Worldwide, influenza epidemics emerge almost every year and patient visits to the ED increase dramatically during the flu seasons. Most influenza infections are self-limiting and manageable with symptomatic treatment, and antiviral therapy might not be necessary in most patients. However, during the outbreak in Taiwan in 2015–2016, we observed extremely rapid disease progression in some patients. Severely ill patients may progress to acute hypoxic respiratory failure within 24 hours even if the initial chest x-ray shows normal findings. Therefore, a simple early prognostic indicator might be clinically important to an emergency physician. In the present study, we found that the qSOFA score was a better prognostic indicator compared with the SIRS criteria.
Since the qSOFA score was developed, many people have evaluated its clinical value for sepsis. Some articles reported that the qSOFA as a good prognostic predictor [25, 33], whereas other studies found that the qSOFA may not be an adequate screening tool in the ED because of its poor sensitivity [34-36]. A recent meta-analysis showed that the qSOFA was better than the SIRS was in predicting in-hospital mortality of sepsis [37], and a similar finding was observed in our cohort. The predictive performance of the qSOFA was better than that of the SIRS (good accuracy, but poor sensitivity) in the prognostication of patients with influenza, and we rationalized that this finding was related to the septic reaction induced by the influenza or a secondary bacterial infection.
The SIRS criteria have been used to predict outcomes in influenza. Tai et al. conducted a retrospective study that included 409 geriatric ED patients (age ≥65 years) who tested positive on RIDT [38] and found that SIRS criteria ≥3 was an acceptable predictor of mortality in this group of patients (OR 3.37, 95% CI 1.05–10.73; sensitivity 60%, 95% CI 46–80%; specificity 70%, 95% CI 66–75%). The present study included all adult patients with influenza, not merely elderly patients, and we included patients with positive RT-PCR test results for influenza to reduce bias. We found that the SIRS had poor predictivity for outcomes in influenza.
Several previous studies have reported the use of different prognostic scales of pneumonia to evaluate influenza [39-44]. Myles et al. [39] compared the performance of Community Assessment Tools (CATs), CURB-65 score, and the Pandemic Medical Early Warning Score in influenza. They found the CATs were a useful triage tool to predict severe outcomes. However, theirs was a case–control study and was limited to H1N1 infections, which might have conferred some bias. Another retrospective study used eight different scoring tools, including CURB-65, Mortality in Emergency Department Sepsis (MEDS) score, the Nursing Home-Acquired Pneumonia score, PMEWS, Pneumonia Severity Index, severity score for the elderly with community-acquired pneumonia score, SMART-COP Score, and Simple Triage Scoring System, to predict the outcomes of influenza in the ED [40, 43]. These researchers found that the PSI and MEDS scores were moderately predictive of in-hospital mortality, and the SMARTCOP score was a good predictor of ICU admission. In the present study, we did not compare these pneumonia scales because all of these scoring tools need further radiographic or laboratory investigations. We did not routinely arrange these exams for every patient with flu-like symptoms in the ED. In addition, the qSOFA score is much easier and simpler to use for the frontline ED staff. Further prospective studies are required to define the roles of these scoring tools for influenza in the ED.
Other studies have attempted to use serum biomarkers to predict outcomes in patients with influenza. Zimmerman et al. reported that serum levels of C-reactive protein were an early predictor of outcome in the ED [45]. Another report concluded that serum level of lactate dehydrogenase >600 IU/L was associated with mortality in influenza-induced pneumonia [46]. However, both of the abovementioned studies were limited to H1N1 influenza. Moreover, serum biomarkers were not optimal as early prognostic predictors because we blood tests will not be conducted for every patient with influenza in a busy ED, especially during an epidemic outbreak.
Patel et al. developed a predictive classification tree model to estimate the mortality rates of the human highly pathogenic avian influenza (HPAI) A/H5N1 based on significant predictors of influenza mortality, including age, duration from symptom onset to hospitalization, country, and per capita government health expenditure. However, the quality of data was inconsistent [47]. Those authors included 617 H5N1 cases in their meta-analysis of articles published in any language. There were wide variations in their database, such as with regard to surveillance and clinical care, vaccination policy, lack of data on antiviral treatment, and time from illness onset to the initiation of antiviral treatment. Furthermore, the abovementioned study was limited to HPAI A/H5N1 and did not include all influenza.
Patients with a qSOFA score ≥1 might already have clinically apparent illness. Emergency physicians might not always need the qSOFA score to facilitate patient disposition. However, this quantitative scoring tool could generate a more objective and more representative picture of every individual with influenza. In addition, in our data, the CCI, admission rate, and mortality rate were relatively higher than in previous studies. This means that our cohort had more severe illness and was therefore much closely representative of the real ED. We believe that our results are reliable and can be applied in clinical practice, especially in the ED.
Limitations
This study has strength in numbers, although it was a single-center retrospective study with the inherent limitations of this study design. In addition, we might not have ordered an influenza test for everyone presenting to the ED with fever or URI symptoms, especially in the non-flu season. Moreover, all tests for influenza generate false negatives. These factors might induce some bias. Further studies are required to confirm our findings and prospectively validate the use of qSOFA in this specific patient population.
The definition of “altered mentation” with regard to the qSOFA score has two versions in the literature. One includes a GCS score ≤13, which was mentioned in the original study of Sepsis-3 [23]. The other was a GCS score <15, according to the definitions of sepsis and septic specified by the Third International Consensus [22]. In the present study, we used the GCS score <15 for analysis. This might have caused an overestimated qSOFA score because of patients with unclear baseline mental status due to underlying disease.