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Mortality prediction by SOFA score in ICU-patients after cardiac surgery; comparison with traditional prognostic-models.

ABSTRACT: BACKGROUND:There are many prognostic models and scoring systems in use to predict mortality in ICU patients. The only general ICU scoring system developed and validated for patients after cardiac surgery is the APACHE-IV model. This is, however, a labor-intensive scoring system requiring a lot of data and could therefore be prone to error. The SOFA score on the other hand is a simpler system, has been widely used in ICUs and could be a good alternative. The goal of the study was to compare the SOFA score with the APACHE-IV and other ICU prediction models. METHODS:We investigated, in a large cohort of cardiac surgery patients admitted to Dutch ICUs, how well the SOFA score from the first 24?h after admission, predict hospital and ICU mortality in comparison with other recalibrated general ICU scoring systems. Measures of discrimination, accuracy, and calibration (area under the receiver operating characteristic curve (AUC), Brier score, R2, and ?-statistic) were calculated using bootstrapping. The cohort consisted of 36,632 Patients from the Dutch National Intensive Care Evaluation (NICE) registry having had a cardiac surgery procedure for which ICU admission was necessary between January 1st, 2006 and June 31st, 2018. RESULTS:Discrimination of the SOFA-, APACHE-IV-, APACHE-II-, SAPS-II-, MPM24-II - models to predict hospital mortality was good with an AUC of respectively: 0.809, 0.851, 0.830, 0.850, 0.801. Discrimination of the SOFA-, APACHE-IV-, APACHE-II-, SAPS-II-, MPM24-II - models to predict ICU mortality was slightly better with AUCs of respectively: 0.809, 0.906, 0.892, 0.919, 0.862. Calibration of the models was generally poor. CONCLUSION:Although the SOFA score had a good discriminatory power for hospital- and ICU mortality the discriminatory power of the APACHE-IV and SAPS-II was better. The SOFA score should not be preferred as mortality prediction model above traditional prognostic ICU-models.

SUBMITTER: Schoe A

PROVIDER: S-EPMC7068937 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Mortality prediction by SOFA score in ICU-patients after cardiac surgery; comparison with traditional prognostic-models.

Schoe Abraham A Bakhshi-Raiez Ferishta F de Keizer Nicolette N van Dissel Jaap T JT de Jonge Evert E

BMC anesthesiology 20200313 1

<h4>Background</h4>There are many prognostic models and scoring systems in use to predict mortality in ICU patients. The only general ICU scoring system developed and validated for patients after cardiac surgery is the APACHE-IV model. This is, however, a labor-intensive scoring system requiring a lot of data and could therefore be prone to error. The SOFA score on the other hand is a simpler system, has been widely used in ICUs and could be a good alternative. The goal of the study was to compa ...[more]

PMID: 32169047

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Project description:BACKGROUND:The Sequential Organ Failure Assessment (SOFA) score is commonly used in ICUs around the world, designed to assess the severity of the patient's clinical state based on function/dysfunction of six major organ systems. The goal of this work is to build a computational model to predict mortality based on a series of SOFA scores. In addition, we examined the possibility of improving the prediction by incorporating a new component designed to measure the performance of the gastrointestinal system, added to the other six components. METHODS:In this retrospective study, we used patients' three latest SOFA scores recorded during an individual ICU stay as input to different machine learning models and ensemble learning models. We added three validated parameters representing gastrointestinal failure. Among others, we used classification models such as Support Vector Machines (SVMs), Neural Networks, Logistic Regression and a penalty function used to increase model robustness in regard to certain extreme cases, which may be found in ICU population. We used the Area under Curve (AUC) performance metric to examine performance. RESULTS:We found an ensemble model of linear and logistic regression achieves a higher AUC compared related works in past years. After incorporating the gastrointestinal failure score along with the penalty function, our best performing ensemble model resulted in an additional improvement in terms of AUC metrics. We implemented and compared 36 different models that were built using both the information from the SOFA score as well as that of the gastrointestinal system. All compared models have approximately similar and relatively large AUC (between 0.8645 and 0.9146) with the best results are achieved by incorporating the gastrointestinal parameters into the prediction models. CONCLUSIONS:Our findings indicate that gastrointestinal parameters carry significant information as a mortality predictor in addition to the conventional SOFA score. This information improves the predictive power of machine learning models by extending the SOFA to include information related to gastrointestinal organ system. The described method improves mortality prediction by considering the dynamics of the extended SOFA score. Although tested on a limited data set, the results' stability across different models suggests robustness in real-time use.

