Development and validation of a sepsis diagnostic scoring model for neonates with suspected sepsis

The value of thromboelastography to neonatology

Hemostatic derangements are common in critically ill and premature neonates. Nevertheless, hemostasis assessment in neonates is still challenging. The hemostatic system undergoes age-related physiological changes during its maturation and exhibits quantitative and qualitative differences between infants and adults. Conventional coagulation tests are mainly responsive to procoagulant factors, regardless of the contribution of cellular elements, anticoagulants and fibrinolytic contributors and, therefore, their role in predicting bleeding in neonatal acquired coagulopathy is somewhat limited. Viscoelastic coagulation tests offer a promising alternative, enabling a bedside and real-time assessment of the entire hemostatic process in short turn-around times with a limited amount of blood. These tests allow a targeted hemostatic monitoring and a tailored management of blood products and anticoagulation. The routine use of VCTs in the NICU remains limited, especially for premature infants, due to the lack of established normative ranges. In this review we will provide an overview of the main evidence related to the clinical application of viscoelastic monitoring in the neonatal setting.

Hemostatic Profile and Serum Levels of Interferon Gamma-Induced Protein 10 (IP-10) in Neonates Born to Mothers with COVID-19 During the Peripartum Period

The COVID-19 pandemic has raised significant concerns regarding its potential impact on maternal and neonatal health. This study aimed to investigate the immunologic and hemostatic profiles of neonates exposed to SARS-CoV-2 during the peripartum period (0-14 days prior to delivery). This retrospective study included 28 neonates born to COVID-19-positive mothers during the peripartum period and a control group of 54 neonates born to mothers who never tested positive for SARS-CoV-2 during pregnancy. Arterial blood samples were collected from all neonates on the second day of life for the simultaneous assessment of full blood count, C-reactive protein (CRP), serum interleukin-6 (IL-6), and Interferon gamma-induced protein 10 (IP-10) levels, as well as Rotational Thromboelastometry (ROTEM) tests (EXTEM, INTEM, and NATEM). Neonates born to COVID-19-positive mothers and those born to COVID-19-negative mothers exhibited similar coagulation profiles based on ROTEM analysis. Multiple linear regression analysis revealed that peripartum COVID-19 infection was associated with higher IP-10 levels in neonates (coefficient: +16.8, 95% CI: +9.0 to +24.6, p < 0.0001). Our study findings suggest that the presence of immunologic disturbance in neonates is related to recent peripartum exposure to maternal SARS-CoV-2 infection, as evidenced by increased IP-10 levels in blood samples obtained from neonates born to SARS-CoV-2-positive mothers. However, peripartum exposure to maternal SARS-CoV-2 did not appear to disrupt the hemostatic profile of the exposed newborns based on ROTEM test results.

Development and Validation of a Nosocomial Infection Nomogram Model in the NICU: A Novel and Nurse-Led Way to Prediction in Preterm Infants

Purpose

Nosocomial infections (NI) are a leading cause of mortality in preterm infants in the Neonatal Intensive Care Unit (NICU). The key to reducing the risk of NI is early detection and treatment in time. Nurses are close observers and primary caregivers for neonates at the bedside of the NICU, who are best positioned to capture the risk signals of NI. This study aims to develop a nurse-led prediction model for NI of preterm infants in the NICU.

Patients and Methods

This study was designed as a retrospective study, preterm infants of the NICU at Renmin Hospital of Wuhan University from January 2020 to December 2023 were selected and divided into the NI group and non-NI group. Clinical data were collected and then analyzed by univariate analysis, least absolute shrinkage and selection operator (LASSO) regression analysis, and multivariate logistic regression analysis. The outcome constructed a nomogram model and its predictive efficacy was evaluated by the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA). Bootstrap method was used to repeat 1,000 times for internal validation.

Results

A total of 892 preterm infants were finally included and a nurse-led predictive model established, which included six variables: skin color changes, respiratory related changes, feeding deterioration, birth weight, number of arterial and venous blood draws, and days of nasogastric tube placement. The model's AUC was 0.953, indicating good discriminatory power. The calibration plot demonstrated good calibration and the Hosmer-Lemeshow test showed high consistency. DCA indicated that the nomogram had good clinical utility. Internal validation showed the AUC of 0.952.

Conclusion

This nomogram model, which is mainly based on nurses' observations, shows good predictive ability. It offered a more convenient option for neonatologists and nurses in the NICU.

