The Sequential Organ Failure Assessment (SOFA) Score: has the time come for an update?

Risk factors for neurological disability outcomes in patients under extracorporeal membrane oxygenation following cardiac arrest: An observational study

OBJECTIVES

This study aimed to identify factors associated with neurological and disability outcomes in patients who underwent ECMO following cardiac arrest.

METHODS

This retrospective, single-center, observational study included adult patients who received ECMO treatment for in-hospital cardiac arrest (IHCA) or out-of-hospital cardiac arrest (OHCA) between February 2016 and March 2020. Factors associated with neurological and disability outcomes in these patients who underwent ECMO were assessed.

SETTING

Hamad General Hospital, Qatar.

MAIN OUTCOME MEASURES

Neurological disability outcomes were assessed using the Modified Rankin Scale (mRS) and the Cerebral Performance Category (CPC) scale.

RESULTS

Among the 48 patients included, 37 (77 %) experienced OHCA, and 11 (23 %) had IHCA. The 28-day survival rate was 14 (29.2 %). Of the survivors, 9 (64.3 %) achieved a good neurological outcome, while 5 (35.7 %) experienced poor neurological outcomes. Regarding disability, 5 (35.7 %) of survivors had no disability, while 9 (64.3 %) had some form of disability. The results showed significantly shorter median time intervals in minutes, including collapse to cardiopulmonary resuscitation (CPR) (3 vs. 6, P = 0.001), CPR duration (12 vs. 35, P = 0.001), CPR to extracorporeal cardiopulmonary resuscitation (ECPR) (20 vs. 40, P = 0.001), and collapse-to-ECPR (23 vs. 45, P = 0.001), in the good outcome group compared to the poor outcome group.

CONCLUSION

This study emphasizes the importance of minimizing the time between collapse and CPR/ECMO initiation to improve neurological outcomes and reduce disability in cardiac arrest patients. However, no significant associations were found between outcomes and other demographic or clinical variables in this study. Further research with a larger sample size is needed to validate these findings.

IMPLICATIONS FOR CLINICAL PRACTICE

The study underscores the significance of reducing the time between collapse and the initiation of CPR and ECMO. Shorter time intervals were associated with improved neurological outcomes and reduced disability in cardiac arrest patients.

The Impact of Common Variations in Sequential Organ Failure Assessment Score Calculation on Sepsis Measurement Using Sepsis-3 Criteria: A Retrospective Analysis Using Electronic Health Record Data

OBJECTIVES

To assess the impact of different methods of calculating Sequential Organ Failure Assessment (SOFA) scores using electronic health record data on the incidence, outcomes, agreement, and predictive validity of Sepsis-3 criteria.

DESIGN

Retrospective observational study.

SETTING

Five Massachusetts hospitals.

PATIENTS

Hospitalized adults, 2015 to 2022.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We defined sepsis as a suspected infection (culture obtained and antibiotic administered) with a concurrent increase in SOFA score by greater than or equal to 2 points (Sepsis-3 criteria). Our reference SOFA implementation strategy imputed normal values for missing data, used Pao2/Fio2 ratios for respiratory scores, and assumed normal baseline SOFA scores for community-onset sepsis. We then implemented SOFA scores using different missing data imputation strategies (averaging worst values from preceding and following days vs. carrying forward nonmissing values), imputing respiratory scores using Spo2/Fio2 ratios, and incorporating comorbidities and prehospital laboratory data into baseline SOFA scores. Among 1,064,459 hospitalizations, 297,512 (27.9%) had suspected infection and 141,052 (13.3%) had sepsis with an in-hospital mortality rate of 10.3% using the reference SOFA method. The percentage of patients missing SOFA components for at least 1 day in the infection window was highest for Pao2/Fio2 ratios (98.6%), followed by Spo2/Fio2 ratios (73.5%), bilirubin (68.5%), and Glasgow Coma Scale scores (57.2%). Different missing data imputation strategies yielded near-perfect agreement in identifying sepsis (kappa 0.99). However, using Spo2/Fio2 imputations yielded higher sepsis incidence (18.3%), lower mortality (8.1%), and slightly lower predictive validity for mortality (area under the receiver operating curves [AUROC] 0.76 vs. 0.78). For community-onset sepsis, incorporating comorbidities and historical laboratory data into baseline SOFA score estimates yielded lower sepsis incidence (6.9% vs. 11.6%), higher mortality (13.4% vs. 9.6%), and higher predictive validity (AUROC 0.79 vs. 0.75) relative to the reference SOFA implementation.

CONCLUSIONS

Common variations in calculating respiratory and baseline SOFA scores, but not in handling missing data, lead to substantial differences in observed incidence, mortality, agreement, and predictive validity of Sepsis-3 criteria.

Comparative Analysis of Artificial Intelligence (AI) Languages in Predicting Sequential Organ Failure Assessment (SOFA) Scores

PURPOSE

The Sequential Organ Failure Assessment (SOFA) score plays a crucial role in intensive care units (ICUs) by providing a reliable measure of a patient's organ function or extent of failure. However, the precise assessment is time-consuming, and daily assessment in clinical practice in the ICU can be challenging.

