Physician agreement on the diagnosis of sepsis in the intensive care unit: estimation of concordance and analysis of underlying factors in a multicenter cohort

Autor: Antony Rapisarda, Adey Tsegaye, Jorge P. Parada, Thomas D. Yager, Jordan A. Kempker, Robert A. Balk, Gourang P. Patel, Paul H. Mayo, Greg S. Martin, Venkataramana K. Sidhaye, Steven M. Opal, Therese Seldon, Russell R. Miller, Stella Hahn, Roslyn A. Brandon, Richard E. Rothman, Mangala Narasimhan, Dayle Sampson, Annette M. Esper, Franco R. D'Alessio, Majid Afshar, Mark Yoder, Richard Bruce Brandon, John P. Burke, Emily R. Gilbert, Leo McHugh, Jared A. Greenberg, Mitchell M. Levy, Bert K. Lopansri
Rok vydání: 2019
Předmět:
Zdroj: Journal of Intensive Care
Journal of Intensive Care, Vol 7, Iss 1, Pp 1-17 (2019)
ISSN: 2052-0492
Popis: Background Differentiating sepsis from the systemic inflammatory response syndrome (SIRS) in critical care patients is challenging, especially before serious organ damage is evident, and with variable clinical presentations of patients and variable training and experience of attending physicians. Our objective was to describe and quantify physician agreement in diagnosing SIRS or sepsis in critical care patients as a function of available clinical information, infection site, and hospital setting. Methods We conducted a post hoc analysis of previously collected data from a prospective, observational trial (N = 249 subjects) in intensive care units at seven US hospitals, in which physicians at different stages of patient care were asked to make diagnostic calls of either SIRS, sepsis, or indeterminate, based on varying amounts of available clinical information (clinicaltrials.gov identifier: NCT02127502). The overall percent agreement and the free-marginal, inter-observer agreement statistic kappa (κfree) were used to quantify agreement between evaluators (attending physicians, site investigators, external expert panelists). Logistic regression and machine learning techniques were used to search for significant variables that could explain heterogeneity within the indeterminate and SIRS patient subgroups. Results Free-marginal kappa decreased between the initial impression of the attending physician and (1) the initial impression of the site investigator (κfree 0.68), (2) the consensus discharge diagnosis of the site investigators (κfree 0.62), and (3) the consensus diagnosis of the external expert panel (κfree 0.58). In contrast, agreement was greatest between the consensus discharge impression of site investigators and the consensus diagnosis of the external expert panel (κfree 0.79). When stratified by infection site, κfree for agreement between initial and later diagnoses had a mean value + 0.24 (range − 0.29 to + 0.39) for respiratory infections, compared to + 0.70 (range + 0.42 to + 0.88) for abdominal + urinary + other infections. Bioinformatics analysis failed to clearly resolve the indeterminate diagnoses and also failed to explain why 60% of SIRS patients were treated with antibiotics. Conclusions Considerable uncertainty surrounds the differential clinical diagnosis of sepsis vs. SIRS, especially before organ damage has become highly evident, and for patients presenting with respiratory clinical signs. Our findings underscore the need to provide physicians with accurate, timely diagnostic information in evaluating possible sepsis. Electronic supplementary material The online version of this article (10.1186/s40560-019-0368-2) contains supplementary material, which is available to authorized users.
Databáze: OpenAIRE
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