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Value of SOFA, APACHE IV and SAPS II scoring systems in predicting short-term mortality in patients with acute myocarditis.

ABSTRACT: Acute myocarditis is an uncommon and potentially life-threatening disease. Scoring systems are essential for predicting outcome and evaluating the therapy effect of adult patients with acute myocarditis. The aim of this study was to determine the value of the Sequential Organ Failure Assessment (SOFA), Acute Physiology and Chronic Health Evaluation IV (APACHE IV) and second Simplified Acute Physiology Score (SAPS II) scoring systems in predicting short-term mortality of these patients. We retrospectively analyzed data from 305 adult patients suffering from acute myocarditis between April 2005 and August 2016. The association between the value of admission SOFA, APACHE IV and SAPS II scores and risk of short-term mortality was determined. Multivariate Cox analysis showed that SOFA, APACHE IV and SAPS II scores were independent risk factors of death in patients with acute myocarditis. For each scoring system, Kaplan-Meier analysis showed that the cumulative short-term mortality was significantly higher in patients with higher admission scores compared with those with lower admission scores. For the prediction of short-term mortality in a patient with acute myocarditis, SAPS II had the highest accuracy followed by the APACHE IV and SOFA scores.

SUBMITTER: Sun D

PROVIDER: S-EPMC5609904 | biostudies-other | 2017 Sep

REPOSITORIES: biostudies-other

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Value of SOFA, APACHE IV and SAPS II scoring systems in predicting short-term mortality in patients with acute myocarditis.

Sun Dating D Ding Hu H Zhao Chunxia C Li Yuanyuan Y Wang Jing J Yan Jiangtao J Wang Dao Wen DW

Oncotarget 20170627 38

Acute myocarditis is an uncommon and potentially life-threatening disease. Scoring systems are essential for predicting outcome and evaluating the therapy effect of adult patients with acute myocarditis. The aim of this study was to determine the value of the Sequential Organ Failure Assessment (SOFA), Acute Physiology and Chronic Health Evaluation IV (APACHE IV) and second Simplified Acute Physiology Score (SAPS II) scoring systems in predicting short-term mortality of these patients. We retros ...[more]

PMID: 28968972

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Project description:BackgroundCoronavirus disease 2019 (COVID-19) has been widely spread and caused tens of thousands of deaths, especially in patients with severe COVID-19. This analysis aimed to explore risk factors for mortality of severe COVID-19, and establish a scoring system to predict in-hospital deaths.MethodsPatients with COVID-19 were retrospectively analyzed and clinical characteristics were compared. LASSO regression as well as multivariable analysis were used to screen variables and establish prediction model.FindingsA total of 2529 patients with COVID-19 was retrospectively analyzed, and 452 eligible severe COVID-19 were used for finally analysis. In training cohort, the median age was 66•0 years while it was 73•0 years in non-survivors. Patients aged 60-75 years accounted for the largest proportion of infected populations and mortality toll. Anti-SARS-CoV-2 antibodies were monitored up to 54 days, and IgG levels reached the highest during 20-30 days. No differences were observed of antibody levels between severe and non-severe patients. About 60.2% of severe patients had complications. Among acute myocardial injury (AMI), acute kidney injury (AKI) and acute liver injury (ALI), the heart was the earliest injured organ, whereas the time from AKI to death was the shortest. Age, diabetes, coronary heart disease (CHD), percentage of lymphocytes (LYM%), procalcitonin (PCT), serum urea, C reactive protein and D-dimer (DD), were identified associated with mortality by LASSO binary logistic regression. Then multivariable analysis was performed to conclude that old age, CHD, LYM%, PCT and DD remained independent risk factors for mortality. Based on the above variables, a scoring system of COVID-19 (CSS) was established to divide patients into low-risk and high-risk groups. This model displayed good discrimination (AUC=0·919) and calibration (P=0·264). Complications in low-risk and high-risk groups were significantly different (P<0·05). Use of corticosteroids in low-risk groups increased hospital stays by 4·5 days (P=0·036) and durations of disease by 7·5 days (P=0·012) compared with no corticosteroids.InterpretationOld age, CHD, LYM%, PCT and DD were independently related to mortality. CSS was useful for predicting in-hospital mortality and complications, and it could help clinicians to identify high-risk patients with poor prognosis.FundingThis work was supported by the Key Project for Anti-2019 novel Coronavirus Pneumonia from the Ministry of Science and Technology, China (grant number 2020YFC0845500).

Project description:BackgroundIn an attempt to further improve liver allograft utilization and outcome in orthotopic liver transplantation (OLT), a variety of clinical scoring systems have been developed. Here we aimed to comparatively investigate the association of the Balance-of-Risk (BAR), Survival-Outcomes-Following-Liver-Transplant (SOFT), Preallocation-Survival-Outcomes-Following-Liver-Transplant (pSOFT), Donor-Risk-Index (DRI), and the Eurotransplant-Donor-Risk-Index (ET-DRI) scores with short- and long-term outcome following OLT.MethodsWe included 338 consecutive patients, who underwent OLT in our institution between May 2010 and November 2017. For each prognostic model, the optimal cutoff values were determined with the help of the Youden-index and their diagnostic accuracy for 90-day post OLT-mortality and major postoperative complications was measured by the area under the receiver operating characteristic curve (AUROC). Patient- and graft survival were analyzed using the Kaplan-Meier method and the log-rank test. Morbidity was assessed using the Clavien-Dindo classification and the Comprehensive-Complication-Index.ResultsBAR, SOFT, and pSOFT performed well above the conventional AUROC-threshold of 0.70 with good prediction of early mortality. Only BAR showed AUC>0.70 for both mortality and major morbidity. With the cutoffs of 14, 31, and 22 respectively for BAR, SOFT, and pSOFT, subgroup analysis showed significant differences (p<0.001) in morbidity and mortality, length of intensive care- and hospital-stay and early allograft dysfunction rates. Five-years patient survival was inferior in the high BAR, pSOFT, and SOFT groups.ConclusionsOut of all scores tested, the BAR-score had the best value in predicting both 90-day morbidity and mortality after OLT showing the highest AUCs. The pSOFT and SOFT scores demonstrated an acceptable accuracy in predicting 90-day morbidity and mortality. The used BAR, SOFT, and pSOFT cutoffs allowed the identification of patients at risk in terms of five-year patient survival. The DRI and ET-DRI scores have failed to predict recipient outcomes in the present setting.

Dataset Information

Value of SOFA, APACHE IV and SAPS II scoring systems in predicting short-term mortality in patients with acute myocarditis.

Publications

Value of SOFA, APACHE IV and SAPS II scoring systems in predicting short-term mortality in patients with acute myocarditis.

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