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Record W3000533498 · doi:10.2196/17206

Hemostatis Analyzer-Supported Hemotherapy Algorithm in Cardiac Surgery: Protocol for a Randomized Controlled Monocentric Trial

2020· article· en· W3000533498 on OpenAlexvenueno aff
Sophie Michel, Florian Piekarski, J. Fischer, Vanessa Hettler, Elisabeth Adam, Lars Holzer, Gösta Lotz, Thomas Walther, Kai Zacharowski, Florian J. Raimann

Bibliographic record

VenueJMIR Research Protocols · 2020
Typearticle
Languageen
FieldMedicine
TopicTrauma, Hemostasis, Coagulopathy, Resuscitation
Canadian institutionsnot available
FundersHemoSonics
KeywordsThromboelastometryMedicineAlgorithmCardiac surgeryHemotherapyPoint of careSurgeryComputer scienceCoagulopathy

Abstract

fetched live from OpenAlex

BACKGROUND: Point of care devices for performing targeted coagulation substitution in patients who are bleeding have become increasingly important in recent years. New on the market is the Quantra. It is a device that uses sonorheometry, a sonic estimation of elasticity via resonance, which is a novel ultrasound-based technology that measures viscoelastic properties of whole blood. Several studies have already shown the comparability of the Quantra with devices already established on the market, such as the rotational thromboelastometry (ROTEM) device. OBJECTIVE: In contrast to existing studies, this study is the first prospective interventional study using this new system in a cardiac surgical patient cohort. We will investigate the noninferiority between an already existing coagulation algorithm based on the ROTEM/Multiplate system and a new algorithm based on the Quantra system for the treatment of coagulopathic cardiac surgical patients. METHODS: The study is divided into two phases. In an initial observation phase, whole blood samples of 20 patients obtained at three defined time points (prior to surgery, after completion of cardiopulmonary bypass, and on arrival in the intensive care unit) will be analyzed using both the ROTEM/Multiplate and Quantra systems. The obtained threshold values will be used to develop a novel algorithm for hemotherapy. In a second intervention phase, the new algorithm will be tested for noninferiority against an algorithm used routinely for years in our department. RESULTS: The main objective of the examination is the cumulative loss of blood within 24 hours after surgery. Statistical calculations based on the literature and in-house data suggest that the new algorithm is not inferior if the difference in cumulative blood loss is <150 mL/24 hours. CONCLUSIONS: Because of the comparability of the Quantra sonorheometry system with the ROTEM measurement methods, the existing hemotherapy treatment algorithm can be adapted to the Quantra device with proof of noninferiority. TRIAL REGISTRATION: ClinicalTrials.gov NCT03902275; https://clinicaltrials.gov/ct2/show/NCT03902275. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/17206.

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)0.015
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.039
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.016
Meta-epidemiology (narrow)0.0050.002
Meta-epidemiology (broad)0.0110.004
Bibliometrics0.0020.002
Science and technology studies0.0020.003
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0390.005

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 head0.224
GPT teacher head0.525
Teacher spread0.301 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations2
Published2020
Admission routes1
Has abstractyes

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