Conocimiento en estudiantes de enfermería sobre sepsis quirúrgico / Knowledge in nursing students about surgical sepsis

Objetivo: Determinar el nivel de conocimiento de los estudiantes de enfermería de la Universidad Técnica de Ambato sobre sepsis quirúrgica. Material y método: La presente investigación tiene un diseño de desarrollo observacional, de tipo descriptivo, cohorte transversal, con un enfoque cuantitativo, ya que el nivel de cono-cimiento se verá representado mediante tablas y gráficos para des-cribir la problemática del periodo octubre 2023 febrero 2024. Re-sultados: Se evidencia un alto porcentaje de respuestas incorrectas por cada ítem por parte de los estudiantes. La categoría Nivel de Conocimiento sobre Definición de Sepsis, fue respondida de ma-nera incorrecta con un porcentaje del 83,9%, la categoría Nivel de Conocimiento sobre Diagnóstico de Sepsis obtuvo 51,7% y, por úl-timo, la Nivel de Conocimiento sobre Tratamiento de Sepsis con el 29,2%. Conclusiones: El nivel de conocimiento de los estudiantes sobre Sepsis Quirúrgica es malo, debido a que existe una subesti-mación de la gravedad de la sepsis como afección potencialmente mortal, lo que puede traer un impacto negativo en los pacientes[AU]

Objective: Determine the level of knowledge of nursing students at the Technical University of Ambato about surgical sepsis. Mate-rials and methods: This research has an observational, descriptive, transversal development design, with a quantitative approach since the level of knowledge will be represented through tables and gra-phs to describe the problems of the period October 2023-February 2024. Results: A high percentage of incorrect answers for each item by the students is evident. The category Level of Knowledge about Definition of Sepsis was answered incorrectly with a percentage of 83.9%, the category Level of Knowledge about Diagnosis of Sepsis obtained 51.7% and, finally, the category Level of Knowledge about Treatment of Sepsis. Sepsis with 29.2%. Conclusions: The level of knowledge of students about Surgical Sepsis is poor because there is an underestimation of the severity of sepsis as a potentially fatal condition, which can have a negative impact on patients[AU]

Objetivo: Determinar o nível de conhecimento dos estudantes de enfermagem da Universidade Técnica de Ambato sobre sepse ci-rúrgica. Material e método: Esta pesquisa possui desenho de coor-te observacional, descritivo, transversal, com abordagem quantita-tiva, uma vez que o nível de conhecimento será representado por meio de tabelas e gráficos para descrever o problema no período de outubro de 2023 a fevereiro de 2024. Resultados: Uma parada. É evidente o percentual de respostas incorretas para cada item por parte dos alunos. A categoria Nível de Conhecimento sobre Defi-nição de Sepse foi respondida incorretamente com percentual de 83,9%, a categoria Nível de Conhecimento sobre Diagnóstico de Sepse obteve 51,7% e por fim, a categoria Nível de Conhecimen-to sobre Tratamento de Sepse com 29,2%. Conclusões: O nível de conhecimento dos estudantes sobre a Sepse Cirúrgica é baixo, pois há uma subestimação da gravidade da sepse como uma condição potencialmente fatal, que pode ter um impacto negativo nos pa-cientes[AU]

Prognostic and diagnostic utility of pancreatic stone protein in pediatric sepsis and mortality.

Background/aim: Early detection and prognosis of sepsis in critically ill children is crucial. The aim of this research was to investigate the prognostic ability of pancreatic stone protein (PSP) in validating sepsis and predicting mortality in a prospective observational study. Materials and methods: In a single-center study, pediatric intensive care unit patients were divided into cohorts of confirmed and suspected sepsis, as well as survivors and nonsurvivors. Patients with positive blood culture growth were considered to have confirmed sepsis, while their negative counterparts were considered to have suspected sepsis. Comparisons were made between complete blood counts, laboratory parameters, mortality indices, and C-reactive protein (CRP), procalcitonin (PCT), and PSP levels. The correlations between PSP and alternative inflammatory markers and mortality indices were then analyzed. The diagnostic and prognostic applicability of PSP for sepsis confirmation and mortality prediction was assessed using receiver operating characteristic curve analysis. Results: PSP levels were significantly elevated in patients with confirmed sepsis and within the nonsurvivor segment. In confirming sepsis and predicting mortality, PSP outperformed CRP and PCT in terms of sensitivity. It had sensitivity of 95% in diagnosing sepsis at a cut-off level of 50 ng/L, with an area under the curve (AUC) of 0.67 (95% CI: 0.52-0.81), and sensitivity of 92% in predicting mortality, with an AUC of 0.71 (95% CI: 0.56-0.83). In addition, PSP showed significant correlations with CRP, PCT, and mortality scores. Conclusion: PSP is emerging as a highly sensitive marker for confirming sepsis and predicting mortality in critically ill pediatric patients. Incorporating the PSP biomarker into routine clinical practice could potentially improve the management of pediatric sepsis.

