Early Detection Of Sepsis Research Articles

MicroRNA as Sepsis Biomarkers: A Comprehensive Review.

Sepsis, a life-threatening condition caused by the body's dysregulated response to infection, presents a significant challenge in clinical management. Timely and accurate diagnosis is paramount for initiating appropriate interventions and improving patient outcomes. In recent years, there has been growing interest in identifying biomarkers that can aid in the early detection and prognostication of sepsis. MicroRNAs (miRNAs) have emerged as potential biomarkers for sepsis due to their involvement in the regulation of gene expression and their stability in various biological fluids, including blood. MiRNAs are small non-coding RNA molecules that play crucial roles in post-transcriptional gene regulation by binding to target messenger RNAs (mRNAs), leading to mRNA degradation or translational repression. The diagnostic and prognostic potential of miRNAs in sepsis stems from their ability to serve as sensitive and specific biomarkers reflective of the underlying pathophysiological processes. Compared to traditional biomarkers such as C-reactive protein (CRP) and procalcitonin (PCT), miRNAs offer several advantages, including their early and sustained elevation during sepsis, as well as their stability in stored samples, making them attractive candidates for clinical use. However, despite their promise, the clinical translation of miRNAs as sepsis biomarkers faces several challenges. These include the need for standardized sample collection and processing methods, the identification of optimal miRNA panels or signatures for differentiating sepsis from other inflammatory conditions, and the validation of findings across diverse patient populations and clinical settings. In conclusion, miRNAs hold great promise as diagnostic and prognostic biomarkers for sepsis, offering insights into the underlying molecular mechanisms and potential therapeutic targets. However, further research is needed to overcome existing challenges and realize the full clinical utility of miRNAs in improving sepsis outcomes.

Sepsis Prediction

Abstract: Sepsis manifests as a life-threatening condition wherein the body's response to infection triggers organ dysfunction. Typically, this immune response inadvertently damages the body's tissues while combating the infection. Within the overall range of sepsis, septic shock represents a critical subset characterized by notable circulatory, cellular, and metabolic abnormalities, resulting in a increased mortality rate than standard sepsis. Noteworthy is the consensus from various studies highlighting the crucial role of early intervention in enhancing the survival chances of sepsis patients. Given the urgency of timely recognition and treatment, there is a heightened focus on sepsis prediction. Traditional scoring systems such as APACHE, SAPS, and SOFA provide insights into disease severity and prognosis but lack the capacity for early sepsis detection. This study uses ML techniques and analyzes extensive patient data, which includes vital signs and medical history, to identify important indicators and prognostic patterns that find the occurrence of sepsis. By applying advanced algorithms like neural networks and ensemble methods, the model shows impressive accuracy in predicting the progression of sepsis. In addition, detailed analysis of trait significance helps to understand key prognostic markers, allowing clinicians to strategically prioritize interventions. Successful integration of this prognostic tool into the clinical setting offers a promising opportunity for preventive management of sepsis, which can reduce mortality and improve patient outcomes. We built a (LSTM) network to distinguish the internal association between different. indicators in clinical data. Analysis includes use of electronic health records, multicenter collaboration, and challenge development. Our goal is to support the research of accurate and timely sepsis predictors, ultimately improving patient outcomes.

Sepsis risk in diabetic patients with urinary tract infection.

