FluA-p score: a novel prediction rule for mortality in influenza A-related pneumonia patients

Influenza is a common contagious respiratory disease and influenza-related epidemics and pandemics have occurred all over the world [1, 2]. Despite advances in medical technology and greater economic development in many countries, influenza still causes numerous hospitalizations and is associated with considerable mortality [3‐5]. Each year, 10–20% of the global population experiences symptomatic influenza, including 3–5 million cases of severe illness and 290–650 thousand deaths [6]. For these reasons, influenza is regarded as the greatest threat to global health in the twenty-first century [7].

Patients infected with influenza may exhibit a broad spectrum of clinical symptoms, ranging from self-limited upper respiratory tract illness to severe pneumonia [8, 9]. Influenza-related pneumonia (Flu-p), including primary viral pneumonia and secondary bacterial pneumonia, is the major cause of influenza-associated hospitalizations and deaths [10]. Primary influenza pneumonia and post-influenza secondary bacterial pneumonia are distinct pathologies but difficult to distinguish clinically. The pathogenesis of primary influenza pneumonia shows diffuse alveolar damage associated with haemorrhage and necrotising bronchiolitis, and the secondary bacterial pneumonia presents with neutrophil influx, loss of alveolar architecture and consolidation [10]. When the diagnosis of pneumonia is confirmed, the first priority is to assess the degree of disease severity. Several prediction rules have been established to help clinicians predict the mortality rate of patients with pneumonia. Scores on the CURB-65 (confusion, urea, respiratory rate, blood pressure, age ≥ 65 years) and the pneumonia severity index (PSI) are the most widely used indices to predict 30-day mortality rates for patients diagnosed with community-acquired pneumonia [11, 12]. However, the validity of these two measures for use with Flu-p patients is questionable [13, 14]. Some variables that might be more useful in predicting severe influenza include PO₂/FiO₂ and lymphocyte counts [15, 16]. But to our knowledge, standard decision rules using these (and perhaps other) variables to predict the extent of Flu-p severity have yet to be developed.

In an effort to remedy this situation we conducted a multicenter, retrospective study with the principal aim being to develop an easy-to-use and accurate severity assessment tool to predict the 30-day mortality rate of patients with influenza A-related pneumonia (FluA-p). Our assessment tool is designed to have greater predictive power than either CURB-65 or PSI scores.

Our study not only assessed several risk factors, but also developed a simple and reliable prediction tool for predicting mortality in patients with FluA-p. Our method showed greater predictive validity than did the common pneumonia severity scores of PSI and CURB-65.

PSI and CURB-65 scores are recommended by the Infectious Diseases Society of America/American Thoracic Society (IDSA/ATS) and the British Thoracic Society (BTS) for the assessment of disease severity of CAP [20, 21]. Numerous studies have found that PSI and CURB-65 scores accurately predict the 30-day mortality rates of CAP and are applicable for use in many clinical settings [22‐24]. Recently, however, some studies suggested that they were insufficient for predicting mortality in settings involving influenza pneumonia [13‐16]. Our results likewise suggested that PSI and CURB-65 scores underestimated the mortality of FluA-p patients. More than half of the deceased patients were classified as low death risk (CURB-65 score 0–2 and PSI risk class I~III). Both CURB-65 and PSI were heavily weighted by age and comorbidities. But many Flu-p patients were young and previously healthy individuals. In our study cohort, 60% of patients were younger than 65 years of age. During the H1N1 influenza A pandemic in 2009, a large proportion of severe cases were young patients who experienced acute respiratory failure [25, 26]. Another issue to consider is that the current severity tool that relies on PSI and CURB-65 scores was possibly derived from patients diagnosed primarily with bacterial and atypical bacterial pneumonia rather than influenza pneumonia [20, 27]. In fact, Guo et al. reported that CURB-65 scores were not powerful predictors of mortality in the context of viral pneumonia [28].

