Etiology, comorbidity and prognosis of hospitalized patients with congestive heart failure

Zhao, Yuetao; Li, J; Xue, Qiao; Gao, Lei; Xu, Qi; Wu, Xue-Ru

doi:10.1186/cc8361

Cited by 4 publications

(4 citation statements)

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“…CHF also tends to co-occur with pneumonia in our study (Figure 4,6), similar to a previous study (Zhao et al 2010), which reported that patients with CHF exhibit an increased risk of developing a multitude of comorbidities, including pneumonia, which worsens with age.…”

Section: Discussionsupporting

confidence: 91%

“…Subjects with COPD are at an increased risk of developing pneumonia due to a variety of reasons, including bronchitis, excessive mucus accumulation, etc (Restrepo et al 2018). CHF also tends to co-occur with pneumonia in our study (Figure 4,6), similar to a previous study (Zhao et al 2010), which reported that patients with CHF exhibit an increased risk of developing a multitude of comorbidities, including pneumonia, which worsens with age.…”

Section: Discussionsupporting

confidence: 91%

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Exploring Comorbidity Networks in Mild Traumatic Brain Injury Subjects through Graph Theory: A Traumatic Brain Injury Model Systems Study

Mehta,

Sudhakar

2024

Preprint

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Traumatic brain injuries (TBIs) are characterized by myriad comorbidities that affect the functioning of the affected individuals. The comorbidities that TBI subjects experience span a wide range, ranging from psychiatric diseases to those that affect the various systems of the body. This is compounded by the fact that the problems that TBI subjects face could span over an extended period post-primary injury. Further, no drug exists to prevent the spread of secondary injuries after a primary impact. In this study, we employed graph theory to understand the patterns of comorbidities after mild TBIs. Upon application of network analysis and a novel clustering algorithm, we discovered interesting associations between comorbidities in young and old subjects with the condition. Specifically, bipolar disorder was seen as related to cardiovascular comorbidities, a pattern that was observed only in the young subjects. Similar associations between obsessive-compulsive disorder and rheumatoid arthritis were observed in young subjects. Psychiatric comorbidities exhibited differential associations with non-psychiatric comorbidities depending on the age of the cohort. The study results might have implications for effective surveillance and the management of comorbidities post mild TBIs.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionsupporting

confidence: 91%

Exploring Comorbidity Networks in Mild Traumatic Brain Injury Subjects through Graph Theory: A Traumatic Brain Injury Model Systems Study

Mehta,

Sudhakar

2024

Preprint

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“…56 In parallel, the older the age was, the higher the complication ratio was, which was the obstacle factor for CR engagement. 57 Meanwhile, previous cardiac-related hospitalizations 1 or 2 times was the positive predictor in the middle engagement phase. Hospitalizations are common after HF diagnosis, with 83% of patients hospitalized at least once and 43% hospitalized at least four times.…”

Section: Discussionmentioning

confidence: 95%

Cardiac Rehabilitation Engagement and Predictive factors in Heart Failure patients: A cross-sectional study

Gao

Sun

et al. 2023

Preprint

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Background: Chronic Heart Failure (CHF) still affects millions of people worldwide despite great advances in therapeutic approaches in the cardiovascular field. Cardiac rehabilitation (CR) is known to improve disease-related symptoms, quality of life and clinical outcomes, yet implementation was suboptimal, a frequently low engagement in rehabilitation programs has been found globally. Objective: To quantify diverse CR-engaged processes and elucidate predictors of the various levels of CR engagement in CHF patients. Methods: CHF patients admitted or discharged from cardiology departments between May 1 2022 to November 1 2022 were enrolled. Individuals who met the inclusion criteria filled the questionnaires, including the generalized anxiety disorders scale, patient health questionnaire, cardiac rehabilitation inventory, patient activation measure, Tampa scale for kinesiophobia heart, social frailty, Patient Health Engagement Scale (PHE-s®) We obtained sociodemographic characteristics and clinical data from medical records. The survey was distributed via mobile phone text messaging or face-to-face completed. Chi-square tests and multivariable logistic regression analyses were performed to examine the factors associated with CR engagement phases. Results: A total of 684 patients were included in the study. Univariate analysis showed that only kinesiophobia had no correlation with engagement phases besides socio-demographic and clinical variables. Multivariate logistic regression analysis revealed that compared with the blackout phaseprocess anxiety (Arousal: OR 0.829, 95%CI: 0.73 ~ 0.94; Adhesion: OR 0.725, 95%CI: 0.64 ~ 0.82; Eudaimonic Project: OR 0.674, 95%CI: 0.59 ~ 0.77), monthly income (RMB yuan) equal to or more than 5,000 (Arousal: OR 6.342, 95%CI: 1.30 ~ 31.01; Adhesion: OR 5.226, 95%CI: 1.09 ~ 24.96; Eudaimonic Project: OR 6.658, 95%CI 1.26 ~ 34.76) were the most important factor impacting CHF patients CR engagement. In the Arousal phase, versus the Blackout phase, regular exercise or not (OR 3.29, 95% CI: 1.19 ~ 9.10), severe depression (OR 0.019, 95% CI: 0.00 ~ 0.813), previous cardiac-related hospitalizations 1 or 2 times (OR 3.75, 95% CI: 1.19 ~ 11.86), Age (OR 0.958, 95% CI: 0.92 ~ 0.998) influenced patient CR engagement. Besides, compared to the Blackout phase, outcome anxiety (OR 1.269, 95% CI: 1.11 ~ 1.46) and activation level (level 2: OR 9.357, 95% CI: 1.44 ~ 60.68; level 3: OR 29.96, 95% CI: 3.67 ~ 244.92; level 4: OR 29.71, 95% CI: 3.62 ~ 243.61) were independent factors predicting the Eudaimonic Project phase. Conclusions: This study characterized CR engagement, and explored demographic, medical, and psychological factors— with the most important being process anxiety, monthly income, patient activation, severe depression, and previous cardiac-related hospitalizations. The predictor factors of CR engagement were not identical among different phases which strongly indicates a significant role in quantifying CR engagement. Our findings suggested that factors could potentially be targeted in clinical practice to identify low CR engagement patients, and strategies implemented to strengthen or overcome these associations to address low CR engagement in CHF patients.

