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

Abstract 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.

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Validation of the Preoperative Score to Predict Postoperative Mortality (POSPOM) in Germany

PLoS ONE ◽

10.1371/journal.pone.0245841 ◽

2021 ◽

Vol 16 (1) ◽

pp. e0245841

Author(s):

Yannik C. Layer ◽

Jan Menzenbach ◽

Yonah L. Layer ◽

Andreas Mayr ◽

Tobias Hilbert ◽

...

Keyword(s):

Hospital Mortality ◽

Postoperative Mortality ◽

University Hospital ◽

Brier Score ◽

Calibration Plot ◽

Coding System ◽

C Statistic ◽

Using Data ◽

Previous Demonstration ◽

Preoperative Score

Background The Preoperative Score to Predict Postoperative Mortality (POSPOM) based on preoperatively available data was presented by Le Manach et al. in 2016. This prognostic model considers the kind of surgical procedure, patients' age and 15 defined comorbidities to predict the risk of postoperative in-hospital mortality. Objective of the present study was to validate POSPOM for the German healthcare coding system (G-POSPOM). Methods and findings All cases involving anaesthesia performed at the University Hospital Bonn between 2006 and 2017 were analysed retrospectively. Procedures codified according to the French Groupes Homogènes de Malades (GHM) were translated and adapted to the German Operationen- und Prozedurenschlüssel (OPS). Comorbidities were identified by the documented International Statistical Classification of Diseases (ICD-10) coding. POSPOM was calculated for the analysed patient collective using these data according to the method described by Le Manach et al. Performance of thereby adapted POSPOM was tested using c-statistic, Brier score and a calibration plot. Validation was performed using data from 199,780 surgical cases. With a mean age of 56.33 years (SD 18.59) and a proportion of 49.24% females, the overall cohort had a mean POSPOM value of 18.18 (SD 8.11). There were 4,066 in-hospital deaths, corresponding to an in-hospital mortality rate of 2.04% (95% CI 1.97 to 2.09%) in our sample. POSPOM showed a good performance with a c-statistic of 0.771 and a Brier score of 0.021. Conclusions After adapting POSPOM to the German coding system, we were able to validate the score using patient data of a German university hospital. According to previous demonstration for French patient cohorts, we observed a good correlation of POSPOM with in-hospital mortality. Therefore, further adjustments of POSPOM considering also multicentre and transnational validation should be pursued based on this proof of concept.

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Early prediction of in-hospital mortality in acute pancreatitis: a retrospective observational cohort study based on a large multicentre critical care database

BMJ Open ◽

10.1136/bmjopen-2020-041893 ◽

2020 ◽

Vol 10 (12) ◽

pp. e041893

Author(s):

Caifeng Li ◽

Qian Ren ◽

Zhiqiang Wang ◽

Guolin Wang

Keyword(s):

Risk Factors ◽

Acute Pancreatitis ◽

Multivariate Analysis ◽

Hospital Mortality ◽

Observational Cohort Study ◽

Calibration Plot ◽

Observational Cohort ◽

Care Database ◽

Retrospective Observational Cohort Study ◽

Apache Iv

ObjectiveTo develop and validate a prediction model for predicting in-hospital mortality in patients with acute pancreatitis (AP).DesignA retrospective observational cohort study based on a large multicentre critical care database.SettingAll subject data were collected from the eICU Collaborative Research Database (eICU-CRD), which covers 200 859 intensive care unit admissions of 139 367 patients in 208 US hospitals between 2014 and 2015.ParticipantsA total of 746 patients with AP were drawn from eICU-CRD. Due to loss to follow-up (four patients) or incomplete data (364 patients), 378 patients were enrolled in the primary cohort to establish a nomogram model and to conduct internal validation.Primary and secondary outcome measuresThe outcome of the prediction model was in-hospital mortality. All risk factors found significant in the univariate analysis were considered for multivariate analysis to adjust for confounding factors. Then a nomogram model was established. The performance of the nomogram model was evaluated by the concordance index (C-index) and the calibration plot. The nomogram model was internally validated using the bootstrap resampling method. The predictive accuracy of the nomogram model was compared with that of Acute Physiology, Age, and Chronic Health Evaluation (APACHE) IV. Decision curve analysis (DCA) was performed to evaluate and compare the potential net benefit using of different predictive models.ResultsThe overall in-hospital mortality rate is 4.447%. Age, BUN (blood urea nitrogen) and lactate (ABL) were the independent risk factors determined by multivariate analysis. The C-index of nomogram model ABL (0.896 (95% CI 0.825 to 0.967)) was similar to that of APACHE IV (p=0.086), showing a comparable discriminating power. Calibration plot demonstrated good agreement between the predicted and the actual in-hospital mortality. DCA showed that the nomogram model ABL was clinically useful.ConclusionsNomogram model ABL, which used readily available data, exhibited high predictive value for predicting in-hospital mortality in AP.

