A comparative analysis of sivelestat sodium hydrate and ulinastatin combination therapy in the treatment of sepsis with acute respiratory distress syndrome.

OBJECTIVE: This comparative analysis aimed to investigate the efficacy of Sivelestat Sodium Hydrate (SSH) combined with Ulinastatin (UTI) in the treatment of sepsis with acute respiratory distress syndrome (ARDS). METHODS: A control group and an observation group were formed with eighty-four cases of patients with sepsis with ARDS, with 42 cases in each group. The control group was intravenously injected with UTI based on conventional treatment, and the observation group was injected with SSH based on the control group. Both groups were treated continuously for 7 days, and the treatment outcomes and efficacy of both groups were observed. The Murray Lung Injury Score (MLIS), Sequential Organ Failure Assessment (SOFA), and Acute Physiology and Chronic Health Evaluation II (APACHE II) were compared. Changes in respiratory function, inflammatory factors, and oxidative stress indicators were assessed. The occurrence of adverse drug reactions was recorded. RESULTS: The total effective rate in the observation group (95.24%) was higher than that in the control group (80.95%) (P < 0.05). The mechanical ventilation time, intensive care unit (ICU) hospitalization time, and duration of antimicrobial medication in the observation group were shorter and multiple organ dysfunction syndrome incidence was lower than those in the control group (P < 0.05). The mortality rate of patients in the observation group (35.71%) was lower than that in the control group (52.38%), but there was no statistically significant difference between the two groups (P > 0.05). MLIS, SOFA, and APACHE II scores in the observation group were lower than the control group (P < 0.05). After treatment, respiratory function, inflammation, and oxidative stress were improved in the observation group (P < 0.05). Adverse reactions were not significantly different between the two groups (P > 0.05). CONCLUSION: The combination of SSH plus UTI improves lung injury and pulmonary ventilation function, and reduces inflammation and oxidative stress in patients with sepsis and ARDS.

Development and validation of risk prediction model for bacterial infections in acute liver failure patients.

Infections significantly increase mortality in acute liver failure (ALF) patients, and there are no risk prediction models for early diagnosis and treatment of infections in ALF patients. This study aims to develop a risk prediction model for bacterial infections in ALF patients to guide rational antibiotic therapy. The data of ALF patients admitted to the Second Hospital of Hebei Medical University in China from January 2017 to January 2022 were retrospectively analyzed for training and internal validation. Patients were selected according to the updated 2011 American Association for the Study of Liver Diseases position paper on ALF. Serological indicators and model scores were collected within 24 h of admission. New models were developed using the multivariate logistic regression analysis. An optimal model was selected by receiver operating characteristic (ROC) analysis, Hosmer-Lemeshow test, the calibration curve, the Brier score, the bootstrap resampling, and the decision curve analysis. A nomogram was plotted to visualize the results. A total of 125 ALF patients were evaluated and 79 were included in the training set. The neutrophil-to-lymphocyte ratio and sequential organ failure assessment (SOFA) were integrated into the new model as independent predictive factors. The new SOFA-based model outperformed other models with an area under the ROC curve of 0.799 [95% confidence interval (CI): 0.652-0.926], the superior calibration and predictive performance in internal validation. High-risk individuals with a nomogram score ≥26 are recommended for antibiotic therapy. The new SOFA-based model demonstrates high accuracy and clinical utility in guiding antibiotic therapy in ALF patients.

The value of IL-6, PCT, qSOFA, NEWS, and SIRS to predict septic shock after Percutaneous nephrolithotomy.

BACKGROUND: There are numerous methods available for predicting sepsis following Percutaneous Nephrolithotomy. This study aims to compare the predictive value of Quick Sequential Organ Failure Assessment (qSOFA), Systemic Inflammatory Response Syndrome (SISR), National Early Warning Score (NEWS), interleukin-6 (IL-6), and procalcitonin (PCT) for septicemia. METHODS: Patients who underwent percutaneous nephrolithotomy were included in the study and divided into a control group and a septic shock group. The effectiveness of qSOFA, SIRS, NEWS, Interleukin-6, and Procalcitonin was assessed, with Receiver Operating Characteristic curves and Area Under the Curve used to compare the predictive accuracy of these four indicators. RESULTS: Among the 401 patients, 16 cases (3.99%) developed septic shock. Females, elderly individuals, and patients with positive urine culture and positive nitrite in urine were found to be more susceptible to septic shock. PCT, IL-6, SIRS, NEWS, qSOFA, and surgical time were identified as independent risk factors for septic shock. The cutoff values are as follows: qSOFA score > 0.50, SIRS score > 2.50, NEWS score > 2.50, and IL-6 > 264.00 pg/ml. Among the 29 patients identified by IL-6 as having sepsis, 16 were confirmed to have developed sepsis. The qSOFA identified 63 septicemia cases, with 16 confirmed to have developed septicemia; NEWS identified 122 septicemia cases, of which 14 cases actually developed septicemia; SIRS identified 128 septicemia patients, with 16 confirmed to have developed septicemia. In terms of predictive ability, IL-6 (AUC 0.993, 95% CI 0.985 ~ 1) demonstrated a higher predictive accuracy compared to qSOFA (AUC 0.952, 95% CI 0.928 ~ 0.977), NEWS (AUC 0.824, 95% CI 0.720 ~ 0.929) and SIRS (AUC 0.928, 95% CI 0.888 ~ 0.969). CONCLUSIONS: IL-6 has higher accuracy in predicting septic shock after PCNL compared to qSOFA, SIRS, and NEWS.

