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Identifying Sepsis in Clinical Database With Sepsis-3 Definition.

To the Editor: We read with great interest the article published in a recent issue of Critical Care Medicine by Shen et al (1), which employed a large population-based registry database to investigate the recurrence of severe sepsis (SS) after surviving one episode of SS. The result showed that a past history of SS significant increased risk of new episode of SS as compared to those without history of SS. Since the study utilized a large clinical database, we are very interested in how SS was identified, because it was impossible to retrieve data by hand. The study used International Classification of Diseases, 9th Revision, Clinical Modification code for bacterial and fungal infection and acute organ dysfunction, and previous study by the same authors showed that the method can identify SS with a sensitivity and specificity of 83.3% and 98.9%, respectively (2). However, the diagnostic performance was calculated against the sepsis definition proposed by American College of Chest Physicians-Society of Critical Care Medicine in 1992 (3, 4). The old definition was found to be unreliable. For example, one in eight ICU patients with infection and new organ failure did not have the requisite minimum of two systemic inflammatory response syndrome (SIRS) criteria to fulfill the definition of sepsis, but they showed protracted courses with significant morbidity and mortality. Since there comes out the Sepsis-3 definition for sepsis, this definition may have some implications for identifying patients with sepsis from large clinical database. Sepsis-3 relies on the Sequential Organ Failure Assessment (SOFA) score to identify patients with sepsis (3). This scoring system is readily available in many clinical databases or can be easily calculated based on physiologic and/or laboratory variables. Our previous study employed SIRS plus infection criteria to identify patients with sepsis (5). The calculation algorithm can be much simpler if Sepsis-3 criteria are employed. The simple Quick SOFA criteria comprises only respiratory rate, systolic blood pressure, and altered mental status, which are readily available in nursing sheet. dysfunction and dysregulated host response) that currently lack clinical utility. Similarly, the ability to identify sophisticated molecular biomarkers may not yet be useful at the bedside or in real time (parenthetically, we received significant feedback questioning our inclusion of lactate in the clinical criteria for septic shock on the grounds that lactate measurement is not available in many places). However, both our new definition and characteristic genomic or proteomic signatures reflect our best current understanding of the pathobiology of sepsis. We also recognized a responsibility to provide clinicians with something of greater clinical utility than what is currently in use. Thus, Seymour et al (3) and Shankar-Hari et al (4) used a data-driven approach (the first time that criteria to identify patients likely to be septic has ever been based on anything more robust than expert opinion) to generate “clinical criteria,” measures easily and routinely obtained at the bedside that have face validity (e.g., that make sense), predictive validity (e.g., that identify patients with outcomes highly consistent with what would be expected of a patient with sepsis) and that do not generate large numbers of false positives but that also do not increase the number of false negatives. We also indicated that these clinical criteria required validation in settings that differed from those characterizing the datasets used, and that prospective validation was essential. I, personally, am uncertain that the “definitions” contained in Sepsis-4 will differ greatly from those in Sepsis-3. The pace of discovery has certainly accelerated, but uncovering fundamental pathobiologic processes (which constitutes the “essence of a thing” or “what something is,” i.e., what the Merriam-Webster dictionary says constitutes a definition) is time consuming. I am certain, however, that improved technology, as identified by Drs. Zimmerman and Davis (1), and analysis of “big data” in the manner used by Seymour et al (3) and Shankar-Hari et al (4) will make it possible to identify “clinical criteria” with face and predictive validity superior to those included in Sepsis-3. Dr. Deutschman received funding from PA Chapter SCCM, Northern Ireland Critical Care Society, and NYU Department of Medicine.