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Hospital Standardized Mortality Ratio: Consequences of Adjusting Hospital Mortality with Indirect Standardization

PLoS ONE ◽

10.1371/journal.pone.0059160 ◽

2013 ◽

Vol 8 (4) ◽

pp. e59160 ◽

Cited By ~ 24

Author(s):

Maurice E. Pouw ◽

Linda M. Peelen ◽

Hester F. Lingsma ◽

Daniel Pieter ◽

Ewout Steyerberg ◽

...

Keyword(s):

Hospital Mortality ◽

Standardized Mortality Ratio ◽

Mortality Ratio ◽

Indirect Standardization

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Effect of Arterial Hypertension on the ICAM-1, VCAM-1 and Е-selectin Level in Type 2 Diabetes Patients

Family Medicine ◽

10.30841/2307-5112.2-3.2021.240763 ◽

2021 ◽

pp. 43-47

Author(s):

Liliia Mogylnytska

Keyword(s):

Insulin Resistance ◽

Type 2 Diabetes ◽

Cardiovascular Disease ◽

Endothelial Dysfunction ◽

Serum Level ◽

Control Group ◽

Regression Equations ◽

Multifactor Regression ◽

Diabetes Patients

Cardiovascular disease is the leading cause of death in diabetes mellitus. Endothelial dysfunction is the first step in the development of atherosclerotic vascular lesions, which underlies cardiovascular pathology, and adhesion molecules secreted by the endothelium during inflammatory changes are involved in the progression of this lesion. The objective: the serum level of adhesive molecules (ІCAM-1, VCAM-1, Е-selectin) in hypertensive and non-hypertensive type 2 diabetes patients as a marker of endothelial dysfunction and its relationship with other risk factors for cardiovascular disease was studied. Materials and methods. We examined 64 patients with type 2 diabetes, which were divided into two subgroups: the first subgroup – 41 hypertensive type 2 diabetes patients (age – 53,56±7,14 years, BMI – 32,2±87,4; HbA1c – 9,97±2,02%), the second subgroup – 23 nonhypertensive type 2 diabetes patients (age – 50,5±4,92 years, BMI – 25,4±5,22; HbA1c – 9,09±1,95%). The control group included 18 people without diabetes with normal blood pressure (age – 50,72±6,98 years, BMI – 24,71±4,88; HbA1c – 5,26±0,42%). The serum level was determined by immunoenzyme assay. The significance of the difference between the mean values was determined by the t-Student test. Multifactor regression analysis was used to assess the relationships between the studied factors. Results. We revealed an increase of serum levels of ІCAM-1, VCAM-1, Е-selectin in hypertensive (+71,62%, +68,42%, +66,95%, respectively) and non-hypertensive type 2 diabetes patients (+46,17%, +62,79%, +42,85%, respectively) compared with the control group (p<0,01). The serum concentration of ІCAM-1, Е-selectin was higher in hypertensive type 2 diabetes patients compared to non-hypertensive type 2 diabetes patients (+17,27%, +16,86%, respectively, p<0,01). There was a significant effect of Hb1Ac, lipids, insulin resistance on the serum level of ІCAM-1, VCAM-1, Е-selectin (p<0,01). The corresponding regression equations are derived. Conclusion. There is an increase of serum level of ІCAM-1, VCAM-1, Е-selectin in hypertensive and non-hypertensive type 2 diabetes patients, which indicates the development of endothelial dysfunction. Hypertension, hyperglycemia, dyslipidemia and insulin resistance contribute to the development of these changes.

