Severe fever with thrombocytopenia syndrome with central nervous system symptom onset: a case report and literature review.

BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS) is a natural focal disease transmitted mainly by tick bites, and the causative agent is SFTS virus (SFTSV). SFTS can rapidly progress to severe disease, with multiple-organ failure (MOF) manifestations such as shock, respiratory failure, disseminated intravascular coagulation (DIC) and death, but cases of SFTS patients with central nervous system (CNS) symptoms onset and marked persistent involuntary shaking of the perioral area and limbs have rarely been reported. CASE PRESENTATION: A 69-year-old woman with fever and persistent involuntary shaking of the perioral area and limbs was diagnosed with SFTS with CNS symptom onset after metagenomic next-generation sequencing (mNGS) of cerebrospinal fluid (CSF) and peripheral blood identified SFTSV. The patient developed a cytokine storm and MOF during the course of the disease, and after aggressive antiviral, glucocorticoid, and gamma globulin treatments, her clinical symptoms improved, her laboratory indices returned to normal, and she had a good prognosis. CONCLUSION: This case gives us great insight that when patients with CNS symptoms similar to those of viral encephalitis combined with thrombocytopenia and leukopenia are encountered in the clinic, it is necessary to consider the possibility of SFTS involving the CNS. Testing for SFTSV nucleic acid in CSF and blood (mNGS or polymerase chain reaction (PCR)) should be carried out, especially in critically ill patients, and treatment should be given accordingly.

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.

Host gene expression signatures to identify infection type and organ dysfunction in children evaluated for sepsis: a multicentre cohort study.

BACKGROUND: Sepsis is defined as dysregulated host response to infection that leads to life-threatening organ dysfunction. Biomarkers characterising the dysregulated host response in sepsis are lacking. We aimed to develop host gene expression signatures to predict organ dysfunction in children with bacterial or viral infection. METHODS: This cohort study was done in emergency departments and intensive care units of four hospitals in Queensland, Australia, and recruited children aged 1 month to 17 years who, upon admission, underwent a diagnostic test, including blood cultures, for suspected sepsis. Whole-blood RNA sequencing of blood was performed with Illumina NovaSeq (San Diego, CA, USA). Samples with completed phenotyping, monitoring, and RNA extraction by March 31, 2020, were included in the discovery cohort; samples collected or completed thereafter and by Oct 27, 2021, constituted the Rapid Paediatric Infection Diagnosis in Sepsis (RAPIDS) internal validation cohort. An external validation cohort was assembled from RNA sequencing gene expression count data from the observational European Childhood Life-threatening Infectious Disease Study (EUCLIDS), which recruited children with severe infection in nine European countries between 2012 and 2016. Feature selection approaches were applied to derive novel gene signatures for disease class (bacterial vs viral infection) and disease severity (presence vs absence of organ dysfunction 24 h post-sampling). The primary endpoint was the presence of organ dysfunction 24 h after blood sampling in the presence of confirmed bacterial versus viral infection. Gene signature performance is reported as area under the receiver operating characteristic curves (AUCs) and 95% CI. FINDINGS: Between Sept 25, 2017, and Oct 27, 2021, 907 patients were enrolled. Blood samples from 595 patients were included in the discovery cohort, and samples from 312 children were included in the RAPIDS validation cohort. We derived a ten-gene disease class signature that achieved an AUC of 94·1% (95% CI 90·6-97·7) in distinguishing bacterial from viral infections in the RAPIDS validation cohort. A ten-gene disease severity signature achieved an AUC of 82·2% (95% CI 76·3-88·1) in predicting organ dysfunction within 24 h of sampling in the RAPIDS validation cohort. Used in tandem, the disease class and disease severity signatures predicted organ dysfunction within 24 h of sampling with an AUC of 90·5% (95% CI 83·3-97·6) for patients with predicted bacterial infection and 94·7% (87·8-100·0) for patients with predicted viral infection. In the external EUCLIDS validation dataset (n=362), the disease class and disease severity predicted organ dysfunction at time of sampling with an AUC of 70·1% (95% CI 44·1-96·2) for patients with predicted bacterial infection and 69·6% (53·1-86·0) for patients with predicted viral infection. INTERPRETATION: In children evaluated for sepsis, novel host transcriptomic signatures specific for bacterial and viral infection can identify dysregulated host response leading to organ dysfunction. FUNDING: Australian Government Medical Research Future Fund Genomic Health Futures Mission, Children's Hospital Foundation Queensland, Brisbane Diamantina Health Partners, Emergency Medicine Foundation, Gold Coast Hospital Foundation, Far North Queensland Foundation, Townsville Hospital and Health Services SERTA Grant, and Australian Infectious Diseases Research Centre.

