scholarly journals Outcome of Patients With Necrotizing Vasculitis Admitted to the Intensive Care Unit (ICU) for Sepsis: Results of a Single-Centre Retrospective Analysis

2020 ◽  
pp. 088506662095376
Author(s):  
Marco Krasselt ◽  
Christoph Baerwald ◽  
Sirak Petros ◽  
Olga Seifert

Introduction/Background: Vasculitis patients have a high risk for infections that may require intensive care unit (ICU) treatment in case of resulting sepsis. Since data on sepsis mortality in this patient group is limited, the present study investigated the clinical characteristics and outcomes of vasculitis patients admitted to the ICU for sepsis. Methods: The medical records of all necrotizing vasculitis patients admitted to the ICU of a tertiary hospital for sepsis in a 13-year period have been reviewed. Mortality was calculated and multivariate logistic regression was used to determine independent risk factors for sepsis mortality. Moreover, the predictive power of common ICU scores was further evaluated. Results: The study included 34 patients with necrotizing vasculitis (mean age 69 ± 9.9 years, 35.3% females). 47.1% (n = 16) were treated with immunosuppressives (mostly cyclophosphamide, n = 35.3%) and 76.5% (n = 26) received glucocorticoids. Rituximab was used in 4 patients (11.8%).The in-hospital mortality of septic vasculitis patients was 41.2%. The Sequential Organ Failure Assessment (SOFA) score (p = 0.003) was independently associated with mortality in multivariate logistic regression. Acute Physiology And Chronic Health Evaluation II (APACHE II), Simplified Acute Physiology Score II (SAPS II) and SOFA scores were good predictors of sepsis mortality in the investigated vasculitis patients (APACHE II AUC 0.73, p = 0.02; SAPS II AUC 0.81, p < 0.01; SOFA AUC 0.898, p < 0.0001). Conclusions: Sepsis mortality was high in vasculitis patients. SOFA was independently associated with mortality in a logistic regression model. SOFA and other well-established ICU scores were good mortality predictors.

2021 ◽  
pp. 088506662199625
Author(s):  
Marco Krasselt ◽  
Christoph Baerwald ◽  
Sirak Petros ◽  
Olga Seifert

Objectives: Patients with connective tissue diseases (CTD) such as systemic lupus erythematosus (SLE) have an increased risk for infections. This study investigated the outcome and characteristics of CTD patients under intensive care unit (ICU) treatment for sepsis. Methods: A single-center retrospective analysis was conducted and reviewed all patients with a CTD diagnosis admitted to the ICU of a university hospital for sepsis between 2006 and 2019. Mortality was computed and multivariate logistic regression was used to detect independent risk factors for sepsis mortality. Furthermore, the positive predictive value of ICU scores such as Sequential Organ Failure Assessment (SOFA) score was evaluated. Results: This study included 44 patients with CTD (mean age 59.8 ± 16.1 years, 68.2% females), most of them with a diagnosed SLE (61.4%) followed by systemic sclerosis (15.9%). 56.8% (n = 25) were treated with immunosuppressives and 81.8% (n = 36) received glucocorticoids. Rituximab was used in 3 patients (6.8%). The hospital mortality of septic CTD patients was high with 40.9%. It was highest among systemic sclerosis (SSc) patients (85.7%). SOFA score and diagnosis of SSc were independently associated with mortality in multivariate logistic regression ( P = 0.004 and 0.03, respectively). The Simplified Acute Physiology Score II (SAPS II), SOFA and Acute Physiology and Chronic Health Evaluation II (APACHE II) scores were good predictors of sepsis mortality in the investigated cohort (SAPS II AUC 0.772, P = 0.002; SOFA AUC 0.756, P = 0.004; APACHE II AUC 0.741, P = 0.007). Conclusions: In-hospital sepsis mortality is high in CTD patients. SSc diagnoses and SOFA were independently associated with mortality. Additionally, common ICU scores were good predictors for mortality.


