Simplified Acute Physiology Score 3 Performance in Austrian COVID-19 Patients with and Without Diabetes

Background: TheSimplified Acute Physiology Score 3 (SAPS 3) is routinely used in intensive care units (ICUs) to predict in-hospital mortality. However, its predictive performance has not been widely evaluated in Coronavirus disease 19 (COVID-19) patients.This studyevaluated and comparedthe performance of SAPS 3for predicting in-hospital mortalityinCOVID-19patients with and without diabetesin Austria.Methods: This study analyzed the Austrian national public health institute (GÖG) data ofCOVID-19patients admitted to ICUs (N=5,850)fromMarch 2020 to March 2021.The SAPS 3 score was calculated and the predicted in-hospital mortality was estimatedusingthreelogit regression equations: standard equation, Central European equation, and Austrian equation recalibrated for COVID-19 patients. Concordance between observed and predicted mortalities was assessed using the standardized mortality ratio (SMR). Discrimination was assessed using the C-statistic. The DeLong test was applied to compare discrimination between diabetes and non-diabetes patients. Accuracy was assessed using the Brier score andcalibration using the calibration plot and Hosmer-Lemeshow test. Results: Theobservedin-hospital mortality was 38.9% in all patients, 42.9% in diabetes, and 37.3% innon-diabetes patients. Themean ±SD SAPS 3 score was 57.4 ±13.2 in all patients,58.8 ±12.9 in diabetes, and 56.8 ±13.2 in non-diabetes patients.The SMR was significantly greater than 1 for standard and Central European equations, while it was close to 1 for the Austrian equation in all, diabetes, and non-diabetes patients. TheC-statistics was 0.69 with aninsignificant (P=0.193) difference between diabetes (0.70)and non-diabetes (0.68)patients. The Brier score was >0.20 for all SAPS 3 equations. Calibration was unsatisfactory for both standard and Central European equations in all cohorts, whereas it was satisfactory for the Austrian equation in diabetes patients.Conclusions:The SAPS 3 score demonstratedlow discrimination and accuracy in COVID-19 patients in Austria with aninsignificant difference between diabetes and non-diabetes patients. All three equations of SAPS 3 were miscalibrated particularly in non-diabetes patients, while the Austrian equation demonstrated satisfactory calibration in diabetes patients. These findingssuggest that both uncalibrated and calibrated versions ofSAPS 3 should be used with caution in COVID-19 patients.

Pediatric Simplified Acute Physiology Score II: Establishment of a New, Repeatable Pediatric Mortality Risk Assessment Score

Objectives: In critical care it is crucial to appropriately assess the risk of mortality for each patient. This is especially relevant in pediatrics, with its need for accurate and repeatable scoring. Aim of this study was to evaluate an age-adapted version of the expanded Simplified Acute Physiology Score II; (p-SAPS II), a repeatable, newly-designed scoring system compared to established scores (Pediatric Sequential Organ Failure Assessment Score/pSOFA, Pediatric Logistic Organ Dysfunction Score-2/PELOD-2 and Pediatric Index of Mortality 3/PIM3).Design: This retrospective cohort pilot study included data collected from patients admitted to the Pediatric Intensive Care Unit (PICU) at the Medical University of Vienna between July 2017 through December 2018.Patients: 231 admissions were included, comprising neonates (gestational age of ≥ 37 weeks) and patients up to 18 years of age with a PICU stay longer than 48 h.Main Outcomes: Mortality risk prediction and discrimination between survivors and non-survivors were the main outcomes of this study. The primary statistical methods for evaluating the performance of each score were the area under the receiver operating characteristic curve (AUROC) and goodness-of-fit test.Results: Highest AUROC curve was calculated for p-SAPS II (AUC = 0.86; 95% CI: 0.77–0.96; p < 0.001). This was significantly higher than the AUROCs of PELOD-2/pSOFA but not of PIM3. However, in a logistic regression model including p-SAPS II and PIM3 as covariates, p-SAPS II had a significant effect on the accuracy of prediction (p = 0.003). Nevertheless, according to the goodness-of-fit test for p-SAPS II and PIM3, p-SAPS II overestimated the number of deaths, whereas PIM3 showed acceptable estimations. Repeatability testing showed increasing AUROC values for p-SAPS II throughout the clinical stay (0.96 at day 28) but still no significant difference to PIM 3. The prediction accuracy, although improved over the days and even exceeded PIM 3.Conclusions: The newly-created p-SAPS II performed better than the established PIM3 in terms of discriminating between survivors and non-survivors. Furthermore, p-SAPS II can be assessed repeatably throughout a patient's PICU stay what improves mortality prediction. However, there is still a need to optimize calibration of the score to accurately predict mortality sooner throughout the clinical stay.

