Dataset Information

Heart rate as an early predictor of severe cardiomyopathy and increased mortality in peripartum cardiomyopathy.

ABSTRACT:

Background

Delays in diagnosis of peripartum cardiomyopathy (PPCM) are common and are associated with worse outcomes; however, few studies have addressed methods for improving early detection.

Hypothesis

We hypothesized that easily accessible data (heart rate [HR] and electrocardiograms [ECGs]) could identify women with more severe PPCM and at increased risk of adverse outcomes.

Methods

Clinical data, including HR and ECG, from patients diagnosed with PPCM between January 1998 and July 2016 at our institution were collected and analyzed. Linear and logistic regression were used to analyze the relationship between HR at diagnosis and the left ventricular ejection fraction (LVEF) at diagnosis. Outcomes included overall mortality, recovery status, and major adverse cardiac events.

Results

Among 82 patients meeting inclusion criteria, the overall mean LVEF at diagnosis was 26 ± 11.1%. Sinus tachycardia (HR > 100) was present in a total of 50 patients (60.9%) at the time of diagnosis. In linear regression, HR significantly predicted lower LVEF (F = 30.00, p < .0001). With age-adjusted logistic regression, elevated HR at diagnosis was associated with a fivefold higher risk of overall mortality when initial HR was >110 beats per minute (adjusted odds ratio 5.35, confidence interval 1.23-23.28), p = .025).

Conclusion

In this study, sinus tachycardia in women with PPCM was associated with lower LVEF at the time of diagnosis. Tachycardia in the peripartum period should raise concern for cardiomyopathy and may be an early indicator of adverse prognosis.

SUBMITTER: Cooney R

PROVIDER: S-EPMC8860487 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Publications

Heart rate as an early predictor of severe cardiomyopathy and increased mortality in peripartum cardiomyopathy.

Cooney Ryan R Scott John R JR Mahowald Madeline M Langen Elizabeth E Sharma Garima G Kao David P DP Davis Melinda B MB

Clinical cardiology 20220207 2

<h4>Background</h4>Delays in diagnosis of peripartum cardiomyopathy (PPCM) are common and are associated with worse outcomes; however, few studies have addressed methods for improving early detection.<h4>Hypothesis</h4>We hypothesized that easily accessible data (heart rate [HR] and electrocardiograms [ECGs]) could identify women with more severe PPCM and at increased risk of adverse outcomes.<h4>Methods</h4>Clinical data, including HR and ECG, from patients diagnosed with PPCM between January 1 ...[more]

PMID: 35129215

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Project description:BackgroundAutonomic dysregulation is one of the recognized pathophysiological mechanisms in sepsis, generating the hypothesis that heart rate variability (HRV) can be used to predict mortality in sepsis.MethodsThis was a systematic review of studies evaluating HRV as a predictor of death in patients with sepsis. The search was performed by independent researchers in PubMed, LILACS and Cochrane, including papers in English, Portuguese or Spanish, indexed until August 20th, 2017 with at least 10 patients. Study quality was assessed by Newcastle-Ottawa Scale. To analyze the results, we divided the articles between those who measured HRV for short-term recordings (≤ 1 hour), and those who did long-term recordings (≥ 24 hours).ResultsNine studies were included with a total of 536 patients. All of them were observational studies. Studies quality varied from 4 to 7 stars in Newcastle-Ottawa Scale. The mortality rate in the studies ranged from 8 to 61%. Seven studies performed HRV analysis in short-term recordings. With the exception of one study that did not explain which group had the lowest results, all other studies showed reduction of several HRV parameters in the non-survivors in relation to the surviving septic patients. SDNN (Standard deviation of the Normal to Normal interval), TP (Total Power), VLF (Very Low Frequency Power), LF (Low Frequency Power), LF/HF (Low Frequency Power / High Frequency Power), nLF (Normalized Low Frequency Power), α1/α2 (short-term and long-term fractal scaling coefficients from DFA) and r-MSSD (Square root of the squared mean of the difference of successive NN-intervals) of the non-survivor group were reduced in relation to the survivors in at least one study. Two studies found that SDNN is associated with mortality in sepsis, even after adjusting for possible confounding factors. Three studies performed HRV analysis using long-term recordings. Only one of these studies found difference between surviving and non-surviving groups, and even so, in only one HRV parameter: LogHF.ConclusionsSeveral HRV parameters are reduced in nonsurviving septic patients in short-term recording. Two studies have found that SDNN is associated with mortality in sepsis, even after adjusting for possible confounding factors.

Project description:AIMS:Heart failure is a syndrome with increasing prevalence in concordance with the aging population and better survival rates from myocardial infarction. Morbidity and mortality are high in chronic heart failure patients, particularly in those with hospital admission for acute decompensation. Several risk stratification tools and score systems have been established to predict mortality in chronic heart failure patients. However, identification of patients at risk with easy obtainable clinical factors that can predict mortality in acute decompensated heart failure (ADHF) are needed to optimize the care-path. METHODS AND RESULTS:We retrospectively analyzed electronic medical records of 78 patients with HFrEF and HFmrEF who were hospitalized with ADHF in the Heart Center of the University Hospital Cologne in the year 2011 and discharged from the ward after successful treatment. 37.6?±?16.4 months after index hospitalization 30 (38.5%) patients had died. This mortality rate correlated well with the calculated predicted survival with the Seattle Heart Failure Model (SHFM) for each individual patient. In our cohort, we identified elevated heart rate at discharge as an independent predictor for mortality (p?=?0.016). The mean heart rate at discharge was lower in survived patients compared to patients who died (72.5?±?11.9 vs. 79.1?±?11.2 bpm. Heart rate of 77 bpm or higher was associated with an almost doubled mortality risk (p?=?0.015). Heart rate elevation of 5 bpm was associated with an increase of mortality of 25% (p?=?0.022). CONCLUSIONS:Patients hospitalized for ADHF seem to have a better prognosis, when heart rate at discharge is?<?77 bpm. Heart rate at discharge is an easily obtainable biomarker for risk prediction of mortality in HFrEF and HFmrEF patients treated for acute cardiac decompensation. Taking into account this parameter could be useful for guiding treatment strategies in these high-risk patients. Prospective data for validation of this biomarker and specific intervention are needed.

Dataset Information

Heart rate as an early predictor of severe cardiomyopathy and increased mortality in peripartum cardiomyopathy.

Background

Hypothesis

Methods

Results

Conclusion

Publications

Heart rate as an early predictor of severe cardiomyopathy and increased mortality in peripartum cardiomyopathy.

Similar Datasets

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