International Consensus Criteria for Pediatric Sepsis and Septic Shock.

Importance: Sepsis is a leading cause of death among children worldwide. Current pediatric-specific criteria for sepsis were published in 2005 based on expert opinion. In 2016, the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) defined sepsis as life-threatening organ dysfunction caused by a dysregulated host response to infection, but it excluded children. Objective: To update and evaluate criteria for sepsis and septic shock in children. Evidence Review: The Society of Critical Care Medicine (SCCM) convened a task force of 35 pediatric experts in critical care, emergency medicine, infectious diseases, general pediatrics, nursing, public health, and neonatology from 6 continents. Using evidence from an international survey, systematic review and meta-analysis, and a new organ dysfunction score developed based on more than 3 million electronic health record encounters from 10 sites on 4 continents, a modified Delphi consensus process was employed to develop criteria. Findings: Based on survey data, most pediatric clinicians used sepsis to refer to infection with life-threatening organ dysfunction, which differed from prior pediatric sepsis criteria that used systemic inflammatory response syndrome (SIRS) criteria, which have poor predictive properties, and included the redundant term, severe sepsis. The SCCM task force recommends that sepsis in children be identified by a Phoenix Sepsis Score of at least 2 points in children with suspected infection, which indicates potentially life-threatening dysfunction of the respiratory, cardiovascular, coagulation, and/or neurological systems. Children with a Phoenix Sepsis Score of at least 2 points had in-hospital mortality of 7.1% in higher-resource settings and 28.5% in lower-resource settings, more than 8 times that of children with suspected infection not meeting these criteria. Mortality was higher in children who had organ dysfunction in at least 1 of 4-respiratory, cardiovascular, coagulation, and/or neurological-organ systems that was not the primary site of infection. Septic shock was defined as children with sepsis who had cardiovascular dysfunction, indicated by at least 1 cardiovascular point in the Phoenix Sepsis Score, which included severe hypotension for age, blood lactate exceeding 5 mmol/L, or need for vasoactive medication. Children with septic shock had an in-hospital mortality rate of 10.8% and 33.5% in higher- and lower-resource settings, respectively. Conclusions and Relevance: The Phoenix sepsis criteria for sepsis and septic shock in children were derived and validated by the international SCCM Pediatric Sepsis Definition Task Force using a large international database and survey, systematic review and meta-analysis, and modified Delphi consensus approach. A Phoenix Sepsis Score of at least 2 identified potentially life-threatening organ dysfunction in children younger than 18 years with infection, and its use has the potential to improve clinical care, epidemiological assessment, and research in pediatric sepsis and septic shock around the world.

Serum Levels of Vitamin C and Thiamin in Children With Suspected Sepsis: A Prospective Observational Cohort Study.

OBJECTIVES: Vitamin C and thiamin have been trialed as adjunctive therapies in adults with septic shock but their role in critically ill children is unclear. We assessed serum levels of vitamin C and thiamin in children evaluated for sepsis. DESIGN: Single-center prospective observational study. Serum levels of vitamin C and thiamin were measured on admission and association with multiple organ dysfunction syndrome (MODS) was explored using logistic regression. SETTING: Emergency department and PICU in a tertiary children's hospital, Queensland, Australia. PATIENTS: Children greater than 1 month and less than 17 years evaluated for sepsis. INTERVENTIONS: Not applicable. MEASUREMENTS AND MAIN RESULTS: Vitamin levels were determined in 221 children with a median age of 3.5 (interquartile range [IQR] 1.6, 8.3) years. Vitamin C levels were inversely correlated with severity as measured by pediatric Sequential Organ Failure Assessment (Spearman's rho = -0.16, p = 0.018). Median (IQR) vitamin C levels on admission were 35.7 (17.9, 54.1) µmol/L, 36.1 (21.4, 53.7) µmol/L, and 17.9 (6.6, 43.0) µmol/L in children without organ dysfunction, single organ dysfunction, and MODS, respectively (p = 0.017). In multivariable analyses, low levels of vitamin C at the time of sampling were associated with greater odds of MODS (adjusted odds ratio [aOR] 3.04; 95% CI, 1.51-6.12), and vitamin C deficiency was associated with greater odds of MODS at 24 hours after sampling (aOR 3.38; 95% CI, 1.53-7.47). Median (IQR) thiamin levels were 162 (138, 192) nmol/L, 185 (143, 200) nmol/L, and 136 (110, 179) nmol/L in children without organ dysfunction, single organ dysfunction, and MODS, respectively (p = 0.061). We failed to identify an association between thiamin deficiency and either MODS at sampling (OR 2.52; 95% CI, 0.15-40.86) or MODS at 24 hours (OR 2.96; 95% CI, 0.18-48.18). CONCLUSIONS: Critically ill children evaluated for sepsis frequently manifest decreased levels of vitamin C, with lower levels associated with higher severity.

