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Record W4226424068 · doi:10.1186/s13063-022-06219-7

A multicenter, open-label, randomized, proof-of-concept phase II clinical trial to assess the efficacy and safety of icatibant in patients infected with SARS-CoV-2 (COVID-19) and admitted to hospital units without invasive mechanical ventilation: study protocol (ICAT-COVID)

2022· article· en· W4226424068 on OpenAlexfundno aff
Pierre Malchair, Aurema Otero, Jordi Giol, Xavier Solanich, Thiago Carnaval, Alonso Fernández-Nistal, Ana Sánchez-Gabriel, Carmen Montoto, Ramón Lleonart, Sebastián Videla, Arnau Antolí, M Benjumeda, Tania Bernal, Laura Calatayud, Xavier Corbella, Anna Ferrer, Vanesa García‐Barberán, Mercè Gasa, Carlota Gudiol, Pilar Hereu, Javier Jacob, Hector Ignacio Jofré, Ferrán Llopis, Leire Matellán, Natàlia Pallarés, Raül Rigo‐Bonnin, Gemma Rocamora, Freddy Rodríguez, Alexander Rombauts, José Carlos Ruibal, Joan Sabater‐Riera, Carmen Serrano, Ana Suárez-Lledó, Cristian Tebé, Jesús Villoria, Alvaro Zarauza

Bibliographic record

VenueTrials · 2022
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsnot available
FundersUniversitat de BarcelonaCentres de Recerca de CatalunyaGeneralitat de CatalunyaCanadian Institute for Theoretical Astrophysics
KeywordsMedicineIcatibantRandomized controlled trialRandomizationCytokine stormClinical trialInternal medicineOff-label usePneumoniaCoronavirus disease 2019 (COVID-19)Intensive care medicineInfectious disease (medical specialty)BradykininDisease

Abstract

fetched live from OpenAlex

BACKGROUND: COVID-19 has quickly become a global pandemic with a substantial number of deaths and is a considerable burden for healthcare systems worldwide. Although most cases are paucisymptomatic and limited to the viral infection-related symptoms, some patients evolve to a second phase, with an impaired inflammatory response (cytokine storm) that may lead to acute respiratory distress syndrome and death. This is thought to be caused by increased bradykinin synthesis. METHODS: ICAT-COVID is a multicenter, randomized, open-label, proof-of-concept phase II clinical trial assessing the clinical efficacy and safety of adding icatibant to the standard of care in patients hospitalized with COVID-19 without invasive mechanical ventilation. Patients hospitalized with a confirmed COVID-19 pneumonia diagnosis (RT-PCR or antigen test ≤ 10 days prior to randomization, and radiographic evidence of pulmonary infiltrates), rated "4" or "5" on the WHO's clinical status scale, are eligible. Patients will be randomized on a 1:1 ratio to either standard of care-plus-icatibant (experimental group) or to standard of care alone (control group). The experimental group will receive 30 mg of icatibant subcutaneously 3 times a day for 3 days (for a total of 9 doses). The expected sample size is 120 patients (60 per group) from 2 sites in Spain. Primary outcomes are the efficacy and safety of Icatibant. The main efficacy outcome is the number of patients reaching grades "2" or "1" on the WHO scale within 10 days of starting treatment. Secondary outcomes include "long-term efficacy": number of patients discharged who do not present COVID-19-related relapse or comorbidity up until 28 days after discharge, and mortality. DISCUSSION: Icatibant, a bradykinin type 2 receptor antagonist with proven effectiveness and safety against hereditary angioedema attacks, may be beneficial for COVID-19 patients by inhibiting bradykinin's action on endothelial cells and by inhibiting the SARS-CoV-2 M protease. Our working hypothesis is that treatment with standard of care-plus-icatibant is effective and safe to treat patients infected with SARS-CoV-2 admitted to hospital for pneumonia without invasive mechanical ventilation. TRIAL REGISTRATION: EudraCT 2020-002166-13. CLINICALTRIALS: gov NCT04978051.

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)0.005
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0110.002

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 head0.402
GPT teacher head0.573
Teacher spread0.172 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

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