Prognostic value of plasma pentraxin 3 levels in patients with septic shock admitted to intensive care

Objective To evaluate the usefulness of a new marker, pentraxin, as a prognostic marker in septic shock patients. Materials and methods Single-centre prospective observational study that included all consecutive patients 18 years or older who were admitted to the intensive care unit (ICU) with septic shock. Serum levels of procalcitonin (PCT), C-reactive protein (CRP) and pentraxin (PTX3) were measured on ICU admission. Results Seventy-five septic shock patients were included in the study. The best predictors of in-hospital mortality were the severity scores: SAPS II (AUC = 0.81), SOFA (AUC = 0.79) and APACHE II (AUC = 0.73). The ROC curve for PTX3 (ng/mL) yielded an AUC of 0.70, higher than the AUC for PCT (0.43) and CRP (0.48), but lower than lactate (0.79). Adding PTX3 to the logistic model increased the predictive capacity in relation to SAPS II, SOFA and APACHE II for in-hospital mortality (AUC 0.814, 0.795, and 0.741, respectively). In crude regression models, significant associations were found between in-hospital mortality and PTX3. This positive association increased after adjusting for age, sex and immunosuppression: adjusted OR T3 for PTX3 = 7.83, 95% CI 1.35–45.49, linear P trend = 0.024. Conclusion Our results support the prognostic value of a single determination of plasma PTX3 as a predictor of hospital mortality in septic shock patients.

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Predictive Values of Initial Severity Scores at Intensive Care Unit Admission for Patients With Overnight or Prolonged Stay

10.21203/rs.3.rs-915561/v1 ◽

2021 ◽

Author(s):

Koji Hosokawa ◽

Nobuaki Shime

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Hospital Mortality ◽

Predictive Value ◽

Apache Ii ◽

Icu Patients ◽

Prolonged Stay ◽

Saps Ii ◽

Icu Stay ◽

Severity Scores

Abstract Background: The predictive value of disease severity scores for intensive care unit (ICU) patients is occasionally inaccurate because ICU patients with mild symptoms are also considered. We, thus, aimed to evaluate the accuracy of severity scores in predicting mortality of patients with complicated conditions admitted for > 24 hours. Methods: Overall, 35,353 adult patients using nationwide ICU data were divided into two groups: (1) overnight ICU stay after elective surgery and alive on discharge within 24 hours and (2) death within 24 hours or prolonged stay. The performance and accuracy of Sequential Organ Failure Assessment (SOFA), Acute Physiology and Chronic Health Evaluation (APACHE) II and III, and Simplified Acute Physiology Score (SAPS) II scores in predicting in-hospital mortality were evaluated. Results: In the overnight stay group, the correlation between SOFA and APACHE III scores or SAPS II was low because many had a SOFA score of 0. In the prolonged stay group, the predictive value of SAPS II and APACHE II and III showed high accuracy but that of SOFA was moderate. Conclusions: When overnight ICU stay patients were not included, the high predictive value for in-hospital mortality of SAPS II and APACHE II and III was evident.

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Ang-2, Tie-2, and Ang-2/Tie-2 ratio serum levels as diagnostic and prognostic biomarkers of sepsis in critically ill patients

Revista Romana de Medicina de Laborator ◽

10.1515/rrlm-2016-0007 ◽

2016 ◽

Vol 24 (2) ◽

pp. 187-199 ◽

Cited By ~ 1

Author(s):

János Szederjesi ◽

Anca Georgescu ◽

Ario Santini ◽

Emőke Almásy ◽

Alexandra Lazar ◽

...

Keyword(s):

