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  1. Hung SK, Ng CJ, Kuo CF, Goh ZNL, Huang LH, Li CH, et al.
    PLoS One, 2017;12(11):e0187495.
    PMID: 29091954 DOI: 10.1371/journal.pone.0187495
    BACKGROUND: Splenic abscess is rare but has mortality rates as high as 14% even with recent improvements in management. Early and appropriate intervention may improve patient outcomes, yet at present there is no identified method that can predict mortality risk rapidly and accurately for emergency physicians, surgeons, and intensivists to decide on the ideal course of action.

    OBJECTIVE: This study aims to evaluate the performance of Mortality in Emergency Department Sepsis Score (MEDS), Modified Early Warning Score (MEWS), Rapid Emergency Medicine Score (REMS) and Rapid Acute Physiology Score (RAPS) for predicting the mortality risk of adult splenic abscess patients. This will expedite decision making in the emergency department (ED) to increase survival rates and help avoid unnecessary splenectomies.

    METHODS: Data of 114 adult patients admitted to the EDs of 4 research and training hospitals who had undergone an abdominal contrast CT scan and diagnosed with splenic abscess between Jan 2000 and April 2015 were analyzed. The MEDS, MEWS, REMS, and RAPS and their corresponding mortality risks were calculated, with their abilities to predict patient mortality assessed through receiver operating characteristic curve analysis and calibration analysis.

    RESULTS: MEDS was found to be the best performing scoring system across all indicators, with sensitivity, specificity, and accuracy of 92.86%, 88.00%, and 88.60% respectively; its area under curve for AUROC analysis was 0.92. With a cutoff value of 8, negative predictive value of MEDS was 98.88%.

    CONCLUSION: Our series is the largest multicenter study in adult ED patients with splenic abscess. The results from the present study show that MEDS is superior to MEWS, REMS and RAPS in predicting mortality, thus allowing earlier detection of critically ill adult ED splenic abscess patients. Therefore, we recommend that MEDS be used for predicting severity of illness and risk stratification in these patients.

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