Contributions of individual qSOFA elements to assessment of severity and for prediction of mortality.

BACKGROUND: The quick sequential [sepsis-related] organ failure assessment (qSOFA) acts as a prompt to consider possible sepsis. The contributions of individual qSOFA elements to assessment of severity and for prediction of mortality remain unknown. METHODS: A total of 3974 patients with community-acquired pneumonia were recruited to an observational prospective cohort study. The area under the receiver operating characteristic curve (AUROC), odds ratio, relative risk and Youden's index were employed to assess discrimination. RESULTS: Respiratory rate ≥22/min demonstrated the most superior diagnostic value, indicated by largest odds ratio, relative risk and AUROC, and maximum Youden's index for mortality. However, the indices for altered mentation and systolic blood pressure (SBP) ≤100 mm Hg decreased notably in turn. The predictive validities of respiratory rate ≥22/min, altered mentation and SBP ≤100 mm Hg were good, adequate and poor for mortality, indicated by AUROC (0.837, 0.734 and 0.671, respectively). Respiratory rate ≥22/min showed the strongest associations with SOFA scores, pneumonia severity index, hospital length of stay and costs. However, SBP ≤100 mm Hg was most weakly correlated with the indices. CONCLUSIONS: Respiratory rate ≥22/min made the greatest contribution to parsimonious qSOFA to assess severity and predict mortality. However, the contributions of altered mentation and SBP ≤100 mm Hg decreased strikingly in turn. It is the first known prospective evidence of the contributions of individual qSOFA elements to assessment of severity and for prediction of mortality, which might have implications for more accurate clinical triage decisions.

Respiratory rate ≥22/min demonstrated the most superior diagnostic value.Respiratory rate ≥22/min showed the strongest association with severity.Respiratory rate ≥22/min, altered mentation and SBP ≤100 mm Hg predicted mortality well, adequately and poorly, respectively.

Comparing the Predictive Value of SOFA and SIRS for Mortality in the Early Hours of Hospitalization of Sepsis Patients: A Systematic Review and Meta-analysis.

BACKGROUND: Sepsis, a deadly infection causing organ failure and Systemic Inflammatory Response Syndrome (SIRS), is detected early in hospitalization using the SIRS criteria, while sequential organ failure (SOFA) assesses organ failure severity. A systematic review and meta-analysis was evaluated to investigate the predictive value of the SIRS criteria and the SOFA system for mortality in early hospitalization of sepsis patients. METHODS: Inclusion criteria were full reports in peer-reviewed journals with data on sepsis assessment using SOFA and SIRS, and their relationship with outcomes. For quality assessment, we considered study population, sepsis diagnosis criteria, and outcomes. The area under the curve (AUC) of these criteria was extracted for separate meta-analysis and forest plots. RESULTS: Twelve studies met the inclusion criteria. The studies included an average of 56.1% males and a mean age of 61.9 (±6.1) among 32,979 patients. The pooled AUC was 0.67 (95% CI: 0.60-0.73) for SIRS and 0.79 (95% CI: 0.73-0.84) for SOFA. Significant heterogeneity between studies was indicated by an I2 above 50%, leading to a meta-regression analysis. This analysis, with age and patient number as moderators, revealed age as the major cause of heterogeneity in comparing the predictive value of the SOFA score with SIRS regarding the in-hospital mortality of sepsis patients (P<0.05). CONCLUSION: The SOFA score outperformed the SIRS criteria in predicting mortality, emphasizing the need for a holistic approach that combines clinical judgment and other diagnostic tools for better patient management and outcomes.

Early Sepsis Response System Does Not Correlate with Pediatric Early Warning Score in Sepsis Recognition.