2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 665.1-666
Author(s):  
P. Korsten ◽  
F. Kück ◽  
K. Tejiozem Donfack ◽  
R. Vasko ◽  
A. Lena ◽  
...  

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


2020 ◽  
pp. 088506662091758 ◽  
Author(s):  
Marco Krasselt ◽  
Christoph Baerwald ◽  
Sirak Petros ◽  
Olga Seifert

Introduction/Background: Patients with rheumatoid arthritis (RA) have a high risk of infections that may require intensive care unit (ICU) admission in case of resulting sepsis. Data regarding the mortality of these patients are very limited. This study investigated clinical characteristics and outcomes of patients with RA admitted to the ICU for sepsis and compared the results to a control cohort without RA. Methods: All patients with RA as well as sex-, age-, and admission year-matched controls admitted to the ICU of a university hospital for sepsis between 2006 and 2019 were retrospectively analyzed. Mortality was calculated for both the groups, and multivariate logistic regression was used to determine independent risk factors for sepsis mortality. The positive predictive value of common ICU scores was also investigated. Results: The study included 49 patients with RA (mean age 67.2 ± 9.0 years, 63.3% females) and 51 matched controls (mean age 67.4 ± 9.5 years, 64.7% females). Among the patients with RA, 42.9% (n = 21) were treated with conventional synthetic (cs) disease-modifying antirheumatic drugs (DMARDs) and 30.6% (n = 15) received glucocorticoids only. Seven (14.3%) patients received biologic (b) DMARDs. The hospital mortality was higher among patients with RA (42.9% vs 15.7%, P = .0016). Rheumatoid arthritis was independently associated with mortality in multivariate logistic regression ( P = .001). In patients with RA, renal replacement therapy ( P = .024), renal failure ( P = .027), and diabetes mellitus ( P = .028) were independently associated with mortality. Acute Physiology and Chronic Health Evaluation II (APACHE II), Simplified Acute Physiology Score II (SAPS II), and Sequential Organ Failure Assessment (SOFA) scores were good predictors of sepsis mortality in patients with RA (APACHE II area under the curve [AUC]: 0.78, P = .001; SAPS II AUC: 0.78, P < .001; SOFA AUC 0.78, P < .001), but their predictive power was higher among controls. Conclusions: Hospital sepsis mortality was higher in patients with RA than in controls. Rheumatoid arthritis itself is independently associated with an increased sepsis mortality. Renal replacement therapy, renal failure, and diabetes were associated with an increased mortality. Common ICU scores were less well predictors of sepsis mortality in patients with RA compared to non-RA controls.


2005 ◽  
Vol 22 (Supplement 34) ◽  
pp. 169
Author(s):  
K. Desa ◽  
Z. Zupan ◽  
B. Krstulovic ◽  
V. Golubovic ◽  
A. Sustic

Author(s):  
Piotr A. Fuchs ◽  
Iwona J. Czech ◽  
Łukasz J. Krzych

Background: The Simplified Acute Physiology Score (SAPS) II, Acute Physiology and Chronic Health Evaluation (APACHE) II, and Sequential Organ Failure Assessment (SOFA) scales are scoring systems used in intensive care units (ICUs) worldwide. We aimed to investigate their usefulness in predicting short- and long-term prognosis in the local ICU. Methods: This single-center observational study covered 905 patients admitted from 1 January 2015 to 31 December 2017 to a tertiary mixed ICU. SAPS II, APACHE II, and SOFA scores were calculated based on the worst values from the first 24 h post-admission. Patients were divided into surgical (SP) and nonsurgical (NSP) subjects. Unadjusted ICU and post-ICU discharge mortality rates were considered the outcomes. Results: Baseline SAPS II, APACHE II, and SOFA scores were 41.1 ± 20.34, 14.07 ± 8.73, and 6.33 ± 4.12 points, respectively. All scores were significantly lower among SP compared to NSP (p < 0.05). ICU mortality reached 35.4% and was significantly lower for SP (25.3%) than NSP (57.9%) (p < 0.001). The areas under the receiver-operating characteristic (ROC) curves were 0.826, 0.836, and 0.788 for SAPS II, APACHE II, and SOFA scales, respectively, for predicting ICU prognosis, and 0.708, 0.709, and 0.661 for SAPS II, APACHE II, and SOFA, respectively, for post-ICU prognosis. Conclusions: Although APACHE II and SAPS II are good predictors of ICU mortality, they failed to predict survival after discharge. Surgical patients had a better prognosis than medical ICU patients.