Early Predictive Value of Different Indicators for Persistent Organ Failure in Acute Pancreatitis: A Systematic Review and Network Meta-Analysis.

GOALS: In this study, we conducted this network meta-analysis (based on the ANOVA model) to evaluate the predictive efficacy of each early predictor. BACKGROUND: Persistent organ failure (POF) is one of the determining factors in patients with acute pancreatitis (AP); however, the diagnosis of POF has a long-time lag (>48 h). It is of great clinical significance for the early noninvasive prediction of POF. STUDY: We conducted a comprehensive and systematic search in PubMed, Cochrane library, Embase, and Web of Science to identify relevant clinical trials, case-control studies, or cohort studies, extracted the early indicators of POF in studies, and summarized the predictive efficacy of each indicator through network meta-analysis. The diagnostic odds ratio (DOR) was used to rank the prediction efficiency of each indicator. RESULTS: We identified 23 studies in this network meta-analysis, including 10,393 patients with AP, of which 2014 patients had POF. A total of 10 early prediction indicators were extracted. The mean and 95% CI lower limit of each predictive indicator were greater than 1.0. Albumin had the largest diagnostic odds ratio, followed by high-density lipoprotein-cholesterol (HDL-C), Ranson Score, beside index for severity in acute pancreatitis Score, acute physiology and chronic health evaluation II, C-reactive protein (CRP), Interleukin 6 (IL-6), Interleukin 8 (IL-8), Systemic Inflammatory Response Syndrome (SIRS) and blood urea nitrogen. CONCLUSIONS: Albumin, high-density lipoprotein-cholesterol, Ranson Score, and beside index for severity in acute pancreatitis Score are effective in the early prediction of POF in patients with AP, which can provide evidence for developing effective prediction systems. However, due to the limitations of the extraction method of predictive indicators in this study, some effective indicators may not be included in this meta-analysis.

Organ Dysfunction in Children With Blood Culture-Proven Sepsis: Comparative Performance of Four Scores in a National Cohort Study.

OBJECTIVES: Previous studies applying Sepsis-3 criteria to children were based on retrospective analyses of PICU cohorts. We aimed to compare organ dysfunction criteria in children with blood culture-proven sepsis, including emergency department, PICU, and ward patients, and to assess relevance of organ dysfunctions for mortality prediction. DESIGN: We have carried out a nonprespecified, secondary analysis of a prospective dataset collected from September 2011 to December 2015. SETTING: Emergency departments, wards, and PICUs in 10 tertiary children's hospitals in Switzerland. PATIENTS: Children younger than 17 years old with blood culture-proven sepsis. We excluded preterm infants and term infants younger than 7 days old. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We compared the 2005 International Pediatric Sepsis Consensus Conference (IPSCC), Pediatric Logistic Organ Dysfunction-2 (PELOD-2), pediatric Sequential Organ Failure Assessment (pSOFA), and Pediatric Organ Dysfunction Information Update Mandate (PODIUM) scores, measured at blood culture sampling, to predict 30-day mortality. We analyzed 877 sepsis episodes in 807 children, with a 30-day mortality of 4.3%. Percentage with organ dysfunction ranged from 32.7% (IPSCC) to 55.3% (pSOFA). In adjusted analyses, the accuracy for identification of 30-day mortality was area under the curve (AUC) 0.87 (95% CI, 0.82-0.92) for IPSCC, 0.83 (0.76-0.89) for PELOD-2, 0.85 (0.78-0.92) for pSOFA, and 0.85 (0.78-0.91) for PODIUM. When restricting scores to neurologic, respiratory, and cardiovascular dysfunction, the adjusted AUC was 0.89 (0.84-0.94) for IPSCC, 0.85 (0.79-0.91) for PELOD-2, 0.87 (0.81-0.93) for pSOFA, and 0.88 (0.83-0.93) for PODIUM. CONCLUSIONS: IPSCC, PELOD-2, pSOFA, and PODIUM performed similarly to predict 30-day mortality. Simplified scores restricted to neurologic, respiratory, and cardiovascular dysfunction yielded comparable performance.