Sepsis is a leading cause of pediatric morbidity and mortality worldwide with early recognition and management improving patient outcomes. Early recognition warning systems, utilizing the electronic medical record (EMR), are recommended for children's hospitals. Validated pediatric early warning score (PEWS) recognize hospitalized children at risk for worsening and need for higher level of care. The goal of this study was to develop a novel pediatric sepsis early response warning system and compare this tool with the existing generic PEWS system in recognizing sepsis. A novel early sepsis warning system was integrated into the EMR of a tertiary pediatric children's hospital. In patients meeting criteria a best practice alert (BPA) triggers and children with a sepsis BPA trigger were evaluated from December, 2018 through May, 2020. BPA data was analyzed and identified children meeting sepsis criteria. Subjects identified as having sepsis were then correlated with PEWS scores at the time of the BPA. The BPA triggered in 736 pediatric subjects, with 181 in the emergency department, 275 in the pediatric inpatient floor and 280 in the pediatric intensive care unit. Pediatric sepsis criteria identified 524 of 736 (71%) as having sepsis. PEWS scores identified only 66 (13%) of the 524 subjects who had sepsis. Implementation of a sepsis trigger tool into EMR is feasible. Best practice alerts identify subjects with early sepsis and can be implemented to electronic medical record.

Urinary cystatin-C and urinary NGAL associated with sepsis predicts longer hospital stay in premature newborns.

Aim: To evaluate the urinary biomarkers related to sepsis in preterm newborns (NBs) and to investigate the predictive capacity of these biomarkers for a longer hospital stay.Methods: Serum and urine were collected from 27 healthy NBs, 24 NBs with neonatal infection without sepsis and 11 NBs with sepsis for the measurement of sindecan-1, lipocalin associated with urinary neutrophil gelatinase (uNGAL), urinary cystatin-C (uCysC) and urinary kidney injury molecule-1.Results: Levels of uNGAL and urinary cystatin-C were elevated in NBs with sepsis and neonatal infection, and uNGAL was significant predictor of hospital stay longer than 30 days (odds ratio: 1.052; 95% CI: 1.012-1.093; p = 0.01).Conclusion: uNGAL was associated with sepsis in preterm NBs and was useful to predict extended hospital stay.

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Analysis of the diagnostic value of coagulation markers and coagulation function indices on the occurrence of DIC in sepsis and its prognosis.

Sepsis is a life-threatening condition that has the potential to multiple organ dysfunction and mortality. One of its frequent complications is disseminated intravascular coagulation (DIC), characterized by hyperactive clotting mechanisms that cause widespread clot formation and tissue damage. This study aimed to investigate early diagnostic markers of sepsis-associated DIC by comparing inflammatory factor levels, 28-day survival rates, coagulation function, and markers between patients with sepsis (non-DIC group) and those with sepsis-induced DIC (DIC group). The study analyzed the diagnostic efficacy of coagulation function and markers in predicting the occurrence and prognosis of sepsis-associated DIC, presenting survival curves. Results indicated significantly increased levels of APTT, TAT, tPAIC, PIC, and sTM in the DIC group compared to the non-DIC group. Sequential Organ Failure Assessment (SOFA) scores on days 1, 3, and 7 were notably lower in the non-DIC group. Correlation analysis revealed positive associations between PT, APTT, TAT, tPAIC, PIC, sTM levels, and SOFA scores, as well as negative associations with Fib and SOFA scores. Survival curves showed substantially lower mortality rates in the non-DIC group, highlighting significant survival disparities between groups. Combining all four coagulation indicators (TAT+ tPAIC + PIC + sTM) showed promising diagnostic value in evaluating disease severity, early DIC diagnosis, and sepsis prognosis.

Clinical Phenotyping for Prognosis and Immunotherapy Guidance in Bacterial Sepsis and COVID-19.

OBJECTIVES: It is suggested that sepsis may be classified into four clinical phenotypes, using an algorithm employing 29 admission parameters. We applied a simplified phenotyping algorithm among patients with bacterial sepsis and severe COVID-19 and assessed characteristics and outcomes of the derived phenotypes. DESIGN: Retrospective analysis of data from prospective clinical studies. SETTING: Greek ICUs and Internal Medicine departments. PATIENTS AND INTERVENTIONS: We analyzed 1498 patients, 620 with bacterial sepsis and 878 with severe COVID-19. We implemented a six-parameter algorithm (creatinine, lactate, aspartate transaminase, bilirubin, C-reactive protein, and international normalized ratio) to classify patients with bacterial sepsis intro previously defined phenotypes. Patients with severe COVID-19, included in two open-label immunotherapy trials were subsequently classified. Heterogeneity of treatment effect of anakinra was assessed. The primary outcome was 28-day mortality. MEASUREMENTS AND MAIN RESULTS: The algorithm validated the presence of the four phenotypes across the cohort of bacterial sepsis and the individual studies included in this cohort. Phenotype α represented younger patients with low risk of death, ß was associated with high comorbidity burden, and δ with the highest mortality. Phenotype assignment was independently associated with outcome, even after adjustment for Charlson Comorbidity Index. Phenotype distribution and outcomes in severe COVID-19 followed a similar pattern. CONCLUSIONS: A simplified algorithm successfully identified previously derived phenotypes of bacterial sepsis, which were predictive of outcome. This classification may apply to patients with severe COVID-19 with prognostic implications.