Urinary tract infections (UTI) is a prevalent condition in those with diabetes, and in severe cases, it may escalate to sepsis. Therefore, it is important to analyze the risk variables associated with sepsis in diabetes individuals with UTI. This research was a retrospective cross-sectional analysis. From January 2011 to June 2022, a group of individuals with diabetes were identified as having UTI at a tertiary hospital situated in Southeastern China. Patient data, including information on urine culture, was collected retrospectively from a clinical record database. The participants were categorized into the sepsis and non-sepsis groups. The risk variables were derived using both uni-and multiple- variable regression analysis. The research included 1919 patients, of whom 1106 cases (57.63%) had positive urine cultures. In total, 445 blood culture samples were tested, identifying 186 positive cases (41.80%). The prevalence of bacteria in urine and blood samples was highest for Escherichia coli and Klebsiella pneumoniae, respectively. Moreover, 268 individuals (13.97%) exhibited sepsis. The regression analysis indicated a positive correlation between sepsis and albumin (ALB)<34.35 g/L, C-reactive protein (CRP)>55.84 mg/L and white blood cell count (WBC) >8.485 X 109/L in diabetic cases with UTIs. By integrating the three aforementioned parameters, the area under the receiver operating characteristic curve was 0.809. The early detection of sepsis in diabetic individuals with UTI may be achieved using a comprehensive analysis of CRP, WBC, and ALB test findings.

Factors Affecting Neutrophil Functions During Sepsis: Human Microbiome and Epigenetics.

Sepsis is a severe disease that occurs when the body's immune system reacts excessively to infection. The body's response, which includes an intense anti-bacterial reaction, can damage its tissues and organs. Neutrophils are the major components of white blood cells in circulation and play a vital role in innate immunity while fighting against infections, and are considered a feature determining sepsis classification. There's a plethora of basic research detailing neutrophil functioning, among which, the study of neutrophil extracellular traps (NETs) is providing novel insights into mechanisms and treatments of sepsis. This review explores their functions, dysfunctions, and influences in the context of sepsis. The interplay between neutrophils and the human microbiome and the impact of DNA methylation on neutrophil function in sepsis are crucial areas of study. The interaction between neutrophils and the human microbiome is complex, particularly in the context of sepsis where dysbiosis may occur. We highlight the importance of deciphering neutrophil's functional alterations and their epigenetic features in sepsis because it is critical for defining sepsis endotypes and opening up the possibility for novel diagnostic methods and therapy. Specifically, epigenetic signatures are pivotal since they will provide a novel implication for sepsis diagnostic method when used in combination with the cell-free DNA (cfDNA). Research is exploring how specific patterns of DNA methylation in neutrophils, detectable in cfDNA, could serve as biomarkers for the early detection of sepsis.

Ventilator-associated pneumonia – An unwanted terror and a loathsome burden on the health-care cost in the recent era

Ventilator-associated pneumonia – An unwanted terror and a loathsome burden on the health-care cost in the recent era

A Secondary Retrospective Analysis of the Predictive Value of Neutrophil-Reactive Intensity (NEUT-RI) in Septic and Non-Septic Patients in Intensive Care.

Effective identification and management in the early stages of sepsis are critical for achieving positive outcomes. In this context, neutrophil-reactive intensity (NEUT-RI) emerges as a promising and easily interpretable parameter. This study aimed to assess the predictive value of NEUT-RI in diagnosing sepsis and to evaluate its prognostic significance in distinguishing 28-day mortality outcomes. This study is a secondary, retrospective, observational analysis. Clinical data upon ICU admission were collected. We enrolled septic patients and a control group of critically ill patients without sepsis criteria. The patients were divided into subgroups based on renal function for biomarker evaluation with 28-day outcomes reported for septic and non-septic patients. A total of 200 patients were included in this study. A significant difference between the "septic" and "non-septic" groups was detected in the NEUT-RI plasma concentration (53.80 [49.65-59.05] vs. 48.00 [46.00-49.90] FI, p < 0.001, respectively). NEUT-RI and procalcitonin (PCT) distinguished between not complicated sepsis and septic shock (PCT 1.71 [0.42-12.09] vs. 32.59 [8.83-100.00], <0.001 and NEUT-RI 51.50 [47.80-56.30] vs. 56.20 [52.30-61.92], p = 0.005). NEUT-RI, PCT, and CRP values were significantly different in patients with "renal failure". NEUT-RI and PCT at admission in the ICU in the septic group were higher in patients who died (58.80 [53.85-73.10] vs. 53.05 [48.90-57.22], p = 0.005 and 39.56 [17.39-83.72] vs. 3.22 [0.59-32.32], p = 0.002, respectively). Both NEUT-RI and PCT showed a high negative predictive value and low positive predictive value. The inflammatory biomarkers assessed in this study offer valuable support in the early diagnosis of sepsis and could have a possible role in anticipating the outcome. NEUT-RI elevation appears particularly promising for early sepsis detection and severity discrimination upon admission.