Predicting mortality in pediatric sepsis: A nationwide data analysis using a pediatric sepsis surveillance method.

INTRODUCTION: A sepsis surveillance method using electronic health records is increasingly used to describe the epidemiology of adult sepsis. However, its application in pediatric populations has been limited, and real-world epidemiology of pediatric sepsis remains unknown. We aimed to determine whether this surveillance method could identify children with sepsis at high-risk of mortality. PATIENTS AND METHODS: From a nationwide inpatient database in Japan, we included children who underwent blood culture and received antimicrobials for ≥ 4 days between 2014 and 2021. We stratified these children into those with sepsis or without sepsis by the presence of organ dysfunction. We evaluated the discrimination for in-hospital mortality by the sepsis diagnosis and the number of organ dysfunction. RESULTS: Among 6553 eligible children, in-hospital mortality was 7.2 % in 875 children with sepsis and 0.2 % in 5678 children without sepsis. Sepsis diagnosis discriminated in-hospital mortality with a sensitivity of 0.84 and a specificity of 0.87. The area under the curve for mortality based on the number of organ dysfunction was 0.88 (95 % confidence interval:0.84 to 0.93). In-hospital mortality incrementally increased with the number of organ dysfunction; zero, 0.2 %; one, 3.4 %; two, 12.7 %; three, 20.9 %; four, 33.3 %; and five, 50.0 %. CONCLUSIONS: The surveillance method effectively identified children with sepsis with high-risk of mortality and demonstrated strong discrimination of mortality.

Unresponsive Low Mixed Venous Oxygen Saturation During Early Intensive Care Unit Stay is Associated With Increased Risk of Organ Dysfunction After Cardiac Surgery: A Single-Center Retrospective Study.

OBJECTIVES: The aim of the study was to determine if unresponsive mixed venous oxygen saturation (SvO2) values during early postoperative hours are associated with postoperative organ dysfunction. DESIGN: A single-center retrospective observational study. SETTING: A university hospital. PARTICIPANTS: A total of 6,282 adult patients requiring cardiac surgery who underwent surgery in a University Hospital from 2007 to 2020. INTERVENTIONS: A pulmonary artery catheter was used to gather SvO2 samples after surgery at admission to the intensive care unit (ICU) and 4 hours later. For the analysis, patients were divided into 4 groups according to their SvO2 values. The rate of organ dysfunctions categorized according to the SOFA score was then studied among these subgroups. MEASUREMENTS AND MAIN RESULTS: The crude mortality rate for the cohort at 1 year was 4.3%. Multiple organ dysfunction syndrome (MODS) was present in 33.0% of patients in the early postoperative phase. During the 4-hour initial treatment period, 43% of the 931 patients with low SvO2 on admission responded to goal-directed therapy to increase SvO2 >60%; whereas, in 57% of the 931 patients, the low SvO2 was sustained. According to the adjusted logistic regression analyses, the odds ratio for MODS (4.23 [95% CI 3.41-5.25]), renal- replacement therapy (4.97 [95% CI 3.28-7.52]), time on a ventilator (2.34 [95% CI 2.17-2.52]), and vasoactive-inotropic score >30 (3.62 [95% CI 2.96-4.43]) were the highest in the group with sustained low SvO2. CONCLUSIONS: Patients with SvO2 <60% at ICU admission and 4 hours later had the greatest risk of postoperative MODS. Responsiveness to a goal-directed therapy protocol targeting maintaining or increasing SvO2 ≥60% at and after ICU admission may be beneficial.

Characterization of multiple organ failure after ruptured abdominal aortic aneurysm repair.

