Evidence map›Paper›PMID 42277941›Full record

ArticleJournal of cardiovascular imaging2026

Segmental strain in chronic ischemic cardiomyopathy: clarifying the role of multiple-comparison adjustment and the clinical interpretation of limits of agreement.

Maajid Mohi Ud Din Malik, Rajesh Prasad Jayaswal

Abstract readLetter
In one paragraph

Article in Journal of cardiovascular imaging, 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

2 authors.

Maajid Mohi Ud Din MalikDepartment of Radiology and Imaging Technology, Dr. D.Y. Patil School of Allied Health Sciences, Dr. D.Y. Patil Vidyapeeth (Deemed to Be University), Pune, 411018, India. maajid.malik@dpu.edu.in.
Rajesh Prasad JayaswalDepartment of Medical Laboratory Technology, University Institute of Allied Health Sciences, Chandigarh University, Mohali, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Khidr and colleagues recently reported an intermodality comparison of left ventricular longitudinal strain by feature-tracking cardiac magnetic resonance (FT-CMR) and 2D speckle-tracking echocardiography (2D-STE) in 55 stable patients with chronic ischemic heart disease and reduced ejection fraction. Their analysis showed a strong global longitudinal strain (GLS) correlation (r = 0.793, P < 0.001) and explicitly cautioned against treating the two modalities as interchangeable for individual or longitudinal assessment. We support these conclusions and write to extend two methodological points. First, the 17 segment-level paired comparisons in Table 4 are reported without explicit multiplicity adjustment. On recomputation against a Bonferroni threshold of α/17≈0.00294, 11 of 17 segmental differences remain statistically significant, indicating that the original segmental signal is more statistically robust than an unadjusted reader might assume; we therefore recommend explicit reporting of adjusted P-values together with a unified mixed-effects formulation that accommodates within-patient segment-to-segment correlation. Second, the GLS limits of agreement span 8.3 percentage points (- 3.2% to + 5.1%), a width sufficient to misclassify individual patients across established GLS thresholds. A worked example is provided, and the recommendation to confine longitudinal follow-up to a single platform is argued to deserve more prominent placement in the Abstract and Conclusions.

Indexed as

Data Interpretation, StatisticalEchocardiographyMagnetic Resonance Imaging, CineModels, StatisticalMyocardial IschemiaVentricular Function, Left

Identifiers

PMID42277941
PMCPMC13262300

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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.