Evidence map›Paper›PMID 33244882›Full record

ArticleESC heart failure2021

Identifying different phenotypes in takotsubo cardiomyopathy by latent class analysis.

Pengyang Li, Qiying Dai, Peng Cai, Catherine Teng, Su Pan, Richard A F Dixon, Qi Liu

Abstract read
In one paragraph

Article in ESC heart failure, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Takotsubo syndrome and chaos theory.European heart journal. Case reports · 2023
    Article
  6. Article
  7. "Obesity paradox" and takotsubo syndrome.International journal of cardiology. Cardiovascular risk and prevention · 2022
    Review
  8. Article
  9. Review
  10. Article
  11. Article
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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

7 authors.

Pengyang LiDepartment of Medicine, Saint Vincent Hospital, Worcester, MA, USA.
Qiying DaiDivision of Cardiology, Saint Vincent Hospital, Worcester, MA, USA.
Peng CaiDepartment of Mathematical Sciences, Worcester Polytechnic Institute, Worcester, MA, USA.
Catherine TengDepartment of Medicine, Greenwich Hospital, Greenwich, CT, USA.
Su PanWafic Said Molecular Cardiology Research Laboratory, Texas Heart Institute, 6770 Bertner Avenue, MC-255, Houston, TX, 77030, USA.
Richard A F DixonWafic Said Molecular Cardiology Research Laboratory, Texas Heart Institute, 6770 Bertner Avenue, MC-255, Houston, TX, 77030, USA.
Qi LiuWafic Said Molecular Cardiology Research Laboratory, Texas Heart Institute, 6770 Bertner Avenue, MC-255, Houston, TX, 77030, USA.ORCID 0000-0001-7716-1417

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsThis study sought to determine whether clinical clusters exist in takotsubo cardiomyopathy. Takotsubo cardiomyopathy (TCM) is a heterogeneous disorder with a complex, poorly understood pathogenesis. To better understand the heterogeneity of TCM, we identified different clinical phenotypes in a large sample of TCM patients by using latent class analysis (LCA). METHODS AND

resultsUsing the National Inpatient Sample (NIS) database, we identified 3139 patients admitted to hospitals in 2016-2017 with a primary diagnosis of TCM. We performed LCA based on several patient demographics and comorbidities: age, sex, hypertension, hyperlipidaemia, diabetes mellitus, obesity, current smoking, asthma, chronic obstructive pulmonary disease (COPD), and anxiety and depressive disorders. We then repeated LCA separately with the NIS 2016 and 2017 data sets and performed a robust test to validate our results. We also compared in-hospital outcomes among the different clusters identified by LCA. Four patient clusters were identified. C1 (n = 1228, 39.4%) had the highest prevalence of hyperlipidaemia (93.4%), hypertension (61.6%), and diabetes (34.3%). In C2 (n = 440, 14.0%), all patients had COPD, and many were smokers (45.8%). C3 (n = 376, 11.8%) largely comprised patients with anxiety disorders (98.4%) and depressive disorders (80.1%). C4 (n = 1097, 34.8%) comprised patients with isolated TCM and few comorbidities. Among all clusters, C1 had the lowest in-hospital mortality (1.0%) and the shortest length of stay (3.2 ± 3.1 days), whereas C2 had the highest in-hospital mortality (3.4%).

conclusionsUsing LCA, we identified four clinical phenotypes of TCM. These may reflect different pathophysiological processes in TCM. Our findings may help identify treatment targets and select patients for future clinical trials.

Indexed as

Takotsubo CardiomyopathyComorbidityHospital MortalityHumansLatent Class AnalysisPhenotypeLatent class analysisPhenotypeTakotsubo cardiomyopathy

Identifiers

PMID33244882
PMCPMC7835582

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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.