Associations between YKL-40 and markers of disease severity and death in patients with necrotizing soft-tissue infection

Background Necrotizing soft-tissue infection (NSTI) is a severe and fast-progressing bacterial infection. Prognostic biomarkers may provide valuable information in treatment guidance and decision-making, but none have provided sufficient robustness to have a clinical impact. YKL-40 may reflect the ongoing pathological inflammatory processes more accurately than traditional biomarkers as it is secreted by the activated immune cells, but its prognostic yields in NSTI remains unknown. For this purpose, we investigated the association between plasma YKL-40 and 30-day mortality in patients with NSTI, and assessed its value as a marker of disease severity. Methods We determined plasma YKL-40 levels in patients with NSTI (n = 161) and age-sex matched controls (n = 65) upon admission and at day 1, 2 and 3. Results Baseline plasma YKL-40 was 1191 ng/mL in patients with NSTI compared with 40 ng/mL in controls (p < 0.001). YKL-40 was found to be significantly higher in patients with septic shock (1942 vs. 720 ng/mL, p < 0.001), and in patients receiving renal-replacement therapy (2382 vs. 1041 ng/mL, p < 0.001). YKL-40 correlated with Simplified Acute Physiology Score II (Rho 0.33, p < 0.001). Baseline YKL-40 above 1840 ng/mL was associated with increased risk of 30-day mortality in age-sex-comorbidity adjusted analysis (OR 3.77, 95% CI; 1.59–9.24, p = 0.003), but after further adjustment for Simplified Acute Physiology Score II no association was found between YKL-40 and early mortality. Conclusion High plasma YKL-40 to be associated with disease severity, renal-replacement therapy and risk of death in patients with NSTI. However, YKL-40 is not an independent predictor of 30-day mortality.

POS0825 DEVELOPMENT OF A NEW AND SIMPLIFIED FORMULA TO PREDICT MORTALITY IN PATIENTS WITH ANCA-ASSOCIATED VASCULITIS ADMITTED TO THE INTENSIVE CARE UNIT