METHODS

Realistic scenarios in an ICU setting were created, and the data mining precision of ChatGPT 4.0 Plus, Bard, and Perplexity AI were assessed using Spearman's as well as the intraclass correlation coefficients regarding the accuracy in determining the SOFA score.

RESULTS

The strongest correlation was observed between the actual SOFA score and the score calculated by ChatGPT 4.0 Plus (r correlation coefficient 0.92) (p<0.001). In contrast, the correlation between the actual SOFA and that calculated by Bard was moderate (r=0.59, p=0.070), while the correlation with Perplexity AI was substantial, at 0.89, with a p<0.001. The interclass correlation coefficient analysis of SOFA with those of ChatGPT 4.0 Plus, Bard, and Perplexity AI was ICC=0.94.

CONCLUSION

Artificial intelligence (AI) tools, particularly ChatGPT 4.0 Plus, show significant promise in assisting with automated SOFA score calculations via AI data mining in ICU settings. They offer a pathway to reduce the manual workload and increase the efficiency of continuous patient monitoring and assessment. However, further development and validation are necessary to ensure accuracy and reliability in a critical care environment.

What factors are effective on the CPR duration of patients under extracorporeal cardiopulmonary resuscitation: a single-center retrospective study

BACKGROUND

Extracorporeal cardiopulmonary resuscitation (ECPR) is an alternative method for patients with reversible causes of cardiac arrest (CA) after conventional cardiopulmonary resuscitation (CCPR). However, cardiopulmonary resuscitation (CPR) duration during ECPR can vary due to multiple factors. Healthcare providers need to understand these factors to optimize the resuscitation process and improve outcomes. The aim of this study was to examine the different variables impacting the duration of CPR in patients undergoing ECPR.

METHODS

This retrospective, single-center, observational study was conducted on adult patients who underwent ECPR due to in-hospital CA (IHCA) or out-of-hospital CA (OHCA) at Hamad General Hospital (HGH), the tertiary governmental hospital of Qatar, between February 2016 and March 2020. Univariate and multivariate binary logistic regression analyses were performed to identify the prognostic factors associated with CPR duration, including demographic and clinical variables, as well as laboratory tests.

RESULTS

The mean ± standard division age of the 48 participants who underwent ECPR was 41.50 ± 13.15 years, and 75% being male. OHCA and IHCA were reported in 77.1% and 22.9% of the cases, respectively. The multivariate analysis revealed that several factors were significantly associated with an increased CPR duration: higher age (OR: 1.981, 95%CI: 1.021-3.364, P = 0.025), SOFA score (OR: 3.389, 95%CI: 1.289-4.911, P = 0.013), presence of comorbidities (OR: 3.715, 95%CI: 1.907-5.219, P = 0.026), OHCA (OR: 3.715, 95%CI: 1.907-5.219, P = 0.026), and prolonged collapse-to-CPR time (OR: 1.446, 95%CI:1.092-3.014, P = 0.001). Additionally, the study found that the initial shockable rhythm was inversely associated with the duration of CPR (OR: 0.271, 95%CI: 0.161-0.922, P = 0.045). However, no significant associations were found between laboratory tests and CPR duration.

CONCLUSION

These findings suggest that age, SOFA score, comorbidities, OHCA, collapse-to-CPR time, and initial shockable rhythm are important factors influencing the duration of CPR in patients undergoing ECPR. Understanding these factors can help healthcare providers better predict and manage CPR duration, potentially improving patient outcomes. Further research is warranted to validate these findings and explore additional factors that may impact CPR duration in this population.

Predictive performance of the sequential organ failure assessment score for in-hospital mortality in patients with end-stage kidney disease in intensive care units: A multicenter registry in Japan

INTRODUCTION

There is limited evidence regarding whether the performance of the Sequential Organ Failure Assessment (SOFA) score differs between patients with and without end-stage kidney disease (ESKD) in intensive care units (ICUs).

METHODS

We used a multicenter registry (Japanese Intensive care Patient Database) to enroll adult ICU patients between April 2018 and March 2021. We recalibrated the SOFA score using a logistic regression model and evaluated its predictive ability in both ESKD and non-ESKD groups. The primary outcome was in-hospital mortality.

RESULTS

128 134 patients were enrolled. The AUROC of the SOFA score was lower in the ESKD group than in the non-ESKD group [0.789 (95% CI, 0.774-0.804) vs. 0.846 (95% CI, 0.841-0.850)]. The calibration plot revealed good performance in both groups. However, it overestimated in-hospital mortality in ESKD groups.

CONCLUSION

The SOFA score demonstrated good predictive ability in patients with and without ESKD, but it overestimated the in-hospital mortality in ESKD patients.

Lactate combined with SOFA score for improving the predictive efficacy of SOFA score in patients with severe heatstroke

BACKGROUND

The relationship between lactate levels and multiple organ dysfunction in patients with severe heatstroke remains unclear. In this study, we aimed to elucidate the clinical significance of lactate in severe heatstroke prognosis and assess whether incorporating lactate in the SOFA score improves its predictive efficacy.