Umbilical cord blood culture for early onset sepsis in preterm infants.

Umbilical cord blood culture (UCBC) may have a diagnostic utility for early onset sepsis (EOS) detection in preterm infants. It may prevent sampling the newborn and collect a higher volume of blood for pathogenic identification. Retrospective analysis at a tertiary care center in Canada of preterm infants ≤ 34 0/7 weeks' gestation with UCBC taken at birth. Of 505 admitted infants, 195 had UCBC. 170 UCBCs were negative; 44 of these had also negative neonatal blood culture (NBC). No infants with negative UCBC showed EOS symptoms in the first week of life. 25 UCBCs were positive: 18 were contaminants (all with negative NBC) and 7 were confirmed as EOS. 18 infants with UCBC contaminants remained asymptomatic. 7 EOS cases were identified, with varying bacteriological profiles; 5 displayed sepsis symptoms while 2 were asymptomatic. Risk of EOS increased with prolonged rupture of membranes. UCBC effectively detected EOS establishing it as a method with possibly better diagnostic performance than NBC in high-risk neonates. Further studies are needed to improve UCBC technique and lower contamination rates. Umbilical cord blood culture has a higher bacterial identification rate than peripheral venous blood culture for the early identification of early-onset sepsis in preterm infants. Umbilical cord blood cultures that showed no growth were reliable predictors of not developing early onset sepsis. Umbilical cord blood culture should be considered as part of the evaluation for early onset sepsis in the preterm infants.

Application of Machine Learning and its use in determining Sepsis Prediction

Sepsis is a potentially life-threatening and serious condition that occurs when an infection spreads across the body and triggers a widespread inflammatory response. It has a significantly high death rate, especially for patients in the ICU. Early detection and treatment of sepsis is necessary. Machine learning models for sepsis detection can be trained on a variety of data sources, such as electronic health records (EHRs), vital signs, laboratory test results, and demographic information. Exploratory Data analysis was performed using different pre-processing techniques. To classify the disease, the Random Forest Classifier is used, and comparison also performed among various Classifiers like MLP, KNN, etc. Key Words: Sepsis Prediction, Random Forest Classifier, vital signs.

Serial monitoring of pancreatic stone protein for the detection of sepsis in intensive care unit patients with complicated abdominal surgery: A prospective, longitudinal cohort study

PurposeThe objective of this study was to assess the performance of pancreatic stone protein (PSP) monitoring for the detection of sepsis, prediction of outcome and distinction between bacterial and fungal infections in intensive care unit (ICU) patients with complicated abdominal surgery. Materials and methodsIn this prospective multicenter cohort study, patients with complicated abdominal surgery had serial PSP measurements during their ICU stay. Infectious episodes were classified as bacterial, fungal or mixed. PSPmax (maximal PSP value within 48 h of the diagnosis of infection) and ΔPSP (difference between PSPmax and the preceding PSP value) were used for analyses. ResultsPSPmax was obtained for 118 infectious episodes (68 patients). ΔPSP was available for 73 episodes (48 patients). Both PSPmax and ΔPSP were significantly higher in patients with sepsis and in patients with a fatal outcome. A PSPmax ≥124 ng/ml and a ΔPSP ≥34 ng/ml could detect sepsis with a sensitivity/specificity of 84%/54% and 69%/76%, respectively. There was no significant difference of PSPmax or ΔPSP between patients with bacterial/mixed versus fungal infections. ConclusionsSerial PSP monitoring may be an additional tool for the early detection of sepsis in patients with complicated abdominal surgery who are at high risk of severe infections.

