Evidence map›Paper›PMID 41882681›Full record

ArticlePerioperative medicine (London, England)2026

Towards routine monitoring for myocardial injury after noncardiac surgery.

Dushanthi Dissanayake, Su-Yin MacDonell, P J Devereaux, Janny Xue Chen Ke

Abstract readLetter
In one paragraph

Article in Perioperative medicine (London, England), 2026. 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
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.

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

4 authors.

Dushanthi DissanayakeDepartment of Anesthesia, Pain Management & Perioperative Medicine, Dalhousie University, Halifax, Canada.
Su-Yin MacDonell *Department of Anesthesiology, Pharmacology & Therapeutics, Faculty of Medicine, The University of British Columbia, Vancouver, BC, Canada.
P J Devereaux *Department of Health Evidence and Impact and Department of Medicine, McMaster University, Hamilton, Canada.
Janny Xue Chen KeDepartment of Anesthesia, Pain Management & Perioperative Medicine, Dalhousie University, Halifax, Canada. janny.ke@ubc.ca.ORCID http://orcid.org/0000-0002-3121-9780

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Myocardial injury after noncardiac surgery (MINS) occurs in approximately 13% of adults ≥ 45 years of age who undergo major inpatient noncardiac surgery and is associated with an increased risk of 30-day and 1-year mortality. Routine perioperative troponin monitoring is needed to avoid missing the majority of MINS events. Although there are challenges to the implementation of MINS surveillance, there has been enormous growth in the uptake of MINS monitoring across Canadian centres. In this paper, we explore challenges to routine screening for MINS and strategies to overcome them. The key challenges were stratifying who to monitor, management strategies and outcomes requiring further research, and resource limitations. Several groups have documented high uptake of perioperative troponin monitoring at centres that have established institutional protocols. Strategies to facilitate implementation of the MINS guidelines include multidisciplinary collaboration, standardized clinical pathways, and audit and feedback. Implementation of a routine MINS monitoring program requires concerted multidisciplinary effort throughout the perioperative period, encompassing the preadmission clinic, postoperative wards, and outpatient clinics.

Indexed as

ImplementationMyocardial injury after noncardiac surgeryPerioperative medicineTroponin

Identifiers

PMID41882681
PMCPMC13014797

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.