Neutrophil-to-Lymphocyte Ratio Predicts Sepsis in Adult Patients Meeting Two or More Systemic Inflammatory Response Syndrome Criteria.

Introduction: Determining which patients who meet systemic inflammatory response syndrome (SIRS) criteria have bacterial sepsis is a difficult challenge for emergency physicians. We sought to determine whether the neutrophil-to-lymphocyte ratio (NLR) could be used to exclude bacterial sepsis in adult patients who meet ≥2 SIRS criteria and are being evaluated for sepsis. Methods: Consenting adult patients meeting ≥2 SIRS criteria and undergoing evaluation for sepsis were enrolled. We recorded patient age, gender, vital signs, and laboratory results. We then later reviewed health records for culture results, end organ dysfunction, survival to discharge, and final diagnoses. Patients were classified as having sepsis if they met ≥2 SIRS criteria and were ultimately diagnosed with a bacterial source. We analyzed data using descriptive statistics and sensitivity and specificity analyses. A receiver operating characteristic curve (ROC) was created to determine test characteristics. Results: A total of 231 patients had complete datasets. Patients' median age was 69 (interquartile range [IQR] 54-81), and 49.6% were male. There were 154 patients (66.7%) ultimately diagnosed with sepsis with an identified bacterial source, while 77 patients with ≥2 SIRS criteria had non-infectious reasons for their presentations (33.3%). Septic patients had a median NLR 12.36 (IQR [interquartile range] 7.29-21.69), compared to those without sepsis (median NLR 5.62, IQR 3.89-9.11, P < 0.001). The NLR value of 3 applied as a cutoff for sepsis had a sensitivity of 96.8 (95% confidence interval [CI] 92.2-98.8), and a specificity of 18.2 (95% CI 10.6-29.0). The ROC for NLR had an area under the curve of 0.74. Conclusion: The neutrophil-to-lymphocyte ratio is a sensitive tool to help determine which patients with abnormal SIRS screens have bacterial sepsis.

The clinical application value of multi-site mNGS detection of patients with sepsis in intensive care units.

BACKGROUND: Sepsis remains a leading cause of mortality in intensive care units, and rapid and accurate pathogen detection is crucial for effective treatment. This study evaluated the clinical application of multi-site metagenomic next-generation sequencing (mNGS) for the diagnosis of sepsis, comparing its performance against conventional methods. METHODS: A retrospective analysis was conducted on 69 patients with sepsis consecutively admitted to the Department of Intensive Care Medicine, Meizhou People's Hospital. Samples of peripheral blood and infection sites were collected for mNGS and conventional method tests to compare the positive rate of mNGS and traditional pathogen detection methods and the distribution of pathogens. The methods used in this study included a comprehensive analysis of pathogen consistency between peripheral blood and infection site samples. Additionally, the correlation between the pathogens detected and clinical outcomes was investigated. RESULTS: Of the patients with sepsis, 57.97% experienced dyspnea, and 65.2% had underlying diseases, with hypertension being the most common. mNGS demonstrated a significantly higher pathogen detection rate (88%) compared to the conventional method tests (26%). The pathogen consistency rate was 60% between plasma and bronchoalveolar lavage fluid samples, and that of plasma and local body fluid samples was 63%. The most frequently detected pathogens were gram-negative bacteria, and Klebsiella pneumonia. There were no significant differences in the clinical features between the pathogens. CONCLUSION: mNGS is significantly superior to conventional methods in pathogen detection. There was a notable high pathogen consistency detection between blood and local body fluid samples, supporting the clinical relevance of mNGS. This study highlights the superiority of mNGS in detecting a broad spectrum of pathogens quickly and accurately. TRIAL REGISTRATION: Not applicable.

Heart-type fatty acid binding protein (H-FABP) as an early biomarker in sepsis-induced cardiomyopathy: a prospective observational study.

