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Minimum quality threshold in pre-clinical sepsis studies (MQTiPSS): an international expert consensus initiative for improvement of animal modeling in sepsis

Abstract

BACKGROUND:Pre-clinical animal studies precede the majority of clinical trials. While the clinical definitions of sepsis and recommended treatments are regularly updated, a systematic review of pre-clinical models of sepsis has not been done and clear modeling guidelines are lacking. OBJECTIVE:To address this deficit, a Wiggers-Bernard Conference on pre-clinical sepsis modeling was held in Vienna in May 2017. The goal of the conference was to identify limitations of pre-clinical sepsis models and to propose a set of guidelines, defined as the "Minimum Quality Threshold in Pre-Clinical Sepsis Studies" (MQTiPSS), to enhance translational value of these models. METHODS:A total of 31 experts from 13 countries participated and were divided into 6 thematic working groups (WG): (1) study design, (2) humane modeling, (3) infection types, (4) organ failure/dysfunction, (5) fluid resuscitation, and (6) antimicrobial therapy endpoints. As basis for the MQTiPSS discussions, the participants conducted a literature review of the 260 most highly cited scientific articles on sepsis models (2002-2013). RESULTS:Overall, the participants reached consensus on 29 points; 20 at "recommendation" (R) and 9 at "consideration" (C) strength. This executive summary provides a synopsis of the MQTiPSS consensus (Tables 1, 2, and 3). Detailed commentaries to all Rs and Cs are simultaneously published in three separate full-length papers. CONCLUSIONS:We believe that these recommendations and considerations will serve to bring a level of standardization to pre-clinical models of sepsis and ultimately improve translation of pre-clinical findings. These guideline points are proposed as "best practices" for animal models of sepsis that should be implemented. In order to encourage its wide dissemination, this article is freely accessible in Shock, Infection and Intensive Care Medicine Experimental.

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