Thromboelastometry-Based Profiling of Haemostatic Alterations in Neonatal Sepsis by Causative Pathogens

Background: Neonatal sepsis is a serious condition with high mortality, especially in premature and low-birth-weight neonates. This study aims to examine whether the haemostatic profile of neonates with sepsis defers depending on the type of bacteria (Gram-positive or Gram-negative), by using the method of Rotational Thromboelastometry (ROTEM). Methods: This single-centre prospective cohort study was conducted on 128 neonates with sepsis, including 95 cases caused by Gram-negative pathogens and 33 cases caused by Gram-positive bacteria. All participants were hospitalised in the Neonatal Intensive Care Unit (NICU). ROTEM parameters were compared between neonates with Gram-positive and Gram-negative infections. Results: The ROTEM parameters were found to be significantly different between neonates suffering from Gram-positive versus Gram-negative infections, with Gram-positive pathogens associated with an increased clotting potential compared to Gram-negative pathogens. This is reflected in the higher ROTEM values such as A10, α-angle, and MCF in the EXTEM and INTEM assays. Multivariant analysis showed that Gram-positive infections were linked to increased clot thickness at 10 min (coefficient: 8.9, CI: 2.8-15.0, p = 0.004), higher maximum clot stability (coefficient: 10.4, CI: 4.3-16.6, p = 0.001), and a bigger α-angle (coefficient: 8.0, CI: 2.7-13.2, p = 0.003). Similar findings were observed in the INTEM assay parameters. Conclusions: Neonatal sepsis caused by Gram-positive bacteria leads to a hypercoagulable haemostatic state, whereas neonates with sepsis caused by Gram-negative bacteria exhibit a more hypocoagulable profile and a higher incidence of haemorrhagic episodes. These findings provide valuable insights into the haemostatic disorders associated with sepsis, and may aid in developing an individualised approach for the treatment of those disorders, dependent on and adapted for the specific type of causative organism.

The Role of Rotational Thromboelastometry in Early Detection of the Hemostatic Derangements in Neonates with Systemic Candida Infection

BACKGROUND

Systemic Candida infection (SCI) is the third most common cause of late-onset sepsis in Neonatal Intensive Care Units (NICU). While platelet involvement in fungal infections has been extensively studied, evaluation of the hemostatic mechanism in Candida infections, especially in neonates, has not been widely investigated. The aim of the current study was to evaluate the hemostatic profile of neonates with SCI through rotational thromboelastometry (ROTEM), a laboratory method that assesses the viscoelastic properties of blood.

METHODS

This is a single-centered prospective cohort study including a group of neonates with SCI (n = 21); the control group consisted of healthy neonates (n = 24). Demographics, clinical parameters, and laboratory data were recorded at the disease onset. Neonatal scores for the assessment of disease severity (Modified NEOMOD, nSOFA, and NeoBAT) were also calculated. ROTEM parameters of neonates with SCI were compared to those of healthy neonates.

RESULTS

ROTEM parameters differed between neonates with SCI and healthy neonates, indicating a hypocoagulable profile of infected neonates. Specifically, neonates with SCI had significantly prolonged clotting time (CT) and clot formation time (CFT), as well as lower clot amplitude at 10 min (A10) and maximum clot firmness (MCF) when compared to healthy neonates (p values < 0.05), findings that remained consistent after adjusting for confounding factors such as gestational age, birth weight, and sex. In addition, a strong correlation was noted between ROTEM parameters and disease severity based on the modified NEOMOD, nSOFA, and NeoBAT scores.

CONCLUSIONS

ROTEM parameters revealed a hypocoagulable profile in neonates during the early stages of SCI, which is also associated with disease severity. The results of this study highlight the need for monitoring of hemostatic status of this vulnerable group of patients and indicate that ROTEM analysis may have a role in the early detection of the hemostatic derangements associated with SCI in neonates, in order to ensure timely diagnosis and targeted therapeutic intervention.

Neonatal Sepsis: A Comprehensive Review

Neonatal sepsis remains a significant cause of neonatal morbidity and mortality globally. At present, no clear consensus definition for sepsis in neonates exists, even though a positive blood culture is considered as the gold standard for definitive diagnosis. The accurate and timely diagnosis of sepsis in neonates presents significant difficulties, since "culture negative" or "suspected" sepsis varies widely worldwide. Antibiotic overuse and resistance are emerging problems, but on the other hand, under-recognition of sepsis and delayed antibiotic treatment could have serious or even fatal adverse outcomes in this vulnerable population. In the context of rapid recognition of sepsis and timely initiation of appropriate antibiotic therapy, various sepsis risk assessment tools have been developed, a variety of biomarkers are in clinical use or under research for future use, and new diagnostic techniques are under evaluation. In this review, we summarize the most recent data on neonatal sepsis, the utility of sepsis risk assessment tools for term and preterm infants with sepsis, and current diagnostic and preventive tools.