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VALIDATION AND COMPARISON OF TWO 30-DAY RE-ADMISSION PREDICTION MODELS IN PATIENTS WITH DIABETES

Endocrine Practice ◽

10.4158/ep-2019-0125 ◽

2019 ◽

Vol 25 (11) ◽

pp. 1151-1157

Author(s):

Ahmad A. Alamer ◽

Asad E. Patanwala ◽

Ali M. Aldayyen ◽

Maryam T. Fazel

Keyword(s):

Confidence Interval ◽

Predictive Performance ◽

The United States ◽

Brier Score ◽

Risk Indicator ◽

C Statistic ◽

Tertiary Center ◽

Lemeshow Test ◽

Receiver Operating ◽

Diabetes Patients

Objective: The objective was to evaluate the 30-day re-admission predictive performance of the HOSPITAL score and Diabetes Early Re-admission Risk Indicator (DERRI™) in hospitalized diabetes patients. Methods: This was a case-control study in an academic, tertiary center in the United States. Adult hospitalized diabetes patients were randomly identified between January 1, 2014, and September 30, 2017. Patients were categorized into two groups: ( 1) re-admitted within 30 days, and ( 2) not re-admitted within 30 days. Predictive performance of the HOSPITAL and DERRI™ scores was evaluated by calculating receiver operating characteristics curves (c-statistic), Hosmer-Lemeshow goodness-of-fit tests, and Brier scores. Results: A total of 200 patients were included (100 re-admitted, 100 non–re-admitted). The HOSPITAL score had a c-statistic of 0.731 (95% confidence interval [CI], 0.661 to 0.800), Hosmer-Lemeshow test P = .211, and Brier score 0.212. The DERRI™ score had a c-statistic of 0.796 (95% CI, 0.734 to 0.857), Hosmer-Lemeshow test P = .114, and Brier score 0.212. The difference in receiver operating characteristic curves was not statistically significant between the two scores but showed a higher c-statistic with the DERRI™ score ( P = .055). Conclusion: Both HOSPITAL and DERRI™ scores showed good predictive performance in 30-day re-admission of adult hospitalized diabetes patients. There was no significant difference in discrimination and calibration between the scores. Abbreviations: CI = confidence interval; DERRI™ = Diabetes Early Re-admission Risk Indicator; IQR = interquartile range

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Is the EuroSCORE II reliable in surgical mitral valve repair? A single-centre validation study

European Journal of Cardio-Thoracic Surgery ◽

10.1093/ejcts/ezaa403 ◽

2020 ◽

Author(s):

Davide Carino ◽

Paolo Denti ◽

Guido Ascione ◽

Benedetto Del Forno ◽

Elisabetta Lapenna ◽

...

Keyword(s):

Mitral Valve ◽

Mitral Valve Repair ◽

Goodness Of Fit ◽

Area Under The Curve ◽

High Volume ◽

Brier Score ◽

Calibration Plot ◽

Valve Repair ◽

Goodness Of Fit Test ◽

High Level

Abstract OBJECTIVES The EuroSCORE II is widely used to predict 30-day mortality in patients undergoing open and transcatheter cardiac surgery. The aim of this study is to evaluate the discriminatory ability of the EuroSCORE II in predicting 30-day mortality in a large cohort of patients undergoing surgical mitral valve repair in a high-volume centre. METHODS A retrospective review of our institutional database was carried on to find all patients who underwent mitral valve repair in our department from January 2012 to December 2019. Discrimination of the EuroSCORE II was assessed using receiver operating characteristic curves. The maximum Youden’s Index was employed to define the optimal cut-point. Calibration was assessed by generating calibration plot that visually compares the predicted mortality with the observed mortality. Calibration was also tested with the Hosmer–Lemeshow goodness-of-fit test. Finally, the accuracy of the models was tested calculating the Brier score. RESULTS A total of 2645 patients were identified, and the median EuroSCORE II was 1.3% (0.6–2.0%). In patients with degenerative mitral regurgitation (MR), the EuroSCORE II showed low discrimination (area under the curve 0.68), low accuracy (Brier score 0.27) and low calibration with overestimation of the 30-day mortality. In patients with secondary MR, the EuroSCORE II showed a good overall performance estimating the 30-day mortality with good discrimination (area under the curve 0.88), good accuracy (Brier score 0.003) and good calibration. CONCLUSIONS In patients with degenerative MR operated on in a high-volume centre with a high level of expertise in mitral valve repair, the EuroSCORE II significantly overestimates the 30-day mortality.

