scholarly journals 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

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.

scholarly journals 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

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.

scholarly journals Validation of APACHE II, APACHE III and SAPS II scores in short- and long-term mortality prediction in a mixed intensive care unit in Poland: a cohort study

2020 ◽  
Author(s):  
Szymon Czajka ◽  
Katarzyna Ziębińska ◽  
Konstanty Marczenko ◽  
Barbara Posmyk ◽  
Anna Szczepańska ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Hospital Mortality ◽  
Mortality Prediction ◽  
Apache Ii ◽  
Post Discharge ◽  
Saps Ii ◽  
Apache Iii ◽  
Short And Long Term ◽  
Long Term Mortality

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.

scholarly journals Short- and long-term mortality prediction in critically ill subjects: a cohort study

2020 ◽  
Author(s):  
Szymon Czajka ◽  
Katarzyna Ziębińska ◽  
Konstanty Marczenko ◽  
Barbara Posmyk ◽  
Anna Szczepańska ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Diagnostic Accuracy ◽  
Mortality Prediction ◽  
Apache Ii ◽  
Post Discharge ◽  
Saps Ii ◽  
Apache Iii ◽  
Icu Discharge ◽  
Long Term Mortality

Abstract Background. There are several scoring systems used for in-hospital mortality prediction in critical illness. Their application in a local scenario requires validation to ensure appropriate diagnostic accuracy. Also, their use in assessing post-discharge mortality in the ICU survivors has not been extensively studied.Aim. To evaluate the ability of APACHE II, III and SAPS II to predict in-hospital and post-discharge mortality in adult ICU patients.Material and methods. APACHE II, APACHE III and SAPS II, with corresponding predicted mortality ratios, were calculated for 303 consecutive patients admitted to the 10-bed ICU in 2016. Long-term mortality was calculated based on information taken from PESEL database.Results. Median APACHE II, APACHE III and SAPS II scores were 19, 67 and 44 points, with corresponding in-hospital mortality ratios of 28.1, 18.5 and 34.8%. Observed in-hospital mortality was 35.6%. 12-month post-discharge mortality reached 17.4%. All systems predicted in-hospital mortality (p<0.05): APACHE II (AUC=0.783; 95%CI 0.732-0.828), APACHE III (AUC=0.793; 95%CI 0.743-0.838) and SAPS II (AUC=0.792; 95%CI 0.742-0.836), as well as mortality after ICU discharge (p<0.05): APACHE II (AUC=0.712; 95%CI 0.643-0.775), APACHE III (AUC=0.721; 95%CI 0.653-0.783) and SAPS II (AUC=0.695; 95%CI 0.625-0.759), with no statistically significant difference between them (p>0.05).Conclusions. Although the predictive values were the highest for APACHE III and SAPS II, no differences were noticed between the scores. In case of post-discharge mortality, diagnostic accuracy was much lower. Further studies are needed to create scores estimating the long-term prognosis of subjects successfully discharged from the ICU.

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

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.

Association Between Albumin Level and Mortality Among Cardiac Intensive Care Unit Patients

2020 ◽  
pp. 088506662096387
Author(s):  
Mitchell Padkins ◽  
Thomas Breen ◽  
Nandan Anavekar ◽  
Gregory Barsness ◽  
Kianoush Kashani ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Albumin Level ◽  
Post Discharge ◽  
Cardiac Intensive Care Unit ◽  
Short And Long Term ◽  
Cardiac Intensive Care ◽  
Long Term Mortality

Purpose: To study the effect of hypoalbuminemia on short- and long-term mortality in Cardiac Intensive Care Unit (CICU) patients. Methods: We reviewed 12,418 unique CICU patients from 2007 to 2018. Hypoalbuminemia was defined as an admission albumin level <3.5 g/dL. Predictors of hospital mortality were identified using multivariable logistic regression. Results: We included 2,680 patients (22%) with a measured admission albumin level. The median age was 68 (39% females). Admission diagnoses included acute coronary syndrome, heart failure, cardiac arrest, and cardiogenic shock. The median albumin level was 3.4 g/dL and 55% of patients had hypoalbuminemia. Hospital mortality occurred in 16%, and patients with hypoalbuminemia had higher hospital mortality (21% vs. 9%, adjusted OR 2.64, 95% CI 2.09-3.34, p < 0.001). Albumin level was inversely associated with hospital mortality (adjusted OR 0.60 per 1 g/dL higher albumin level, 95% CI 0.47-0.75, p <0.001), with a stepwise increase in the hospital mortality at lower albumin levels. Post-discharge mortality was higher in hospital survivors with hypoalbuminemia, and increased as a function of lower albumin levels. Conclusion: Hypoalbuminemia is common in CICU patients and associated with higher short- and long-term mortality. Progressively lower serum albumin was incrementally associated with higher hospital and post-discharge mortality.

scholarly journals Comparing APACHE II, APACHE IV, SAPS II, and SOFA Predictive Power in Poisoned Patients Admitted to the Intensive Care Unit

2020 ◽  
Vol 10 (2) ◽  
Author(s):  
Samaneh Silakhori ◽  
Bita Dadpour ◽  
Majid Khadem-Rezaiyan ◽  
Alireza Sedaghat ◽  
Farzad Mirzakhani
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Scoring Systems ◽  
Cross Sectional Study ◽  
Mortality Prediction ◽  
Apache Ii ◽  
Cross Sectional ◽  
Saps Ii ◽  
Hospitalization Period ◽  
Apache Iv