Intensive Care ◽

Critically Ill ◽

Positive Association ◽

Serum Levels ◽

Apache Ii ◽

Medical Patients ◽

Tyrosine Kinase 2 ◽

Severity Scores ◽

Group A ◽

Group B

Abstract Sepsis represents one the main cause of death in patients admitted to the intensive care. Biomarkers offer an alternative approach to the diagnostic and prognostic evaluation and improve the outcomes. Angiopoietin 2 (Ang-2) and Tyrosine kinase 2 (Tie-2) are biomarkers which may be involved in sepsis, Ang-2 being responsible for vascular remodelling while Tie-2 is their endothelial receptor. The aim of the study: To assess the Ang-2, Tie-2 and Ang-2/Tie-2 ratio serum levels in septic and non-septic patients and to investigate the independent value of circulating Ang-2, Tie-2, and Ang-2/Tie-2 ratios as predictors of prognosis in critically ill medical patients. Study design: The study included 74 adults admitted to an intensive care unit (ICU). The patients were separated in two groups: Group A [sepsis: n=40] and Group B [no-sepsis: n= 34] patients. Serum levels of Ang-2 and Tie-2 were determined in the first 12 hours after admission and were correlated with ICU severity scores, APACHE II, SOFA and SAPS and with the death rate. Results: Group A gave significantly higher values (p=0.01), for serum Ang-2 (11.07±9.21 ng/ml) compared to Group B (6.18±5.28 ng/ml). The level of Tie-2 was also higher (11.03±5.12 ng/ml) in Group A compared to Group B (9.46±4.99 ng/ml) (p=0.19). In Group A, the Ang-2/Tie2 ratio showed higher values than Group B (p=0.02). There was a positive association between severity scores (APACHE II, SAPS, and SOFA) and Ang-2, and Ang-2/ Tie-2 ratio, but not for Tie2. Conclusions: In our study Ang-2 and Ang-2/Tie-2 ratio serum levels had independent diagnostic value in patients with sepsis, as measured on admission.

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Improvement of APACHE II score system for disease severity based on XGBoost algorithm

BMC Medical Informatics and Decision Making ◽

10.1186/s12911-021-01591-x ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Yan Luo ◽

Zhiyu Wang ◽

Cong Wang

Keyword(s):

Intensive Care ◽

Hospital Mortality ◽

Patient Outcomes ◽

External Validation ◽

Apache Ii ◽

Validation Dataset ◽

Apache Ii Score ◽

Severity Scores ◽

The Impact ◽

Improve Patient

Abstract Background Prognostication is an essential tool for risk adjustment and decision making in the intensive care units (ICUs). In order to improve patient outcomes, we have been trying to develop a more effective model than Acute Physiology and Chronic Health Evaluation (APACHE) II to measure the severity of the patients in ICUs. The aim of the present study was to provide a mortality prediction model for ICUs patients, and to assess its performance relative to prediction based on the APACHE II scoring system. Methods We used the Medical Information Mart for Intensive Care version III (MIMIC-III) database to build our model. After comparing the APACHE II with 6 typical machine learning (ML) methods, the best performing model was screened for external validation on anther independent dataset. Performance measures were calculated using cross-validation to avoid making biased assessments. The primary outcome was hospital mortality. Finally, we used TreeSHAP algorithm to explain the variable relationships in the extreme gradient boosting algorithm (XGBoost) model. Results We picked out 14 variables with 24,777 cases to form our basic data set. When the variables were the same as those contained in the APACHE II, the accuracy of XGBoost (accuracy: 0.858) was higher than that of APACHE II (accuracy: 0.742) and other algorithms. In addition, it exhibited better calibration properties than other methods, the result in the area under the ROC curve (AUC: 0.76). we then expand the variable set by adding five new variables to improve the performance of our model. The accuracy, precision, recall, F1, and AUC of the XGBoost model increased, and were still higher than other models (0.866, 0.853, 0.870, 0.845, and 0.81, respectively). On the external validation dataset, the AUC was 0.79 and calibration properties were good. Conclusions As compared to conventional severity scores APACHE II, our XGBoost proposal offers improved performance for predicting hospital mortality in ICUs patients. Furthermore, the TreeSHAP can help to enhance the understanding of our model by providing detailed insights into the impact of different features on the disease risk. In sum, our model could help clinicians determine prognosis and improve patient outcomes.

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A Comparison of the Performance of Out-of-hospital Cardiac Arrest Score and Standard Severity Scores in Predicting Hospital Mortality and Neurological Consequence in Out-of-hospital Cardiac Arrest Patients

Journal of Health Science and Medical Research ◽

10.31584/jhsmr.2021821 ◽

2021 ◽

Author(s):

Natthaka Sathaporn ◽

Bodin Khwannimit

Keyword(s):