Heparin-binding protein as a biomarker for the diagnosis of sepsis in the intensive care unit: a retrospective cross-sectional study in China.

OBJECTIVES: This study aims to investigate the diagnostic value of heparin-binding protein (HBP) in sepsis and develop a sepsis diagnostic model incorporating HBP with key biomarkers and disease-related scores for rapid, and accurate diagnosis of sepsis in the intensive care unit (ICU). DESIGN: Clinical retrospective cross-sectional study. SETTING: A comprehensive teaching tertiary hospital in China. PARTICIPANTS: Adult patients (aged ≥18 years) who underwent HBP testing or whose blood samples were collected when admitted to the ICU. MAIN OUTCOME MEASURES: HBP, C reactive protein (CRP), procalcitonin (PCT), white blood cell count (WBC), interleukin-6 (IL-6), lactate (LAC), Acute Physiology and Chronic Health Evaluation II (APACHE II) and Sequential Organ Failure Assessment (SOFA) score were recorded. RESULTS: Between March 2019 and December 2021, 326 patients were enrolled in this study. The patients were categorised into a non-infection group (control group), infection group, sepsis group and septic shock group based on the final diagnosis. The HBP levels in the sepsis group and septic shock group were 45.7 and 69.0 ng/mL, respectively, which were significantly higher than those in the control group (18.0 ng/mL) and infection group (24.0 ng/mL) (p<0.001). The area under the curve (AUC) value of HBP for diagnosing sepsis was 0.733, which was lower than those corresponding to PCT, CRP and SOFA but higher than those of IL-6, LAC and APACHE II. Multivariate logistic regression analysis identified HBP, PCT, CRP, IL-6 and SOFA as valuable indicators for diagnosing sepsis. A sepsis diagnostic model was constructed based on these indicators, with an AUC of 0.901, a sensitivity of 79.7% and a specificity of 86.9%. CONCLUSIONS: HBP could serve as a biomarker for the diagnosis of sepsis in the ICU. Compared with single indicators, the sepsis diagnostic model constructed using HBP, PCT, CRP, IL-6 and SOFA further enhanced the diagnostic performance of sepsis.

Explainable Deep Learning Model for Predicting Serious Adverse Events in Hospitalized Geriatric Patients Within 72 Hours.

Background: The global aging population presents a significant challenge, with older adults experiencing declining physical and cognitive abilities and increased vulnerability to chronic diseases and adverse health outcomes. This study aims to develop an interpretable deep learning (DL) model to predict adverse events in geriatric patients within 72 hours of hospitalization. Methods: The study used retrospective data (2017-2020) from a major medical center in Taiwan. It included non-trauma geriatric patients who visited the emergency department and were admitted to the general ward. Data preprocessing involved collecting prognostic factors like vital signs, lab results, medical history, and clinical management. A deep feedforward neural network was developed, and performance was evaluated using accuracy, sensitivity, specificity, positive predictive value (PPV), and area under the receiver operating characteristic curve (AUC). Model interpretation utilized the Shapley Additive Explanation (SHAP) technique. Results: The analysis included 127,268 patients, with 2.6% experiencing imminent intensive care unit transfer, respiratory failure, or death during hospitalization. The DL model achieved AUCs of 0.86 and 0.84 in the validation and test sets, respectively, outperforming the Sequential Organ Failure Assessment (SOFA) score. Sensitivity and specificity values ranged from 0.79 to 0.81. The SHAP technique provided insights into feature importance and interactions. Conclusion: The developed DL model demonstrated high accuracy in predicting serious adverse events in geriatric patients within 72 hours of hospitalization. It outperformed the SOFA score and provided valuable insights into the model's decision-making process.

[Related factors of euthyroid sick syndrome in patients with sepsis].

OBJECTIVE: To evaluate the prevalence of euthyroid sick syndrome (ESS) in sepsis patients and to explore its influencing factors. METHODS: In the study, 365 patients diagnosed with sepsis in the emergency critical care department of Shanghai First People's Hospital from January 2017 to January 2023 were retrospectively enrolled. The patients were divided into ESS and non-ESS groups based on whether the patients were complicated with ESS.Baseline variables and relevant clinical data of the enrolled patients were collected. The prevalence of ESS in sepsis patients and its influencing factors were evaluated by multivariate Logistic regression analysis, and the 30-day survival rates were compared between the two groups. The optimal cutoff value for free triiodothyronine (FT3) was explored to predict death in the patients with sepsis. RESULTS: There were 103 sepsis patients with ESS, accounting for 28.2% of the total cases. The severity of sepsis in ESS group was significantly higher than that in non-ESS group (P < 0.05). The acute physiology and chronic health evaluationⅡ(APACHEⅡ)score and sequential organ failure assessment (SOFA) score of ESS group were significantly higher than those of non-ESS group (P < 0.05). C-reactive protein (CRP), procalcitonin (PCT), serum amyloid A (SAA) and interleukin-6 (IL-6) in ESS group were higher than those in non-ESS group. total cholesterol(TC)and high-density liptein cholesterol(HDL-C)in ESS group were lower than those in non-ESS group, and the differences were statistically significant (P < 0.05).Multivariate Logistic regression analysis showed that PCT, IL-6, CRP, SAA and activated partial thromboplatin time (APTT) were independent risk factors for ESS in the sepsis patients (OR values were 1.105, 1.006, 1.005, 1.009 and 1.033, respectively; 95% CI were 1.044-1.170, 1.001-1.012, 1.001-1.009, 1.005-1.014, 1.004-1.062, respectively, P < 0.05).The 30-day survival rate in ESS group was significantly lower than that in non-ESS group, the Long-rank chi-square test value was 16.611, and the difference was statistically significant (P < 0.05).The receiver operation characteristic area under the curve (AUCROC)of FT3 predicted death in the patients with sepsis was 0.924 (95% CI 0.894-0.954). The serum FT3 cutoff point was 3.705 pmol/L, the specificity was 0.868, and the sensitivity was 0.950. CONCLUSION: In this study, the incidence of ESS in sepsis patients was determined to be 28.2% with poor prognosis. The results showed that PCT, IL-6, CRP, SAA and APTT were independent risk factors for ESS in sepsis patients, while HDL-C was a protective factor (P < 0.05). FT3 is a novel potential biomarker for predicting death in patients with sepsis.

