Relationship Between Exercise Oscillatory Ventilation Loop and Prognosis of Heart Failure

Nakade, Taisuke; Adachi, Hitoshi; Murata, Makoto

doi:10.1253/circj.cj-18-1047

Cited by 8 publications

(7 citation statements)

References 32 publications

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“…In subjects with heart failure, Arena et al (2008) reported that patients with the largest ventilatory oscillation during the first half of exercise had significantly poorer prognoses and higher risk of cardiac events (Arena et al 2008). Nakade et al (2019) plotted and quantified the loop size of V  E versus end tidal partial pressure for CO 2 ; a larger loop was associated with cardiovascular death in heart failure patients (Nakade et al 2019). Quantification of EOV characteristics can provide useful information that may be neglected by a binary definition of EOV (Castro et al 2017).…”

Section: Discussionmentioning

confidence: 99%

“…Some individuals may exhibit oscillatory breathing patterns that are abnormal but do not comply with any established criteria of EOV and are therefore neglected by a binary approach (Castro et al 2017). Furthermore, large ventilatory oscillations occurring at low exercise intensity (Arena et al 2008) and greater magnitude ventilatory oscillations (Nakade et al 2019) are associated with worse prognosis; this suggests that a method of quantifying the degree of EOV may provide additional prognostic information. EOV by current definitions may represent the abnormal extreme of a more insidious process characterized by a chronic deterioration of ventilatory control (Castro et al 2017).…”

Section: Introductionmentioning

confidence: 99%

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Novel application of Poincaré analysis to detect and quantify exercise oscillatory ventilation

et al. 2021

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Objective. Exercise oscillatory ventilation (EOV) is frequently observed in individuals with cardiac disease. Assessment of EOV relies on pattern recognition and this subjectivity and lack of quantification limits the widespread clinical use of EOV as a prognostic marker. Poincaré analysis quantifies the short (SD1) and long-term (SD2) variability of a signal and may provide an alternative means to identify and quantify unstable exercise breathing patterns. This study aimed to determine if Poincaré analysis can distinguish between the breathing patterns of healthy control subjects and individuals being assessed for heart transplantation with and without EOV. Approach. Thirty-nine subjects performed a cardiopulmonary exercise test as part of heart transplant assessment and were subjectively classified into two groups according to the presence of EOV: non-EOV (n = 19) and EOV (n = 20). The control group (n = 24) consisted of healthy adults. Poincaré analysis (SD1 and SD2) was performed for minute ventilation ( V ̇ E) and tidal volume (VT) normalized to forced vital capacity ( V ̇ En and V ̇ Tn ), and breathing frequency (BF) for breath-by-breath data over the 10–15 ml · min−1 · kg−1 V ̇ O2 range. Main results. Poincaré analysis showed similar exercise ventilatory responses between the non-EOV and control group. BF was found to discriminate between subjects with stable and unstable ventilation. BF SD1 was significantly higher in the EOV group compared to the non-EOV (7.9 versus 4.6, p < 0.01) and control (7.9 versus 4.2, p < 0.01) groups. The EOV group had significantly greater BF SD2 compared to the non-EOV (5.7 versus 3.5, p < 0.01) and control (5.7 versus 3.5, p < 0.01) groups. Significance. We demonstrated that this novel application of Poincaré analysis can objectively distinguish and quantify unstable from stable breathing patterns during exercise. In subjects being assessed for heart transplantation the presence of EOV is associated with greater BF variability. Poincaré analysis provides an objective measure to identify and quantify EOV. Summary at a glance. As EOV may indicate abnormal ventilatory control, there is a need for an objective measure to identify and quantify unstable from stable ventilation during exercise. We developed a method of quantifying BF variation by the application of Poincaré analysis and demonstrated higher than normal variability of BF in subjects being assessed for heart transplantation who demonstrated EOV.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Novel application of Poincaré analysis to detect and quantify exercise oscillatory ventilation

et al. 2021

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“…In addition, according to severity, heart failure can be divided into acute heart failure and chronic heart failure. 2 …”

Section: Introductionmentioning

confidence: 99%

“…Heart failure can be classified into left heart failure, right heart failure or whole heart failure depending on its location. In addition, according to severity, heart failure can be divided into acute heart failure and chronic heart failure 2…”

Section: Introductionmentioning

confidence: 99%

Early prediction of in-hospital mortality in patients with congestive heart failure in intensive care unit: a retrospective observational cohort study