BACKGROUND: Sepsis-induced cardiomyopathy (SICM) is a common and life-threatening complication of sepsis, significantly contributing to elevated mortality. This study aimed to identify crucial indicators for the prompt and early assessment of SICM. METHODS: Patients diagnosed with sepsis or SICM within 24 h of intensive care unit (ICU) admission were enrolled in this prospective observational study. Patients were assigned to the training set, validation set and external test set. The primary endpoint was 7-day ICU mortality, and the secondary endpoint was 28-day ICU mortality. Three machine learning algorithms were utilized to identify relevant indicators for diagnosing SICM, incorporating 64 indicators including serum biomarkers associated with cardiac, renal, and liver function, lipid metabolism, coagulation, and inflammation. Internal and external validations were performed on the screening results. Patients were then stratified based on the cut-off value of the most diagnostically effective biomarker identified, and their prognostic outcomes were observed and analyzed. RESULTS: A total of 270 patients were included in the training and validation set, and 52 patients were included in the external test set. Age, sex, and comorbidities did not significantly differ between the sepsis and SICM groups (P > 0.05). The support vector machine (SVM) algorithm identified six indicators with an accuracy of 84.5%, the random forest (RF) algorithm identified six indicators with an accuracy of 81.9%, and the logistic regression (LR) algorithm screened out seven indicators. Following rigorous selection, a diagnostic model for sepsis-induced cardiomyopathy was established based on heart-type fatty acid binding protein (H-FABP) (OR 1.308, 95% CI 1.170-1.462, P < 0.001) and retinol-binding protein (RBP) (OR 1.020, 95% CI 1.006-1.034, P < 0.05). H-FABP alone exhibited the highest diagnostic performance in both the internal (AUROC 0.689, P < 0.05) and external sets (AUROC 0.845, P < 0.05). Patients with SICM were further stratified based on an H-FABP diagnostic cut-off value of 8.335 ng/mL. Kaplan-Meier curve analysis demonstrated that elevated H-FABP levels at admission were associated with higher 7-day ICU mortality in patients with SICM (P < 0.05). CONCLUSIONS: This study revealed that H-FABP concentrations measured within 24 h of patient admission could serve as a crucial biomarker for the early and rapid diagnosis and short-term prognostic evaluation of SICM.

Clinical Phenotyping for Prognosis and Immunotherapy Guidance in Bacterial Sepsis and COVID-19.

OBJECTIVES: It is suggested that sepsis may be classified into four clinical phenotypes, using an algorithm employing 29 admission parameters. We applied a simplified phenotyping algorithm among patients with bacterial sepsis and severe COVID-19 and assessed characteristics and outcomes of the derived phenotypes. DESIGN: Retrospective analysis of data from prospective clinical studies. SETTING: Greek ICUs and Internal Medicine departments. PATIENTS AND INTERVENTIONS: We analyzed 1498 patients, 620 with bacterial sepsis and 878 with severe COVID-19. We implemented a six-parameter algorithm (creatinine, lactate, aspartate transaminase, bilirubin, C-reactive protein, and international normalized ratio) to classify patients with bacterial sepsis intro previously defined phenotypes. Patients with severe COVID-19, included in two open-label immunotherapy trials were subsequently classified. Heterogeneity of treatment effect of anakinra was assessed. The primary outcome was 28-day mortality. MEASUREMENTS AND MAIN RESULTS: The algorithm validated the presence of the four phenotypes across the cohort of bacterial sepsis and the individual studies included in this cohort. Phenotype α represented younger patients with low risk of death, ß was associated with high comorbidity burden, and δ with the highest mortality. Phenotype assignment was independently associated with outcome, even after adjustment for Charlson Comorbidity Index. Phenotype distribution and outcomes in severe COVID-19 followed a similar pattern. CONCLUSIONS: A simplified algorithm successfully identified previously derived phenotypes of bacterial sepsis, which were predictive of outcome. This classification may apply to patients with severe COVID-19 with prognostic implications.

[Establishment and evaluation of a nomogram model for predicting the risk of sepsis in diabetic foot patients].

