D Tirotta1, M Gambacorta2, M La Regina3, T Attardo4, A Lo Gullo3,5, F Panzone6, A Mazzone7, M Campanini8, F Dentali9. 1. From the Department of Internal Medicine, Cervesi Hospital, Cattolica, (RN), AUSL Romagna, Cattolica, Italy. 2. Department of Internal Medicine, Media Valle del Tevere Hospital, ASL Umbria 1, Todi, Italy. 3. Deparment of Internal Medicine, East Ligurian Hospital, La Spezia, ASL5 Liguria, La Spezia, Italy. 4. Department of Internal Medicine, Canicattì Hospital, ASP1 Agrigento, Canicatti, Italy. 5. Department of Clinical and Experimental Medicine, University of Messina, Messina, Italy. 6. Department of Internal Medicine, Oristano, ASL 5, Oristano, Italy. 7. Department of Internal Medicine, Legnano Hospital, Legnano, Italy. 8. Department of Internal Medicine, Novara Hospital, Novara, Italy. 9. Department of Internal Medicine, Insumbria University, Varese, Italy.
Abstract
BACKGROUND: Due to aging and resources limitation, septic patients are often admitted to medical wards (MWs). Early warning deterioration is a relevant issue in this setting. Unfortunately, a suitable prognostic score has not been identified, yet. AIM: To explore the ability of Modified Early Warning Score (MEWS) to predict the in-hospital mortality in septic patients admitted to MWs. DESIGN: Secondary analysis of a multicentric prospective study. METHODS: Consecutive septic patients with positive blood culture admitted to 31 Italian MWs were included. Baseline characteristics, clinics, isolates, rate of transfer to ICU, MEWS was collected on admission according to the study protocol. The accuracy of MEWS in predicting the in-hospital mortality was assessed with the area under the receiver-operating characteristic curves. Sensitivity, specificity, positive and negative predictive value (PPV and NPV), likelihood ratio (LR) were calculated for different MEWS cut-offs and age/comorbidities subgroups. RESULTS: In total 526 patients were included in this analysis. Median MEWS was (range 0-11). In-hospital mortality was 14.8% and transfer to ICU 1.3%. Mortality progressively increased according to MEWS (3% in MEWS 0 vs. 27% in MEWS >5; Chi square for trend P < 0.05). The AUC of MEWS in predicting in-hospital mortality was 0.596 (95% CI, 0.524, 0.669). MEWS did not appear to have an adequate sensitivity, sensibility, PPV, NPV and LR both in the whole population and in the pre-specified subgroups. CONCLUSIONS: Our findings do not seem to support the use of MEWS to predict the in-hospital mortality risk of sepsis in MWs.
BACKGROUND: Due to aging and resources limitation, septic patients are often admitted to medical wards (MWs). Early warning deterioration is a relevant issue in this setting. Unfortunately, a suitable prognostic score has not been identified, yet. AIM: To explore the ability of Modified Early Warning Score (MEWS) to predict the in-hospital mortality in septic patients admitted to MWs. DESIGN: Secondary analysis of a multicentric prospective study. METHODS: Consecutive septic patients with positive blood culture admitted to 31 Italian MWs were included. Baseline characteristics, clinics, isolates, rate of transfer to ICU, MEWS was collected on admission according to the study protocol. The accuracy of MEWS in predicting the in-hospital mortality was assessed with the area under the receiver-operating characteristic curves. Sensitivity, specificity, positive and negative predictive value (PPV and NPV), likelihood ratio (LR) were calculated for different MEWS cut-offs and age/comorbidities subgroups. RESULTS: In total 526 patients were included in this analysis. Median MEWS was (range 0-11). In-hospital mortality was 14.8% and transfer to ICU 1.3%. Mortality progressively increased according to MEWS (3% in MEWS 0 vs. 27% in MEWS >5; Chi square for trend P < 0.05). The AUC of MEWS in predicting in-hospital mortality was 0.596 (95% CI, 0.524, 0.669). MEWS did not appear to have an adequate sensitivity, sensibility, PPV, NPV and LR both in the whole population and in the pre-specified subgroups. CONCLUSIONS: Our findings do not seem to support the use of MEWS to predict the in-hospital mortality risk of sepsis in MWs.
Authors: Kais Gadhoumi; Alex Beltran; Christopher G Scully; Ran Xiao; David O Nahmias; Xiao Hu Journal: Physiol Meas Date: 2021-06-17 Impact factor: 2.688
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