A latent class approach for sepsis diagnosis supports use of procalcitonin in the emergency room for diagnosis of severe sepsis

Sepsis is defined as the host response to infection and it is an important cause of morbidity and mortality around the world [1, 2]. The surviving sepsis campaign issued a call for global action against sepsis and pointed out diagnosis as a fundamental challenge [3, 4]. In early stages of the process, the source of infection may be unclear and the related systemic response indistinguishable of no-infectious diseases. Consequently, clinicians often miss or delay this diagnosis. This is especially worrying; since there is strong evidence supporting that early treatment is associated with greater clinical success [5]. An ideal “Gold Standard” is not available for sepsis diagnosis, as microbiology is not enough sensitive and laboratory tests are not specific for using as reference standards. The lack of any reference standard has been overcome by using techniques that avoid the need for comparison with a single accurate test. These techniques can be broadly divided into latent class analysis (LCA) and Bayesian analysis [6]. LCA has been used widely in psychiatry as well as other disciplines [7–11] but, it has not been yet applied to the evaluation of sepsis.

On the other hand, sepsis is associated with the simultaneous activation of the inflammatory and coagulation cascades, and most of their components are markers or mediators in the host response [12, 13]. From this close interplay between inflammation and coagulation, which is a recognized way toward organ dysfunction and mortality [14], emerges the rationale to characterize the host response to infection. Three potential biomarkers have shown regular presence in systemic infections: C-reactive protein (CRP), procalcitonin (PCT), and D-dimer (DD); the latter as an unspecific signal of coagulation activation [15–19]. So far, however, no large prospective studies support any of them as a single independent criterion for sepsis. We aimed to estimate the diagnostic accuracy of these three biomarkers as diagnostic tests for sepsis, with the application of the latent class analysis, in patients at the ER admittance with a presumptive infection as main diagnosis.

Prospective single center study on the diagnostic accuracy of a test. The study protocol and a pre-specified nested analysis were previously published [20, 21].

Our results suggest that, under a “classical” definition of sepsis, three typical biomarkers (CRP, PCT and DD) are not capable enough to differentiate septic from non-septic patients in the ER. Indeed, the kappa-statistic measure for multi-rater agreement between experts for this definition was 0.65 for sepsis-no sepsis and 0.73 for infection with and without sepsis, which underlines the limitations for clinical diagnosis in this condition. Using another analytic approach, however, a higher cut-off point for PCT (2 ng/ml) is able to identify and to exclude a specific population more severely ill and with better microbiological confirmation. To the best of our knowledge, this is the first research that incorporates the novel concept of a latent class to the process of diagnosis in sepsis.

The performance of a diagnostic test is judged by how accurately the test result can identify a diseased or no diseased person. The true disease status is the “gold standard” against which a test should be compared. However, there are many conditions for which the definitive diagnosis is very difficult or expensive to establish. This is especially true for the diagnosis of a complex clinical condition as sepsis, in which even within the construct of “systemic response to infection” there is not a real “gold standard” against which the diagnostic criteria can be calibrated [22, 28, 29]. Psychological and social sciences have a long tradition in coping with primary study objects that are not directly observable. Constructs such as intelligence, fear or trust can only be measured indirectly. Inference proceeds by modeling the relationship between observable and latent variables in such a way that the parameters of interest are estimable from the implied relations between observable variables. When the unobservable variable is categorical, the term latent class analysis (LCA) applies [6, 7]. In other words, LCA postulates the existence of an unobserved categorical variable that divides the population of interest in to classes. Members of the population with a set of observed variables will respond differently depending on the latent class to which they belong. This technique can be applied to the problems related to diagnostic testing, with the unobserved categorical variable being “disease present” or “disease absent” [20].

Given the established interplay between inflammation and coagulation in sepsis [14, 30–32], it is reasonable to characterize the host response to infection as a potential diagnosis tool on the basis of three recognized markers of these two cascades. The sensible mathematical model of the latent diagnostic classification, using individuals’ values of CRP, DD and PCT, was able to identify a subset of patients attended in the ER with suspicion of infection and with clear differences in clinical status, microbiological profile and 28-day mortality. Although this subset was identified among those patients classified as sepsis by the expert committee, there is not a unique clear cut-off in any variable or test that may define the cluster specifically as severe or bacteremic sepsis (Table 3). Furthermore, among these three potential biomarkers, PCT proved to be the most contributor to the “new” standard of more severe disease but with a higher cut-off point than that usually suggested. Our main result, consequently, is that PCT is useful to identify a subgroup of more severely ill septic patients attending the ER. Such a finding was previously reported by Hausfater P et al. [33], whom studied 243 patients with body temperature of 38.5°C or greater attended in the adult emergency department of an academic tertiary care hospital. They found, using standard statistical methods, that PCT is an independent variable that can predict whether a febrile episode has a bacterial origin, and that at a threshold of 2 μg/l it is independently associated with critical illness. The coincidence with our findings is remarkable, despite the fact that their study population was extremely different: all the patients consulted by a febrile episode, 29% of them were immunocompromised, and only 81% were hospitalized in that consultation.