BACKGROUND: Multiple organ failure (MOF) is associated with poor outcomes and increased mortality in sepsis and trauma. There are limited data regarding MOF in patients after ruptured abdominal aortic aneurysm (rAAA) repair. We aimed to identify the contemporary prevalence and characteristics of patients with rAAA with MOF. METHODS: We retrospectively reviewed patients with rAAA who underwent repair (2010-2020) at our multihospital institution. Patients who died within the first 2 days after repair were excluded. MOF was quantified by modified (excluding hepatic system) Denver, Sequential Organ Failure Assessment (SOFA) score, and Multiple Organ Dysfunction Score (MODS) for postoperative days 3 to 5 to determine the prevalence of MOF. MOF was defined as a Denver score of >3, dysfunction in two or more organ systems by SOFA score, or a MODS score of >8. Kaplan-Meier curves and log-rank testing were used to evaluate differences in 30-day mortality between multiple organ failure and patients without MOF. Logistic regression was used to assess predictors of MOF. RESULTS: Of 370 patients with rAAA, 288 survived past two days (mean age, 73±10.1 years; 76.7% male; 44.1% open repair), and 143 had data for MOF calculation recorded. From postoperative days 3 to 5, 41 (14.24%) had MOF by Denver, 26 (9.03%) by SOFA, and 39 (13.54%) by MODS criteria. Among these scoring systems, pulmonary and neurological systems were impacted most commonly. Among patients with MOF, pulmonary derangement occurred in 65.9% (Denver), 57.7% (SOFA), and 56.4% (MODS). Similarly, neurological derangement occurred in 92.3% (SOFA) and 89.7% (MODS), but renal derangement occurred in 26.8% (Denver), 23.1% (SOFA), and 10.3% (MODS). MOF by all three scoring systems was associated with increased 30-day mortality (Denver: 11.3% vs 41.5% [P < .01]; DOFA: 12.6% vs 46.2% [P < .01]; MODS: 12.5% vs 35.9% [P < .01]), as was MOF by any criteria (10.8% vs 35.7 %; P < .01). Patients with MOF were more likely to have a higher body mass index (55.9±26.6 vs 49.0±15.0; P = .011) and to have had a preoperative stroke (17.9% vs 6.0%; P = .016). Patients with MOF were less likely to have undergone endovascular repair (30.4% vs 62.1%; P < .001). Endovascular repair was protective against MOF (any criteria) on multivariate analysis (odds ratio, 0.23; 95% confidence interval, 0.08-0.64; P = .019) after adjusting for age, gender, and presenting systolic blood pressure. CONCLUSIONS: MOF occurred in only 9% to 14% of patients after rAAA repair, but was associated with a three-fold increase in mortality. Endovascular repair was associated with a reduced MOF incidence.

Longitudinal Analysis of Contrasts in Gene Expression Data.

We are interested in detecting a departure from the baseline in a longitudinal analysis in the context of multiple organ dysfunction syndrome (MODS). In particular, we are given gene expression reads at two time points for a fixed number of genes and individuals. The individuals can be subdivided into two groups, denoted as groups A and B. Using the two time points, we compute a contrast of gene expression reads per individual and gene. The age of each individual is known and it is used to compute, for each gene separately, a linear regression of the gene expression contrasts on the individual's age. Looking at the intercept of the linear regression to detect a departure from the baseline, we aim to reliably single out those genes for which there is a difference in the intercept among those individuals in group A and not in group B. In this work, we develop testing methodology for this setting based on two hypothesis tests-one under the null and one under an appropriately formulated alternative. We demonstrate the validity of our approach using a dataset created by bootstrapping from a real data application in the context of multiple organ dysfunction syndrome (MODS).

Comparison of Administrative versus Electronic Health Record-based Methods for Identifying Sepsis Hospitalizations.