Diagnostic Accuracy of Clinical Sign Algorithms to Identify Sepsis in Young Infants Aged 0 to 59 Days: A Systematic Review and Meta-analysis

CONTEXT

Accurate identification of possible sepsis in young infants is needed to effectively manage and reduce sepsis-related morbidity and mortality.

OBJECTIVE

Synthesize evidence on the diagnostic accuracy of clinical sign algorithms to identify young infants (aged 0-59 days) with suspected sepsis.

DATA SOURCES

MEDLINE, Embase, CINAHL, Global Index Medicus, and Cochrane CENTRAL Registry of Trials.

STUDY SELECTION

Studies reporting diagnostic accuracy measures of algorithms including infant clinical signs to identify young infants with suspected sepsis.

DATA EXTRACTION

We used Cochrane methods for study screening, data extraction, risk of bias assessment, and determining certainty of evidence using Grading of Recommendations Assessment Development and Evaluation.

RESULTS

We included 19 studies (12 Integrated Management of Childhood Illness [IMCI] and 7 non-IMCI studies). The current World Health Organization (WHO) 7-sign IMCI algorithm had a sensitivity of 79% (95% CI 77%-82%) and specificity of 77% (95% CI 76%-78%) for identifying sick infants aged 0-59 days requiring hospitalization/antibiotics (1 study, N = 8889). Any IMCI algorithm had a pooled sensitivity of 84% (95% CI 75%-90%) and specificity of 80% (95% CI 64%-90%) for identifying suspected sepsis (11 studies, N = 15523). When restricting the reference standard to laboratory-supported sepsis, any IMCI algorithm had a pooled sensitivity of 86% (95% CI 82%-90%) and lower specificity of 61% (95% CI 49%-72%) (6 studies, N = 14278).

LIMITATIONS

Heterogeneity of algorithms and reference standards limited the evidence.

CONCLUSIONS

IMCI algorithms had acceptable sensitivity for identifying young infants with suspected sepsis. Specificity was lower using a reference standard of laboratory-supported sepsis diagnosis.

Enhancing Early Detection of Sepsis in Neonates through Multimodal Biosignal Integration: A Study of Pulse Oximetry, Near-Infrared Spectroscopy (NIRS), and Skin Temperature Monitoring

Sepsis continues to be challenging to diagnose due to its non-specific clinical signs and symptoms, emphasizing the importance of early detection. Our study aimed to enhance the accuracy of sepsis diagnosis by integrating multimodal monitoring technologies with conventional diagnostic methods. The research included a total of 121 newborns, with 39 cases of late-onset sepsis, 35 cases of early-onset sepsis, and 47 control subjects. Continuous monitoring of biosignals, including pulse oximetry (PO), near-infrared spectroscopy (NIRS), and skin temperature (ST), was conducted. An algorithm was then developed in Python to identify early signs of sepsis. The model demonstrated the capability to detect sepsis 6 to 48 h in advance with an accuracy rate of 87.67 ± 7.42%. Sensitivity and specificity were recorded at 76% and 90%, respectively, with NIRS and ST having the most significant impact on predictive accuracy. Despite the promising results, limitations such as sample size, data variability, and potential biases were noted. These findings highlight the critical role of non-invasive biosensing methods in conjunction with conventional biomarkers and cultures, offering a strong foundation for early sepsis detection and improved neonatal care. Further research should be conducted to validate these results across different clinical settings.