OBJECTIVE: To establish a nomogram model for predicting the risk of sepsis in diabetic foot patients, and to provide reference for clinical prevention and treatment. METHODS: The clinical data of 430 patients with diabetic foot who were hospitalized in Chu Hsien-I Memorial Hospital of Tianjin Medical University from January 2022 to March 2023 were reviewed and collected, including age, gender, past medical history, smoking and drinking history, family history, diabetes course, Texas grade of diabetic foot and laboratory indicators within 24 hours after admission. Patients were divided into sepsis group and non-sepsis group according to the presence or absence of sepsis during hospitalization. The differences in clinical data between the two groups were compared. Multivariate Logistic regression analysis was used to screen the influencing factors of sepsis in patients with diabetic foot during hospitalization, and a nomogram predictive model was established. The performance of the prediction model was evaluated by receiver operator characteristic curve (ROC curve), calibration curve and decision curve analysis (DCA). Internal validation was performed by using Bootstrap method. RESULTS: A total of 430 patients were enrolled, among which 90 patients developed sepsis during hospitalization and 340 patients did not. There were statistically significant differences in diabetes course, Texas grade of diabetic foot, white blood cell count (WBC), neutrophil count (NEU), lymphocyte count (LYM), neutrophil to lymphocyte ratio (NLR), hemoglobin (Hb), albumin (Alb), glycosylated hemoglobin (HbA1c), C-reactive protein (CRP), and blood urea nitrogen (BUN) between the two groups. Multivariate Logistic regression analysis showed that diabetes course [odds ratio (OR) = 2.774, 95% confidence interval (95%CI) was 1.053-7.308, P = 0.039], Texas grade of diabetic foot (OR = 2.312, 95%CI was 1.014-5.273, P = 0.046), WBC (OR = 1.160, 95%CI was 1.042-1.291, P = 0.007), HbA1c (OR = 1.510, 95%CI was 1.278-1.784, P < 0.001), CRP (OR = 1.007, 95%CI was 1.000-1.014, P = 0.036) were independent risk factors for sepsis in patients with diabetic foot during hospitalization, while Alb was a protective factor (OR = 0.885, 95%CI was 0.805-0.972, P = 0.011). A nomogram predictive model was constructed based on the above 6 indicators. The ROC curve showed that the area under ROC curve (AUC) of the nomogram predictive model for identifying the sepsis patients was 0.919 (95%CI was 0.889-0.948). The AUC of the nomogram predictive model after internal verification was 0.918 (95%CI was 0.887-0.946). Hosmer-Lemeshow test showed χ 2 = 2.978, P = 0.936, indicating that the calibration degree of the predictive model was good. Calibration curve showed that the predicted probability of sepsis was in good agreement with the actual probability. DCA curve showed that the nomogram predictive model had good clinical usefulness. CONCLUSIONS: The nomogram predictive model based on the risk factors of diabetes course, Texas grade of diabetic foot, WBC, HbA1c, CRP and Alb has good predictive value for the occurrence of sepsis in patients with diabetic foot during hospitalization, which is helpful for clinical screening of the possibility of diabetic foot patients progressing to sepsis, and timely personalized intervention for different patients.

[Predictive value of plasma exosome count for the prognosis in septic patients].

OBJECTIVE: To investigate the predictive value of plasma exosome count for the prognosis of patients with sepsis. METHODS: A prospective observational study was conducted. The patients with sepsis admitted to intensive care unit (ICU) of Zhejiang Hospital from November 2020 to December 2021 were enrolled as the study subjects. On the 1st day of admission to the ICU, the patient's gender, age, underlying disease, infection site, mean arterial pressure (MAP) and severity scores were recorded, and venous blood was taken for detecting the blood routine, blood biochemistry, and procalcitonin (PCT), and arterial blood was taken for blood gas analysis, simultaneously, the patient's noradrenaline (NA) dosage was recorded. On the 1st, 3rd, 5th, and 7th day of ICU admission, plasma exosomes were extracted, and the number of exosomes was detected by nanoparticle tracking analyzer. The endpoint of observation was the death of the patient 28 days after admission to the ICU. The differences in baseline data and plasma exosome counts of patients with different 28-day prognosis were analyzed and compared. The Spearman correlation method was used to analyze the correlation between plasma exosome counts and other clinical indicators. Binary multivariate Logistic regression analysis was used to screen the 28-day death risk factors of septic patients. The receiver operator characteristic curve (ROC curve) was plotted to analyze the predictive value of each index on the 28-day death of septic patients. The Kaplan-Meier method was used to analyze the 28-day survival curve. RESULTS: A total of 26 patients with sepsis were enrolled, of whom 21 survived and 5 died on the 28th day. Compared with the survival group, the patients in the death group had lower MAP, higher sequential organ failure assessment (SOFA) score, acute physiology and chronic health evaluation II (APACHE II) score, white blood cell count (WBC), cardiac troponin I (cTnI), and worse oxygenation. The plasma exosome count on the 1st day of ICU admission in the death group was significantly higher than that in the survival group (×1015/L: 16.96±9.11 vs. 5.20±2.42, P < 0.05). Subsequently, the plasma exosome counts in both groups continued to decrease, and there was no statistically significant difference between the two groups. Spearman correlation analysis showed that the plasma exosome count on the 1st day of ICU admission in septic patients was significantly positively correlated with SOFA score, APACHE II score, blood lactic acid (Lac), alanine aminotransferase (ALT) and NA dosage (r values were 0.572, 0.585, 0.463, 0.411, 0.696, all P < 0.05), and it significantly negatively correlated with MAP and oxygenation index (PaO2/FiO2; r values were -0.392 and -0.496, both P < 0.05). Multivariate Logistic regression analysis showed that plasma exosome count on the 1st day of ICU admission was an independent risk factor for 28-day death in septic patients [odds ratio (OR) = 1.385, 95% confidence interval (95%CI) was 1.075-1.785, P = 0.012]. ROC curve analysis showed that the area under the ROC curve (AUC) of plasma exosome count on the 1st day of ICU admission for predicting 28-day death in septic patients was 0.800 (95%CI was 0.449-1.000); when the optimal cut-off value was 14.50×1015/L, the sensitivity was 80.0% and the specificity was 100%. According to the optimal cut-off value of 1-day plasma exosome count, the patients were divided into two groups for Kaplan-Meier survival curve analysis, and the results showed that the cumulative survival rate of patients with plasma exosome count < 14.50×1015/L was significantly higher than that of patients with plasma exosome count ≥ 14.50×1015/L (Log-Rank test: χ 2 = 19.100, P < 0.001). CONCLUSIONS: The plasma exosome count of septic patients is significantly increased on the 1st day of admission to the ICU, which is related to the severity, and can predict the risk of death at 28 days.