2019 ◽  
Vol 8 (10) ◽  
pp. 1709 ◽  
Author(s):  
Tsung-Lun Tsai ◽  
Min-Hsin Huang ◽  
Chia-Yen Lee ◽  
Wu-Wei Lai

Besides the traditional indices such as biochemistry, arterial blood gas, rapid shallow breathing index (RSBI), acute physiology and chronic health evaluation (APACHE) II score, this study suggests a data science framework for extubation prediction in the surgical intensive care unit (SICU) and investigates the value of the information our prediction model provides. A data science framework including variable selection (e.g., multivariate adaptive regression splines, stepwise logistic regression and random forest), prediction models (e.g., support vector machine, boosting logistic regression and backpropagation neural network (BPN)) and decision analysis (e.g., Bayesian method) is proposed to identify the important variables and support the extubation decision. An empirical study of a leading hospital in Taiwan in 2015–2016 is conducted to validate the proposed framework. The results show that APACHE II and white blood cells (WBC) are the two most critical variables, and then the priority sequence is eye opening, heart rate, glucose, sodium and hematocrit. BPN with selected variables shows better prediction performance (sensitivity: 0.830; specificity: 0.890; accuracy 0.860) than that with APACHE II or RSBI. The value of information is further investigated and shows that the expected value of experimentation (EVE), 0.652 days (patient staying in the ICU), is saved when comparing with current clinical experience. Furthermore, the maximal value of information occurs in a failure rate around 7.1% and it reveals the “best applicable condition” of the proposed prediction model. The results validate the decision quality and useful information provided by our predicted model.


Author(s):  
Shao-Chun Wu ◽  
Sheng-En Chou ◽  
Hang-Tsung Liu ◽  
Ting-Min Hsieh ◽  
Wei-Ti Su ◽  
...  

Background: Prediction of mortality outcomes in trauma patients in the intensive care unit (ICU) is important for patient care and quality improvement. We aimed to measure the performance of 11 prognostic scoring systems for predicting mortality outcomes in trauma patients in the ICU. Methods: Prospectively registered data in the Trauma Registry System from 1 January 2016 to 31 December 2018 were used to extract scores from prognostic scoring systems for 1554 trauma patients in the ICU. The following systems were used: the Trauma and Injury Severity Score (TRISS); the Acute Physiology and Chronic Health Evaluation (APACHE II); the Simplified Acute Physiology Score (SAPS II); mortality prediction models (MPM II) at admission, 24, 48, and 72 h; the Multiple Organ Dysfunction Score (MODS); the Sequential Organ Failure Assessment (SOFA); the Logistic Organ Dysfunction Score (LODS); and the Three Days Recalibrated ICU Outcome Score (TRIOS). Predictive performance was determined according to the area under the receiver operator characteristic curve (AUC). Results: MPM II at 24 h had the highest AUC (0.9213), followed by MPM II at 48 h (AUC: 0.9105). MPM II at 24, 48, and 72 h (0.8956) had a significantly higher AUC than the TRISS (AUC: 0.8814), APACHE II (AUC: 0.8923), SAPS II (AUC: 0.9044), MPM II at admission (AUC: 0.9063), MODS (AUC: 0.8179), SOFA (AUC: 0.7073), LODS (AUC: 0.9013), and TRIOS (AUC: 0.8701). There was no significant difference in the predictive performance of MPM II at 24 and 48 h (p = 0.37) or at 72 h (p = 0.10). Conclusions: We compared 11 prognostic scoring systems and demonstrated that MPM II at 24 h had the best predictive performance for 1554 trauma patients in the ICU.


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