Bleeding Scoring Systems in Neonates: A Systematic Review

We conducted a systematic review aiming to summarize the data on the current hemorrhage prediction models and evaluate their potential for generalized application in the neonatal population. The electronic databases PubMed and Scopus were searched, up to September 20, 2023, for studies that focused on development and/or validation of a prediction model for bleeding risk in neonates, and described the process of model building. Nineteen studies fulfilled the inclusion criteria for the present review. Eighteen bleeding risk prediction models in the neonatal population were identified, four of which were internally validated, one temporally and one externally validated. The existing prediction models for neonatal hemorrhage are mostly based on clinical variables and do not take into account the clinical course and hemostatic profile of the neonates. Most studies aimed at predicting the risk of intraventricular hemorrhage (IVH) reflecting the fact that IVH is the most frequent and serious bleeding complication in preterm neonates. A justification for the study sample size for developing the prediction model was given only by one study. Prediction and stratification of risk of hemorrhage in neonates is yet to be optimized. To this end, qualitative standards for model development need to be further improved. The assessment of the risk of bleeding incorporating platelet count, coagulation parameters, and a set of relevant clinical variables is crucial. Large, rigorous, collaborative cohort studies are warranted to develop a robust prediction model to inform the need for transfusion, which is a fundamental step towards personalized transfusion therapy in neonates.

Assessment of hemostatic profile in neonates with necrotizing enterocolitis using Rotational Thromboelastometry (ROTEM)

BACKGROUND

This study aimed to explore the hemostatic profile of neonates with necrotizing enterocolitis (NEC) using Rotational Thromboelastometry (ROTEM) and to investigate if ROTEM parameters have the capacity to play a role in the differentiation of NEC from sepsis at the disease onset.

METHODS

This observational study included 62 neonates (mean gestational age 31.6 weeks and mean birth weight 1620g) hospitalized in a neonatal intensive care unit. The neonates were categorized in three groups: neonates with NEC (Bell stage II and above), neonates with sepsis and healthy neonates and they were matched 1:1:1 with regards to gestational age, delivery mode, and sex. Clinical, laboratory data as well as measurements of ROTEM parameters at disease onset were recorded.

RESULTS

ROTEM parameters differed between neonates with NEC and neonates with sepsis, indicating that NEC results in accelerated clot formation and higher clot strength compared to sepsis. The EXTEM CFT and A10 parameters demonstrated the highest diagnostic performance for NEC in terms of discrimination between NEC and sepsis (AUC, 0.997; 95% CI: 0.991-1.000 and 0.973; 95% CI: 0.932-1.000, respectively).

CONCLUSIONS

Neonates with NEC manifested accelerated clot formation and higher clot strength compared to septic and healthy neonates, as these were expressed by ROTEM parameters.

IMPACT

This work reports data on the hemostatic profile of neonates with necrotizing enterocolitis (NEC) using Rotational Thromboelastometry (ROTEM) and the capacity of ROTEM parameters in differentiating of NEC from sepsis at the disease onset. Neonates with NEC present acceleration of coagulation and exhibit a hypercoagulable profile, as this is expressed by ROTEM parameters, in comparison to septic and healthy neonates. ROTEM parameters demonstrated a good diagnostic capacity in differentiating NEC from sepsis at the disease onset.

Contemporary tools for evaluation of hemostasis in neonates. Where are we and where are we headed?

The assessment of hemostatic disorders in neonates is crucial, but remains challenging for clinicians. Although the concept of developmental hemostasis is widely accepted among hemostasis specialists globally, it is probably under-recognized by clinicians and laboratory practitioners. In parallel with age-dependent hemostatic status maturation, comprehension of the differences between normal values is crucial for the accurate diagnosis of potential hemorrhagic and thrombotic disorders of the vulnerable neonatal population. This review outlines the basics of developmental hemostasis and the features of the available coagulation testing methods, with a focus on novel tools for evaluating the neonatal hemostatic profile. Common errors, issues, and pitfalls during the assessment of neonatal hemostasis are discussed, along with their impact on patient management. Current knowledge gaps and research areas are addressed. Further studying to improve our understanding of developmental hemostasis and its reflection on everyday clinical practice is warranted.

Assessment of Hemostatic Profile in Neonates with Intrauterine Growth Restriction: A Systematic Review of Literature