Background:ANCA-associated vasculitis (AAV) can present with a wide range of symptoms, including acute kidney injury (AKI) requiring renal replacement therapy or diffuse alveolar hemorrhage (1). These two manifestations often require admission to an intensive care unit (ICU) and are associated with increased mortality. To predict ICU mortality, the Simplified Acute Physiology Score version 2 (SAPS2) is often used but has not been formally tested in AAV patients (2). In addition, it is cumbersome to assess.Objectives:To develop a novel, simplified formula to predict ICU mortality in an AAV ICU population from an academic tertiary care center.Methods:We retrospectively recorded clinical and laboratory parameters in patients admitted to our ICU from 2000-2018. We performed risk factor analysis using univariate and multivariate logistic regression. In the multivariate case we applied the least absolute shrinkage and selection operator (lasso) method for variable selection. We considered average marginal effects and partial dependence plots in order to describe the influence of various independent variables on the probability of death more specifically. We evaluated our new score by comparing the corresponding area under the curve (AUC) to the AUC corresponding to the established SAPS2 score.Results:We analyzed 58 patients with AAV (39 granulomatosis with polyangiitis, 19 with microscopic polyangiitis) with a mean age of 74±14 (GPA) and 73±12 (MPA). 19/39 (48.7%) of GPA and 9/19 (47.4%) were female. Reasons for admission included disease manifestations or infectious complications from treatment (e. g. pneumonia, urinary tract infection). In total, 13/58 (22.4%) patients died throughout the study (10 GPA, 3 MPA patients). Using a cut-off threshold of 40 for SAPS2, sensitivity and specificity for mortality were 0.92 and 0.60, respectively. Confidence interval for the AUC was [0.68,0.95]. In the fitted multivariate logistic regression model, lasso was applied for variable selection. The identified variables included: disease duration, pH, procalcitonin, hemoglobin, leukocytes on admission, coronary heart disease, and pneumonia on admission. The estimated mortality is given by the formula ƒ(β0 + β1χ1 + …+ β7χ7), where ƒ(u)=1/(1+exp(−u)). Table 1 shows the estimated mortality for various values of the new score.Table 1.Example scores predicting mortality using the novel formula.ScorePredicted mortality-2.20.1-1.10.2500.51.10.752.20.9Testing if the AUC corresponding to the new model is significantly larger than the one corresponding to the SAPS2 score as independent variable resulted in p-value of 0.037. To identify possible overfitting, a 5-fold cross validation was performed. This resulted in a CI for the AUC of [0.64,0.96], suggesting that the new score allows for simpler prediction of mortality.Conclusion:We developed a novel formula corresponding to a score which is able to simpler predict mortality in patients with AAV admitted to the ICU. We will test our formula in the available ICU database MIMIC III, which comprises a large dataset of ICU patients.References:[1]Kitching AR, Anders H-J, Basu N, Brouwer E, Gordon J, Jayne DR, et al. ANCA-associated vasculitis. Nature Reviews Disease Primers. 2020 Aug 27;6(1):1–27.[2]Le Gall JR, Lemeshow S, Saulnier F. A new Simplified Acute Physiology Score (SAPS II) based on a European/North American multicenter study. JAMA. 1993 Dec 22;270(24):2957–63.Disclosure of Interests:PETER KORSTEN Speakers bureau: Chugai, Boehringer-Ingelheim, Sanofi Aventis, Abbvie, GSK, Novartis, Consultant of: Lilly, Gilead, Abbvie, Boehringer-Ingelheim, GSK, Novartis, Grant/research support from: GSK, Fabian Kück: None declared, Karaine Tejiozem Donfack: None declared, Radovan Vasko: None declared, Andreas Lena: None declared, Björn Tampe: None declared

Índices de gravidade em vítimas de trauma contuso na terapia intensiva: capacidade preditiva de mortalidade

RESUMO Objetivo: Identificar a capacidade preditiva de mortalidade dos índices Revised Trauma Score, Rapid Emergency Medicine Score, modified Rapid Emergency Medicine Score e Simplified Acute Physiology Score III em vítimas de trauma contuso internadas em unidade de terapia intensiva e comparar seu desempenho. Método: Coorte retrospectiva de pacientes com trauma contuso de uma unidade de terapia intensiva a partir do registro em prontuários. Receiver Operating Characteristic e intervalo de confiança de 95% da área sob a curva foram analisados para comparar os resultados. Resultados: Dos 165 pacientes analisados, 66,7% tiveram tratamento cirúrgico. A mortalidade na unidade de terapia intensiva e no hospital foi de 17,6% e 20,6%, respectivamente. Para mortalidade na terapia intensiva, houve variação das áreas sob a curva entre 0,672 e 0,738; porém, melhores resultados foram observados em pacientes cirúrgicos (0,747 a 0,811). Resultados similares foram observados para mortalidade hospitalar. Em todas as análises, as áreas sob a curva dos índices não diferiram significativamente. Conclusão: Houve acurácia moderada dos índices de gravidade, com melhora na performance quando aplicados em pacientes cirúrgicos. Os quatro índices apresentaram predição similar para os desfechos analisados.

