Prognostic Importance of Sleep Quality in Patients With Heart Failure

Lee, Kyoung Suk; Lennie, Terry A.; Heo, Seongkum; Song, Eun Kyeung; Moser, Debra K.

doi:10.4037/ajcc2016219

Cited by 44 publications

(63 citation statements)

References 44 publications

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“…[33] Moreover, anxiety, appetite and sleep were confirmed to be predictors of readmission for CHF in retrospective studies, which may have been impacted by the fact that the patient's status influences the risk of readmission. [34][35][36][37] Kitamura M not only confirmed that daily activities were independent predictors of readmission in heart failure patients within 90 days, but also calculated the cut-off value by ROC curve [38] and the study have also proved that self-care and daily activities are the mediating factors of readmission of heart failure. [39] While Hochang Benjamin Lee et al emphasized that personality disorders as predictors of incident cardiovascular disease increased risk disease, [40] our results are quite the opposite, which may be because the subjects studied were different; Apart from the results on patient paranoia, these findings were similar to the results of our reports on the readmission risk factors for CHF.…”

Section: Discussionmentioning

confidence: 74%

A Nomogram based on a Patient-reported Outcomes Measure: Predicting the Risk of Readmission for Patients with Chronic Heart Failure

Han

Tian

Yang

et al. 2020

Preprint

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Background Health-related quality of life, evaluated by a patient-reported outcomes measure, is an important prognostic marker in patients with chronic heart failure. This study aimed to use PROM to establish an effective readmission nomogram for chronic heart failure.Methods Using patient-reported outcomes measure as a measurement tool, we conducted a readmission nomogram for chronic heart failure on a prospective observational study comprising 454 patients with chronic heart failure hospitalized between May 2017 to January 2020. Concordance index and calibration curve were used to evaluate the discriminative ability and predictive accuracy of the nomogram. A bootstrap resampling method was used for internal validation of results. ResultsThe median follow-up period in the study was 197 days. After a final COX regression analysis, the computed gender, income, health care, appetite-sleep, anxiety, depression, paranoia, support, and independence were identified and included in the nomogram. The nomogram showed moderate discrimination, with concordance index of 0.737 (95% CI 0.673-0.800). The calibration curves for the probability of readmission for patients with chronic heart failure showed high consistency between the probability, as predicted, and the actual probability.Conclusions This model offers a platform to assess the risk of readmission for different populations with CHF and can assist clinicians with personalized treatment recommendations.

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Section: Discussionmentioning

confidence: 74%

A Nomogram based on a Patient-reported Outcomes Measure: Predicting the Risk of Readmission for Patients with Chronic Heart Failure

Han

Tian

Yang

et al. 2020

Preprint

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“…Staniute et al further also demonstrated that anxiety, depression and social support can indirectly affect the quality of life of patients with HF [38]. Moreover, anxiety, appetite and sleep were confirmed to be predictors of readmission for CHF in retrospective studies, which may have been impacted by the fact that the patient's status influences the risk of readmission [39][40][41][42]. Kitamura M not only confirmed that daily activities were independent predictors of readmission in heart failure patients within 90 days, but also calculated the cutoff value by ROC curve [43] and the study have also proved that self-care and daily activities are the mediating factors of readmission of heart failure [44].…”

Section: Discussionmentioning

confidence: 96%

A nomogram based on a patient-reported outcomes measure: predicting the risk of readmission for patients with chronic heart failure

Han

Ren

Tian

et al. 2020

Health Qual Life Outcomes

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Background: Health-related quality of life, as evaluated by a patient-reported outcomes measure (PROM), is an important prognostic marker in patients with chronic heart failure. This study aimed to use PROM to establish an effective readmission nomogram for chronic heart failure. Methods: Using a PROM as a measurement tool, we conducted a readmission nomogram for chronic heart failure on a prospective observational study comprising of 454 patients with chronic heart failure hospitalized between May 2017 to January 2020. A Concordance index and calibration curve were used to evaluate the discriminative ability and predictive accuracy of the nomogram. A bootstrap resampling method was used for internal validation of results. Results: The median follow-up period in the study was 372 days. After a final COX regression analysis, the gender, income, health care, appetite-sleep, anxiety, depression, paranoia, support, and independence were identified and included in the nomogram. The nomogram showed moderate discrimination, with a concordance index of 0.737 (95% CI 0.673-0.800). The calibration curves for the probability of readmission for patients with chronic heart failure showed high consistency between the probability, as predicted, and the actual probability. Conclusions: This model offers a platform to assess the risk of readmission for different populations with CHF and can assist clinicians with personalized treatment recommendations.

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“…For example, in patients with heart failure, 63% report poor sleep quality that is associated with reduced cardiac event-free survival. 29 In AF specifically, sleep quality is poor in 50% to 55% of patients. 12 , 30 , 31 In this exploratory study, we examined sleep quality among AF patients being treated with ablation and who then participated in a randomized rehabilitation trial.…”

Section: Discussionmentioning

confidence: 99%

Effect of Rehabilitation on Sleep Quality After Ablation for Atrial Fibrillation

et al. 2018

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Background:Low sleep quality is common in patients with atrial fibrillation (AF). Positive effects of cardiac rehabilitation on patients treated for AF with ablation have been found, but whether cardiac rehabilitation affects sleep quality is unknown. The objectives of this study were to investigate (1) differences in sleep quality between cardiac rehabilitation and usual care groups and (2) whether other factors could affect sleep quality.Methods:From the randomized CopenHeartRFA trial, 210 patients treated for AF with ablation were included. A rehabilitation program consisting of physical exercise and psychoeducational consultations was tested. Sleep quality was measured with the Pittsburg Sleep Quality Index (PSQI) questionnaire before intervention and at the end of intervention. Anxiety, depression, and European Heart Rhythm Association scores were assessed.Results:No difference between groups in sleep quality was found (PSQI global mean [SD] score, 6.60 [3.61] points for the cardiac rehabilitation group [n = 83] and 6.08 [3.60] points for the usual care group [n = 90]; P = .34), although improvements in sleep quality were noted in both groups. Sleep latency, duration, and efficiency were significant by type of AF at 1 month. Anxiety, depression, and higher European Heart Rhythm Association scores at 4 months were associated with a higher PSQI global mean score at the end of intervention.Conclusion:The rehabilitation program showed no effect on sleep quality. A large proportion of patients reported poor sleep quality, and patients reporting anxiety, depression, or AF symptoms described worse sleep quality compared with patients who did not experience anxiety, depression, or AF symptoms. More research in the field is warranted.

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Prognostic Importance of Sleep Quality in Patients With Heart Failure

Abstract: Impaired sleep quality was prevalent in patients with heart failure and was associated with poor cardiac event-free survival. Clinicians should assess and manage sleep quality in patients with heart failure to improve outcomes.

Cited by 44 publications

References 44 publications

A Nomogram based on a Patient-reported Outcomes Measure: Predicting the Risk of Readmission for Patients with Chronic Heart Failure

A Nomogram based on a Patient-reported Outcomes Measure: Predicting the Risk of Readmission for Patients with Chronic Heart Failure

A nomogram based on a patient-reported outcomes measure: predicting the risk of readmission for patients with chronic heart failure

Effect of Rehabilitation on Sleep Quality After Ablation for Atrial Fibrillation

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