC) level (370.78 ± 109.79 vs. 329.15 ± 79.71, p = 0.019) were significantly higher in the CSF group, while the lymphocyte-to-monocyte ratio (LMR) (4.81 ± 1.66 vs. 5.96 ± 1.75, p < 0.001) and albumin (ALB) level (44.13 ± 4.10 vs. 45.69 ± 4.11, p = 0.036) were lower. Multivariable logistic analysis showed that the LMR (odds ratio: 0.614, 95% CI: 0.464–0.814, p = 0.001), mean D (odds ratio: 2.643, 95% CI: 1.54–4.51, p < 0.001) and URIC level (odds ratio: 1.006, 95% CI: 1.001–1.012, p = 0.018) were independent predictors of CSF in CAE.

Conclusions

The LMR was a negative independent predictor of CSF in isolated CAE, while URIC level and mean D were positive independent predictors.

Diagnostic blood RNA profiles for human acute spinal cord injury

Diagnosis of spinal cord injury (SCI) severity at the ultra-acute stage is of great importance for emergency clinical care of patients as well as for potential enrollment into clinical trials. The lack of a diagnostic biomarker for SCI has played a major role in the poor results of clinical trials. We analyzed global gene expression in peripheral white blood cells during the acute injury phase and identified 197 genes whose expression changed after SCI compared with healthy and trauma controls and in direct relation to SCI severity. Unsupervised coexpression network analysis identified several gene modules that predicted injury severity (AIS grades) with an overall accuracy of 72.7% and included signatures of immune cell subtypes. Specifically, for complete SCIs (AIS A), ROC analysis showed impressive specificity and sensitivity (AUC: 0.865). Similar precision was also shown for AIS D SCIs (AUC: 0.938). Our findings indicate that global transcriptomic changes in peripheral blood cells have diagnostic and potentially prognostic value for SCI severity.