[Exploring the optimal range of pulse oxygen saturation in patients with sepsis: a retrospective study based on MIMIC- IV data].

OBJECTIVE: To explore the optimal pulse oxygen saturation (SpO2) range during hospitalization for patients with sepsis. METHODS: A case-control study design was employed. Demographic information, vital signs, comorbidities, laboratory parameters, critical illness scores, clinical treatment information, and clinical outcomes of sepsis patients were extracted from the Medical Information Mart for Intensive Care- IV (MIMIC- IV). A generalized additive model (GAM) combined with a Loess smoothing function was employed to analyze and visualize the nonlinear relationship between SpO2 levels during hospitalization and in-hospital all-cause mortality. The optimal range of SpO2 was determined, and Logistic regression model along with Kaplan-Meier curve were utilized to validate the association between the determined range of SpO2 and in-hospital all-cause mortality. RESULTS: A total of 5 937 patients met the inclusion criteria, among whom 1 191 (20.1%) died during hospitalization. GAM analysis revealed a nonlinear and U-shaped relationship between SpO2 levels and in-hospital all-cause mortality among sepsis patients during hospitalization. Multivariable Logistic regression analysis further confirmed that patients with SpO2 levels between 0.96 and 0.98 during hospitalization had a decreased mortality compared to those with SpO2 < 0.96 [hypoxia group; odds ratio (OR) = 2.659, 95% confidence interval (95%CI) was 2.190-3.229, P < 0.001] and SpO2 > 0.98 (hyperoxia group; OR = 1.594, 95%CI was 1.337-1.900, P < 0.001). Kaplan-Meier survival curve showed that patients with SpO2 between 0.96 and 0.98 during hospitalization had a higher probability of survival than those patient with SpO2 < 0.96 and SpO2 > 0.98 (Log-Rank test: χ 2 = 113.400, P < 0.001). Sensitivity analyses demonstrated that, with the exception of subgroups with smaller sample sizes, across the strata of age, gender, body mass index (BMI), admission type, race, heart rate, systolic blood pressure, diastolic blood pressure, mean arterial pressure, respiratory rate, body temperature, myocardial infarction, congestive heart failure, cerebrovascular disease, chronic liver disease, diabetes mellitus, sequential organ failure assessment (SOFA), simplified acute physiology score II (SAPS II), systemic inflammatory response syndrome score (SIRS), and Glasgow coma score (GCS), the mortality of patients with SpO2 between 0.96 and 0.98 was significantly lower than those of patients with SpO2 < 0.96 and SpO2 > 0.98. CONCLUSIONS: During hospitalization, the level of SpO2 among sepsis patients exhibits a U-shaped relationship with in-hospital all-cause mortality, indicating that heightened and diminished oxygen levels are both associated with increased mortality risk. The optimal SpO2 range is determined to be between 0.96 and 0.98.

[Construction and validation of a risk nomogram for sepsis-associated acute kidney injury in intensive care unit].