Project description:INTRODUCTION: To systematically review studies evaluating the performance of Sequential Organ Failure Assessment (SOFA)-based models for predicting mortality in patients in the intensive care unit (ICU). METHODS: Medline, EMBASE and other databases were searched for English-language articles with the major objective of evaluating the prognostic performance of SOFA-based models in predicting mortality in surgical and/or medical ICU admissions. The quality of each study was assessed based on a quality framework for prognostic models. RESULTS: Eighteen articles met all inclusion criteria. The studies differed widely in the SOFA derivatives used and in their methods of evaluation. Ten studies reported about developing a probabilistic prognostic model, only five of which used an independent validation data set. The other studies used the SOFA-based score directly to discriminate between survivors and non-survivors without fitting a probabilistic model. In five of the six studies, admission-based models (Acute Physiology and Chronic Health Evaluation (APACHE) II/III) were reported to have a slightly better discrimination ability than SOFA-based models at admission (the receiver operating characteristic curve (AUC) of SOFA-based models ranged between 0.61 and 0.88), and in one study a SOFA model had higher AUC than the Simplified Acute Physiology Score (SAPS) II model. Four of these studies used the Hosmer-Lemeshow tests for calibration, none of which reported a lack of fit for the SOFA models. Models based on sequential SOFA scores were described in 11 studies including maximum SOFA scores and maximum sum of individual components of the SOFA score (AUC range: 0.69 to 0.92) and delta SOFA (AUC range: 0.51 to 0.83). Studies comparing SOFA with other organ failure scores did not consistently show superiority of one scoring system to another. Four studies combined SOFA-based derivatives with admission severity of illness scores, and they all reported on improved predictions for the combination. Quality of studies ranged from 11.5 to 19.5 points on a 20-point scale. CONCLUSIONS: Models based on SOFA scores at admission had only slightly worse performance than APACHE II/III and were competitive with SAPS II models in predicting mortality in patients in the general medical and/or surgical ICU. Models with sequential SOFA scores seem to have a comparable performance with other organ failure scores. The combination of sequential SOFA derivatives with APACHE II/III and SAPS II models clearly improved prognostic performance of either model alone. Due to the heterogeneity of the studies, it is impossible to draw general conclusions on the optimal mathematical model and optimal derivatives of SOFA scores. Future studies should use a standard evaluation methodology with a standard set of outcome measures covering discrimination, calibration and accuracy.

Project description:BackgroundThe sequential organ failure assessment (SOFA) score has poor discriminative ability for death in severely or critically ill patients with Coronavirus disease 2019 (COVID-19) requiring intensive care unit (ICU) admission. Our aim was to create a new score powered to predict 28-day mortality.MethodsRetrospective, observational, bicentric cohort study including 425 patients with COVID-19 pneumonia, acute respiratory failure and SOFA score ≥ 2 requiring ICU admission for ≥72 h. Factors with independent predictive value for 28-day mortality were identified after stepwise Cox proportional hazards (PH) regression. Based on the regression coefficients, an equation was computed representing the COVID-SOFA score. Discriminative ability was tested using receiver operating characteristic (ROC) analysis, concordance statistics and precision-recall curves. This score was internally validated.ResultsMedian (Q1-Q3) age for the whole sample was 64 [55-72], with 290 (68.2%) of patients being male. The 28-day mortality was 54.58%. After stepwise Cox PH regression, age, neutrophil-to-lymphocyte ratio (NLR) and SOFA score remained in the final model. The following equation was computed: COVID-SOFA score = 10 × [0.037 × Age + 0.347 × ln(NLR) + 0.16 × SOFA]. Harrell's C-index for the COVID-SOFA score was higher than the SOFA score alone for 28-day mortality (0.697 [95% CI; 0.662-0.731] versus 0.639 [95% CI: 0.605-0.672]). Subsequently, the prediction error rate was improved up to 16.06%. Area under the ROC (AUROC) was significantly higher for the COVID-SOFA score compared with the SOFA score for 28-day mortality: 0.796 [95% CI: 0.755-0.833] versus 0.699 [95% CI: 0.653-0.742, p < 0.001]. Better predictive value was observed with repeated measurement at 48 h after ICU admission.ConclusionsThe COVID-SOFA score is better than the SOFA score alone for 28-day mortality prediction. Improvement in predictive value seen with measurements at 48 h after ICU admission suggests that the COVID-SOFA score can be used in a repetitive manner. External validation is required to support these results.