Needless to say, sepsis is not an illness but a syndrome suspected mainly on clinical criteria, and the misdiagnosis of sepsis is associated with an extremely adverse outcome. Consequently, we are not proposing a new methodological approach for sepsis diagnosis. Instead, we are identifying a new cut-off point for procalcitonin to be able to detect more severely ill patients. This goal was not achieved by the conventional clinical gold standard with expert consensus and, in this way, LCA is just an instrument to show that we can improve the process of sepsis diagnosis in the emergency room. The recent literature is full of studies evaluating PCT for sepsis diagnosis [16, 17, 34, 35], but in the setting of the ER there are less investigations testing its potential usefulness. In a secondary care hospital of Finland, a population of 539 patients admitted to the ER with suspicion of infection and with clinician’s order for blood cultures was studied [16]. In assessing how the parameters differentiated all sepsis patients (n = 358) from patients with no sepsis (n = 181), AUC-ROC for PCT was 0.73 (95% CI 0.69 – 0.78), and PCT emerged as the best marker for severe sepsis with an AUC-ROC = 0.77 (95% CI 0.71 – 0.84). Riedel et al. evaluated the usefulness of PCT as a diagnostic predictive marker of bacteremia and sepsis in 259 patients who had blood cultures obtained in the ER of a tertiary medical center in Baltimore [35]. In16 patients there was evidence of bacteremia and 12(75%) patients had a PCT level of more than 0.1 ng/ml. The PCT cut-off value that maximizes the AUC-ROC (0.79) was 0.1475 ng/ml., but with sensitivity just in 75% and specificity of 79.8%. In a recent meta-analysis [36], Wacker C. et al. analyzed 30 reports, although only two from ER, accounting for 3244 patients. Bivariate analysis yielded a mean sensitivity of 0.77 (95% CI = 0.72–0.81) and specificity of 0.79 (95% CI = 0.74–0.84) and the area under the receiver operating characteristic curve was 0.85 (95% CI = 0.81–0.88). The median cut-off for PCT of the studies included was 1.1 ng/ml (IQR = 0.5–2.0) and the absence of a threshold effect suggests that a cut-off between 1.0 and 2.0 ng/ml, close to our findings, is helpful for discrimination of patients with sepsis from other inflammatory conditions. However, the studies had substantial heterogeneity (I ² = 96%, 95% CI = 94–99) and none of the subgroups investigated like population, admission category, assay used, severity of disease, and description and masking of the reference standard, could account for that heterogeneity. They concluded that the test may be helpful for diagnosis of sepsis in critically ill patients, but it must be interpreted in context with information from careful medical history, physical examination and microbiological assessment.

Our study has several limitations. First, this is a single center study in a specific geographic location with some particularities from an epidemiological point of view [2, 37], which are obstacles for external validity. Moreover, the pre-test probability of sepsis should be significantly different in patients admitted to the ER and in patients admitted to ICU, even with the same clinical suspicion of bacterial infection, and this is an acknowledged consideration in the use and interpretation of any diagnostic test. As we mentioned before, the clinical diagnostic “gold standard” utilized here performed poorly, as the concordance between experts was 0.65 for sepsis-no sepsis and 0.73 for infection with and without sepsis. This weakness, indeed, underlines the limitations for clinical diagnosis in this condition. On the other hand, LCA also has its limitations as “gold” standard. Under this approach, sepsis is not formally defined but rather is a mathematically defined entity that does not necessarily correspond with a clinically relevant status. Additionally, LCA modeling requires sophisticated analytic techniques and software, and the full model or the hypothetical “true” state of disease cannot be fully tested with the observed data. Finally, although blood sampling was performed immediately after the patient was admitted to the study, he/she could be in the ER at any time within the last 24 hours before recruitment. This is important because biomarker’s kinetic, notably PCT, and their levels may varying considerably during 24 hours.

In summary, the “holy grail” of sepsis diagnosis is an evolving process and the fine exercise of clinical suspicion should be complemented by appropriate laboratory test. In this scenario, PCT emerges as an acceptable choice underscoring both microbiology and prognosis in selected patients. A higher level of PCT seems related more strongly with these two components of the infectious phenomena.