METHODS

This study was a multicenter retrospective cohort investigation included 275 patients. Logistic regression analysis was performed to examine the relationship between lactate levels and patient outcomes and complications, including acute kidney injury (AKI), disseminated intravascular coagulation (DIC), and myocardial injury. Further, receiver operating characteristic (ROC) curves and clinical decision curve analysis (DCA) were used to evaluate the predictive power of lactate and SOFA scores in severe heatstroke-associated death. Lastly, the Kaplan-Meier survival curve was employed to differentiate the survival rates among the various patient groups.

RESULTS

After adjusting for confounding factors, lactate was demonstrated as an independent risk factor for death (OR = 1.353, 95% CI [1.170, 1.569]), AKI (OR = 1.158, 95% CI [1.007, 1.332]), DIC (OR = 1.426, 95% CI [1.225, 1.659]), and myocardial injury (OR = 2.039, 95% CI [1.553, 2.679]). The area under the curve (AUC) of lactate for predicting death from severe heatstroke was 0.7540, with a cutoff of 3.35. The Kaplan-Meier survival curve analysis showed that patients with elevated lactate levels had higher mortality rates. Additionally, the ROC curves demonstrated that combining lactate with the SOFA score provided better predictive efficacy than the SOFA score alone in patients with severe heatstroke (AUC: 0.9025 vs. 0.8773, DeLong test, P < 0.001). Finally, the DCA curve revealed a higher net clinical benefit rate for lactate combined with the SOFA score.

CONCLUSIONS

Lactate is an independent risk factor for severe heatstroke-related death as well as a risk factor for AKI, DIC, and myocardial injury associated with severe heatstroke. Thus, combining lactate with the SOFA score can significantly improve its predictive efficacy in patients with severe heatstroke.

Continuous monitoring of physiological data using the patient vital status fusion score in septic critical care patients

Accurate and standardized methods for assessing the vital status of patients are crucial for patient care and scientific research. This study introduces the Patient Vital Status (PVS), which quantifies and contextualizes a patient's physical status based on continuous variables such as vital signs and deviations from age-dependent normative values. The vital signs, heart rate, oxygen saturation, respiratory rate, mean arterial blood pressure, and temperature were selected as input to the PVS pipeline. The method was applied to 70 pediatric patients in the intensive care unit (ICU), and its efficacy was evaluated by matching high values with septic events at different time points in patient care. Septic events included systemic inflammatory response syndrome (SIRS) and suspected or proven sepsis. The comparison of maximum PVS values between the presence and absence of a septic event showed significant differences (SIRS/No SIRS: p < 0.0001, η2 = 0.54; Suspected Sepsis/No Suspected Sepsis: p = 0.00047, η2 = 0.43; Proven Sepsis/No Proven Sepsis: p = 0.0055, η2 = 0.34). A further comparison between the most severe PVS in septic patients with the PVS at ICU discharge showed even higher effect sizes (SIRS: p < 0.0001, η2 = 0.8; Suspected Sepsis: p < 0.0001, η2 = 0.8; Proven Sepsis: p = 0.002, η2 = 0.84). The PVS is emerging as a data-driven tool with the potential to assess a patient's vital status in the ICU objectively. Despite real-world data challenges and potential annotation biases, it shows promise for monitoring disease progression and treatment responses. Its adaptability to different disease markers and reliance on age-dependent reference values further broaden its application possibilities. Real-time implementation of PVS in personalized patient monitoring may be a promising way to improve critical care. However, PVS requires further research and external validation to realize its true potential.

Validation of Adult Sepsis Event and Epidemiologic Analysis of Sepsis Prevalence and Mortality Using Adult Sepsis Event's Electronic Health Records-Based Sequential Organ Failure Assessment Criteria: A Single-Center Study in South Korea

OBJECTIVES

In 2018, the Centers for Disease Control and Prevention introduced the Adult Sepsis Event (ASE) definition, using electronic health records (EHRs) data for surveillance and sepsis quality improvement. However, data regarding ASE outside the United States remain limited. We therefore aimed to validate the diagnostic accuracy of the ASE and to assess the prevalence and mortality of sepsis using ASE.

DESIGN

Retrospective cohort study.

SETTING

A single center in South Korea, with 2732 beds including 221 ICU beds.

PATIENTS

During the validation phase, adult patients who were hospitalized or visiting the emergency department between November 5 and November 11, 2019, were included. In the subsequent phase of epidemiologic analysis, we included adult patients who were admitted from January to December 2020.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

ASE had a sensitivity of 91.6%, a specificity of 98.3%, a positive predictive value (PPV) of 57.4%, and a negative predictive value of 99.8% when compared with the Sepsis-3 definition. Of 126,998 adult patient hospitalizations in 2020, 6,872 cases were diagnosed with sepsis based on the ASE (5.4% per year), and 893 patients were identified as having sepsis according to the International Classification of Diseases, 10th Edition (ICD-10) (0.7% per year). Hospital mortality rates were 16.6% (ASE) and 23.5% (ICD-10-coded sepsis). Monthly sepsis prevalence and hospital mortality exhibited less variation when diagnosed using ASE compared with ICD-10 coding (coefficient of variation [CV] for sepsis prevalence: 0.051 vs. 0.163, Miller test p < 0.001; CV for hospital mortality: 0.087 vs. 0.261, p = 0.001).

