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Record W6906297442 · doi:10.17605/osf.io/z9nuj

Pediatric Hemorrhagic Shock Consensus Conference

2022· other· en· W6906297442 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Science Framework · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsResuscitationDelphi methodHemorrhagic shockObservational studyConsensus conferenceStandardizationTranexamic acidPediatric traumaShock (circulatory)MEDLINE

Abstract

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Trauma is the leading cause of pediatric mortality, potential years of life lost, and a significant medical cost in the developed world. (1,2) In addition, children have a higher incidence of mortality compared with adults. Mortality in children with traumatic hemorrhagic shock is 50% compared to 20-25% reported in adults. (3,4) Estimates indicate that there are 1,000 preventable traumatic deaths after injury in children per year in the US due to inadequate or delayed care. Recent retrospective and prospective observational studies indicate that resuscitation practices (appropriate blood product ratios and tranexamic acid (TXA) use) can dramatically reduce mortality in children with traumatic hemorrhagic shock. (5,6) Due to these alarming statistics, resuscitation and hemostatic strategies are a key target for standardization and subsequent investigation. However, clinical trial design surrounding this topic would be very difficult due to not only the lack of standardization in resuscitation approaches, transfusion strategies, utilization of hemostatic monitoring and adjuncts, but also the lack of agreed upon critical definitions and common data elements for study. To address these challenges, we organized a multidisciplinary team of highly engaged international experts and key stakeholders to develop consensus statements on best practice based on the current literature, consensus statements on research priorities, and methods of dissemination and implementation of the conference proceedings. Consensus statements will be developed via a highly structured process to include using the Delphi Method. A panel of 21 international experts (USA, Canada, Europe, Israel) that represent trauma surgery, transfusion medicine/hematology, anesthesia, critical care, and emergency medicine will form the consensus committee. The conference will also lead to the generation of a multidisciplinary research network focused on improving outcomes for children with traumatic hemorrhagic shock. Aim 1: Review the current state of the art for the management of pediatric traumatic hemorrhagic shock. To achieve this aim, one full day of lectures will be used to review and discuss in detail current knowledge in the biology of traumatic hemorrhagic shock, methods to monitor shock and its consequences, hemorrhage control methods, and resuscitation practice patterns and outcomes in this population. Lectures will also include the importance of collecting common data elements, structure of a pediatric trauma resuscitation research network, and the Delphi Method for consensus statement generation. Aim 2: Develop evidence-based informed consensus statements for the management of pediatric traumatic hemorrhagic shock. To achieve this aim, we will use the Delphi Method process to create consensus recommendations for best practices for the management of pediatric traumatic hemorrhagic shock. Specific topics for discussion will include the use of tourniquets, prehospital blood use, transfusion and hemostatic adjunct strategies, hemostasis monitoring, airway and blood pressure management. Aim 3: Develop a consensus statement on research priorities. To achieve this aim, consensus statements will be developed that describe the mission and goals for a pediatric trauma resuscitation research network. Consensus statements will also be generated on specific research topics that need to be prioritized for the development of clinical trials. Recognizing the paucity of literature on many important topics in pediatric traumatic shock resuscitation, current knowledge gaps and research priorities in this population will be identified that will be critical to improving patient care. Aim 4: Develop a robust dissemination and implementation methods for consensus statements generated and for the results of future trials. To achieve this aim, we will collaborate with experts in the field of dissemination and implementation to develop methods that are optimal for the pediatric trauma community. Methods will include publishing a supplement in Pediatric Critical Care that summarizes the conference proceedings. Other methods such as the development of decision support tools, and the use of video conferencing and social media venues will be explored. The use of the dissemination and implementation tools established during the conference will be incorporated by the newly formed pediatric trauma resuscitation research network to change practice based on the evidence it generates. This network will begin multi-institutional collaboration to study generated research questions and maintain its framework and momentum with regular conference calls and yearly meetings. Consensus Methods: A “medical consensus” is a public statement on a particular aspect of medical knowledge that is generally agreed upon as an evidence-based, state-of-the art knowledge by a representative group of experts in that area. (20) A specific method to commonly used to establish consensus is the Delphi Method. To begin the process of developing consensus, the planning committee has agreed upon important topics (listed in agenda) that the consensus committee will discuss with the goal of generating consensus statements. Lectures during day 1 of the conference will cover these topics in detail to inform the discussion within the consensus committee. In addition, the planning committee will collect the current literature on consensus topics in a systematic approach and share as a pre-meeting packet to the consensus committee for review at least one month prior to this meeting. Members of the planning committee will perform scoping and systematic reviews with formal guidance from library science experts (UAB Library Services). Searches for all literature pertinent to the consensus statements, will use a Boolean approach that will take into account the keywords in the PICOS domains (21, 22): P (population), I (intervention), C (comparator), O (outcome), S (study design). In each instance, the librarian will search at least in PubMed, Medline and the Cochrane Library. Thereafter, two members of the consensus committee will independently select relevant papers through Covidence software. Retained papers will be used to write the first draft of one or multiple summaries and a first draft of recommendation(s) for the topics by the primary lecturer on the topic, using the GRADE methodology. (23-27) Although we will not be publishing formal systematic reviews, identical search methods and methodology to select the relevant literature will be carried out to provide the most relevant, current literature on which to base our consensus statements and discussion. The consensus statement development will be initially drafted by the faculty lecturer on the topic and will then be voted on by all members of the consensus committee utilizing the RAND/UCLA Appropriateness Methodology, a method developed to combine the best available scientific evidence with the collective judgement of the experts. All experts rate the consensus statement on a Likert scale (1=disagreement, 9=strong agreement). The highest and lowest scores are discarded followed by calculation of the median and range. The median value determines how the recommendation is categorized: agreement (median=7-9), equipoise (median=4-6), or disagreement (median=1-3). The range (remaining lowest and highest values) determines if the recommendation is “strong” or “weak.” (28) If there is not agreement, those not in agreement can aid discussion to amend statement to facilitate agreement until voting can occur on the adjusted statement. If there is not consensus after three votes, the faculty lecturer will moderate discussion to develop changes from audience feedback to attempt to gain consensus. If after 5 total cycles of voting, there is no consensus, we will publish consensus could not be obtained. Two hours will be allotted for each topic.

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)0.027
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.046
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.048
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0040.002
Science and technology studies0.0030.001
Scholarly communication0.0050.004
Open science0.0060.006
Research integrity0.0120.012
Insufficient payload (model declined to judge)0.0460.023

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 head0.042
GPT teacher head0.339
Teacher spread0.297 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2022
Admission routes1
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