Usefulness of mid-regional proadrenomedullin levels in the resuscitation phase of severely burned patients and its utility in early sepsis detection

IntroductionMid-regional proadrenomedullin (MR-proADM) reflects the adrenomedullin level, which has vasodilatory activity, decreases endothelial permeability, and downregulates proinflammatory cytokines. Sepsis diagnosis in these patients is difficult, and MR-proADM is a widely studied sepsis biomarker. This study evaluates MR-proADM levels during the resuscitation phase, considering the potential influence of haemodynamic changes and its usefulness for the early sepsis detection in burn patients. MethodsA prospective observational study performed in the Critical Burn Unit. Demographic data, burn characteristics, comorbidities, prognostic/severity scales, and haemodynamic parameters were collected. The resuscitation protocol guided by diuresis, transpulmonary thermodilution, and lactate levels was followed. Blood samples were collected at various time points for biomarker measurement. Biomarker levels, including MR-proADM, C-reactive protein, and procalcitonin were measured during the resuscitation phase and septic episodes. ResultsTwenty-seven patients were included, with a mean age of 51 years, a mean total body surface area burn of 41.8%, a mean Abbreviated Burn Severity Index of 9.7, and a mean Baux score of 92. MR-proADM levels were elevated on admission (0.9 ± 0.5 nmol/l) and continued to increase slightly during the resuscitation phase (2.4 ± 2.2 nmol/l). Haemodynamic changes during resuscitation did not significantly affect MR-proADM levels. Twelve of the 27 patients developed sepsis, whose MR-proADM levels were significantly elevated on the day of clinical diagnosis (3.91 ± 2.99 nmol/l) and even the day before (2.57 ± 3.37). Higher MR-proADM levels were associated with greater severity as measured by the Sequential Organ Failure Assessment score. The mean MR-proadrenomedullin values during resuscitation in the patients who died was 3.51 ± 2.30 nmol/l, whereas in the survivors it was 1.28 ± 1.10 nmol/l (p = 0.0001). ConclusionMR-proadrenomedullin values are elevated after thermal injury but are not affected by haemodynamic changes. During septic episodes in burn patients, MR-proADM rises early (the day before sepsis diagnosis). Higher levels of MR-proADM are associated with greater organ dysfunction and mortality.

Culture-free biphasic approach for early sepsis detection: A true game changer.

Culture-free biphasic approach for early sepsis detection: A true game changer.

Early detection of late-onset neonatal sepsis from noninvasive biosignals using deep learning: A multicenter prospective development and validation study

BackgroundNeonatal sepsis is responsible for significant morbidity and mortality worldwide. Its accurate and timely diagnosis is hindered by vague symptoms and the urgent necessity for early antibiotic intervention. The gold standard for diagnosing the condition is the identification of a pathogenic organism from normally sterile sites via laboratory testing. However, this method is resource-intensive and cannot be conducted continuously. ObjectiveThis study aimed to predict the onset of late-onset sepsis (LOS) with good diagnostic value as early as possible using non-invasive biosignal measurements from neonatal intensive care unit (NICU) monitors. MethodsIn this prospective multicenter study, we developed a multimodal machine learning algorithm based on a convolutional neural network (CNN) structure that uses the power spectral density (PSD) of recorded biosignals to predict the onset of LOS. This approach aimed to discern LOS-related pathogenic spectral signatures without labor-intensive manual artifact removal. ResultsThe model achieved an area under the receiver operating characteristic score of 0.810 (95 % CI 0.698–0.922) on the validation dataset. With an optimal operating point, LOS detection had 83 % sensitivity and 73 % specificity. The median early detection was 44 h before clinical suspicion. The results highlighted the additive importance of electrocardiogram and respiratory impedance (RESP) signals in improving predictive accuracy. According to a more detailed analysis, the predictive power arose from the morphology of the electrocardiogram’s R-wave and sudden changes in the RESP signal. ConclusionRaw biosignals from NICU monitors, in conjunction with PSD transformation, as input to the CNN, can provide state-of-the-art prediction performance for LOS without the need for artifact removal. To the knowledge of the authors, this is the first study to highlight the independent and additive predictive potential of electrocardiogram R-wave morphology and concurrent, sudden changes in the RESP waveform in predicting the onset of LOS using non-invasive biosignals.