CONCLUSIONS

ASE demonstrated high sensitivity and a moderate PPV compared with the Sepsis-3 criteria in a Korean population. The prevalence of sepsis, as defined by ASE, was 5.4% per year and was similar to U.S. estimates. The prevalence of sepsis by ASE was eight times higher and exhibited less monthly variability compared with that based on the ICD-10 code.

DEVELOPMENT AND INTERNAL-EXTERNAL VALIDATION OF THE ACCI-SOFA MODEL FOR PREDICTING IN-HOSPITAL MORTALITY OF PATIENTS WITH SEPSIS-3 IN THE ICU: A MULTICENTER RETROSPECTIVE COHORT STUDY

ABSTRACT

Objective: To achieve a better prediction of in-hospital mortality, the Sequential Organ Failure Assessment (SOFA) score needs to be adjusted and combined with comorbidities. This study aims to enhance the prediction of SOFA score for in-hospital mortality in patients with Sepsis-3. Methods: This study adjusted the maximum SOFA score within the first 3 days (Max Day3 SOFA) in relation to in-hospital mortality using logistic regression and incorporated the age-adjusted Charlson Comorbidity Index (aCCI) as a continuous variable to build the age-adjusted Charlson Comorbidity Index-Sequential Organ Failure Assessment (aCCI-SOFA) model. The outcome was in-hospital mortality. We developed, internally validated, and externally validated the aCCI-SOFA model using cohorts of Sepsis-3 patients from the MIMIC-IV, MIMIC-III (CareVue), and the FAHWMU cohort. The predictive performance of the model was assessed through discrimination and calibration, which was assessed using the area under the receiver operating characteristic and calibration curves, respectively. The overall predictive effect was evaluated using the Brier score. Measurements and main results: Compared with the Max Day3 SOFA, the aCCI-SOFA model showed significant improvement in area under the receiver operating characteristic with all cohorts: development cohort (0.81 vs 0.75, P < 0.001), internal validation cohort (0.81 vs 0.76, P < 0.001), MIMIC-III (CareVue) cohort (0.75 vs 0.68, P < 0.001), and FAHWMU cohort (0.72 vs 0.67, P = 0.001). In sensitivity analysis, it was suggested that the application of aCCI-SOFA in early nonseptic shock patients had greater clinical value, with significant differences compared with the original SOFA scores in all cohorts ( P < 0.05). Conclusion: For septic patients in intensive care unit, the aCCI-SOFA model exhibited superior predictive performance. The application of aCCI-SOFA in early nonseptic shock patients had greater clinical value.

Early warning system enables accurate mortality risk prediction for acute gastrointestinal bleeding admitted to intensive care unit

Acute gastrointestinal (GI) bleeding are potentially life-threatening conditions. Early risk stratification is important for triaging patients to the appropriate level of medical care and intervention. Patients admitted to intensive care unit (ICU) has a high mortality, but risk tool is scarce for these patients. This study aimed to develop and validate a risk score to improve the prognostication of death at the time of patient admission to ICU. We developed and internally validated a nomogram for mortality in patients with acute GI bleeding from the eICU Collaborative Research Database (eICU-CRD), and externally validated it in patients from the Medical Information Mart for Intensive Care III database (MIMIC-III) and Wuhan Tongji Hospital. The performance of the model was assessed by examining discrimination (C-index), calibration (calibration curves) and usefulness (decision curves). 4750 patients were included in the development cohort, with 1184 patients in the internal validation cohort, 1406 patients in the MIMIC-III validation cohort, and 342 patients in the Tongji validation cohort. The nomogram, which incorporated ten variables, showed good calibration and discrimination in the training and validation cohorts, yielded C-index ranged from 0.832 (95%CI 0.811-0.853) to 0.926 (95CI% 0.905-0.947). The nomogram-defined high-risk group had a higher mortality than the low-risk group (44.8% vs. 3.5%, P < 0.001; 41.4% vs 3.1%, P < 0.001;53.6% vs 7.5%, P < 0.001; 38.2% vs 4.2%, P < 0.001). The model performed better than the conventional Glasgow-Blatchford score, AIMS65 and the newer Oakland and Sengupta scores for mortality prediction in both the derivation and validation cohorts concerning discrimination and usefulness. Our nomogram is a reliable prognostic tool that might be useful to identify high-risk acute GI bleeding patients admitted to ICU.

Early Prediction of Mortality for Septic Patients Visiting Emergency Room Based on Explainable Machine Learning: A Real-World Multicenter Study

BACKGROUND

Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department.

METHODS

This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO2/FIO2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine). The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley's additive explanations (SHAP).

RESULTS

Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756-0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626-0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results.

CONCLUSION

Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.