Han

Zhang

et al. 2022

BMJ Open

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ObjectiveCongestive heart failure (CHF) is a clinical syndrome in which the heart disease progresses to a severe stage. Early diagnosis and risk assessment of death of patients with CHF are critical to prognosis and treatment. The purpose of this study was to establish a nomogram that predicts the in-hospital death of patients with CHF in the intensive care unit (ICU).DesignA retrospective observational cohort study.Setting and participantsData for the study were from 30 411 patients with CHF in the Medical Information Mart for Intensive Care database and the eICU Collaborative Research Database (eICU-CRD).Primary outcomeIn-hospital mortality.MethodsUnivariate logistic regression analysis was used to select risk factors associated with in-hospital mortality of patients with CHF, and multivariate logistic regression was used to build the prediction model. Discrimination, calibration and clinical validity of the model were evaluated by AUC, calibration curve, Hosmer-Lemeshow χ2 test and decision curve analysis, respectively. Finally, data from 15 503 patients with CHF in the multicentre eICU-CRD were used for external validation of the established nomogram.ResultsThe inclusion criteria were met by 15 983 subjects, whose in-hospital mortality rate was 12.4%. Multivariate analysis determined that the independent risk factors were age, race, norepinephrine, dopamine, phenylephrine, vasopressin, mechanical ventilation, intubation, hepatic failure (HepF), heart rate, respiratory rate, temperature, systolic blood pressure (SBP), anion gap (AG), blood urea nitrogen (BUN), creatinine, chloride, mean corpuscular volume (MCV), red blood cell distribution width (RDW) and white cell count (WCC). The C-index of the nomogram (0.767, 95% CI 0.759 to 0.779) was superior to that of the traditional Sequential Organ Failure Assessment, Acute Physiology Score III and Get With The Guidelines Heart Failure scores, indicating its discrimination power. Calibration plots demonstrated that the predicted results are in good agreement with the observed results. The decision curves of the derivation and validation sets both had net benefits.ConclusionThe 20 independent risk factors for in-hospital mortality of patients with CHF were age, race, norepinephrine, dopamine, phenylephrine, vasopressin, mechanical ventilation, intubation, HepF, heart rate, respiratory rate, temperature, SBP, AG, BUN, creatinine, chloride, MCV, RDW and WCC. The nomogram, which included these factors, accurately predicted the in-hospital mortality of patients with CHF. The novel nomogram has the potential for use in clinical practice as a tool to predict and assess mortality of patients with CHF in the ICU.

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“…Therefore, we used CPX as an alternative modality for optimising pacing settings. CPX can be used to evaluate the severity of heart failure and the state of cardiac function during exercise by calculating the lowest minute ventilation and carbon dioxide output ratio7 and end-tidal carbon dioxide pressure,8 respectively. Therefore, CPX represents an effective alternative to TTE in patients with AF that offers an added advantage of exercise tolerance assessment.…”

Section: Discussionmentioning

confidence: 99%

Ventricular sense response pacing in cardiac resynchronisation therapy: a potentially effective treatment option for heart failure in patients with atrial fibrillation

Higuchi

Hasegawa²,

Chiba³

2022

BMJ Case Rep

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Cardiac resynchronisation therapy (CRT) for atrial fibrillation (AF) with intraventricular conduction and low cardiac output may not allow high-frequency biventricular pacing (BiVP). To this end, drugs and ablation treatments are commonly used. Ventricular sense response pacing (VSRP) senses self-pulse and can produce a state comparable with BiVP. If found to be effective for cardiac resynchronisation, the benefit of CRT with VSRP is expected to extend to patients with AF. Herein, we describe the case of a man in his early 60s with low cardiac output caused by AF and left bundle branch block. CRT-defibrillator (CRT-D) implantation was performed, and VSRP was applied. We found VSRP to be more effective in improving cardiac function than drug-induced BiVP. VSRP may become an effective treatment option following CRT-D implantation in patients with AF.

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Relationship Between Exercise Oscillatory Ventilation Loop and Prognosis of Heart Failure

Cited by 8 publications

References 32 publications

Novel application of Poincaré analysis to detect and quantify exercise oscillatory ventilation

Novel application of Poincaré analysis to detect and quantify exercise oscillatory ventilation

Early prediction of in-hospital mortality in patients with congestive heart failure in intensive care unit: a retrospective observational cohort study

Ventricular sense response pacing in cardiac resynchronisation therapy: a potentially effective treatment option for heart failure in patients with atrial fibrillation

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