Neutrophil-to-lymphocyte Ratio as a Marker for Diagnosis and Prognostication of Sepsis.

PURPOSE: Exploring the ideal marker for early diagnosis and prognosis of sepsis is crucial due to limitations of available sepsis indicators. Hence, we aimed to evaluate the neutrophil-to-lymphocyte ratio (NLR) as a diagnostic and prognostic marker of sepsis. MATERIALS AND METHODS: This prospective case-control study was conducted at a tertiary care teaching public hospital. NLR values among cases and controls were compared for diagnosis. Among cases, serial trends in NLR values, outcome (survival or death), and various parameters [such as Sequential Organ Failure Assessment (SOFA) score, duration of intensive care unit (ICU) stay, etc.] were compared between survivors and nonsurvivors for prognosis. Analysis was performed using MS Excel and PSPP version 1.0.1. RESULTS: A total of 120 patients (60 cases and 60 controls) were analyzed. The NLR among cases was significantly higher (p = 1.31 × 10-16) than in controls. Using binary logistic regression, a high NLR was found to be a statistically significant predictor of sepsis category (p = 2.25 × 10-5). The association of various variables among survivors and nonsurvivors of cases showed statistically significant differences: NLR (p = 5.29 × 10-5), mean = 13.27, interquartile range (IQR) = 5.90, z-value = -4.042), C-reactive protein (CRP) (p = 4.80 × 10-7), mean = 74.40, IQR = 21.30, z-value = -5.034), D-dimer (p = 4.32 × 10-8), mean = 7.09, IQR = 0.88, z-value = -5.477), SOFA score (p = 0.00118, mean = 8.50, IQR = 3.00, z-value = -3.244), and duration of hospital stay (p = 0.03578, mean = 13.45, IQR = 8.00, z-value = -2.099). CONCLUSION: The NLR emerges as a valuable marker for both diagnosis and prognosis in sepsis. Elevated NLR levels aid in diagnosing sepsis at very early stages, and the trend of NLR demonstrates a dynamic course throughout the disease process. Persistently elevated NLR and high NLR values correlate with poor outcomes in sepsis. Additionally, NLR can be correlated with other prognostic markers of sepsis and mortality. Therefore, we recommend the utilization of NLR as a quick, easy, and cost-effective marker for both early diagnosis and regular prognostication of sepsis.

[Development and validation of a nomogram for predicting 3-month mortality risk in patients with sepsis-associated acute kidney injury].

OBJECTIVE: To develop and evaluate a nomogram prediction model for the 3-month mortality risk of patients with sepsis-associated acute kidney injury (S-AKI). METHODS: Based on the American Medical Information Mart for Intensive Care- IV (MIMIC- IV), clinical data of S-AKI patients from 2008 to 2021 were collected. Initially, 58 relevant predictive factors were included, with all-cause mortality within 3 months as the outcome event. The data were divided into training and testing sets at a 7 : 3 ratio. In the training set, univariate Logistic regression analysis was used for preliminary variable screening. Multicollinearity analysis, Lasso regression, and random forest algorithm were employed for variable selection, combined with the clinical application value of variables, to establish a multivariable Logistic regression model, visualized using a nomogram. In the testing set, the predictive value of the model was evaluated through internal validation. The receiver operator characteristic curve (ROC curve) was drawn, and the area under the curve (AUC) was calculated to evaluate the discrimination of nomogram model and Oxford acute severity of illness score (OASIS), sequential organ failure assessment (SOFA), and systemic inflammatory response syndrome score (SIRS). The calibration curve was used to evaluate the calibration, and decision curve analysis (DCA) was performed to assess the net benefit at different probability thresholds. RESULTS: Based on the survival status at 3 months after diagnosis, patients were divided into 7 768 (68.54%) survivors and 3 566 (31.46%) death. In the training set, after multiple screenings, 7 variables were finally included in the nomogram model: Logistic organ dysfunction system (LODS), Charlson comorbidity index, urine output, international normalized ratio (INR), respiratory support mode, blood urea nitrogen, and age. Internal validation in the testing set showed that the AUC of nomogram model was 0.81 [95% confidence interval (95%CI) was 0.80-0.82], higher than the OASIS score's 0.70 (95%CI was 0.69-0.71) and significantly higher than the SOFA score's 0.57 (95%CI was 0.56-0.58) and SIRS score's 0.56 (95%CI was 0.55-0.57), indicating good discrimination. The calibration curve demonstrated that the nomogram model's calibration was better than the OASIS, SOFA, and SIRS scores. The DCA curve suggested that the nomogram model's clinical net benefit was better than the OASIS, SOFA, and SIRS scores at different probability thresholds. CONCLUSIONS: A nomogram prediction model for the 3-month mortality risk of S-AKI patients, based on clinical big data from MIMIC- IV and including seven variables, demonstrates good discriminative ability and calibration, providing an effective new tool for assessing the prognosis of S-AKI patients.