Rationale: Despite the importance of sepsis surveillance, no optimal approach for identifying sepsis hospitalizations exists. The Centers for Disease Control and Prevention Adult Sepsis Event Definition (CDC-ASE) is an electronic medical record-based algorithm that yields more stable estimates over time than diagnostic coding-based approaches but may still result in misclassification. Objectives: We sought to assess three approaches to identifying sepsis hospitalizations, including a modified CDC-ASE. Methods: This cross-sectional study included patients in the Veterans Affairs Ann Arbor Healthcare System admitted via the emergency department (February 2021 to February 2022) with at least one episode of acute organ dysfunction within 48 hours of emergency department presentation. Patients were assessed for community-onset sepsis using three methods: 1) explicit diagnosis codes, 2) the CDC-ASE, and 3) a modified CDC-ASE. The modified CDC-ASE required at least two systemic inflammatory response syndrome criteria instead of blood culture collection and had a more sensitive definition of respiratory dysfunction. Each method was compared with a reference standard of physician adjudication via medical record review. Patients were considered to have sepsis if they had at least one episode of acute organ dysfunction graded as "definitely" or "probably" infection related on physician review. Results: Of 821 eligible hospitalizations, 449 were selected for physician review. Of these, 98 (21.8%) were classified as sepsis by medical record review, 103 (22.9%) by the CDC-ASE, 132 (29.4%) by the modified CDC-ASE, and 37 (8.2%) by diagnostic codes. Accuracy was similar across the three methods of interest (80.6% for the CDC-ASE, 79.6% for the modified CDC-ADE, and 84.2% for diagnostic codes), but sensitivity and specificity varied. The CDC-ASE algorithm had sensitivity of 58.2% (95% confidence interval [CI], 47.2-68.1%) and specificity of 86.9% (95% CI, 82.9-90.2%). The modified CDC-ASE algorithm had greater sensitivity (69.4% [95% CI, 59.3-78.3%]) but lower specificity (81.8% [95% CI, 77.3-85.7%]). Diagnostic codes had lower sensitivity (32.7% [95% CI, 23.5-42.9%]) but greater specificity (98.6% [95% CI, 96.7-99.55%]). Conclusions: There are several approaches to identifying sepsis hospitalizations for surveillance that have acceptable accuracy. These approaches yield varying sensitivity and specificity, so investigators should carefully consider the test characteristics of each method before determining an appropriate method for their intended use.

Obesity and alcoholic etiology as risk factors for multisystem organ failure in acute pancreatitis: Multinational study.

BACKGROUND: Multisystem organ failure (MSOF) is the most important determinant of mortality in acute pancreatitis (AP). Obesity and alcoholic etiology have been examined as potential risk factors for MSOF, but prior studies have not adequately elucidated their independent effects on the risk of MSOF. OBJECTIVE: We aimed to determine the adjusted effects of body mass index (BMI) and alcoholic etiology on the risk of MSOF in subjects with AP. METHODS: A prospective observational study of 22 centers from 10 countries was conducted. Patients admitted to an APPRENTICE consortium center with AP between August 2015 and January 2018 were enrolled. Multivariable logistic regression was used to estimate the adjusted effects of BMI, etiology, and other relevant covariates on the risk of MSOF. Models were stratified by sex. RESULTS: Among 1544 AP subjects, there was a sex-dependent association between BMI and the risk of MSOF. Increasing BMI was associated with increased odds of MSOF in males (OR 1.10, 95% confidence interval [CI] 1.04-1.15) but not in females (OR 0.98, 95% CI 0.90-1.1). Male subjects with AP, whose BMIs were 30-34 and >35 kg/m2 , had odds ratios of 3.78 (95% CI 1.62-8.83) and 3.44 (95% CI 1.08-9.99), respectively. In females, neither higher grades of obesity nor increasing age increased the risk of MSOF. Alcoholic etiology was independently associated with increased odds of MSOF compared with non-alcohol etiologies (OR 4.17, 95% CI 2.16-8.05). CONCLUSION: Patients with alcoholic etiology and obese men (but not women) are at substantially increased risk of MSOF in AP.

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

The Sequential Organ Failure Assessment (SOFA) score was developed more than 25 years ago to provide a simple method of assessing and monitoring organ dysfunction in critically ill patients. Changes in clinical practice over the last few decades, with new interventions and a greater focus on non-invasive monitoring systems, mean it is time to update the SOFA score. As a first step in this process, we propose some possible new variables that could be included in a SOFA 2.0. By so doing, we hope to stimulate debate and discussion to move toward a new, properly validated score that will be fit for modern practice.

Application of organ dysfunction assessment scores following pediatric lung transplantation.

