Evidence map›Paper›PMID 35165601›Full record

ArticleCureus2022

Decision-Making Dilemma in Preoperative Cardiac Evaluation: Should We Turn the Page or Close the Book?

Shikha Jha

Open access · diamondAbstract readCase Reports
In one paragraph

Article in Cureus, 2022. 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 100% 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

1 author at 1 institution in 1 country.

Shikha JhaInternal Medicine, Saint Peter's University Hospital, New Brunswick, USA.
Saint Peter's University Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coronary artery disease is one of the most dreadful and life-threatening diseases out of all cardiac diseases. The diagnosis and management of coronary artery disease comprise stepwise approaches. All these approaches are mostly guideline-driven. While the majority of the time, guidelines help us take the most appropriate care, exceptions do exist. For example, patients may have unusual risk factors and abnormal test results; however, they do not fit into the guideline algorithm to proceed further.  This case report of a 68-year-old male patient depicts a true example of such a situation. He presented to the cardiologist's office for pre-operative cardiac evaluation for urological surgery. In view of associated risk factors, an exercise stress test was done, which showed critical abnormalities. As per the pre-operative cardiac assessment guidelines, the patient did not meet the criteria for further testing. However, a clinician's strong judgment and persistent negotiation superseded those barriers. Given critical abnormalities of the exercise stress test, the patient underwent cardiac catheterization. He was found to have triple vessel disease on cardiac catheterization. The scheduled surgery was withheld, and the patient underwent a coronary artery bypass graft. This life-threatening condition could have been easily missed if only the guidelines were to be followed. While guidelines cover a significant portion of the bell curve, this case report represents the importance of not missing the tail ends of the curve. It enhances the importance of thinking out of the box based on clinical training and expertise.

Indexed as

cardiac clearancecoronary artery angiogramcoronary artery bypass graft surgerydisease risk assessmentexercise stress testmultivessel coronary artery disease (mvcad)pre operative

Identifiers

PMID35165601
PMCPMC8831317
OpenAlexW4205463188

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.