Evidence map›Paper›PMID 33961122›Full record

ReviewCurrent cardiology reports2021

Invasive Therapies for Acute Coronary Syndromes in the COVID-19 Era.

Sanket Borgaonkar, Joshua Hahn, Marilyne Daher, Waleed Kayani, Hani Jneid

Open access · bronzeAbstract readReview
In one paragraph

Review in Current cardiology reports, 2021. 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 94% 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

5 authors at 2 institutions in 1 country.

Sanket BorgaonkarDivision of Cardiology, Baylor College of Medicine, Houston, TX, USA.
Joshua HahnDivision of Cardiology, Baylor College of Medicine, Houston, TX, USA.
Marilyne DaherDivision of Cardiology, Baylor College of Medicine, Houston, TX, USA.
Waleed KayaniDivision of Cardiology, Baylor College of Medicine, Houston, TX, USA.
Hani JneidDivision of Cardiology, Baylor College of Medicine, Houston, TX, USA. Jneid@bcm.edu.ORCID http://orcid.org/0000-0002-8754-358X
Baylor College of Medicine · USMichael E. DeBakey VA Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewTo identify and address the challenges associated with the care of ACS patients during the coronavirus 2019 pandemic. RECENT

findingsThe COVID-19 pandemic has had a considerable global impact with over 2.0 million deaths worldwide so far. There has been considerable evidence suggesting that COVID-19 increases the risk of acute coronary syndromes (ACS). We propose characterizing ACS patients into 3 distinct categories to better assist in appropriate triage and management: critically ill patients, non-critically ill ST elevation myocardial infarction (STEMI) patients, and non-critically ill non-ST elevation myocardial infarction (NSTEMI)/unstable angina (UA) patients. We thoroughly review treatments strategies, management considerations, and current consensus statements for the care of COVID-19 patients with ACS. As we continue to gain more experience with management of COVID-19 in ACS patients and as health-care workers and patients continue to get vaccinated, we must continue to adapt our strategies to treat this high-risk group of patients.

Indexed as

Acute Coronary SyndromeCOVID-19Non-ST Elevated Myocardial InfarctionHumansPandemicsSARS-CoV-2Acute coronary syndromeCardiac catheterizationCOVID-19Health personnelPersonal protective equipmentST elevation myocardial infarction

Identifiers

PMID33961122
PMCPMC8102148
OpenAlexW3157922615

What OpenQuestion holds

Textmetadata
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.