Several studies have reported lymphocytopenia in severe influenza [27, 29, 30]. Shi et al. suggested that lymphocytopenia was an early and reliable predictor of mortality in patients diagnosed with influenza A(H1N1)pdm09 pneumonia [27]. Although the mechanisms of lymphocytopenia in severe influenza are not well elucidated, it is believed that the reduction of T lymphocytes (including CD8 + T effector and central memory cells, CD4 + T, and/or NK cells), rather than B lymphocytes, in the peripheral blood might be the causes of lymphocytopenia [31, 32]. Lymphocytopenia also plays a role in suppressive cellular immunity and the delayed clearance of viruses [33].

Smoking history was another pedictor of FluA-p mortality in our study, which is a finding commensurate with some previous reports [34‐36]. Wong and colleagues, for example, found that influenza-related mortality for all-causes and for cardiovascular and respiratory diseases was greater in current and ex-smokers than in never smokers [34]. A case-control study by Hennessy et al. found that smoking (OR 3.03, 95% CI 1.01–9.23) was a significant risk factor for death in patients with A(H1N1) pdm09 [35]. Although the precise nature of the association between smoking and influenza-related mortality has yet to be determined, some potential mechanisms suggest the possibility of biological associations. Smoking could disrupt the normal defenses of the respiratory tract by causing peribronchiolar inflammation, slowing mucociliary clearance, and/or damaging respiratory epithelial cells [37]. Animal studies using mouse models have shown that smoking induces inflammatory mediators and suppresses innate immunity against influenza infection [38]. Smoking could increase viral replication by directly suppressing epithelial antiviral pathways, facilitating cytokine release in mucosal innate immunity and increasing deoxyribonucleic acid (DNA) methylation for viral infection [39].

BUN, pO₂/FiO₂, and arterial PH were parameters in calculating PSI and/or CURB-65 scores. Our study showed that these parameters were valuable predictors of mortality in FluA-p patients. Early administration of NAI therapy is associated with better outcomes in severe influenza [40, 41]. Old age, obesity, pregnancy and chronic medical conditions, such as COPD, diabetes mellitus, and chronic kidney disease, have been associated with poorer outcomes in patients with influenza [35, 42, 43]. However, in our study only cardiovascular disease was identified as a risk factor for mortality in FluA-p patients. Other studies have shown that coinfections can worsen illness severity and increase mortality in severe influenza [44, 45]. In our univariate analyses, coinfections were associated with increased mortality for FluA-p patients, but coinfections were not significant predictors in the multivariate analysis.

FluA-p score is a very simple severity assessment tool containing only seven parameters and it serves as a reliable prediction rule. ROC showed better predictive validity compared to PSI risk class and the CURB-65 score. Although the specificity of score 2 is not good (only 25%), judging from the performance of score − 2 ~ 1 and score 3 ~ 6, we believe it is mainly because patients with score 2 were scarce (only 16 cases) in our study. Larger subgroup sample sizes would allow for stronger inferences Using a cutoff value of 7, the new FluA-p score could stratify patients into two groups with significantly different death risks. We believe this novel assessment tool is suitable for use in clinical settings with FluA-p patients. In addition, the parameters include indicators widely used in clinics, even in small and perhaps less equipped hospitals. Consequently, we think the assessment tool has a great practical value.

Some limitations of our study should be noted. First, despite our respectable sample size and comprehensive statistical approach, the retrospective research design meant some unavoidable selection bias. For example, the nucleic acid tests were performed based on the subjective judgement of the attending physicians. It was possible that more severe (or milder) patients were inclined to be tested; thus, not all respiratory cases were eligible for swabbing and there was likely some type of selection. Second, due to the retrospective study design, we were unable to retrieve and evaluate vaccination data, and the incomplete data might have lowered the accuracy of our results. Finally, some studies have suggested that the clinical characteristics and prognosis of immunocompromised patients with influenza is not the same as that for immunocompetent hosts [46, 47]. Thus, it is important to further assess our influenza prediction model in immunocompromised patients.

We developed a simple and reliable prediction rule for 30-day mortality in patients hospitalised with FluA-p. The prediction rule could help clinicians to more accurately assess influenza disease severity. Our recommendation is that clinicians should pay particular attention to patients with FluA-p scores ≥7, as such individuals have an increased risk for death.