Project description:Background and aimThe efficacy of Sequential Organ Failure Assessment (SOFA) score as predictor of clinical outcomes among ICU-admitted COVID-19 patients is still controversial. We aimed to assess whether SOFA-score in different time intervals could predict 28-day mortality compared with other well-acknowledged risk factors of COVID-19 mortality.MethodsThis observational prospective cohort was conducted on 1057 patients from March 2020 to March 2022 at Masih Daneshvari Hospital, Iran. The univariate and multivariate Cox proportional analysis were performed to assess the hazards of SOFA-score models. Receiver operating characteristic (ROC) curves were designed to estimate the predictive values.ResultsMean SOFA-score during first 96 h (HR: 3.82 [CI: 2.75-5.31]), highest SOFA-score (HR: 2.70 [CI: 1.93-3.78]), and initial SOFA-score (HR: 1.65 [CI: 1.30-2.11]) had strongest association with 28-day mortality (p < .0001). In contrast, SOFA scores at 48 and 96 h as well as Δ-SOFA: 48-0 h and Δ-SOFA: 96-0 h did not show significant correlations. Among them, merely mean SOFA-score (HR: 2.28 [CI: 2.21-3.51]; p < .001) remained as independent prognosticator on multivariate regression analysis; though having less odds of predicting value compared with age (HR: 3.81 [CI: 1.98-5.21]), hypertension (HR: 3.11 [CI: 1.26-3.81]), coronary artery disease [CAD] (HR: 2.82 [CI: 1.51-4.8]), and diabetes mellitus (HR: 2.45 [CI: 1.36-2.99]). The area under ROC (AUROC) for mean SOFA-score (0.77) and highest SOFA-score (0.71) were larger than other SOFA intervals. Calculating the first 96 h of SOFA trends, it was obtained that fatality rate was <12.3% if the score dropped, between 28.8% and 46.29% if the score remained unchanged, and >50.45% if the score increased.ConclusionTo predict the 28-day mortality among ICU-admitted COVID-19 patients, mean SOFA upon first 96 h of ICU stay is reliable; while having inadequate accuracy comparing with well-acknowledged COVID-19 mortality predictors (age, diabetes mellitus, hypertension, CAD). Notably, increased SOFA levels in the course of first 96 h of ICU-admission, prognosticate at least 50% fatality regardless of initial SOFA score.

Project description:BackgroundOutcomes in well-resourced, intensive care units (ICUs) in Kenya are thought to be comparable to those in high-income countries (HICs) but risk-adjusted mortality data is unavailable. We undertook an evaluation of the Aga Khan University Hospital, Nairobi ICU to analyze patient clinical-demographic characteristics, compare the performance of Sequential Organ Failure Assessment (SOFA), delta-SOFA at 48 hours and Mortality Prediction Model-III (MPM-III) mortality prediction systems, and identify factors associated with increased risk of mortality.MethodsA retrospective cohort study was conducted of adult patients admitted to the ICU between January 2015 and September 2017. SOFA and MPM-III scores were determined at admission and SOFA repeated at 48 hours.ResultsApproximately 33% of patients did not meet ICU admission criteria. Mortality among the population of critically ill patients in the ICU was 31.7%, most of whom were male (61.4%) with a median age of 53.4 years. High adjusted odds of mortality were found among critically ill patients with leukemia (aOR 6.32, p<0.01), tuberculosis (aOR 3.96, p<0.01), post-cardiac arrest (aOR 3.57, p<0.01), admissions from the step-down unit (aOR 3.13, p<0.001), acute kidney injury (aOR 2.97, p<0.001) and metastatic cancer (aOR 2.45, p = 0.04). The area under the receiver-operating characteristic (ROC) curve of admission SOFA was 0.77 (95% CI, 0.73-0.81), MPM-III 0.74 (95% CI, 0.69-0.79), delta-SOFA 0.69 (95% CI, 0.63-0.75) and 48-hour SOFA 0.83 (95% CI, 0.79-0.87). The difference between SOFA at 48 hours and admission SOFA, MPM-III and delta-SOFA was statistically significant (chi2 = 17.1, 24.2 and 26.5 respectively; p<0.001). Admission SOFA, MPM-III and 48-hour SOFA were well calibrated (p >0.05) while delta-SOFA was borderline (p = 0.05).ConclusionMortality among the critically ill was higher than expected in this well-resourced ICU. 48-hour SOFA performed better than admission SOFA, MPM-III and delta-SOFA in our cohort. While a large proportion of patients did not meet admission criteria but were boarded in the ICU, critically ill patients stepped-up from the step-down unit were unlikely to survive. Patients admitted following a cardiac arrest, and those with advanced disease such as leukemia, stage-4 HIV and metastatic cancer, had particularly poor outcomes. Policies for fair allocation of beds, protocol-driven admission criteria and appropriate case selection could contribute to lowering the risk of mortality among the critically ill to a level on par with HICs.

Dataset Information

Mortality prediction by SOFA score in ICU-patients after cardiac surgery; comparison with traditional prognostic-models.

Publications

Mortality prediction by SOFA score in ICU-patients after cardiac surgery; comparison with traditional prognostic-models.

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