Evidence map›Paper›PMID 36685426›Full record

ArticleHeliyon2023

Mostafa Hemmati, Hadi Tabesh, Ali Peyghambari, Hamidreza Bazrafshan

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 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
0.2field-weighted citation impact, top 47% 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, 1 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

4 authors at 2 institutions in 2 countries.

Mostafa HemmatiDepartment of Life Science Engineering, Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran.
Hadi TabeshDepartment of Life Science Engineering, Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran.
Ali PeyghambariDepartment of Life Science Engineering, Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran.
Hamidreza BazrafshanLMU Klinikum, Ludwig Maximilian University of Munich, Munich, Germany.
University of Tehran · IRLMU Klinikum · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Thyroid hormone replacement therapy is used to raise undesirably low concentrations of natural thyroid hormones, commonly by administrating levothyroxine (LT4). Finding the appropriate LT4 dose regime, particularly for patients undergone thyroidectomy, is still demanding more effort, and much research has been conducted. Providing a new fuzzy logic system, a useful control algorithm, we aim to introduce a proper LT4 dosing regimen for every thyroidectomized patient in a computerized environment. Consequently, we contrast the differences between our proposed dose regime and conventional monotherapy methods using THYROSIM, a thyroid simulation application. Considering our nine defined comparative criteria, results reveal that the FLS dose regime is dominant in terms of six indexes, while the discrepancies are not noticeable in the other three indexes. A great superiority of FLS dose regime is its ability to reduce the time to reach desirable thyrotropin (Thyroid Stimulating Hormone, TSH) serum concentration to 6 days post-thyroidectomy, and keep the T4, T3, and TSH values in the normal window afterward. The proposed FLS could be an applicable decision support system for physicians as they can define their intended Individual Target Value of TSH for each patient to optimize LT4 dose adjustment.

Indexed as

Fuzzy logic systemLevothyroxinePersonalized dose adjustmentThyroidTotal thyroidectomy

Identifiers

PMID36685426
PMCPMC9852674
OpenAlexW4313550052

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.