Evidence map›Paper›PMID 32819038›Full record

ArticleHealthcare informatics research2020

Identifying a Personalized Anesthetic with Fuzzy PROMETHEE.

Ilker Ozsahin

Open access · goldAbstract read
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Article in Healthcare informatics research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
3.0field-weighted citation impact, top 8% 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

6 citing papers in PubMed, 16 citations in OpenAlex.

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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 2 countries.

Ilker OzsahinDepartment of Biomedical Engineering, Faculty of Engineering, Near East University, Nicosia/TRNC, Mersin, Turkey.
Mersin Üniversitesi · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveDuring an anesthetic evaluation, the individual's medical history and overall fitness for the whole medical procedure should be carefully examined. The objective of this study was to apply a multi-criteria decision-making technique to determine the proper anesthetic agent for specific patients.

methodsThe fuzzy PROMETHEE (Preference Ranking Organization Method for Enrichment of Evaluations) method was applied to determine the most appropriate agent. Minimum alveolar concentration, blood:gas and oil:gas partition coefficients, onset of action, recovery time, duration, induction and maintenance doses, and washout time were used as the criteria for the analysis. After defining the values of each criteria, the criteria weights and the preference function were set, and finally the results for two different examples, one for general ranking and one for a specific individual were obtained.

resultsThe results show that nitrous oxide and xenon are among the preferred inhaled anesthetics in the ranking of the inhaled anesthetics, whereas midazolam was identified as the preferred injected agent. When the weights are selected according to a specific patient's condition, namely a 70-year-old woman to undergo an emergent laparoscopic appendectomy with comorbidities, including severe chronic obstructive pulmonary disease as a consequence of a life-long smoking habit, morbid obesity, and type II diabetes, the results changed significantly. In this case, desflurane and etomidate come first in the ranking of inhaled and injected anesthetics, respectively, while nitrous oxide is the least preferred anesthetic agent.

conclusionExpert opinion is always needed. Assigning weights to criteria and grading alternatives are the major challenges in multi-criteria decision-making studies. Fuzzy PROMETHEE is proposed to solve a multi-criteria decision-making problem in selecting a general anesthetic.

Indexed as

Anesthetic AgentsClinical Decision-MakingGeneral AnesthesiaNitrous OxideXenon

Identifiers

PMID32819038
PMCPMC7438688
OpenAlexW3048896005

What OpenQuestion holds

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Registered trials

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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.