OBJECTIVE: Organ dysfunction (OD) after lung transplantation can reflect preoperative organ failure, intraoperative acute organ damage and post-operative complications. We assessed two OD scoring systems, both the PEdiatric Logistic Organ Dysfunction (PELOD) and the pediatric Sequential Organ Failure Assessment (pSOFA) scores, in recognizing risk factors for morbidity as well as recipients with prolonged post-transplant morbidity. DESIGN: Medical records of recipients from January 2009 to March 2016 were reviewed. PELOD and pSOFA scores were calculated on post-transplant days 1-3. Risk factors assessed included cystic fibrosis (CF), prolonged surgical time and worst primary graft dysfunction (PGD) score amongst others. Patients were classified into three groups based on their initial scores (group A) and subsequent trends either uptrending (group B) or downtrending (group C). Morbidity outcomes were compared between these groups. RESULTS: Total 98 patients were enrolled aged 0-20 years. Risk factors for higher pSOFA scores ≥ 5 on day 1 included non-CF diagnosis and worst PGD scores (p = .0006 and p = .03, respectively). Kruskal Wallis analysis comparing pSOFA group A versus B versus C scores showed significantly prolonged ventilatory days (median 1 vs. 4 vs. 2, p = .0028) and ICU days (median 4 vs. 10 vs. 6, p = .007). Similarly, PELOD group A versus B versus C scores showed significantly prolonged ventilatory days (1 vs. 5 vs. 2, p = < .0001). CONCLUSION: Implementing pSOFA scores bedside is a more effective tool compared to PELOD in identifying risk factors for worsened OD post-lung transplant and can be valuable in providing direction on morbidity outcomes in the ICU.

Sequential organ failure assessment scores to predict outcomes: from adults to neonates.

PURPOSE OF REVIEW: Organ dysfunction severity scores (sequential organ failure assessment or SOFA) are commonly used in the adult and pediatric populations when assessing risk of mortality and adverse outcomes from sepsis. In contrast to sepsis definition in adults and children, clinical and laboratory criteria for defining neonatal sepsis have been inconclusive. More recently, studies have attempted to better understand the clinical progression of neonatal sepsis and associated mortality. This data has guided the development of a neonatal SOFA (nSOFA) score, based on common patterns of organ dysfunction observed in this population. RECENT FINDINGS: Although SOFA scores in the adult and pediatric populations have their limitations with moderate sensitivities and specificities depending on the clinical setting, the nSOFA score has been validated in predicting sepsis attributable mortality in very low birth weight (VLBW) infants across several patient cohorts. Furthermore, the nSOFA score has been adapted for use in neonatal disease states, other than sepsis, with similar prognostic utility. SUMMARY: Utilizing an nSOFA scoring system for prediction of sepsis attributable mortality in preterm infants allows for targeted interventions based on risk stratification, as well as better delineation of neonatal sepsis with subsequent improvements in research and patient safety outcomes.

Clinically Interpretable Machine Learning Models for Early Prediction of Mortality in Older Patients with Multiple Organ Dysfunction Syndrome: An International Multicenter Retrospective Study.

BACKGROUND: Multiple organ dysfunction syndrome (MODS) is associated with a high risk of mortality among older patients. Current severity scores are limited in their ability to assist clinicians with triage and management decisions. We aim to develop mortality prediction models for older patients with MODS admitted to the ICU. METHODS: The study analyzed older patients from 197 hospitals in the United States and 1 hospital in the Netherlands. The cohort was divided into the young-old (65-80 years) and old-old (≥80 years), which were separately used to develop and evaluate models including internal, external, and temporal validation. Demographic characteristics, comorbidities, vital signs, laboratory measurements, and treatments were used as predictors. We used the XGBoost algorithm to train models, and the SHapley Additive exPlanations (SHAP) method to interpret predictions. RESULTS: Thirty-four thousand four hundred and ninety-seven young-old (11.3% mortality) and 21 330 old-old (15.7% mortality) patients were analyzed. Discrimination AUROC of internal validation models in 9 046 U.S. patients was as follows: 0.87 and 0.82, respectively; discrimination of external validation models in 1 905 EUR patients was as follows: 0.86 and 0.85, respectively; and discrimination of temporal validation models in 8 690 U.S. patients: 0.85 and 0.78, respectively. These models outperformed standard clinical scores like Sequential Organ Failure Assessment and Acute Physiology Score III. The Glasgow Coma Scale, Charlson Comorbidity Index, and Code Status emerged as top predictors of mortality. CONCLUSIONS: Our models integrate data spanning physiologic and geriatric-relevant variables that outperform existing scores used in older adults with MODS, which represents a proof of concept of how machine learning can streamline data analysis for busy ICU clinicians to potentially optimize prognostication and decision making.