The Role of New Morphological Parameters Provided by the BC 6800 Plus Analyzer in the Early Diagnosis of Sepsis

Background: Late diagnosis of sepsis is associated with adverse consequences and high mortality rate. The aim of this study was to evaluate the diagnostic value of hematologic research parameters, that reflect the cell morphology of blood cells, available on the BC 6800 plus automated analyzer (Mindray) for the early detection of sepsis. Materials and Methods: A complete blood count (CBC) was performed by Mindray BC 6800 Plus Analyzer in 327 patients (223 with a confirmed diagnosis of sepsis following sepsis-3 criteria, 104 without sepsis), admitted at the Intensive Care Unit of the Novara’s Hospital (Italy) and in 56 patients with localized infection. Results: In univariate logistic regression, age, Hb, RDW, MO#, NMR, NeuX, NeuY, NeuZ, LymX, MonX, MonY, MonZ were associated with sepsis (p &lt; 0.005). In multivariate analysis, only RDW, NeuX, NeuY, NeuZ, MonX and MonZ were found to be independent predictors of sepsis (p &lt; 0.005). Morphological research parameters are confirmed to be predictors of sepsis even when analyzing the group with localized infection. Conclusions: In addition to already established biomarkers and basic CBC parameters, new morphological cell parameters can be a valuable aid in the early diagnosis of sepsis at no additional cost.

Fetal chronic hypoxia does not affect urinary presepsin levels in newborns at birth.

Early sepsis detection and diagnosis still constitutes an open issue since the accuracy of standard-of care parameters is biased by a series of perinatal factors including hypoxia. Therefore, we aimed at investigating the effect of fetal chronic hypoxia insult on urine levels of a promising new marker of sepsis, namely presepsin (P-SEP). We conducted a prospective case-control study in 22 cases of early-intrauterine growth restriction (E-IUGR) compared with 22 small-for-gestational-age (SGA) newborns and 66 healthy controls. P-SEP urine samples were collected over the first 72 h from birth. Blood culture and C-reactive protein (CRP) blood levels were measured in E-IUGR and SGA infants. Perinatal standard monitoring parameters and main outcomes were also recorded. No significant urinary P-SEP differences (p>0.05, for all) were observed among studied groups. Moreover, no significant correlations (p>0.05, for both) between urinary P-SEP and blood CRP levels in both E-IUGR and SGA groups (R=0.08; R=0.07, respectively) were observed. The present results showing the lack of influence of fetal chronic hypoxia on urinary P-SEP levels offer additional data to hypothesize the possible use of urinary P-SEP measurement in neonates in daily clinical practice. Further multicenter prospective data are needed, including infants with early-onset sepsis.

Subtle variation in sepsis-III definitions markedly influences predictive performance within and across methods

Early detection of sepsis is key to ensure timely clinical intervention. Since very few end-to-end pipelines are publicly available, fair comparisons between methodologies are difficult if not impossible. Progress is further limited by discrepancies in the reconstruction of sepsis onset time. This retrospective cohort study highlights the variation in performance of predictive models under three subtly different interpretations of sepsis onset from the sepsis-III definition and compares this against inter-model differences. The models are chosen to cover tree-based, deep learning, and survival analysis methods. Using the MIMIC-III database, between 867 and 2178 intensive care unit admissions with sepsis were identified, depending on the onset definition. We show that model performance can be more sensitive to differences in the definition of sepsis onset than to the model itself. Given a fixed sepsis definition, the best performing method had a gain of 1–5% in the area under the receiver operating characteristic (AUROC). However, the choice of onset time can cause a greater effect, with variation of 0–6% in AUROC. We illustrate that misleading conclusions can be drawn if models are compared without consideration of the sepsis definition used which emphasizes the need for a standardized definition for sepsis onset.