Clinical complexity of an Italian cardiovascular intensive care unit: the role of mortality and severity risk scores.

AIMS: The identification of patients at greater mortality risk of death at admission into an intensive cardiovascular care unit (ICCU) has relevant consequences for clinical decision-making. We described patient characteristics at admission into an ICCU by predicted mortality risk assessed with noncardiac intensive care unit (ICU) and evaluated their performance in predicting patient outcomes. METHODS: A total of 202 consecutive patients (130 men, 75 ±â€Š12 years) were admitted into our tertiary-care ICCU in a 20-week period. We evaluated, on the first 24 h data, in-hospital mortality risk according to Acute Physiology and Chronic Health Evaluation II (APACHE II) and Simplified Acute Physiology Score 3 (SAPS 3); Sepsis related Organ Failure Assessment (SOFA) Score and the Mayo Cardiac intensive care unit Admission Risk Score (M-CARS) were also calculated. RESULTS: Predicted mortality was significantly lower than observed (5% during ICCU and 7% at discharge) for APACHE II and SAPS 3 (17% for both scores). Mortality risk was associated with older age, more frequent comorbidities, severe clinical presentation and complications. The APACHE II, SAPS 3, SOFA and M-CARS had good discriminative ability in distinguishing deaths and survivors with poor calibration of risk scores predicting mortality. CONCLUSION: In a recent contemporary cohort of patients admitted into the ICCU for a variety of acute and critical cardiovascular conditions, scoring systems used in general ICU had good discrimination for patients' clinical severity and mortality. Available scores preserve powerful discrimination but the overestimation of mortality suggests the importance of specific tailored scores to improve risk assessment of patients admitted into ICCUs.

Restrictive calcium replacement in septic shock: a multicenter before-after intervention study. / Reposición restrictiva de calcio en pacientes con shock séptico: estudio de intervención antes-después.

OBJECTIVES: To study the impact of a restrictive calcium replacement protocol in comparison with a liberal one in patients with septic shock. MATERIAL AND METHODS: Multicenter retrospective before-after study that estimated the impact of implementing a restrictive calcium replacement protocol in patients with septic shock. Patients admitted to an intensive care unit between May 2019 and April 2021 were assigned to liberal calcium replacement, and those admitted between May 2021 and April 2022 were assigned to a restrictive protocol. The primary outcome measure was 28-day mortality. Patients were matched with propensity scores. RESULTS: A total of 644 patients were included; liberal replacement was used in 453 patients and the restrictive replacement in 191. We paired 553 patients according to propensity scores, 386 in the liberal group and 167 in the restrictive group. Mortality did not differ significantly between the groups at 28 days (35.3% vs 32.3%, respectively; hazard ratio, 0.97; 95% CI, 0.72-1.29) or after resolution of septic shock (81.5% vs 83.8%; hazard ratio, 0.89; 95% CI, 0.73-1.09). Nor did scores on the Sepsis-related Organ Failure Assessment scale differ (2.1 vs 2.6; P = 0.20). CONCLUSION: The implementation of a restrictive calcium replacement protocol in patients with septic shock was not associated with a decrease in 28-day mortality in comparison with use of a liberal protocol. However, we were able to reduce calcium replacement without adverse effects.

OBJETIVO: Investigar el efecto de un protocolo de reposición restrictiva de calcio frente a una estrategia liberal en pacientes con shock séptico. METODO: Estudio multicéntrico, antes-después y retrospectivo que evaluó el efecto de la implementación de un protocolo de reposición restrictiva de calcio en pacientes con shock séptico. Los pacientes que ingresaron en unidades de cuidados intensivos (UCI) entre mayo de 2019 y abril de 2021 se asignaron al grupo con administración liberal, y los que se presentaron entre mayo de 2021 y abril de 2022 ­tras la implementación del protocolo­ al grupo con administración restrictiva. La variable de resultado principal fue la mortalidad a 28 días. Se realizó un emparejamiento por puntuación de propensión. RESULTADOS: Se incluyeron 644 pacientes, 453 en el grupo liberal y 191 en el grupo restrictivo. De los que 553 se emparejaron (386 en el grupo liberal, y 167 en el grupo restrictivo). No hubo diferencias entre los dos grupos en la mortalidad a los 28 días (35,3% vs 32,3%; HR: 0,97; IC 95%: 0,72-1,29), en la finalización del shock (81,5% vs a 83,8%; HR: 0,89; IC 95%: 0,73-1,09) ni en la puntuación de la escala SOFA (2,1 vs 2,6; p = 0,20). CONCLUSIONES: La implementación de un protocolo de administración restrictiva de calcio, en pacientes con shock séptico, no se asoció a una disminución de la mortalidad a los 28 días en comparación con una administración liberal. No obstante, la reposición de calcio podría reducirse sin efectos adversos.