Surviving Sepsis Campaign Research Priorities 2023

OBJECTIVES

To identify research priorities in the management, epidemiology, outcome, and pathophysiology of sepsis and septic shock.

DESIGN

Shortly after publication of the most recent Surviving Sepsis Campaign Guidelines, the Surviving Sepsis Research Committee, a multiprofessional group of 16 international experts representing the European Society of Intensive Care Medicine and the Society of Critical Care Medicine, convened virtually and iteratively developed the article and recommendations, which represents an update from the 2018 Surviving Sepsis Campaign Research Priorities.

METHODS

Each task force member submitted five research questions on any sepsis-related subject. Committee members then independently ranked their top three priorities from the list generated. The highest rated clinical and basic science questions were developed into the current article.

RESULTS

A total of 81 questions were submitted. After merging similar questions, there were 34 clinical and ten basic science research questions submitted for voting. The five top clinical priorities were as follows: 1) what is the best strategy for screening and identification of patients with sepsis, and can predictive modeling assist in real-time recognition of sepsis? 2) what causes organ injury and dysfunction in sepsis, how should it be defined, and how can it be detected? 3) how should fluid resuscitation be individualized initially and beyond? 4) what is the best vasopressor approach for treating the different phases of septic shock? and 5) can a personalized/precision medicine approach identify optimal therapies to improve patient outcomes? The five top basic science priorities were as follows: 1) How can we improve animal models so that they more closely resemble sepsis in humans? 2) What outcome variables maximize correlations between human sepsis and animal models and are therefore most appropriate to use in both? 3) How does sepsis affect the brain, and how do sepsis-induced brain alterations contribute to organ dysfunction? How does sepsis affect interactions between neural, endocrine, and immune systems? 4) How does the microbiome affect sepsis pathobiology? 5) How do genetics and epigenetics influence the development of sepsis, the course of sepsis and the response to treatments for sepsis?

CONCLUSIONS

Knowledge advances in multiple clinical domains have been incorporated in progressive iterations of the Surviving Sepsis Campaign guidelines, allowing for evidence-based recommendations for short- and long-term management of sepsis. However, the strength of existing evidence is modest with significant knowledge gaps and mortality from sepsis remains high. The priorities identified represent a roadmap for research in sepsis and septic shock.

Amino acid kinetics in the critically ill

PURPOSE OF REVIEW

Stable isotope methods have been used for many years to assess whole body protein and amino acid kinetics in critically ill patients. In recent years, new isotope approaches and tracer insights have been developed. The tracer pulse approach has some advantages above the established primed-continuous tracer infusion approach because of the high amount of metabolic information obtained, easy applicability, and low tracer costs. Effects of disease severity and sex on amino acid kinetics in ICU patients will also be addressed.

RECENT FINDINGS

Current knowledge was synthesized on specific perturbations in amino acid metabolism in critically ill patients, employing novel methodologies such as the pulse tracer approach and computational modeling. Variations were evaluated in amino acid production and linked to severity of critical illness, as measured by SOFA score, and sex. Production of the branched-chain amino acids (BCAAs), glutamine, tau-methylhistidine and hydroxyproline were elevated in critical illness, likely related to increased transamination of the individual BCAAs or increased breakdown of proteins. Citrulline production was reduced, indicative of impaired gut mucosa function. Sex and disease severity independently influenced amino acid kinetics in ICU patients.

SUMMARY

Novel tracer and computational approaches have been developed to simultaneously measure postabsorptive kinetics of multiple amino acids that can be used in critical illness. The collective findings lay the groundwork for targeted individualized nutritional strategies in ICU settings aimed at enhancing patient outcomes taking into account disease severity and sex.

Modified Cardiovascular Sequential Organ Failure Assessment Score in Sepsis: External Validation in Intensive Care Unit Patients

BACKGROUND

There is a need to update the cardiovascular (CV) Sequential Organ Failure Assessment (SOFA) score to reflect the current practice in sepsis. We previously proposed the modified CV SOFA score from data on blood pressure, norepinephrine equivalent dose, and lactate as gathered from emergency departments. In this study, we externally validated the modified CV SOFA score in multicenter intensive care unit (ICU) patients.

METHODS

A multicenter retrospective observational study was conducted on ICU patients at six hospitals in Korea. We included adult patients with sepsis who were admitted to ICUs. We compared the prognostic performance of the modified CV/total SOFA score and the original CV/total SOFA score in predicting 28-day mortality. Discrimination and calibration were evaluated using the area under the receiver operating characteristic curve (AUROC) and the calibration curve, respectively.

RESULTS

We analyzed 1,015 ICU patients with sepsis. In overall patients, the 28-day mortality rate was 31.2%. The predictive validity of the modified CV SOFA (AUROC, 0.712; 95% confidence interval [CI], 0.677-0.746; P < 0.001) was significantly higher than that of the original CV SOFA (AUROC, 0.644; 95% CI, 0.611-0.677). The predictive validity of modified total SOFA score for 28-day mortality was significantly higher than that of the original total SOFA (AUROC, 0.747 vs. 0.730; 95% CI, 0.715-0.779; P = 0.002). The calibration curve of the original CV SOFA for 28-day mortality showed poor calibration. In contrast, the calibration curve of the modified CV SOFA for 28-day mortality showed good calibration.