Cardiac Arrest ◽

Hospital Mortality ◽

Apache Ii ◽

Secondary Outcome ◽

Saps 3 ◽

Saps Ii ◽

Severity Scores ◽

Overall Performance ◽

Hospital Cardiac Arrest ◽

Better Than

Objective: There is limited data to determine the performance of general and specific severity score in out-of-hospital cardiac arrest (OHCA) patients. Hence, we compared the performance of the OHCA score with Acute Physiology and Chronic Health Evaluation (APACHE) and Simplified Acute Physiology Score (SAPS) to predict outcome in OHCA patients.Material and Methods: A retrospective study was conducted in a mixed intensive care unit of a tertiary hospital. The primary outcome was in-hospital mortality. The secondary outcome was poor neurological outcome.Results: A total of 190 OHCA patients were enrolled. The OHCA score had moderate discrimination with an area under the receiver operating characteristic curve (AUC) 0.77 (95% CI 0.7-0.837) whereas discrimination of APACHE II-IV, SAPS II, and SAPS 3 were good with an AUC more than 0.8. The actual hospital mortality rate was 64.7%. The OHCA score predicted hospital mortality of 95.3±8.4, which significantly overestimated the mortality with standardized mortality ratio 0.68 (95% CI 0.56-0.81). However, all severity scores revealed poor calibration. Additionally, overall performance of APACHE II-IV, SAPS II and SAPS 3 were better than the OHCA score. For secondary outcome, discrimination of the OHCA score was moderate with an AUC 0.790 (95% CI 0.700-0.878) whereas other severity scores demonstrated good discrimination with AUC more than 0.8.Conclusion: APACHE II-IV, SAPS II, and SAPS 3 indicated superior overall performance and demonstrated good discrimination for predicting hospital mortality and unfavorable neurological consequence better than the OHCA score. However, all severity scores attested poor calibration, therefore, specific scores for OHCA patients should be modified.

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Investigate predictive capacity of in-hospital mortality of four severity score systems on critically ill patients with acute kidney injury

Journal of Investigative Medicine ◽

10.1136/jim-2019-001003 ◽

2019 ◽

Vol 67 (8) ◽

pp. 1103-1109 ◽

Cited By ~ 4

Author(s):

Yu Gong ◽

Feng Ding ◽

Fen Zhang ◽

Yong Gu

Keyword(s):

Acute Kidney Injury ◽

Hospital Mortality ◽

Critically Ill ◽

Critically Ill Patients ◽

Kidney Injury ◽

Mortality Prediction ◽

Apache Ii ◽

University Teaching ◽

Predictive Capacity ◽

Saps Ii

Although significant improvements have been achieved in the renal replacement therapy of acute kidney injury (AKI), the mortality of patients with AKI remains high. The aim of this study is to prospectively investigate the capacity of Acute Physiology and Chronic Health Evaluation version II (APACHE II), Simplified Acute Physiology Score version II (SAPS II), Sepsis-related Organ Failure Assessment (SOFA) and Acute Tubular Necrosis Individual Severity Index (ATN-ISI) to predict in-hospital mortality of critically ill patients with AKI. A prospective observational study was conducted in a university teaching hospital. 189 consecutive critically ill patients with AKI were selected according Risk, Injury, Failure, Loss, or End-stage kidney disease criteria. APACHE II, SAPS II, SOFA and ATN-ISI counts were obtained within the first 24 hours following admission. Receiver operating characteristic analyses (ROCs) were applied. Area under the ROC curve (AUC) was calculated. Sensitivity and specificity of in-hospital mortality prediction were calculated. In this study, the in-hospital mortality of critically ill patients with AKI was 37.04% (70/189). AUC of APACHE II, SAPS II, SOFA and ATN-ISI was 0.903 (95% CI 0.856 to 0.950), 0.893 (95% CI 0.847 to 0.940), 0.908 (95% CI 0.866 to 0.950) and 0.889 (95% CI 0.841 to 0.937) and sensitivity was 90.76%, 89.92%, 90.76% and 89.08% and specificity was 77.14%, 70.00%, 71.43% and 71.43%, respectively. In this study, it was found APACHE II, SAPS II, SOFA and ATN-ISI are reliable in-hospital mortality predictors of critically ill patients with AKI. Trial registration number: NCT00953992.

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Validation of APACHE II, APACHE III and SAPS II scores in in-hospital and one year mortality prediction in a mixed intensive care unit in Poland: a cohort study

10.21203/rs.3.rs-24209/v3 ◽

2020 ◽

Author(s):

Szymon Czajka ◽

Katarzyna Ziębińska ◽

Konstanty Marczenko ◽

Barbara Posmyk ◽

Anna Szczepańska ◽

...