SOFA score performs worse than age for predicting mortality in patients with COVID-19.

The use of the Sequential Organ Failure Assessment (SOFA) score, originally developed to describe disease morbidity, is commonly used to predict in-hospital mortality. During the COVID-19 pandemic, many protocols for crisis standards of care used the SOFA score to select patients to be deprioritized due to a low likelihood of survival. A prior study found that age outperformed the SOFA score for mortality prediction in patients with COVID-19, but was limited to a small cohort of intensive care unit (ICU) patients and did not address whether their findings were unique to patients with COVID-19. Moreover, it is not known how well these measures perform across races. In this retrospective study, we compare the performance of age and SOFA score in predicting in-hospital mortality across two cohorts: a cohort of 2,648 consecutive adult patients diagnosed with COVID-19 who were admitted to a large academic health system in the northeastern United States over a 4-month period in 2020 and a cohort of 75,601 patients admitted to one of 335 ICUs in the eICU database between 2014 and 2015. We used age and the maximum SOFA score as predictor variables in separate univariate logistic regression models for in-hospital mortality and calculated area under the receiver operator characteristic curves (AU-ROCs) and area under precision-recall curves (AU-PRCs) for each predictor in both cohorts. Among the COVID-19 cohort, age (AU-ROC 0.795, 95% CI 0.762, 0.828) had a significantly better discrimination than SOFA score (AU-ROC 0.679, 95% CI 0.638, 0.721) for mortality prediction. Conversely, age (AU-ROC 0.628 95% CI 0.608, 0.628) underperformed compared to SOFA score (AU-ROC 0.735, 95% CI 0.726, 0.745) in non-COVID-19 ICU patients in the eICU database. There was no difference between Black and White COVID-19 patients in performance of either age or SOFA Score. Our findings bring into question the utility of SOFA score-based resource allocation in COVID-19 crisis standards of care.

Construction and evaluation of short-term and long-term mortality risk prediction model for patients with sepsis based on MIMIC-IV database. / 基于MIMIC-IVæž„å»ºåŠè¯„ä¼°è„“æ¯’ç—‡æ‚£è€ è¿‘æœŸå’Œè¿œæœŸæ­»äº¡é£Žé™©é¢„æµ‹æ¨¡åž‹.

OBJECTIVES: Given the high incidence and mortality rate of sepsis, early identification of high-risk patients and timely intervention are crucial. However, existing mortality risk prediction models still have shortcomings in terms of operation, applicability, and evaluation on long-term prognosis. This study aims to investigate the risk factors for death in patients with sepsis, and to construct the prediction model of short-term and long-term mortality risk. METHODS: Patients meeting sepsis 3.0 diagnostic criteria were selected from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database and randomly divided into a modeling group and a validation group at a ratio of 7꞉3. Baseline data of patients were analyzed. Univariate Cox regression analysis and full subset regression were used to determine the risk factors of death in patients with sepsis and to screen out the variables to construct the prediction model. The time-dependent area under the curve (AUC), calibration curve, and decision curve were used to evaluate the differentiation, calibration, and clinical practicability of the model. RESULTS: A total of 14 240 patients with sepsis were included in our study. The 28-day and 1-year mortality were 21.45% (3 054 cases) and 36.50% (5 198 cases), respectively. Advanced age, female, high sepsis-related organ failure assessment (SOFA) score, high simplified acute physiology score II (SAPS II), rapid heart rate, rapid respiratory rate, septic shock, congestive heart failure, chronic obstructive pulmonary disease, liver disease, kidney disease, diabetes, malignant tumor, high white blood cell count (WBC), long prothrombin time (PT), and high serum creatinine (SCr) levels were all risk factors for sepsis death (all P<0.05). Eight variables, including PT, respiratory rate, body temperature, malignant tumor, liver disease, septic shock, SAPS II, and age were used to construct the model. The AUCs for 28-day and 1-year survival were 0.717 (95% CI 0.710 to 0.724) and 0.716 (95% CI 0.707 to 0.725), respectively. The calibration curve and decision curve showed that the model had good calibration degree and clinical application value. CONCLUSIONS: The short-term and long-term mortality risk prediction models of patients with sepsis based on the MIMIC-IV database have good recognition ability and certain clinical reference significance for prognostic risk assessment and intervention treatment of patients.

[Early diagnostic value of Presepsin in sepsis: a prospective study on a population with suspected sepsis in fever clinics].