Intrauterine growth restriction (IUGR) affects nearly 10 to 15% of pregnancies and is responsible for many short- and long-term adverse consequences, including hemostatic derangement. Both thrombotic and hemorrhagic events are described in the perinatal period in these neonates. The aim of this study was to systematically review the literature on the laboratory studies used to evaluate the hemostatic system of the IUGR small for gestational age neonate. We reviewed the current literature via PubMed and Scopus until September 2022. Following our inclusion/exclusion criteria, we finally included 60 studies in our review. Thrombocytopenia, characterized as hyporegenerative and a kinetic upshot of reduced platelet production due to in utero chronic hypoxia, was the main finding of most studies focusing on growth-restricted neonates, in most cases is mild and usually resolves spontaneously with the first 2 weeks of life. In regard to coagulation, growth-restricted newborns present with prolonged standard coagulation tests. Data regarding coagulation factors, fibrinolytic system, and anticoagulant proteins are scarce and conflicting, mainly due to confounding factors. As thromboelastography/rotational thromboelastometry (TEG/ROTEM) provides a more precise evaluation of the in vivo coagulation process compared with standard coagulation tests, its use in transfusion guidance is fundamental. Only one study regarding TEG/ROTEM was retrieved from this population, where no difference in ROTEM parameters compared with appropriate for gestational age neonates was found. Despite the laboratory aberrations, no correlation could be achieved with clinical manifestations of bleeding or thrombosis in the studies included. More studies are needed to assess hemostasis in IUGR neonates and guide targeted therapeutic interventions.

Thromboelastometry and prediction of in-hospital mortality in neonates with sepsis

INTRODUCTION

This study aimed at evaluating the role of rotational thromboelastometry (ROTEM) assays in the prediction of in-hospital mortality of neonates with sepsis.

METHODS

Over a 6-year period, 129 neonates with confirmed sepsis, hospitalized in our neonatal intensive care unit (NICU) were included in the study. Demographics, clinical, and laboratory data were recorded at the sepsis onset and ROTEM assays were performed. Modified neonatal multiple organ dysfunction (NEOMOD) and neonatal sequential organ failure assessment (nSOFA) were calculated simultaneously. Mortality during in-hospital stay was the main outcome measure.

RESULTS

In-hospital mortality was associated with patient intense hypocoagulability expressed by lower ROTEM MCF in the INTEM assay. The INTEM MCF demonstrated the best prognostic performance for NICU mortality in septic neonates among the other ROTEM parameters but without statistical significance (area under the curve [AUC] = 0.731; 95% confidence interval [CI]: 0.593-0.869).

CONCLUSION

Our results indicate that ROTEM INTEM MCF parameter has good predictive capacity for in-hospital mortality of septic neonates, similar to that of modified NEOMOD score, nSOFA score, and platelet count, highlighting the integral role of coagulation in sepsis pathophysiology. Hence, ROTEM could serve as a valuable monitoring tool to identify neonates at risk.

Fibrinogen contribution to clot strength in patients with sepsis and hematologic malignancies and thrombocytopenia-a prospective, single-center, analytical, cross-sectional study

Background

Patients with hematological malignancies (HM) frequently present thrombocytopenia and higher risk of bleeding. Although transfusion is associated with higher risk of adverse events and poor outcomes, prophylactic transfusion of platelets is a common practice to prevent hemorrhagic complications. Thromboelastometry has been considered a better predictor for bleeding than isolated platelet counts in different settings. In early stages of sepsis, hypercoagulability may occur due to higher fibrinogen levels.

Objectives

To evaluate the behavior of coagulation in patients with HM who develop sepsis and to verify whether a higher concentration of fibrinogen is associated with a proportional increase in maximum clot firmness (MCF) even in the presence of severe thrombocytopenia.

Methods

We performed a unicentric analytical cross-sectional study with 60 adult patients with HM and severe thrombocytopenia, of whom 30 had sepsis (sepsis group) and 30 had no infections (control group). Coagulation conventional tests and specific coagulation tests, including thromboelastometry, were performed. The main outcome evaluated was MCF.

Results

Higher levels of fibrinogen and MCF were found in sepsis group. Both fibrinogen and platelets contributed to MCF. The relative contribution of fibrin was significantly higher (60.5 ± 12.8% vs 43.6 ± 9.7%; P < .001) and that of platelets was significantly lower (39.5 ± 12.8% vs 56.4 ± 9.7%; P < .001) in the sepsis group compared with the control group.

Conclusion

Patients with sepsis and HM presented higher concentrations of fibrinogen than uninfected patients, resulting in greater MCF amplitudes even in the presence of thrombocytopenia.

A predictive model for the identification of the risk of sepsis in patients with Gram-positive bacteria in the intensive care unit

Background

Gram-positive bacterial infections are very common in the intensive care unit (ICU) and may lead to sepsis. However, there are no models to predict the risk of sepsis in persons with Gram-positive bacterial infections. Therefore, the purpose of this study was to create and validate a nomogram for predicting the risk of sepsis in patients with common gram-positive bacterial infections.

