Abstract
ABSTRACTObjectivesTo compare the accuracy of the SOFA and APACHE II scores in predicting mortality among ICU patients with sepsis in an LMIC.DesignA multicentre, cross-sectional study.SettingA total of 15 adult ICUs throughout Vietnam.ParticipantsWe included all patients aged ≥ 18 years who were admitted to ICUs for sepsis and who were still in ICUs from 00:00 hour to 23:59 hour of the specified study days (i.e., 9thJanuary, 3rdApril, 3rdJuly, and 9thOctober of the year 2019).Primary and secondary outcome measuresThe primary outcome was hospital all-cause mortality (hospital mortality). We also defined the secondary outcome as all-cause deaths in the ICU (ICU mortality).ResultsOf 252 patients, 40.1% died in hospitals, and 33.3% died in ICUs. SOFA (AUROC: 0.688 [95% CI: 0.618-0.758]; cut-off value ≥ 7.5; PAUROC<0.001) and APACHE II scores (AUROC: 0.689 [95% CI: 0.622-0.756]; cut-off value ≥ 20.5; PAUROC<0.001) both had a poor discriminatory ability for predicting hospital mortality. However, the discriminatory ability for predicting ICU mortality of SOFA (AUROC: 0.713 [95% CI: 0.643-0.783]; cut-off value ≥ 9.5; PAUROC<0.001) was fair and was better than that of APACHE II score (AUROC: 0.672 [95% CI: 0.603-0.742]; cut-off value ≥ 18.5; PAUROC<0.001). A SOFA score ≥ 8 (adjusted OR: 2.717; 95% CI: 1.371-5.382) and an APACHE II score ≥ 21 (adjusted OR: 2.668; 95% CI: 1.338-5.321) were independently associated with an increased risk of hospital mortality. Additionally, a SOFA score ≥ 10 (adjusted OR: 2.194; 95% CI: 1.017-4.735) was an independent predictor of ICU mortality, in contrast to an APACHE II score ≥ 19, for which this role did not.ConclusionsIn this study, SOFA and APACHE II scores were worthwhile in predicting mortality among ICU patients with sepsis. However, due to better discrimination for predicting ICU mortality, the SOFA was preferable to the APACHE II score in predicting mortality.Clinical trials registry – India: CTRI/2019/01/016898Strengths and limitations of this studyAn advantage of the present study was data from multi centres, which had little missing data.Due to the absence of a national registry of intensive care units (ICUs) to allow systematic recruitment of units, we used a snowball method to identify suitable units, which might have led to the selection of centres with a greater interest in sepsis management.Due to the study’s real-world nature, we did not make a protocol for microbiological investigations. Moreover, we mainly evaluated resources utilized in ICUs; therefore, the data detailing the point-of-care testing and life-sustaining treatments were not available. Additionally, to improve the feasibility of conducting the study in busy ICUs, we opted not to collect data on antibiotic resistance and appropriateness.Due to our independent variables (e.g., SOFA score that was greater than or equal to the cut-off value) that might be associated with primary outcome only measured upon ICU admission, the mixed-effects logistic regression model could not be used to predict discrete outcome variables measured at two different times, i.e., inside and outside the ICU settings.Although the sample size was large enough, the confidence interval was slightly wide (±6.03%), which might influence the normal distribution of the sample.
Publisher
Cold Spring Harbor Laboratory