OBJECTIVE: To analyze the early diagnostic value of plasma soluble cluster of differentiation 14 subtype (sCD14-ST, Presepsin) in sepsis in a population with suspected sepsis in fever clinic. METHODS: A prospective observational study was conducted. The patients admitted to the fever clinic of Beijing Chaoyang Hospital from April to December 2022 were enrolled as the study objects. According to sequential organ failure assessment (SOFA) score, the patients were divided into low SOFA score group (SOFA score ≤3) and high SOFA score group (SOFA score > 3). Venous blood was collected at the time of admission. The level of plasma Presepsin was detected by chemiluminescence enzyme-linked immunoassay. The level of plasma procalcitonin (PCT) was detected by enzyme-linked immunofluorescence method. The level of C-reactive protein (CRP) was detected by scattering turbidimetry. White blood cell count (WBC) and neutrophil count (NEUT) were measured by automatic blood cell analyzer. For patients with fear of cold or chills, venous blood of upper limbs was taken for blood culture at the time of admission. The differences in inflammatory biomarkers were compared between the two groups. Binary multivariate Logistic regression analysis was used to screen the early risk factors of sepsis in fever outpatients with suspected sepsis. Receiver operator characteristic curve (ROC curve) was drawn to investigate the early diagnostic value of Presepsin and other inflammatory markers in sepsis, and to analyze the optimal cut-off value. RESULTS: A total of 149 fever outpatients with suspected sepsis were enrolled, including 92 patients with low SOFA score and 57 patients with high SOFA score. Plasma PCT and Presepsin levels in the high SOFA score group were significantly higher than those in the low SOFA score group [PCT (µg/L): 0.77 (0.18, 2.02) vs. 0.22 (0.09, 0.71), Presepsin (ng/L): 1 129.00 (785.50, 1 766.50) vs. 563.00 (460.50, 772.25), both P < 0.01]. There was no significant difference in WBC, NEUT, CRP or positive rate of blood culture between the high and low SOFA score groups [WBC (×109/L): 11.32±5.47 vs. 11.14±5.29, NEUT (×109/L): 9.88±4.89 vs. 9.60±5.10, CRP (mg/L): 54.05 (15.95, 128.90) vs. 46.11 (19.60, 104.60), blood culture positivity rate: 42.3% (11/26) vs. 29.4% (10/34), all P > 0.05]. Multivariate Logistic regression analysis showed that Presepsin was an early risk factor for sepsis in suspected sepsis patients in fever clinics [odds ratio (OR) = 16.96, 95% confidence interval (95%CI) was 6.35-45.29, P = 0.000]. ROC curve analysis showed that the early diagnostic value of Presepsin in sepsis was significantly better than WBC, NEUT, CRP, PCT, and blood culture [the area under the ROC curve (AUC) and 95%CI: 0.832 (0.771-0.899) vs. 0.522 (0.424-0.619), 0.532 (0.435-0.629), 0.533 (0.435-0.632), 0.664 (0.574-0.753), 0.554 (0.458-0.650)]. When the optimal cut-off value of Presepsin was 646.50 ng/L, its sensitivity and positive predictive value were higher than those of WBC, NEUT, CRP, and PCT (sensitivity: 89.5% vs. 38.6%, 68.4%, 38.6%, 57.9%; positive predictive value: 64.6% vs. 44.9%, 44.3%, 47.8%, 55.9%). CONCLUSIONS: Plasma PCT and Presepsin have early diagnostic value for sepsis in suspected sepsis patients in fever clinics, and Presepsin is more sensitive than PCT and can be used as an early marker of sepsis.

Usefulness of the qSOFA score for predicting hospital mortality in cancer patients.

BACKGROUND: The quick Sequential Sepsis-related Organ Failure Assessment (qSOFA) is a score that has been proposed to quickly identify patients at higher risk of death. OBJECTIVE: To describe the usefulness of the qSOFA score to predict in-hospital mortality in cancer patients. MATERIAL AND METHODS: Cross-sectional study carried out between January 2021 and December 2022. Hospital mortality was the dependent variable. The area under the ROC curve (AUC) was calculated to determine the discriminative ability of qSOFA to predict in-hospital mortality. RESULTS: A total of 587 cancer patients were included. A qSOFA score higher than 1 obtained a sensitivity of 57.2%, specificity of 78.5%, a positive predictive value of 55.4% and negative predictive value of 79.7%. The AUC of qSOFA for predicting in-hospital mortality was 0.70. In-hospital mortality of patients with qSOFA scores of 2 and 3 points was 52.7 and 64.4%, respectively. In-hospital mortality was 31.9% (187/587). CONCLUSION: qSOFA showed acceptable discriminative ability for predicting in-hospital mortality in cancer patients.

ANTECEDENTES: El quick Sequential Sepsis-related Organ Failure Assessment (qSOFA) es una puntuación propuesta para identificar de forma rápida a pacientes con mayor probabilidad de morir. OBJETIVO: Describir la utilidad de la puntuación qSOFA para predecir mortalidad hospitalaria en pacientes con cáncer. MATERIAL Y MÉTODOS: Estudio transversal realizado entre enero de 2021 y diciembre de 2022. La mortalidad hospitalaria fue la variable dependiente. Se calculó el área bajo la curva ROC (ABC) para determinar la capacidad discriminativa de qSOFA para predecir mortalidad hospitalaria. RESULTADOS: Se incluyeron 587 pacientes con cáncer. La puntuación qSOFA < 1 obtuvo una sensibilidad de 57.2 %, una especificidad de 78.5 %, un valor predictivo positivo de 55.4 % y un valor predictivo negativo de 79.7 %. El ABC de qSOFA para predecir mortalidad hospitalaria fue de 0.70. La mortalidad hospitalaria de los pacientes con qSOFA de 2 y 3 puntos fue de 52.7 y 64.4 %, respectivamente. La mortalidad hospitalaria fue de 31.9 % (187/587). CONCLUSIÓN: qSOFA mostró capacidad discriminativa aceptable para predecir mortalidad hospitalaria en pacientes con cáncer.