CONCLUSION

In patients with sepsis in the ICU, the modified SOFA score performed better than the original SOFA score in predicting 28-day mortality.

Effect of Inhaled Ciclesonide in Non-Critically Ill Hospitalized Patients With Coronavirus Disease 2019: A Multicenter Observational Study in Japan

Background

Coronavirus disease 2019 (COVID-19) is an ongoing global pandemic. Although systemic steroids play an important role in treating patients with severe COVID-19, the role of inhaled corticosteroids in non-critically ill, hospitalized patients with COVID-19 remains unclear.

Methods

We analyzed findings in non-critically ill, hospitalized patients with COVID-19 who were >18 years old and were admitted to 64 Japanese hospitals between January and September 2020. We performed propensity score matching analysis to evaluate 28-day and in-hospital mortality rates with or without inhaled ciclesonide within 2 days of admission. Sensitivity analyses using inverse probability weighting analysis, and generalized estimating equation method were also performed.

Results

Eligible patients (n = 3638) were divided into ciclesonide (n = 290) and control (n = 3, 393) groups. The 1-to-4 propensity score matching analysis included 271 ciclesonide users and 1084 nonusers. There were no significant differences between the 2 groups for 28-day (3.3% vs 2.3%; risk difference, 1.0% [95% confidence interval, -1.2 to 3.3]) or in-hospital (4.8% vs 2.6%; risk difference, 2.2 [-.5 to 4.9]) mortality rates. The sensitivity analysis showed similar outcomes.

Conclusions

From this multicenter observational study in Japan, inhaled ciclesonide did not decrease 28-day or in-hospital mortality rates in non-critically ill, hospitalized patients with COVID-19. Future large, multinational, randomized trials are required to confirm our results.

Surviving Sepsis After Burn Campaign

INTRODUCTION

The Surviving Sepsis Campaign was developed to improve outcomes for all patients with sepsis. Despite sepsis being the primary cause of death after thermal injury, burns have always been excluded from the Surviving Sepsis efforts. To improve sepsis outcomes in burn patients, an international group of burn experts developed the Surviving Sepsis After Burn Campaign (SSABC) as a testable guideline to improve burn sepsis outcomes.

METHODS

The International Society for Burn Injuries (ISBI) reached out to regional or national burn organizations to recommend members to participate in the program. Two members of the ISBI developed specific "patient/population, intervention, comparison and outcome" (PICO) questions that paralleled the 2021 Surviving Sepsis Campaign [1]. SSABC participants were asked to search the current literature and rate its quality for each topic. At the Congress of the ISBI, in Guadalajara, Mexico, August 28, 2022, a majority of the participants met to create "statements" based on the literature. The "summary statements" were then sent to all members for comment with the hope of developing an 80% consensus. After four reviews, a consensus statement for each topic was created or "no consensus" was reported.

RESULTS

The committee developed sixty statements within fourteen topics that provide guidance for the early treatment of sepsis in burn patients. These statements should be used to improve the care of sepsis in burn patients. The statements should not be considered as "static" comments but should rather be used as guidelines for future testing of the best treatments for sepsis in burn patients. They should be updated on a regular basis.

CONCLUSION

Members of the burn community from the around the world have developed the Surviving Sepsis After Burn Campaign guidelines with the goal of improving the outcome of sepsis in burn patients.

Prognostic Performance of Sequential Organ Failure Assessment, Acute Physiology and Chronic Health Evaluation III, and Simplified Acute Physiology Score II Scores in Patients with Suspected Infection According to Intensive Care Unit Type

We investigated the prognostic performance of scoring systems by the intensive care unit (ICU) type. This was a retrospective observational study using data from the Marketplace for Medical Information in the Intensive Care IV database. The primary outcome was in-hospital mortality. We obtained Sequential Organ Failure Assessment (SOFA), Acute Physiology and Chronic Health Evaluation (APACHE) III, and Simplified Acute Physiology Score (SAPS) II scores in each ICU type. Prognostic performance was evaluated with the area under the receiver operating characteristic curve (AUROC) and was compared among ICU types. A total of 29,618 patients were analyzed, and the in-hospital mortality was 12.4%. The overall prognostic performance of APACHE III was significantly higher than those of SOFA and SAPS II (0.807, [95% confidence interval, 0.799-0.814], 0.785 [0.773-0.797], and 0.795 [0.787-0.811], respectively). The prognostic performance of SOFA, APACHE III, and SAPS II scores was significantly different between ICU types. The AUROC ranges of SOFA, APACHE III, and SAPS II were 0.723-0.826, 0.728-0.860, and 0.759-0.819, respectively. The neurosurgical and surgical ICUs had lower prognostic performance than other ICU types. The prognostic performance of scoring systems in patients with suspected infection is significantly different according to ICU type. APACHE III systems have the highest prediction performance. ICU type may be a significant factor in the prognostication.

