Evidence map›Paper›PMID 39450216›Full record

ReviewCureus2024

N-acetylcysteine Clinical Applications.

Zoubaida Yahia, Amer Yahia, Tarek Abdelaziz

Abstract readReview
In one paragraph

Review in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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

3 authors.

Zoubaida YahiaGeneral Practice, Wrightington, Wigan and Leigh NHS Foundation Trust, Wigan, GBR.
Amer YahiaMedical Assessment Unit, Royal Derby Hospital, Derby, GBR.
Tarek AbdelazizAcute Medicine, Blackpool Victoria Hospital, Blackpool, GBR.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to evaluate the therapeutic application of N-acetylcysteine (NAC) as a treatment or adjunct therapy for various medical conditions. While its efficacy in treating acetaminophen overdose, cystic fibrosis, and chronic obstructive pulmonary disease is well-established, emerging evidence suggests that NAC may also benefit a broader spectrum of illnesses due to its safety, simplicity, and affordability. A comprehensive review was conducted by searching PubMed, relevant books, and conference proceedings for publications discussing NAC about the specified health conditions. The clinically relevant data were analysed using the American Family Physician Evidence-Based Medicine Toolkit, following a standard integrated review methodology. NAC shows potential as an adjunctive treatment for a wide range of medical conditions, particularly chronic diseases. It may be beneficial for polycystic ovary syndrome, endometriosis, male infertility, cataracts, glaucoma, dry eye syndrome, parkinsonism, multiple sclerosis, Alzheimer's disease, stroke outcomes, non-acetaminophen-induced acute liver failure, Crohn's disease, ulcerative colitis, schizophrenia, bipolar disorder, and obsessive-compulsive disorder. Although evidence for some conditions is less robust, NAC's therapeutic potential warrants further investigation. Given the aging population and the decline in glutathione levels, the use of NAC should be considered across a variety of medical conditions. This paper suggests that NAC supplementation could play a significant role in reducing morbidity and mortality associated with numerous chronic diseases.

Indexed as

adjunct therapycataractschronic diseasesendometriosisglaucomamale infertilityn-acetylcysteineneurodegenerative diseasespolycystic ovary syndromepsychiatric disorders

Identifiers

PMID39450216
PMCPMC11499967

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.