Methods

Patients infected with three common Gram-positive bacteria who were admitted to the Multiparameter Intelligent Monitoring in Intensive Care IV (MIMIC IV) database were included in this retrospective cohort study. A Cox regression model was used to develop a nomogram for predicting 3-day, 1-week, 2-week, and 1-month sepsis probability. The performance of the nomogram was analyzed using receiver operating characteristic (ROC) curves, calibration curves, and decision curves.

Results

In total, 19,961 eligible patients were enrolled from MIMIC IV datasets. All participants were allocated to training and validation cohorts at random in a 7:3 ratio. The use of more than 3 types of antibiotics, dementia, ethnicity, aspartate aminotransferase (AST), neutrophils, the use of antifungal drug, ventilation and need for vasopressors were all discovered to be highly correlated with enhanced probability of sepsis in patients with Gram-positive bacteria. A prediction nomogram was constructed using these 8 predictors. The area under the curve (AUC) for predicting 3-day, 1-week, 2-week, and 1-month sepsis risk in the training cohort was 0.857, 0.774, 0.740, and 0.728, respectively, and that in the validation cohort was 0.855, 0.781, 0.742, and 0.742, respectively. The predictive power of our model is better than the SOFA score. The model had good predictive performance in all three classes of Gram-positive bacteria. Based on the calibration and clinical decision curves, the nomogram correctly predicted sepsis in patients with Gram-positive bacteria.

Conclusions

We were able to build a nomogram to predict the probability of sepsis in patients with Gram-positive bacteria, particularly those infected with Streptococcus spp. and Staphylococcus spp. This model performs effectively, and it might be used clinically to manage patients with Gram-positive bacteria.

Machine learning applications on neonatal sepsis treatment: a scoping review

INTRODUCTION

Neonatal sepsis is a major cause of health loss and mortality worldwide. Without proper treatment, neonatal sepsis can quickly develop into multisystem organ failure. However, the signs of neonatal sepsis are non-specific, and treatment is labour-intensive and expensive. Moreover, antimicrobial resistance is a significant threat globally, and it has been reported that over 70% of neonatal bloodstream infections are resistant to first-line antibiotic treatment. Machine learning is a potential tool to aid clinicians in diagnosing infections and in determining the most appropriate empiric antibiotic treatment, as has been demonstrated for adult populations. This review aimed to present the application of machine learning on neonatal sepsis treatment.

METHODS

PubMed, Embase, and Scopus were searched for studies published in English focusing on neonatal sepsis, antibiotics, and machine learning.

RESULTS

There were 18 studies included in this scoping review. Three studies focused on using machine learning in antibiotic treatment for bloodstream infections, one focused on predicting in-hospital mortality associated with neonatal sepsis, and the remaining studies focused on developing machine learning prediction models to diagnose possible sepsis cases. Gestational age, C-reactive protein levels, and white blood cell count were important predictors to diagnose neonatal sepsis. Age, weight, and days from hospital admission to blood sample taken were important to predict antibiotic-resistant infections. The best-performing machine learning models were random forest and neural networks.

CONCLUSION

Despite the threat antimicrobial resistance poses, there was a lack of studies focusing on the use of machine learning for aiding empirical antibiotic treatment for neonatal sepsis.

Sepsis-Induced Coagulopathy: An Update on Pathophysiology, Biomarkers, and Current Guidelines

Significant cross talk occurs between inflammation and coagulation. Thus, coagulopathy is common in sepsis, potentially aggravating the prognosis. Initially, septic patients tend to exhibit a prothrombotic state through extrinsic pathway activation, cytokine-induced coagulation amplification, anticoagulant pathways suppression, and fibrinolysis impairment. In late sepsis stages, with the establishment of disseminated intravascular coagulation (DIC), hypocoagulability ensues. Traditional laboratory findings of sepsis, including thrombocytopenia, increased prothrombin time (PT) and fibrin degradation products (FDPs), and decreased fibrinogen, only present late in the course of sepsis. A recently introduced definition of sepsis-induced coagulopathy (SIC) aims to identify patients at an earlier stage when changes to coagulation status are still reversible. Nonconventional assays, such as the measurement of anticoagulant proteins and nuclear material levels, and viscoelastic studies, have shown promising sensitivity and specificity in detecting patients at risk for DIC, allowing for timely therapeutic interventions. This review outlines current insights into the pathophysiological mechanisms and diagnostic options of SIC.