SOFA in sepsis: with or without GCS.

PURPOSE: Sepsis is a global public health burden. The sequential organ failure assessment (SOFA) is the most commonly used scoring system for diagnosing sepsis and assessing severity. Due to the widespread use of endotracheal intubation and sedative medications in sepsis, the accuracy of the Glasgow Coma Score (GCS) is the lowest in SOFA. We designed this multicenter, cross-sectional study to investigate the predictive efficiency of SOFA with or without GCS on ICU mortality in patients with sepsis. METHODS: First, 3048 patients with sepsis admitted to Peking Union Medical College Hospital (PUMCH) were enrolled in this survey. The data were collected from June 8, 2013 to October 12, 2022. Second, 18,108 patients with sepsis in the eICU database were enrolled. Third, 2397 septic patients with respiratory system ≥ 3 points in SOFA in the eICU database were included. We investigated the predictive efficiency of SOFA with or without GCS on ICU mortality in patients with sepsis in various ICUs of PUMCH, and then we validated the results in the eICU database. MAIN RESULTS: In data of ICUs in PUMCH, the predictive efficiency of SOFA without GCS (AUROC [95% CI], 24 h, 0.724 [0.688, 0.760], 48 h, 0.734 [0.699, 0.769], 72 h, 0.748 [0.713, 0.783], 168 h, 0.781 [0.747, 0.815]) was higher than that of SOFA with GCS (AUROC [95% CI], 24 h, 0.708 [0.672, 0.744], 48 h, 0.721 [0.685, 0.757], 72 h, 0.735 [0.700, 0.757], 168 h, 0.770 [0.736, 0.804]) on ICU mortality in patients with sepsis, and the difference was statistically significant (P value, 24 h, 0.001, 48 h, 0.003, 72 h, 0.004, 168 h, 0.005). In septic patients with respiratory system ≥ 3 points in SOFA in the eICU database, although the difference was not statistically significant (P value, 24 h, 0.148, 48 h, 0.178, 72 h, 0.132, 168 h, 0.790), SOFA without GCS (AUROC [95% CI], 24 h, 0.601 [0.576, 0.626], 48 h, 0.625 [0.601, 0.649], 72 h, 0.639 [0.615, 0.663], 168 h, 0.653 [0.629, 0.677]) had a higher predictive efficiency on ICU mortality than SOFA with GCS (AUROC [95% CI], 24 h, 0.591 [0.566, 0.616], 48 h, 0.616 [0.592, 0.640], 72 h, 0.628 [0.604, 0.652], 168 h, 0.651 [0.627, 0.675]). CONCLUSIONS: In severe sepsis, it is realistic and feasible to discontinue the routine GCS for SOFA in patients with a respiratory system ≥ 3 points, and even better predict ICU mortality.

Patterns of Multiple Organ Dysfunction and Renal Recovery in Critically Ill Children and Young Adults Receiving Continuous Renal Replacement Therapy.

OBJECTIVES: Acute kidney injury requiring dialysis (AKI-D) commonly occurs in the setting of multiple organ dysfunction syndrome (MODS). Continuous renal replacement therapy (CRRT) is the modality of choice for AKI-D. Mid-term outcomes of pediatric AKI-D supported with CRRT are unknown. We aimed to describe the pattern and impact of organ dysfunction on renal outcomes in critically ill children and young adults with AKI-D. DESIGN: Retrospective cohort. SETTING: Two large quarternary care pediatric hospitals. PATIENTS: Patients 26 y old or younger who received CRRT from 2014 to 2020, excluding patients with chronic kidney disease. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Organ dysfunction was assessed using the Pediatric Logistic Organ Dysfunction-2 (PELOD-2) score. MODS was defined as greater than or equal to two organ dysfunctions. The primary outcome was major adverse kidney events at 30 days (MAKE30) (decrease in estimated glomerular filtration rate greater than or equal to 25% from baseline, need for renal replacement therapy, and death). Three hundred seventy-three patients, 50% female, with a median age of 84 mo (interquartile range [IQR] 16-172) were analyzed. PELOD-2 increased from 6 (IQR 3-9) to 9 (IQR 7-12) between ICU admission and CRRT initiation. Ninety-seven percent of patients developed MODS at CRRT start and 266 patients (71%) had MAKE30. Acute kidney injury (adjusted odds ratio [aOR] 3.55 [IQR 2.13-5.90]), neurologic (aOR 2.07 [IQR 1.15-3.74]), hematologic/oncologic dysfunction (aOR 2.27 [IQR 1.32-3.91]) at CRRT start, and progressive MODS (aOR 1.11 [IQR 1.03-1.19]) were independently associated with MAKE30. CONCLUSIONS: Ninety percent of critically ill children and young adults with AKI-D develop MODS by the start of CRRT. Lack of renal recovery is associated with specific extrarenal organ dysfunction and progressive multiple organ dysfunction. Currently available extrarenal organ support strategies, such as therapeutic plasma exchange lung-protective ventilation, and other modifiable risk factors, should be incorporated into clinical trial design when investigating renal recovery.