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Relationship between Volume and Survival in Closed Intensive Care Units Is Weak and Apparent Only in Mechanically Ventilated Patients

Anesthesiology ◽

10.1097/aln.0b013e31829c3029 ◽

2013 ◽

Vol 119 (4) ◽

pp. 871-879 ◽

Cited By ~ 9

Author(s):

Rafael Fernández ◽

Susana Altaba ◽

Lluis Cabre ◽

Victoria Lacueva ◽

Antonio Santos ◽

...

Keyword(s):

Hospital Mortality ◽

Standardized Mortality Ratio ◽

Hospital Level ◽

Mechanically Ventilated ◽

Mechanically Ventilated Patients ◽

Risk Of Death ◽

Mortality Ratio ◽

Low Volume ◽

Predicted Risk ◽

Ventilated Patients

Abstract Background: Recent studies have found an association between increased volume and increased intensive care unit (ICU) survival; however, this association might not hold true in ICUs with permanent intensivist coverage. Our objective was to determine whether ICU volume correlates with survival in the Spanish healthcare system. Methods: Post hoc analysis of a prospective study of all patients admitted to 29 ICUs during 3 months. At ICU discharge, the authors recorded demographic variables, severity score, and specific ICU treatments. Follow-up variables included ICU readmission and hospital mortality. Statistics include logistic multivariate analyses for hospital mortality according to quartiles of volume of patients. Results: The authors studied 4,001 patients with a mean predicted risk of death of 23% (range at hospital level: 14–46%). Observed hospital mortality was 19% (range at hospital level: 11–35%), resulting in a standardized mortality ratio of 0.81 (range: 0.5–1.3). Among the 1,923 patients needing mechanical ventilation, the predicted risk of death was 32% (14–60%) and observed hospital mortality was 30% (12–61%), resulting in a standardized mortality ratio of 0.96 (0.5–1.7). The authors found no correlation between standardized mortality ratio and ICU volume in the entire population or in mechanically ventilated patients. Only mechanically ventilated patients in very low-volume ICUs had slightly worse outcome. Conclusion: In the currently studied healthcare system characterized by 24/7 intensivist coverage, the authors found wide variability in outcome among ICUs even after adjusting for severity of illness but no relationship between ICU volume and outcome. Only mechanically ventilated patients in very low-volume centers had slightly worse outcomes.

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SAPS 3—From evaluation of the patient to evaluation of the intensive care unit.Part 2: Development of a prognostic model for hospital mortality at ICU admission

Intensive Care Medicine ◽

10.1007/s00134-006-0147-0 ◽

2006 ◽

Vol 32 (5) ◽

pp. 796-796 ◽

Cited By ~ 4

Author(s):

Rui P. Moreno ◽

Phillip G. H. Metnitz ◽

Eduardo Almeida ◽

Barbara Jordan ◽

Peter Bauer ◽

...

Keyword(s):

Intensive Care ◽

Hospital Mortality ◽

Prognostic Model ◽

Saps 3 ◽

Icu Admission

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Trends in COVID-19 Risk-Adjusted Mortality Rates

Journal of Hospital Medicine ◽

10.12788/jhm.3552 ◽

2020 ◽

Cited By ~ 7

Author(s):

Leora I Horwitz ◽

Simon A Jones ◽

Robert J Cerfolio ◽

Fritz Francois ◽

Joseph Greco ◽

...

Keyword(s):

New York ◽

Hospital Mortality ◽

Health System ◽

Vital Signs ◽

Patient Characteristics ◽

Mortality Rates ◽

Standardized Mortality Ratio ◽

Marginal Effect ◽

Average Probability ◽

Mortality Ratio

Early reports showed high mortality from coronavirus disease 2019 (COVID-19). Mortality rates have recently been lower, raising hope that treatments have improved. However, patients are also now younger, with fewer comorbidities. We explored whether hospital mortality was associated with changing demographics at a 3-hospital academic health system in New York. We examined in-hospital mortality or discharge to hospice from March through August 2020, adjusted for demographic and clinical factors, including comorbidities, admission vital signs, and laboratory results. Among 5,121 hospitalizations, adjusted mortality dropped from 25.6% (95% CI, 23.2-28.1) in March to 7.6% (95% CI, 2.5-17.8) in August. The standardized mortality ratio dropped from 1.26 (95% CI, 1.15-1.39) in March to 0.38 (95% CI, 0.12-0.88) in August, at which time the average probability of death (average marginal effect) was 18.2 percentage points lower than in March. Data from one health system suggest that mortality from COVID-19 is decreasing even after accounting for patient characteristics.

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