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Record W2887736841 · doi:10.1186/s40635-018-0189-y

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

2018· review· en· W2887736841 on OpenAlexaff
Marcin F. Osuchowski, Alfred Ayala, Soheyl Bahrami, Michael Bauer, Mihály Boros, Jean‐Marc Cavaillon, Irshad H. Chaudry, Craig M. Coopersmith, Clifford S. Deutschman, Susanne Drechsler, Philip A. Efron, Claes Frostell, G. Fritsch, Waldemar Goździk, Judith Hellman, Markus Huber‐Lang, Shigeaki Inoue, Sylvia Knapp, Andrey V. Kozlov, Claude Libert, John C. Marshall, Lyle L. Moldawer, Peter Radermacher, Heinz Redl, Daniel G. Remick, Mervyn Singer, Christoph Thiemermann, Ping Wang, W. Joost Wiersinga, Xianzhong Xiao, Basilia Zingarelli

Bibliographic record

VenueIntensive Care Medicine Experimental · 2018
Typereview
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
FundersNational Institute of General Medical Sciences
KeywordsMedicineSepsisIntensive care medicineGuidelineClinical trialStandardizationMEDLINEPathologyInternal medicineComputer science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.505
metaresearch head score (Gemma)0.407
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.495
Threshold uncertainty score0.610

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.5050.407
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0070.012
Bibliometrics0.0170.012
Science and technology studies0.0050.007
Scholarly communication0.0120.008
Open science0.0170.026
Research integrity0.0140.018
Insufficient payload (model declined to judge)0.0030.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.552
GPT teacher head0.582
Teacher spread0.030 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainMethods
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations141
Published2018
Admission routes1
Has abstractyes

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