Diastolic/systolic blood pressure ratio for predicting febrile children with sepsis and progress to septic shock in the emergency department.

OBJECTIVE: Given the scarcity of studies analyzing the clinical predictors of pediatric septic cases that would progress to septic shock, this study aimed to determine strong predictors for pediatric emergency department (PED) patients with sepsis at risk for septic shock and mortality. METHODS: We conducted chart reviews of patients with ≥ 2 age-adjusted quick Sequential Organ Failure Assessment score (qSOFA) criteria to recognize patients with an infectious disease in two tertiary PEDs between January 1, 2021, and April 30, 2022. The age range of included patients was 1 month to 18 years. The primary outcome was development of septic shock within 48 h of PED attendance. The secondary outcome was sepsis-related 28-day mortality. Initial important variables in the PED and hemodynamics with the highest and lowest values during the first 24 h of admission were also analyzed. RESULTS: Overall, 417 patients were admitted because of sepsis and met the eligibility criteria for the study. Forty-nine cases progressed to septic shock within 48 h after admission and 368 were discharged without progression. General demographics, laboratory data, and hemodynamics were analyzed by multivariate analysis. Only the minimum diastolic blood pressure/systolic blood pressure ratio (D/S ratio) during the first 24 h after admission remained as an independent predictor of progression to septic shock and 28-day mortality. The best cutoff values of the D/S ratio for predicting septic shock and 28-day mortality were 0.52 and 0.47, respectively. CONCLUSIONS: The D/S ratio is a practical bedside scoring system in the PED and had good discriminative ability in predicting the progression of septic shock and in-hospital mortality in PED patients. Further validation is essential in other settings.

Hepatic function markers as prognostic factors in patients with acute kidney injury undergoing continuous renal replacement therapy.

Acute kidney injury (AKI) requiring continuous renal replacement therapy (CRRT), secondary to cardiovascular disease and sepsis, is associated with high in-hospital mortality. Although studies have examined cardiovascular disease and sepsis in AKI, the association between AKI and hepatic functional impairment remains unclear. We hypothesized that hepatic function markers would predict mortality in patients undergoing CRRT. We included 1,899 CRRT patients from a multi-centre database. In Phase 1, participants were classified according to the total bilirubin (T-Bil) levels on the day of, and 3 days after, CRRT initiation: T-Bil < 1.2, 1.2 ≤ T-Bil < 2, and T-Bil ≥ 2 mg/dL. In Phase 2, propensity score matching (PSM) was performed to examine the effect of a T-Bil cutoff of 1.2 mg/dL (supported by the Sequential Organ Failure Assessment score); creating two groups based on a T-Bil cutoff of 1.2 mg/dL 3 days after CRRT initiation. The primary endpoint was total mortality 90 days after CRRT initiation, which was 34.7% (n = 571). In Phase 1, the T-Bil, aspartate transaminase (AST), alanine transaminase (ALT), and AST/ALT (De Ritis ratio) levels at CRRT initiation were not associated with the prognosis, while T-Bil, AST, and the De Ritis ratio 3 days after CRRT initiation were independent factors. In Phase 2, T-Bil ≥1.2 mg/dL on day 3 was a significant independent prognostic factor, even after PSM [hazard ratio: 2.41 (95% CI; 1.84-3.17), p < 0.001]. T-Bil ≥1.2 mg/dL 3 days after CRRT initiation predicted 90-day mortality. Changes in hepatic function markers in acute renal failure may enable stratification of high-risk patients.

Automated Calculator for the Pediatric Sequential Organ Failure Assessment Score: Development and External Validation in a Single-Center 7-Year Cohort, 2015-2021.

OBJECTIVES: The pediatric Sequential Organ Failure Assessment (pSOFA) score summarizes severity of organ dysfunction and can be used to predict in-hospital mortality. Manual calculation of the pSOFA score is time-consuming and prone to human error. An automated method that is open-source, flexible, and scalable for calculating the pSOFA score directly from electronic health record data is desirable. DESIGN: Single-center, retrospective cohort study. SETTING: Quaternary 40-bed PICU. PATIENTS: All patients admitted to the PICU between 2015 and 2021 with ICU stay of at least 24 hours. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We used 77 records to evaluate the automated score. The automated algorithm had an overall accuracy of 97%. The algorithm calculated the respiratory component of two cases incorrectly. An expert human annotator had an initial accuracy of 75% at the patient level and 95% at the component level. An untrained human annotator with general clinical research experience had an overall accuracy of 16% and component-wise accuracy of 67%. Weighted kappa for agreement between the automated method and the expert annotator's initial score was 0.92 (95% CI, 0.88-0.95), and between the untrained human annotator and the automated score was 0.50 (95% CI, 0.36-0.61). Data from 9146 patients (in-hospital mortality 3.6%) were included to validate externally the discriminability of the automated pSOFA score. The admission-day pSOFA score had an area under the receiver operating characteristic curve of 0.79 (95% CI, 0.77-0.82). CONCLUSIONS: The developed automated algorithm calculates pSOFA score with high accuracy and is more accurate than a trained expert rater and nontrained data abstracter. pSOFA's performance for predicting in-hospital mortality was lower in our cohort than it was for the originally derived score.