Ventricular arrhythmia predicts poor outcome in polymyositis/dermatomyositis with myocardial involvement

Cluster analysis of clinical phenotypes in idiopathic inflammatory myopathy patients complicated with cardiac involvement

OBJECTIVE

This study aimed to classify idiopathic inflammatory myopathy (IIM) patients with cardiac involvement (IIM-CI) into different categories based on their clinical phenotypes via cluster analysis and to explore their differences in outcomes.

METHODS

IIM-CI patients admitted to Peking Union Medical College Hospital from January 2015 to June 2021 were retrieved. The clinical data, laboratory examinations, and treatment were retrospectively reviewed, and the outcome was traced. A second-order clustering method was employed for categorization.

RESULTS

A total of 88 IIM-CI patients were enrolled in this study and were classified into two categories through cluster analysis. Category I consisted of patients who exhibited distinct cardiac structural and functional changes, such as enlargement of atriums and/or ventricles, along with the remarkable heart insufficiency biomarkers, whereas patients of category II displayed more widely systemic injuries and intensive skeletal muscle weakness. In comparison, pulmonary hypertension (58.8% vs 16.7%, p < 0.01), arrhythmia (82.4% vs 27.8%, p < 0.01), and positive serum anti-mitochondrial-M2 antibody (52.9% vs 5.6%, p < 0.01) were more prevalent in category I than in category II, and serum N-terminal pro-B-type natriuretic peptide levels (1703.5 pg/L vs 364.0 pg/L, p = 0.02) were significantly elevated in category I, whereas skeletal muscle weakness (50.0% vs 74.1%, p = 0.02), interstitial lung disease (20.6% vs 63.0%, p < 0.01), skin rash (11.8% vs 48.1%, p < 0.01), arthralgia (2.9% vs 27.8%, p < 0.01), fever (2.9% vs 27.8%, p < 0.01), and dysphagia (2.9% vs 22.2%, p < 0.01) were more common in category II patients. Heart failure was the primary cause of death in category I, but severe pneumonia was predominantly responsible for deaths in category II.

CONCLUSION

Two categories of IIM-CI were identified based on clinical features with distinctive characteristics. Two categories exhibited differences in clinical manifestations, autoantibody profiles, and the primary cause of death.

An externally validated clinical-laboratory nomogram for myocardial involvement in adult idiopathic-inflammatory-myopathy patients

OBJECTIVES

This study aimed at identifying clinical and laboratory risk factors for myocardial involvement (MI) in idiopathic inflammatory myopathies (IIMs) patients as well as constructing a risk-predicted nomogram for prediction and early identification of MI.

METHODS

An IIMs cohort in southeastern China was constructed, including 504 adult IIMs patients who met the inclusion and exclusion criteria, and were hospitalized at four divisions of the First Affiliated Hospital, Zhejiang University School of Medicine from January 1st 2018 to April 30st 2022. After dividing patients into the training cohort and the validation cohort, risk factors for MI were identified through least absolute shrinkage and selection operator regression and multivariate logistic regression. A risk-predicted nomogram was established and validated internally and externally for discrimination, calibration and practicability.

RESULTS

In this cohort, 17.7% of patients developed MI and the survival was significantly inferior to that of IIMs patients without MI (P < 0.001). In the training cohort, age > 55 years old (P < 0.001), disease activity > 10 points (P < 0.001), interleukin-17A (IL-17A) > 7.5 pg/ml (P < 0.001), lactic dehydrogenase (LDH) > 425 U/L (P < 0.001), anti-mitochondrial antibodies (AMAs, P = 0.017), and anti-MDA5 antibody (P = 0.037) were significantly correlated with development of MI. A nomogram was established by including the above values to predict MI and was found efficient in discrimination, calibration, and practicability through internal and external validation.

CONCLUSION

This study developed and validated a nomogram model to predict the risk of MI in adult IIMs patients, which can benefit the prediction and early identification of MI as well as timely intervention in these patients.

Associations between anti-mitochondrial antibodies and cardiac involvement in idiopathic inflammatory myopathy patients : A systematic review and meta-analysis

OBJECTIVE

The objectives of this study are to analyze the association between anti-mitochondrial antibody (AMA) and cardiac involvement in idiopathic inflammatory myopathy (IIM) and to evaluate the diagnostic value of AMA for cardiac involvement in IIM patients.

METHODS

We conducted a comprehensive search in PubMed, Web of Science, EMBASE, and the Cochrane Library to identify English-language studies published before November 19, 2021. Stata 12.0 software (Stata Corp., College Station, TX, USA) was used for the statistical analyses. We used the sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and summary receiver operating characteristic (SROC) curve to evaluate the diagnostic value of AMA for cardiac involvement in IIM patients. Statistical heterogeneity of studies was assessed using the I2 statistic with 95% confidence intervals (95% CIs).

RESULTS

Seven studies were included in the final analyses, with a total of 2308 IIM patients (including 171 AMA-positive and 2137 AMA-negative patients). The pooled sensitivity of AMA for cardiac involvement in IIM patients was 0.29 (95% CI: 0.19-0.43) and specificity was 0.92 (95% CI: 0.88-0.96). The pooled PLR was 3.9 (95% CI: 2.82-5.38), NLR was 0.76 (95% CI: 0.66-0.88), and the diagnostic odds ratio (DOR) was 5 (95% CI: 3-7). The area under the SROC curve was 0.76 (95% CI: 0.72-0.79).