Validity of the total SOFA score in patients ≥ 80 years old acutely admitted to intensive care units: a post-hoc analysis of the VIP2 prospective, international cohort study

BACKGROUND

Little is known about the performance of the Sequential Organ Failure Assessment (SOFA) score in older critically ill adults. We aimed to evaluate the prognostic impact of physiological disturbances in the six organ systems included in the SOFA score.

METHODS

We analysed previously collected data from a prospective cohort study conducted between 2018 and 2019 in 22 countries. Consecutive patients ≥ 80 years old acutely admitted to intensive care units (ICUs) were eligible for inclusion. Patients were followed up for 30 days after admission to the ICU. We used logistic regression to study the association between increasing severity of organ dysfunction and mortality.

RESULTS

The median SOFA score among 3882 analysed patients was equal to 6 (IQR: 4-9). Mortality was equal to 26.1% (95% CI 24.7-27.5%) in the ICU and 38.7% (95% CI 37.1-40.2%) at day 30. Organ failure defined as a SOFA score ≥ 3 was associated with variable adjusted odds ratios (aORs) for ICU mortality dependant on the organ system affected: respiratory, 1.53 (95% CI 1.29-1.81); cardiovascular 1.69 (95% CI 1.43-2.01); hepatic, 1.74 (95% CI 0.97-3.15); renal, 1.87 (95% CI 1.48-2.35); central nervous system, 2.79 (95% CI 2.34-3.33); coagulation, 2.72 (95% CI 1.66-4.48). Modelling consecutive levels of organ dysfunction resulted in aORs equal to 0.57 (95% CI 0.33-1.00) when patients scored 2 points in the cardiovascular system and 1.01 (0.79-1.30) when the cardiovascular SOFA equalled 3.

CONCLUSIONS

Different components of the SOFA score have different prognostic implications for older critically ill adults. The cardiovascular component of the SOFA score requires revision.

Machine learning-based prediction model of acute kidney injury in patients with acute respiratory distress syndrome

BACKGROUND

Acute kidney injury (AKI) can make cases of acute respiratory distress syndrome (ARDS) more complex, and the combination of the two can significantly worsen the prognosis. Our objective is to utilize machine learning (ML) techniques to construct models that can promptly identify the risk of AKI in ARDS patients.

METHOD

We obtained data regarding ARDS patients from the Medical Information Mart for Intensive Care III (MIMIC-III) and MIMIC-IV databases. Within the MIMIC-III dataset, we developed 11 ML prediction models. By evaluating various metrics, we visualized the importance of its features using Shapley additive explanations (SHAP). We then created a more concise model using fewer variables, and optimized it using hyperparameter optimization (HPO). The model was validated using the MIMIC-IV dataset.

RESULT

A total of 928 ARDS patients without AKI were included in the analysis from the MIMIC-III dataset, and among them, 179 (19.3%) developed AKI after admission to the intensive care unit (ICU). In the MIMIC-IV dataset, there were 653 ARDS patients included in the analysis, and among them, 237 (36.3%) developed AKI. A total of 43 features were used to build the model. Among all models, eXtreme gradient boosting (XGBoost) performed the best. We used the top 10 features to build a compact model with an area under the curve (AUC) of 0.850, which improved to an AUC of 0.865 after the HPO. In extra validation set, XGBoost_HPO achieved an AUC of 0.854. The accuracy, sensitivity, specificity, positive prediction value (PPV), negative prediction value (NPV), and F1 score of the XGBoost_HPO model on the test set are 0.865, 0.813, 0.877, 0.578, 0.957 and 0.675, respectively. On extra validation set, they are 0.724, 0.789, 0.688, 0.590, 0.851, and 0.675, respectively.

CONCLUSION

ML algorithms, especially XGBoost, are reliable for predicting AKI in ARDS patients. The compact model maintains excellent predictive ability, and the web-based calculator improves clinical convenience. This provides valuable guidance in identifying AKI in ARDS, leading to improved patient outcomes.

Immunosuppressive effects of circulating bile acids in human endotoxemia and septic shock: patients with liver failure are at risk

BACKGROUND

Sepsis-induced immunosuppression is a frequent cause of opportunistic infections and death in critically ill patients. A better understanding of the underlying mechanisms is needed to develop targeted therapies. Circulating bile acids with immunosuppressive effects were recently identified in critically ill patients. These bile acids activate the monocyte G-protein coupled receptor TGR5, thereby inducing profound innate immune dysfunction. Whether these mechanisms contribute to immunosuppression and disease severity in sepsis is unknown. The aim of this study was to determine if immunosuppressive bile acids are present in endotoxemia and septic shock and, if so, which patients are particularly at risk.

METHODS

To induce experimental endotoxemia in humans, ten healthy volunteers received 2 ng/kg E. coli lipopolysaccharide (LPS). Circulating bile acids were profiled before and after LPS administration. Furthermore, 48 patients with early (shock onset within < 24 h) and severe septic shock (norepinephrine dose > 0.4 μg/kg/min) and 48 healthy age- and sex-matched controls were analyzed for circulating bile acids. To screen for immunosuppressive effects of circulating bile acids, the capability to induce TGR5 activation was computed for each individual bile acid profile by a recently published formula.