Role of Serum Lactate Clearance as a Predictor of Mortality and Morbidity in Neonatal Sepsis: A Prospective Cohort Study

Introduction: Neonatal sepsis is a global healthcare concern, which is more prevalent in developing countries. However, surprisingly, biomarkers with good sensitivity and specificity to predict mortality and morbidity are lacking. Higher levels of serum lactate are observed in patients exposed to an inflammatory response, but its practical use remains limited. Therefore, the author aimed to investigate the relationship between serum lactate measurements and the severity of neonatal sepsis. Aim: To assess the role of serum lactate clearance as a marker to predict mortality and morbidity in neonatal sepsis. Additionally, the secondary aim was to evaluate the demographic profile of neonatal sepsis and understand the relationship between C-reactive Protein (CRP), Procalcitonin, and lactate clearance in neonatal sepsis. Materials and Methods: A prospective cohort study was conducted in the Sick Newborn Care Unit (SNCU) and Neonatal Intensive Care Unit (NICU) of Chittaranjan Seva Sadan, College of Obstetrics, Gynaecology, and Child Health in Kolkata, India, from June 2020 to May 2021. A total of 93 confirmed cases of neonatal sepsis were included in the study. Serum lactate levels were measured at the time of sepsis diagnosis and 48 hours after the first sample. Lactate clearance was calculated, and the neonates were followed till discharge or death. Various parameters, including complete blood count, CRP, Procalcitonin, culture, and Cerebrospinal Fluid (CSF), were assessed. The data obtained were statistically analysed using paired t-test, one-way Analysis of Variance (ANOVA), and Pearson’s Chi-square test. Results: A total of 93 neonates were included after meeting the inclusion and exclusion criteria. Among them, 10 neonates died, while 83 were successfully discharged. It was found that death was significantly associated (p&lt;0.0001) with lactate clearance. Total 9 (90%) of the deceased neonates had negative lactate clearance, while only 21 (25.3%) discharged neonates had negative lactate clearance. Lactate clearance was also significantly associated with the duration of hypoglycaemia (p=0.008), duration of Nil Per Mouth (NPM) (p=0.01), and need for reintubation (p=0.05). However, no association was found with the duration of hospital stay, duration of fluid therapy, duration of oxygen requirement, and need for ventilation. Conclusion: Lactate clearance showed a significant association with the risk of mortality in patients with neonatal sepsis. Therefore, lactate clearance can be used as a prognostic marker to identify sepsis. Early detection of sepsis can aid in proper management and subsequently reduce mortality

Exosome-Derived microRNA: Potential Target for Diagnosis and Treatment of Sepsis.

Exosome-derived microRNAs (miRNAs) are emerging as pivotal players in the pathophysiology of sepsis, representing a new frontier in both the diagnosis and treatment of this complex condition. Sepsis, a severe systemic response to infection, involves intricate immune and nonimmune mechanisms, where exosome-mediated communication can significantly influence disease progression and outcomes. During the progress of sepsis, the miRNA profile of exosomes undergoes notable alterations, is reflecting, and may affect the progression of the disease. This review comprehensively explores the biology of exosome-derived miRNAs, which originate from both immune cells (such as macrophages and dendritic cells) and nonimmune cells (such as endothelial and epithelial cells) and play a dynamic role in modulating pathways that affect the course of sepsis, including those related to inflammation, immune response, cell survival, and apoptosis. Taking into account these dynamic changes, we further discuss the potential of exosome-derived miRNAs as biomarkers for the early detection and prognosis of sepsis and advantages over traditional biomarkers due to their stability and specificity. Furthermore, this review evaluates exosome-based therapeutic miRNA delivery systems in sepsis, which may pave the way for targeted modulation of the septic response and personalized treatment options.

