Evidence map›Paper›PMID 37601995›Full record

ReviewCureus2023

The Effects of Anti-platelets and Micronutrients in the Recovery of COVID-19 Patients: A Review.

Gurmeet Singh, Nova Fauzi

Open access · diamondAbstract readReview
In one paragraph

Review in Cureus, 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 87% 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

2 authors at 1 institution in 1 country.

Gurmeet SinghInternal Medicine, Respirology, and Critical Illness, Universitas Indonesia, Jakarta, IDN.
Nova FauziInternal Medicine, Respirology, and Critical Illness, Universitas Indonesia, Jakarta, IDN.
University of Indonesia · ID

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 or coronavirus disease is a pneumonia-like condition caused by the SARS-CoV2 virus. Many mutations of this virus have emerged throughout the two-year period of this pandemic. However, clinical presentations, diagnostic methods, and treatment of COVID-19 remain relatively unchanged. Various substances have been assessed for their functions as COVID-19 immunomodulators. Said substances in this article include aspirin, vitamin C, vitamin D3, zinc, and selenium. Aspirin was found to reduce mortality risk and embolism events. Vitamin C did not seem to improve mechanical ventilation-free days but did improve oxygenation (PaO2/FiO2), peripheral capillary oxygen saturation (SpO2), and body temperature in severe COVID-19 patients. Vitamin D3 was not significantly different compared to placebo in improving mortality in hospitalized patients. However, respiratory tract infection (COVID-19 included) events were lower in individuals given vitamin D3 compared to those who were not. Zinc combined with ascorbic acid caused a quick reduction in symptoms but was not significant compared to zinc alone, ascorbic acid alone, or standard care. Individuals with lower levels of selenium were found to have worse outcomes of COVID-19 compared to those with high levels of selenium. However, further studies, especially clinical trials, are needed. Asprinol is a drug that contains vitamins and minerals plus aspirin which are suggested to help alleviate symptoms and improve outcomes of COVID-19. This review aims to assess the efficacy of asprinol contents in COVID-19 patients.

Indexed as

aspirinasprinolcovid-19micronutrientsrecovery

Identifiers

PMID37601995
PMCPMC10439304
OpenAlexW4384931513

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.