Background: This study aimed to assess the performance of the Acute Physiology and Chronic Health Evaluation (APACHE) II, APACHE IV, Simplified Acute Physiologic Score (SAPS) II, and Sequential Organ Failure Assessment (SOFA) scores in predicting mortality rate in poisoning patients admitted to an intensive care unit (ICU).Methods: This cross-sectional study was performed on all admitted patients in the poisoning ICU of Imam Reza Hospital, Mashhad City, Iran. All patients were evaluated for three consecutive days since admission time and then every two days until discharge from ICU or death. The scoring systems mentioned above were calculated and analyzed by MedCalc statistical software version 18.9.1 and SPSS version 16.Results: Overall, 150 patients were studied, out of whom 67% (101) were male. Their mean±SD age was 41.6±18.9 years. In their whole hospitalization period, APACHE II (79.5%), SAPS II (78.7%), APACHE IV (78.4%), and SOFA (72.9%) were the most precise measures. On the first day of admission APACHE II (77.4%), on the second day, APACHE II (83.1%), on the third day, APACHE II (90.7%), and on the fifth day, SOFA (81.6%) were the most precise measures.Conclusion: All four systems have acceptable discriminatory power for poisoned patients. However, it seems that APACHE II can be used for mortality prediction, especially in the early days of admission. 

scholarly journals In-hospital Mortality Prediction among Patients with Fractures of Pelvis and Acetabulum in Intensive Care Unit: Machine Learning versus Conventional System

2021 ◽  
Author(s):  
Yanrong Cai ◽  
Xiang Jiang ◽  
Weifan Dai ◽  
Qinyuan Yu
Keyword(s):  
Machine Learning ◽  
Risk Factors ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Random Forest ◽  
Hospital Mortality ◽  
Mortality Prediction ◽  
Conventional System ◽  
Saps Ii ◽  
Feature Importance

Abstract BackgroundFractures of pelvis and/or Acetabulum are leading risks of death worldwide. However, the capability of in-hospital mortality prediction by conventional system is so far limited. Here, we hypothesis that the use of machine learning (ML) algorithms could provide better performance of prediction than the traditional scoring system Simple Acute Physiologic Score (SAPS) II for patients with pelvic and acetabular trauma in intensive care unit (ICU).MethodsWe developed customized mortality prediction models with ML techniques based on MIMIC-III, an open access de-defined database consisting of data from more than 25,000 patients who were admitted to the Beth Israel Deaconess Medical Center (BIDMC). 307 patients were enrolled with an ICD-9 diagnosis of pelvic, acetabular or combined pelvic and acetabular fractures and who had an ICU stay more than 72 hours. ML models including decision tree, logistic regression and random forest were established by using the SAPS II features from the first 72 hours after ICU admission and the traditional first-24-hours features were used to build respective control models. We evaluated and made a comparison of each model’s performance through the area under the receiver-operating characteristic curve (AUROC). Feature importance method was used to visualize top risk factors for disease mortality.ResultsAll the ML models outperformed the traditional scoring system SAPS II (AUROC=0.73), among which the best fitted random forest model had the supreme performance (AUROC of 0.90). With the use of evolution of physiological features over time rather than 24-hours snapshots, all the ML models performed better than respective controls. Age remained the top of feature importance for all classifiers. Age, BUN (minimum value on day 2), and BUN (maximum value on day 3) were the top 3 predictor variables in the optimal random forest experiment model. In the best decision tree model, the top 3 risk factors, in decreasing order of contribution, were age, the lowest systolic blood pressure on day 1 and the same value on day 3.ConclusionThe results suggested that mortality modeling with ML techniques could aid in better performance of prediction for models in the context of pelvic and acetabular trauma and potentially support decision-making for orthopedics and ICU practitioners.

Evaluation of single intensive care unit performance in Croatia using APACHE II and SAPS II systems

2005 ◽  
Vol 22 (Supplement 34) ◽  
pp. 169
Author(s):  
K. Desa ◽  
Z. Zupan ◽  
B. Krstulovic ◽  
V. Golubovic ◽  
A. Sustic
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Apache Ii ◽  
Saps Ii ◽  
Unit Performance

scholarly journals Changes in muscle ultrasound for the diagnosis of intensive care unit acquired weakness in critically ill patients

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Weiqing Zhang ◽  
Jun Wu ◽  
Qiuying Gu ◽  
Yanting Gu ◽  
Yujin Zhao ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Diagnostic Accuracy ◽  
Biceps Brachii ◽  
Rectus Femoris ◽  
Apache Ii ◽  
Cross Sectional ◽  
Icu Admission ◽  
The Right ◽  
Muscle Ultrasound

AbstractTo test diagnostic accuracy of changes in thickness (TH) and cross-sectional area (CSA) of muscle ultrasound for diagnosis of intensive care unit acquired weakness (ICU-AW). Fully conscious patients were subjected to muscle ultrasonography including measuring the changes in TH and CSA of biceps brachii (BB) muscle, vastus intermedius (VI) muscle, and rectus femoris (RF) muscles over time. 37 patients underwent muscle ultrasonography on admission day, day 4, day 7, and day 10 after ICU admission, Among them, 24 were found to have ICW-AW. Changes in muscle TH and CSA of RF muscle on the right side showed remarkably higher ROC-AUC and the range was from 0.734 to 0.888. Changes in the TH of VI muscle had fair ROC-AUC values which were 0.785 on the left side and 0.779 on the right side on the 10th day after ICU admission. Additionally, Sequential Organ Failure Assessment (SOFA), Acute Physiology, and Chronic Health Evaluation II (APACHE II) scores also showed good discriminative power on the day of admission (ROC-AUC 0.886 and 0.767, respectively). Ultrasonography of changes in muscles, especially in the TH of VI muscle on both sides and CSA of RF muscle on the right side, presented good diagnostic accuracy. However, SOFA and APACHE II scores are better options for early ICU-AW prediction due to their simplicity and time efficiency.

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