Nurses' and Physicians' Experiences After Implementation of a Quality Improvement Project to Improve Sepsis Awareness in Hospitals.

Previous research has explored nurses´ experience with the implementation of early detection alert systems, and nurses and physicians' perceptions of sepsis management and use of sepsis triage. As one of the first, this study aims to investigate the perceived usefulness of an interdisciplinary quality improvement project including standardized sepsis patient pathway to improve the early identification and treatment of sepsis patients. This study was a qualitative study that employed semi-structured interviews with thirteen ward nurses and five ward physicians recruited by convenience and respondent-driven sampling, respectively. The interviews explored the perceived usefulness of mutual training in sepsis care in medical hospital wards. We applied Systematic Text Condensation to analyze the experiences and knowledge of professional identification and cooperation in early identification of sepsis patients. The results revealed three main themes: Awareness of sepsis, collaboration between nurses and physicians, and clinical assessment and judgement. The findings highlighted the positive impact of the project in terms of raising awareness, improving communication, and enhancing the ability to detect and treat sepsis. The study also identified the importance of repetition and reminders to maintain awareness, the need for ongoing training for new healthcare professionals, and the challenges of collaboration and decision-making processes. The sepsis intervention seemed successful in improving awareness of sepsis and enhancing interprofessional collaboration between nurses and physicians. Health professionals continued to rely on their clinical judgment but increased the use of objective measurements and communication of vital signs. Continuous repetition and education for new colleagues were identified as important factors for the sustainability of the intervention. Overall, the study highlights the importance of standardized protocols and training for early detection and management of sepsis in healthcare settings.

Clinical and Protein Biomarkers in Sepsis: Insights from Hospital-Based Case Studies

Background: Sepsis is a severe life-threatening state of infection with a high incidence in clinical settings and is one of the most common causes of hospitalization and deaths in the Critical Care Unit (CCU). The current research work was carried out to investigate the aetiology and pathophysiology of sepsis in the in-patients of Mahavir Hospital, Hyderabad, Telangana, India. This study aims to identify clinical and protein biomarkers that can effectively diagnose and predict the risk outcomes of sepsis in hospitalized patients. Patients and Methods: Observations are based on 20 case studies of patients including male and female subjects. All the parameters studied were investigated using standard protocols by collecting blood samples from the patients and estimating blood and clinical parameters and the protein markers such as procalcitonin (PCT), D-Dimer and C-Reactive Protein (CRP), which are considered as important biomarkers of sepsis. Demographic details were collected in a questionnaire and tabulated. Results: This study identified several clinical parameters and protein biomarkers that were significantly associated with sepsis. It was found that key biomarkers had elevated levels of procalcitonin, C-reactive protein, and specific cytokines. Additionally, clinical parameters such as heart rate, respiratory rate, and white blood cell count were found to be critical indicators. The combination of these biomarkers provided a robust model for the early diagnosis and prognosis of sepsis. The results demonstrated that PCT rapidly rises in almost all tested patient’s blood. Further correlation with demographic parameters and the disease's etiology across various stages revealed that some of these proteins could serve as significant biomarkers for the early detection of sepsis. Conclusion: The identification of these clinical and protein biomarkers offers valuable insights into the pathophysiology of sepsis and can enhance early diagnosis and personalized treatment strategies. Further validation in larger, diverse cohorts is warranted to confirm these findings and facilitate their integration into clinical practice.

Advancing Early Detection of Sepsis With Temporal Convolutional Networks Using ECG Signals

Advancing Early Detection of Sepsis With Temporal Convolutional Networks Using ECG Signals