Objective To evaluate the predicting effect of quick Sequential Organ Failure Assessment (qSOFA) on septic shock, and investigate the probability of improving the predicting effect. Methods Patients with sepsis diagnosed in Emergency Department from July 2015 to June 2016 were enrolled. They were divided into shock group and non-shock group based on whether or not they had septic shock during 72 hours after admission. The multivariate logistic regression analysis was used to find out the independent risk factors affecting the incidence of septic shock. Receiver operating characteristic (ROC) curve was used to analyze those risk factors. Modified Early Warning Score (MEWS), Mortality in Emergency Department Sepsis Score (MEDS), Sequential Organ Failure Assessment (SOFA), Acute Physiology and Chronic HealthEvaluation (APACHE)Ⅱ and qSOFA were also compared with ROC curve analysis. The possibility of improvement of qSOFA predicting effect was discussed. Results A total of 821 patients were enrolled, with 108 in septic shock group and 713 in non-septic shock. The result of multivariate logistic regression analysis indicated that respiratory rate, systolic blood pressure, pH value, oxygenation index, lactate, albumin, Glasgow Coma Score and procalcitonin were the independent risk factors (P<0.05). The result of ROC analysis showed that the area under curve (AUC) of pH value, lactate and procalcitonin was 0.695, 0.678 and 0.694, respectively. Lactate had the highest value of specificity (0.868), positive predictive value (0.356) and positive likelihood ratio (3.644), while the sensitivity (0.889) and negative predictive value (0.961) of procalcitonin were the highest. MEWS, MEDS, SOFA, APACHEⅡ and qSOFA were compared with ROC. SOFA had the best predicting effect with the statistical results of AUC (0.833), sensitivity (0.835), specificity (0.435), positive predictive value (0.971), negative predictive value (0.971), and positive likelihood ratio (5.048); and MEWS had the highest negative likelihood ratio (0.581). qSOFA did not show a best predicting value. Conclusion qSOFA is not the best choice to predict the possibility of septic shock, but its predicting value might be improved when combined with pH value, lactate and procalcitonin.
ObjectiveTo analyze the roles of three scoring systems, i.e. Acute Physiology and Chronic Health Evaluation (APACHE) Ⅱ, Ranson’s criteria, and Sequential Organ Failure Assessment (SOFA), in predicting mortality in patients with severe acute pancreatitis (SAP) admitted to intensive care unit (ICU), and explore the independent risk factors for mortality in SAP patients.MethodsThe electronic medical records of SAP patients who admitted to ICU of West China Hospital, Sichuan University between July 2014 and July 2019 were retrospectively analyzed. Data of the first APACHE Ⅱ, Ranson’s criteria, SOFA score, duration of mechanical ventilation, the use of vasoactive drugs and renal replacement therapy, and outcomes were obtained. The receiver operator characteristic (ROC) curve was used to evaluate the value of APACHE Ⅱ score, Ranson’s criteria, and SOFA score in predicting the prognosis of SAP. Logistic regression models were created to analyze the independent effects of factors on mortality.ResultsA total of 290 SAP patients hospitalized in ICU were screened retrospectively, from whom 60 patients were excluded, and 230 patients including 162 males and 68 females aged (51.1±13.7) years were finally included. The ICU mortality of the 230 patients with SAP was 27.8% (64/230), with 166 patients in the survival group and 64 patients in the death group. The areas under ROC curves of APACHE Ⅱ, Ranson’s criteria, APACHE Ⅱ combined with Ranson’s criteria, and SOFA score in predicting mortality in SAP patients admitted to ICU were 0.769, 0.741, 0.802, and 0.625, respectively. The result showed that APACHE Ⅱcombined with Ranson’s criteria was superior to any single scoring system in predicting ICU death of SAP patients. The result of logistic regression analysis showed that APACHE Ⅱ score [odds ratio (OR)=1.841, 95% confidence interval (CI) (1.022, 2.651), P=0.002], Ranson’s criteria [OR=1.542, 95%CI (1.152, 2.053), P=0.004], glycemic lability index [OR=1.321, 95%CI (1.021, 1.862), P=0.008], the use of vasoactive drugs [OR=15.572, 95%CI (6.073, 39.899), P<0.001], and renal replacement therapy [OR=4.463, 95%CI (1.901, 10.512), P=0.001] contributed independently to the risk of mortality.ConclusionsAPACHE Ⅱ combined with Ranson’s criteria is better than SOFA score in the prediction of mortality in SAP patients admitted to ICU. APACHE Ⅱ score, Ranson’s criteria, glycemic lability index, the use of vasoactive drugs and renal replacement therapy contribute independently to the risk of ICU mortality in patients with SAP.
ObjectiveTo evaluate the predictive value of critical illness scores for hospital mortality of severe respiratory diseases in respiratory intensive care unit (ICU).MethodsThe clinical data of the patients who needed intensive care and primary diagnosed with respiratory diseases from June, 2001 to Octomber, 2012 were extracted from MIMIC-Ⅲ database. The Acute Physiology Score (APS) Ⅲ, Simplified Acute Physiology Score (SAPS) Ⅱ, Oxford Acute Severity of Illness Score (OASIS), Logistic Organ Dysfunction System (LODS), Systemic Inflammatory Response Syndrome (SIRS) and Sequential Organ Failure Assessment (SOFA) were calculated according to the requirements of each scoring system. ICU mortality was set up as primary outcome and receiver operating characteristic (ROC) analysis was performed to evaluate the predictive performances by comparing the areas under ROC curve (AUC). According to whether they received invasive mechanical ventilation during ICU, the patients were divided into two groups (group A: without invasive mechanical ventilation group; group B: with invasive mechanical ventilation group). The AUCs of six scoring systems were calculated for groups A and B, and the ROC curves were compared independently.ResultsA total of 2988 patients were recruited, male accounted for 49.4%, median age was 67 (55, 79), and ICU mortality was 13.2%. The AUCs of SAPSⅡ, LODS, APSⅢ, OASIS, SOFA and SIRS were 0.73 (0.70, 0.75), 0.71 (0.68, 0.73), 0.69 (0.67, 0.72), 0.69 (0.67, 0.72), 0.67 (0.64, 0.70) and 0.58 (0.56, 0.62). Subgroup analysis showed that in group A, the AUCs of OASIS, SAPSⅡ, LODS, APSⅢ, SOFA and SIRS were 0.81 (0.76, 0.85), 0.80 (0.75, 0.85), 0.77 (0.72, 0.83), 0.75 (0.70, 0.80), 0.73 (0.68, 0.78) and 0.63 (0.56, 0.69) in the prediction of ICU mortality; in group B, the AUCs of SAPSⅡ, APSⅢ, LODS, SOFA, OASIS and SIRS were 0.68 (0.64, 0.71), 0.67 (0.63, 0.70), 0.65 (0.62, 0.69), 0.62 (0.59, 0.66), 0.62 (0.58, 0.65) and 0.57 (0.54, 0.61) in the prediction of ICU mortality. The results of independent ROC curve showed that the AUC differences between groups A and B were statistically significant in terms of OASIS, SAPSⅡ, LODS, APSⅢ and SOFA, but there were no significant differences in SIRS.ConclusionsThe predictive values of six critical illness scores for ICU mortality in respiratory intensive care are low. Lack of ability to predict ICU mortality of patients with invasive mechanical ventilation should hold primary responsibility.