Evidence map›Paper›PMID 36737795›Full record

ArticleBMC research notes2023

Erroneous detection of desensitization doses in the prevention of hypersensitivity reactions.

Razvan Costin Stan

Open access · goldAbstract read
In one paragraph

Article in BMC research notes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 99% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Razvan Costin StanDepartment of Biomedical Sciences, Chonnam National University, Seoyang-ro 264, Hwasun, 58128, South Korea. strazvan@jnu.ac.kr.
Chonnam National University Hwasun Hospital · KR

Funding

Korea National Research Foundation 2021R1I1A2059587
6 · The paper itself

Abstract

backgroundDesensitization protocols have empirically established their efficacy and safety in eliminating most of the hypersensitivity reactions to drugs and other allergens. Without such procedures, the offending drugs can otherwise be lethal, for some patients, when singularly administered at therapeutic doses. These binding events and the subsequent signaling cascades have been extensively modulated by different desensitization methods, without any clear explanation as to why it is necessary to use increasing allergen doses. PURPOSE: To use a novel theoretical approach in order to model the desensitization algorithms currently in practice, that seeks to shed light on the mechanism behind their clinical efficacy.

methodAn approach using signal processing concepts is applied in this work to introduce aliasing as the erroneous detection of higher drug doses responsible for the efficacy of desensitization procedures.

resultsAvailable experimental data is modeled and correct predictions as to the efficacy of the drug treatment procedures are produced.

conclusionsDesensitization algorithms may benefit from using concepts from signal processing theory in order to avoid hypersensitivity reactions.

Indexed as

Drug HypersensitivityHypersensitivityDesensitization, ImmunologicHumansAliasingAllergensDrug desensitizationIgESignal processing

Identifiers

PMID36737795
PMCPMC9898960
OpenAlexW4319079834

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.