CONCLUSION

The overall diagnostic value of AMA may not be very high for cardiac involvement in IIM patients.

Cardiovascular manifestations in idiopathic inflammatory myopathies

Cardiovascular involvement in idiopathic inflammatory myopathies (IIM) is an understudied area which is gaining increasing recognition in recent times. Recent advances in imaging modalities and biomarkers have allowed the detection of subclinical cardiovascular manifestations in IIM. However, despite the availability of these tools, the diagnostic challenges and underestimated prevalence of cardiovascular involvement in these patients remain significant. Notably, cardiovascular involvement remains one of the leading causes of mortality in patients with IIM. In this narrative literature review, we outline the prevalence and characteristics of cardiovascular involvement in IIM. Additionally, we explore investigational modalities for early detection of cardiovascular involvement, as well as newer approaches in screening to facilitate timely management. Key points • Cardiac involvement in IIM in majority cases is subclinical and a major cause of mortality. • Cardiac magnetic resonance imaging is sensitive for detection of subclinical cardiac involvement.

Does Cardiac Arrhythmia Predict Worse Outcome in Mild or Moderate Covid-19 Infection?

Covid-19 is a multisystem disease with the lungs being predominantly affected. Cardiac involvement is mostly seen as a rise in troponins, arrhythmias, and ventricular dysfunction. This study aimed to estimate the incidence of arrhythmias seen in Covid-19 infection and assess if arrhythmias predict worsening or mortality. Prospective observational study involving patients with mild to moderate Covid illness admitted in a tertiary care centre. Among the 85 patients (Mean age 45.8 + 14.1 years; 75.31% men), worsening of Covid-19 illness was seen in 29 (34.1%) patients. New onset arrhythmias were detected on Holter in 9 (10.5%) patients. Supraventricular tachycardia was seen in 7 (8.2%) patients of whom 6 showed worsening which was statistically significant (p-value-0.006). Risk factors associated with worsening on univariate analysis were male gender (OR [95%CI] = 6.93(1.49-32.31), p-value - 0.014), new onset supraventricular tachycardia (OR [95% CI] = 14.35 [1.64-125.94], p-value - 0.016) and D-dimer elevation (OR [95% CI] = 1.00(1.00-1.01), p-value - 0.02). On multivariate analysis D-dimer (OR [95% CI] = 1.00(1.00-1.01; p-value 0.046) and supraventricular arrhythmias (OR [95% CI] = 11.12 (1.22-101.14); p-value - 0.033) were independently associated with worsening. Covid-19 infection can lead to cardiac arrhythmias. The development of supraventricular tachycardia in patients with Covid-19 infection predicts higher morbidity and worsening.

The clinical characteristics and outcomes of patients with systemic sclerosis with myocardial involvement

BACKGROUND

Myocardial involvement (MI) is the primary cause of death in patients with systemic sclerosis (SSc). We analyzed patients with SSc and MI to identify their characteristics and outcome.

METHOD

We retrospectively collected data from SSc patients with MI admitted to Peking Union Medical College Hospital between January 2012 and May 2021. SSc patients without MI were randomly selected as controls after matching age and gender at a ratio of 1:3.

RESULTS

In total, 21 SSc patients (17 females) with MI were enrolled. The mean age at SSc onset was 42.3 ± 15.1 years old. Compared with controls, myositis (42.9% vs. 14.3%, P = 0.014) and elevation of CK (33.3% vs. 4.8%, P = 0.002) were more common in patients with MI. Of the 7 patients without cardiovascular symptoms, 3 /5 showed elevations in cardiac troponin-I (cTnI), 6 showed elevations of N-terminal brain natriuretic peptide (NT-proBNP). Eleven patients were followed up for a median period of 15.5 months and four patients developed newly occurring left ventricular ejection fraction (LVEF) < 50%.

CONCLUSION

One third of SSc patients with MI were asymptomatic. Regular monitoring of CTnI, NT-proBNP and echocardiography is helpful for the diagnosis of MI during the early stages. Its prognosis is poor.

Online Automatic Diagnosis System of Cardiac Arrhythmias Based on MIT-BIH ECG Database

Arrhythmias are a relatively common type of cardiovascular disease. Most cardiovascular diseases are often accompanied by arrhythmias. In clinical practice, an electrocardiogram (ECG) can be used as a primary diagnostic tool for cardiac activity and is commonly used to detect arrhythmias. Based on the hidden and sudden nature of the MIT-BIH ECG database signal and the small-signal amplitude, this paper constructs a hybrid model for the temporal correlation characteristics of the MIT-BIH ECG database data, to learn the deep-seated essential features of the target data, combine the characteristics of the information processing mechanism of the arrhythmia online automatic diagnosis system, and automatically extract the spatial features and temporal characteristics of the diagnostic data. First, a combination of median filter and bandstop filter is used to preprocess the data in the ECG database with individual differences in ECG waveforms, and there are problems of feature inaccuracy and useful feature omission which cannot effectively extract the features implied behind the massive ECG signals. Its diagnostic algorithm integrates feature extraction and classification into one, which avoids some bias in the feature extraction process and provides a new idea for the automatic diagnosis of cardiovascular diseases. To address the problem of feature importance variability in the temporal data of the MIT-BIH ECG database, a hybrid model is constructed by introducing algorithms in deep neural networks, which can enhance its diagnostic efficiency.