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“…Frailty was shown to occur frequently in patients with heart failure, with the prevalence ranging from 15 to 74%, depending on the studied population and the method of assessment [ 55 ]. In parallel, the older the age was, the higher the complication ratio was, which was the obstacle factor for CR engagement [ 56 ].…”

Section: Discussionmentioning

confidence: 99%

Cardiac rehabilitation engagement and associated factors among heart failure patients: a cross-sectional study

Yu,

Gao,

Sun

et al. 2023

BMC Cardiovasc Disord

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Background Chronic Heart Failure (CHF) still affects millions of people worldwide despite great advances in therapeutic approaches in the cardiovascular field. Cardiac rehabilitation (CR) is known to improve disease-related symptoms, quality of life and clinical outcomes, yet implementation is suboptimal, a frequently low engagement in rehabilitation programs has been found globally. Objective To quantify diverse CR-engaged processes and elucidate associated factors of the various levels of CR engagement in CHF patients. Methods Discharged patients admitted from cardiology departments between May 2022 to July 2022 were enrolled by mobile phone text messaging, CHF patients from same department between August 2022 to December 2022 were enrolled by face-to-face. Individuals who met the inclusion criteria filled the questionnaires, including the generalized anxiety disorders scale, patient health questionnaire, cardiac rehabilitation inventory, patient activation measure, Tampa scale for kinesiophobia heart, social frailty, Patient Health Engagement Scale (PHE-s®). We obtained sociodemographic characteristics and clinical data from medical records. Chi-square tests and multivariable logistic regression analyses were performed to examine the factors associated with CR engagement phases. Results A total of 684 patients were included in the study. 52.49% patients were in the Adhesion phase. At the multivariate level, compared with the blackout phase process anxiety, monthly income (RMB yuan) equal to or more than 5,000 were the most important factor impacting CHF patients CR engagement. Compared with the Blackout phase, regular exercise or not, severe depression, previous cardiac-related hospitalizations 1 or 2 times, Age influenced patient CR engagement in the Arousal phase. Besides, compared with the Blackout phase, outcome anxiety and activation level were independent factors in the Eudaimonic Project phase. Conclusion This study characterized CR engagement, and explored demographic, medical, and psychological factors—with the most important being process anxiety, monthly income, patient activation, severe depression, and previous cardiac-related hospitalizations. The associated factors of CR engagement were not identical among different phases. Our findings suggested that factors could potentially be targeted in clinical practice to identify low CR engagement patients, and strategies implemented to strengthen or overcome these associations to address low CR engagement in CHF patients.

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Etiology, comorbidity and prognosis of hospitalized patients with congestive heart failure

Cited by 4 publications

References 0 publications

Exploring Comorbidity Networks in Mild Traumatic Brain Injury Subjects through Graph Theory: A Traumatic Brain Injury Model Systems Study

Exploring Comorbidity Networks in Mild Traumatic Brain Injury Subjects through Graph Theory: A Traumatic Brain Injury Model Systems Study

Cardiac Rehabilitation Engagement and Predictive factors in Heart Failure patients: A cross-sectional study

Cardiac rehabilitation engagement and associated factors among heart failure patients: a cross-sectional study

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