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Hospital Mortality ◽

Diagnostic Accuracy ◽

Mortality Prediction ◽

Apache Ii ◽

Post Discharge ◽

Saps Ii ◽

Apache Iii

Abstract Background. There are several scores used for in-hospital mortality prediction in critical illness. Their application in a local scenario requires validation to ensure appropriate diagnostic accuracy. Moreover, their use in assessing post-discharge mortality in intensive care unit (ICU) survivors has not been extensively studied. We aimed to validate APACHE II, APACHE III and SAPS II scores in short- and long-term mortality prediction in a mixed adult ICU in Poland. APACHE II, APACHE III and SAPS II scores, with corresponding predicted mortality ratios, were calculated for 303 consecutive patients admitted to a 10-bed ICU in 2016. Short-term (in-hospital) and long-term (12-month post-discharge) mortality was assessed. Results. Median APACHE II, APACHE III and SAPS II scores were 19 (IQR 12-24), 67 (36.5-88) and 44 (27-56) points, with corresponding in-hospital mortality ratios of 25.8% (IQR 12.1-46.0), 18.5% (IQR 3.8-41.8) and 34.8% (IQR 7.9-59.8). Observed in-hospital mortality was 35.6%. Moreover, 12-month post-discharge mortality reached 17.4%. All the scores predicted in-hospital mortality (p<0.05): APACHE II (AUC=0.78; 95%CI 0.73-0.83), APACHE III (AUC=0.79; 95%CI 0.74-0.84) and SAPS II (AUC=0.79; 95%CI 0.74-0.84); as well as mortality after hospital discharge (p<0.05): APACHE II (AUC=0.71; 95%CI 0.64-0.78), APACHE III (AUC=0.72; 95%CI 0.65-0.78) and SAPS II (AUC=0.69; 95%CI 0.62-0.76), with no statistically significant difference between the scores (p>0.05). The calibration of the scores was good. Conclusions. All the scores are acceptable predictors of in-hospital mortality. In the case of post-discharge mortality, their diagnostic accuracy is lower and of borderline clinical relevance. Further studies are needed to create scores estimating the long-term prognosis of subjects successfully discharged from the ICU.

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Dysbiosis of intestinal microbiota to predict in-hospital mortality in critically ill patients: results of a prospective observational cohort study

10.21203/rs.2.20261/v1 ◽

2020 ◽

Author(s):

Ru Wei ◽

Xu Chen ◽

Linhui Hu ◽

Zhimei He ◽

Xin Ouyang ◽

...

Keyword(s):

Intensive Care ◽

Hospital Mortality ◽

Critically Ill ◽

Intestinal Microbiota ◽

Sofa Score ◽

Critically Ill Patients ◽

Prognostic Value ◽

Apache Ii ◽

Hospital Death ◽

Death Group

Abstract Background: Despite the essential functions of the intestinal microbiota in human physiology, little research has been reported on the gut microbiota alteration in intensive care patients. This investigation aimed to explore the dysbacteriosis of intestinal flora in critically ill patients, and evaluate the prognostic performance of this dysbiosis to predict in-hospital mortality. Methods: A prospective cohort of patients were consecutively recruited at Intensive Care Units (ICUs) in Guangdong Provincial People's Hospital from March 2017 through October 2017. Acute Physiology and Chronic Health Evaluation (APACHE) II score and Sequential Organ Failure Assessment (SOFA) score were assessed, and fecal samples were taken for examination within 24 hours of ICU admission. The taxonomic composition of intestinal microbiome was determined using 16S rDNA gene sequencing. Patients were divided into survival and death group based on the outcomes in hospital. The two groups were statistically compared using the independent samples t test and Metastats analysis. Genera of bacteria showing significantly different abundance between groups were assessed for predictors of in-hospital death. The prognostic value of bacterial abundance alone and in combination with APACHE II or SOFA score were evaluated using the area under the receiver operating characteristic curve (AUROC). Results: Among the 61 patients that were examined, a total of 12 patients (19.7%) died during hospital stay. Bifidobacterium differed significantly in abundance between survival and death group ( P =0.031). The AUROC of Bifidobacterium abundance identifying in-hospital death at a cut-off probability of 0.0041 was 0.718 (95% confidence interval [CI], 0.588-0.826). The panel of Bifidobacterium abundance plus SOFA (AUROC, 0.882; 95% CI, 0.774-0.950) outperformed SOFA (AUROC, 0.649; 95% CI, 0.516-0.767; P =0.012) and Bifidobacterium abundance alone ( P =0.007). The panel of Bifidobacterium abundance plus APACHE II (AUROC, 0.876; 95% CI, 0.766-0.946) outperformed APACHE II (AUROC, 0.724; 95% CI, 0.595-0.831; P =0.035) and Bifidobacterium abundance alone ( P =0.012). Conclusions: Dysbiosis of intestinal microbiota with variable degree of reduction in Bifidobacterium abundance exhibits promising performance in predicting in-hospital mortality, and provides incremental prognostic value to existing scoring systems in the adult intensive care unit (ICU) setting.

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Validation of APACHE II, APACHE III and SAPS II scores in in-hospital and one year mortality prediction in a mixed intensive care unit in Poland: a cohort study

BMC Anesthesiology ◽

10.1186/s12871-020-01203-7 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Szymon Czajka ◽

Katarzyna Ziębińska ◽

Konstanty Marczenko ◽

Barbara Posmyk ◽

Anna J. Szczepańska ◽

...