RESULTS

Although experimental endotoxemia as well as septic shock led to significant increases in total bile acids compared to controls, this increase was mild in most cases. By contrast, there was a marked and significant increase in circulating bile acids in septic shock patients with severe liver failure compared to healthy controls (61.8 µmol/L vs. 2.8 µmol/L, p = 0.0016). Circulating bile acids in these patients were capable to induce immunosuppression, as indicated by a significant increase in TGR5 activation by circulating bile acids (20.4% in severe liver failure vs. 2.8% in healthy controls, p = 0.0139).

CONCLUSIONS

Circulating bile acids capable of inducing immunosuppression are present in septic shock patients with severe liver failure. Future studies should examine whether modulation of bile acid metabolism can improve the clinical course and outcome of sepsis in these patients.

D-DI/PLT can be a prognostic indicator for sepsis

Aims

To investigate the indicators affecting the early outcome of patients with sepsis and to explore its prognostic efficacy for sepsis.

Methods

We collected clinical data from 201 patients with sepsis admitted to the emergency department of Xijing Hospital between June 2019 and June 2022. The patients were categorized into groups (survival or fatality) based on their 28-day prognosis. The clinical characteristics, biochemical indexes, organ function-related indicators, and disease scores of the patients were analyzed for both groups. Risk factor analysis was conducted for the indicators with significant differences.

Results

Among the indicators with significant differences between the deceased and survival groups, D-dimer (D-DI), Sequential Organ Failure Assessment (SOFA) score, platelet (PLT), international normalized ratio (INR), and D-DI/PLT were identified as independent risk factors affecting the prognosis of sepsis patients. Receiver operating characteristic (ROC) curves showed that D-DI/PLT (area under the curve (AUC) = 93.9), D-DI (AUC = 89.6), PLT (AUC = 81.3), and SOFA (AUC = 78.4) had good judgment efficacy. Further, Kaplan Meier (K-M) survival analysis indicated that the 28-day survival rates of sepsis patients were significantly decreased when they had high levels of D-DI/PLT, D-DI, and SOFA as well as low PLTs. The hazard ratio (HR) of D-DI/PLT between the two groups was the largest (HR = 16.19).

Conclusions

D-DI/PLT may be an independent risk factor for poor prognosis in sepsis as well as a clinical predictor of patient prognosis.

Cancer and sepsis

Sepsis is one of the leading causes of death worldwide. While mortality is high regardless of inciting infection or comorbidities, mortality in patients with cancer and sepsis is significantly higher than mortality in patients with sepsis without cancer. Cancer patients are also significantly more likely to develop sepsis than the general population. The mechanisms underlying increased mortality in cancer and sepsis patients are multifactorial. Cancer treatment alters the host immune response and can increase susceptibility to infection. Preclinical data also suggests that cancer, in and of itself, increases mortality from sepsis with dysregulation of the adaptive immune system playing a key role. Further, preclinical data demonstrate that sepsis can alter subsequent tumor growth while tumoral immunity impacts survival from sepsis. Checkpoint inhibition is a well-accepted treatment for many types of cancer, and there is increasing evidence suggesting this may be a useful strategy in sepsis as well. However, preclinical studies of checkpoint inhibition in cancer and sepsis demonstrate results that could not have been predicted by examining either variable in isolation. As sepsis management transitions from a 'one size fits all' model to a more individualized approach, understanding the mechanistic impact of cancer on outcomes from sepsis represents an important strategy towards delivering on the promise of precision medicine in the intensive care unit.

Serial evaluation of the serum lactate level with the SOFA score to predict mortality in patients with sepsis

In patients with sepsis, outcome prediction plays an important role in influencing therapeutic decision making. In this nationwide, prospective, observational cohort study of sepsis patients conducted between September 2019 and December 2020, we evaluated a novel scoring system using serial Sequential Organ Failure Assessment (SOFA) scores and serum lactate to accurately predict mortality in sepsis. Based on the serum lactate score (Lac-score), patients were assigned to 5 categories: lactate < 2, ≥ 2 to < 4, ≥ 4 to < 8, ≥ 8 to < 12, and ≥ 12 mmol/L. Lac-SOFA score was defined as the sum of Lac-score and SOFA score. After screening 7113 patients, 379 were excluded and 6734 were included in analysis. In-hospital mortality AUROC for serial Lac-SOFA score from initial to ICU day 3 was significantly higher than that for serial SOFA score (initial, 0.679 vs. 0.656, day 1, 0.723 vs. 0.709, day 2, 0.760 vs. 0.747, and day 3, 0.797 vs. 0.781; DeLong's test, p < 0.001). The initial Lac-SOFA score significantly correlated with in-hospital mortality when the patients were divided into five classes based on 5-point intervals (p < 0.05). Serial evaluation of lactate levels with the SOFA score may improve the predictive accuracy of the SOFA score for determining mortality risk in sepsis patients.