Blood Urea Nitrogen to Serum Albumin Ratio Independently Predicts Mortality in Critically Ill Patients With Acute Pulmonary Embolism

Acute pulmonary embolism (APE) is one of the prominent causes of death in patients with cardiovascular disease. Currently, reliable biomarkers to predict the prognosis of patients with APE are limited. The present study aimed to investigate the association of blood urea nitrogen to serum albumin (B/A) ratio and intensive care unit (ICU) mortality in critically ill patients with APE. A retrospective cohort study was performed using data extracted from a freely accessible critical care database (MIMIC-III). Adult (≥18 years) patients of first ICU admission with a primary diagnosis of APE in the database were enrolled in the study. The primary endpoint was the ICU mortality rate while the 28-day mortality after ICU admission was the secondary endpoint. The data of survivors and non-survivors were compared. A total of 1048 patients with APE were enrolled in this study, of which 131 patients died in ICU and 169 patients died within 28 days after ICU admission. The B/A ratio in the non-survivors group was significantly higher compared to the survivors group ( P < 0.001). The multivariate analysis revealed that the B/A ratio was an independent predictor of ICU mortality (odds ratio [OR] 1.10, 95% CI 1.07-1.14, P < 0.001) and all-cause mortality within 28 days after ICU admission (hazard ratio [HR] 1.07, 95% CI 1.05-1.09, P < 0.001) in APE patients. The B/A ratio showed a greater area under the curve (AUC) of ICU mortality prediction (0.80; P < 0.001) than simplified acute physiology score II (SAPSII) (0.79), systemic inflammatory response syndrome score (SIRS) (0.62), acute physiology score III (APSIII) (0.76) and sequential organ failure assessment (SOFA) score (0.71). The B/A ratio could be a simple and useful prognostic tool to predict mortality in critically ill patients with APE.

Prognostic indicators in critically ill poisoned patients: development of a risk-prediction nomogram

ObjectivesThe prognosis of acutely poisoned patients is a significant concern for clinical toxicologists. In this study, we sought to determine the clinical and laboratory findings that can contribute to predicting the medical outcomes of poisoned patients admitted to intensive care units (ICUs).MethodsThis retrospective study was performed from January 2009 to January 2016 in the ICU of Vali-e-Asr Hospital in Birjand, Iran. We included all patients with the diagnosis of acute poisoning admitted to the ICU. Demographic data, laboratory results, the Sequential Organ Failure Assessment (SOFA), and acute physiology score + age points + chronic health points (APACHE) II, and the Simplified Acute Physiology Score (SAPS) II, and outcome were collected. Univariate analysis (Mann–Whitney or t-test), multiple logistic regression, receiver operating characteristics (ROC) curve analysis, and Pearson’s correlation test were performed using SPSS, STATA/SE 13.0, and Nomolog software programs.ResultsThe multiple logistic regression analysis revealed that five factors were significant for predicting mortality including age (OR 95% CI: 1.1[1.05–1.12], p<0.001), Glasgow Coma Score (GCS) (OR 95% CI: 0.71[0.6–0.84], p<0.001), white blood cell (WBC) count (OR 95% CI: 1.1[1.01–1.12], p=0.04), serum sodium (Na) (OR 95% CI: 1.08[1.01–1.15], p=0.02), and creatinine levels (Cr) (OR 95% CI: 1.86 [1.23–2.81], p=0.003). We generated a five-variable risk-prediction nomogram which could both predict mortality risk and identify high-risk patients.ConclusionsAge, GCS, WBC, serum creatinine, and sodium levels are the best prognostic factors for mortality in poisoned patients admitted to the ICU. The APACHE II score can discriminate between non-survivors and survivors. The nomogram developed in the current study can provide a more precise, quick, and simple analysis of risks, thereby enabling the users to predict mortality and identify high-risk patients.