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Hospital Mortality ◽

Diagnostic Accuracy ◽

Mortality Prediction ◽

Apache Ii ◽

Post Discharge ◽

Saps Ii ◽

Apache Iii

Abstract Background There are several scores used for in-hospital mortality prediction in critical illness. Their application in a local scenario requires validation to ensure appropriate diagnostic accuracy. Moreover, their use in assessing post-discharge mortality in intensive care unit (ICU) survivors has not been extensively studied. We aimed to validate APACHE II, APACHE III and SAPS II scores in short- and long-term mortality prediction in a mixed adult ICU in Poland. APACHE II, APACHE III and SAPS II scores, with corresponding predicted mortality ratios, were calculated for 303 consecutive patients admitted to a 10-bed ICU in 2016. Short-term (in-hospital) and long-term (12-month post-discharge) mortality was assessed. Results Median APACHE II, APACHE III and SAPS II scores were 19 (IQR 12–24), 67 (36.5–88) and 44 (27–56) points, with corresponding in-hospital mortality ratios of 25.8% (IQR 12.1–46.0), 18.5% (IQR 3.8–41.8) and 34.8% (IQR 7.9–59.8). Observed in-hospital mortality was 35.6%. Moreover, 12-month post-discharge mortality reached 17.4%. All the scores predicted in-hospital mortality (p < 0.05): APACHE II (AUC = 0.78; 95%CI 0.73–0.83), APACHE III (AUC = 0.79; 95%CI 0.74–0.84) and SAPS II (AUC = 0.79; 95%CI 0.74–0.84); as well as mortality after hospital discharge (p < 0.05): APACHE II (AUC = 0.71; 95%CI 0.64–0.78), APACHE III (AUC = 0.72; 95%CI 0.65–0.78) and SAPS II (AUC = 0.69; 95%CI 0.62–0.76), with no statistically significant difference between the scores (p > 0.05). The calibration of the scores was good. Conclusions All the scores are acceptable predictors of in-hospital mortality. In the case of post-discharge mortality, their diagnostic accuracy is lower and of borderline clinical relevance. Further studies are needed to create scores estimating the long-term prognosis of subjects successfully discharged from the ICU.

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Serum Soluble Triggering Receptor Expressed on Myeloid Cells-1 and Procalcitonin Can Reflect Sepsis Severity and Predict Prognosis: A Prospective Cohort Study

Mediators of Inflammation ◽

10.1155/2014/641039 ◽

2014 ◽

Vol 2014 ◽

pp. 1-7 ◽

Cited By ~ 12

Author(s):

Zhenyu Li ◽

Hongxia Wang ◽

Jian Liu ◽

Bing Chen ◽

Guangping Li

Keyword(s):

Sofa Score ◽

Prognostic Significance ◽

Elevated Serum ◽

Myeloid Cells ◽

Serum Levels ◽

Clinical Severity ◽

Apache Ii ◽

Apache Ii Score ◽

Survival Group ◽

Severity Scores

Objective. To investigate the prognostic significance of serum soluble triggering receptor expressed on myeloid cells-1 (sTREM-1), procalcitonin (PCT), N-terminal probrain natriuretic peptide (NT-pro-BNP), C-reactive protein (CRP), cytokines, and clinical severity scores in patients with sepsis.Methods. A total of 102 patients with sepsis were divided into survival group (n=60) and nonsurvival group (n=42) based on 28-day mortality. Serum levels of biomarkers and cytokines were measured on days 1, 3, and 5 after admission to an ICU, meanwhile the acute physiology and chronic health evaluation II (APACHE II) and sequential organ failure assessment (SOFA) scores were calculated.Results. Serum sTREM-1, PCT, and IL-6 levels of patients in the nonsurvival group were significantly higher than those in the survival group on day 1 (P<0.01). The area under a ROC curve for the prediction of 28 day mortality was 0.792 for PCT, 0.856 for sTREM-1, 0.953 for SOFA score, and 0.923 for APACHE II score. Multivariate logistic analysis showed that serum baseline sTREM-1 PCT levels and SOFA score were the independent predictors of 28-day mortality. Serum PCT, sTREM-1, and IL-6 levels showed a decrease trend over time in the survival group (P<0.05). Serum NT-pro-BNP levels showed the predictive utility from days 3 and 5 (P<0.05).Conclusion. In summary, elevated serum sTREM-1 and PCT levels provide superior prognostic accuracy to other biomarkers. Combination of serum sTREM-1 and PCT levels and SOFA score can offer the best powerful prognostic utility for sepsis mortality.

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