OBJECTIVE: To construct and validate a nomogram model for predicting sepsis-associated acute kidney injury (SA-AKI) risk in intensive care unit (ICU) patients. METHODS: A retrospective cohort study was conducted. Adult sepsis patients admitted to the department of ICU of the 940th Hospital of Joint Logistic Support Force of PLA from January 2017 to December 2022 were enrolled. Demographic characteristics, clinical data within 24 hours after admission to ICU diagnosis, and clinical outcomes were collected. Patients were divided into training set and validation set according to a 7 : 3 ratio. According to the consensus report of the 28th Acute Disease Quality Initiative Working Group (ADQI 28), the data were analyzed with serum creatinine as the parameter and AKI occurrence 7 days after sepsis diagnosis as the outcome. Lasso regression analysis and univariate and multivariate Logistic regression analysis were performed to construct the nomogram prediction model for SA-AKI. The discrimination and accuracy of the model were evaluated by the Hosmer-Lemeshow test, receiver operator characteristic curve (ROC curve), decision curve analysis (DCA), and clinical impact curve (CIC). RESULTS: A total of 247 sepsis patients were enrolled, 184 patients developed SA-AKI (74.49%). The number of AKI patients in the training and validation sets were 130 (75.58%) and 54 (72.00%), respectively. After Lasso regression analysis and univariate and multivariate Logistic regression analysis, four independent predictive factors related to the occurrence of SA-AKI were selected, namely procalcitonin (PCT), prothrombin activity (PTA), platelet distribution width (PDW), and uric acid (UA) were significantly associated with the onset of SA-AKI, the odds ratio (OR) and 95% confidence interval (95%CI) was 1.03 (1.01-1.05), 0.97 (0.55-0.99), 2.68 (1.21-5.96), 1.01 (1.00-1.01), all P < 0.05, respectively. A nomogram model was constructed using the above four variables. ROC curve analysis showed that the area under the curve (AUC) was 0.869 (95%CI was 0.870-0.930) in the training set and 0.710 (95%CI was 0.588-0.832) in the validation set. The P-values of the Hosmer-Lemeshow test were 0.384 and 0.294, respectively. In the training set, with an optimal cut-off value of 0.760, a sensitivity of 77.5% and specificity of 88.1% were achieved. Both DCA and CIC plots demonstrated the model's good clinical utility. CONCLUSIONS: A nomogram model based on clinical indicators of sepsis patients admitted to the ICU within 24 hours could be used to predict the risk of SA-AKI, which would be beneficial for early identification and treatment on SA-AKI.

Advancing quantitative PCR with color cycle multiplex amplification.

Quantitative PCR (qPCR) is the gold standard for detection and quantitation of known DNA targets, but the scarcity of spectrally distinct fluorophores and filter sets limits the number of detectable targets. Here, we introduce color cycle multiplex amplification (CCMA) to significantly increase the number of detectable DNA targets in a single qPCR reaction using standard instrumentation. In CCMA, presence of one DNA target species results in a pre-programmed pattern of fluorescence increases. This pattern is distinguished by cycle thresholds (Cts) through rationally designed delays in amplification. For example, we design an assay wherein Staphylococcus aureus sequentially induces FAM, then Cy5.5, then ROX fluorescence increases with more than 3 cycles between each signal. CCMA offers notably higher potential for multiplexing because it uses fluorescence permutation rather than combination. With 4 distinct fluorescence colors, CCMA theoretically allows the detection of up to 136 distinct DNA target sequences using fluorescence permutation. Experimentally, we demonstrated a single-tube qPCR assay screening 21 sepsis-related bacterial DNA targets in samples of blood, sputum, pleural effusion and bronchoalveolar lavage fluid, with 89% clinical sensitivity and 100% clinical specificity, showing its potential as a powerful tool for advanced quantitative screening in molecular diagnostics.

Development and optimization of a diluted whole blood ELISpot assay to test immune function.

Sepsis remains a leading cause of death worldwide with no proven immunomodulatory therapies. Stratifying Patient Immune Endotypes in Sepsis ('SPIES') is a prospective, multicenter observational study testing the utility of ELISpot as a functional bioassay specifically measuring cytokine-producing cells after stimulation to identify the immunosuppressed endotype, predict clinical outcomes in septic patients, and test potential immune stimulants for clinical development. Most ELISpot protocols call for the isolation of PBMC prior to their inclusion in the assay. In contrast, we developed a diluted whole blood (DWB) ELISpot protocol that has been validated across multiple laboratories. Heparinized whole blood was collected from healthy donors and septic patients and tested under different stimulation conditions to evaluate the impact of blood dilution, stimulant concentration, blood storage, and length of stimulation on ex vivo IFNγ and TNFα production as measured by ELISpot. We demonstrate a dynamic range of whole blood dilutions that give a robust ex vivo cytokine response to stimuli. Additionally, a wide range of stimulant concentrations can be utilized to induce cytokine production. Further modifications demonstrate anticoagulated whole blood can be stored up to 24 h at room temperature without losing significant functionality. Finally, we show ex vivo stimulation can be as brief as 4 h allowing for a substantial decrease in processing time. The data demonstrate the feasibility of using ELISpot to measure the functional capacity of cells within DWB under a variety of stimulation conditions to inform clinicians on the extent of immune dysregulation in septic patients.