Insuficiencia cardiaca en España. Epidemiología e importancia del grado de adecuación a las guías de práctica clínica

J, Muñiz García; Mg, Crespo Leiro; A, Castro Beiras

doi:10.1157/13091620

Cited by 30 publications

(5 citation statements)

References 13 publications

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“…Heart failure (HF) is a pathophysiological disorder in which the heart is unable to respond to the body’s metabolic demands, or it does it at the expense of increased ventricular filling pressure [ 1 ].…”

Section: Introductionmentioning

confidence: 99%

Sleep Quality in Patients with Heart Failure in the Spanish Population: A Cross-Sectional Study

Jorge-Samitier

Durante

Gea-Caballero

et al. 2020

IJERPH

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Background: Heart failure is a major problem in western societies. Sleep Disorders maintain a bidirectional relationship with heart failure, as shown by studies conducted in other countries. This study aims to describe the quality of sleep in Spanish patients with heart failure. Materials and methods: We carried out a cross-sectional study to analyze the quality of sleep in a sample of 203 patients with a diagnosis of heart failure admitted to an Internal Medicine Service. The Pittsburg Sleep Quality Index (PSQI) was used to evaluate sleep quality in our sample over a one-month period. Results: 75% of the sample presented sleep disorders. The most common problems included the interruption of sleep (73.5% nocturia and 30% breathing difficulties); 35% had poor sleep efficiency; 33% showed a decrease in daytime performance; 84% had used hypnotics at some point to induce sleep and 35% used them regularly. Conclusions: This is the first study to report on the perceived sleep quality of patients with heart failure in Spain. Self-perception of sleep quality differed from that estimated by the PSQI. The prevalence of the use of sleep-inducing medication was very high. The diurnal dysfunction generated by sleep disorders in a heart failure environment can contribute to the development of self-care and cognitive deterioration problems.

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Section: Introductionmentioning

confidence: 99%

Sleep Quality in Patients with Heart Failure in the Spanish Population: A Cross-Sectional Study

Jorge-Samitier

Durante

Gea-Caballero

et al. 2020

IJERPH

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“…Heart failure (HF) and chronic obstructive pulmonary disease (COPD) are two chronic diseases with the greatest adverse impact on the general population 1 – 3 . Decompensation (in HF) or exacerbation (in COPD) are especially important since they affect autonomy and quality of life and increase mortality and the need for hospital admission or visits to emergency services 4 – 7 .…”

Section: Introductionmentioning

confidence: 99%

Machine learning for the development of diagnostic models of decompensated heart failure or exacerbation of chronic obstructive pulmonary disease

Gálvez-Barrón,

Pérez-López,

Villar-Álvarez

et al. 2023

Sci Rep

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Heart failure (HF) and chronic obstructive pulmonary disease (COPD) are two chronic diseases with the greatest adverse impact on the general population, and early detection of their decompensation is an important objective. However, very few diagnostic models have achieved adequate diagnostic performance. The aim of this trial was to develop diagnostic models of decompensated heart failure or COPD exacerbation with machine learning techniques based on physiological parameters. A total of 135 patients hospitalized for decompensated heart failure and/or COPD exacerbation were recruited. Each patient underwent three evaluations: one in the decompensated phase (during hospital admission) and two more consecutively in the compensated phase (at home, 30 days after discharge). In each evaluation, heart rate (HR) and oxygen saturation (Ox) were recorded continuously (with a pulse oximeter) during a period of walking for 6 min, followed by a recovery period of 4 min. To develop the diagnostic models, predictive characteristics related to HR and Ox were initially selected through classification algorithms. Potential predictors included age, sex and baseline disease (heart failure or COPD). Next, diagnostic classification models (compensated vs. decompensated phase) were developed through different machine learning techniques. The diagnostic performance of the developed models was evaluated according to sensitivity (S), specificity (E) and accuracy (A). Data from 22 patients with decompensated heart failure, 25 with COPD exacerbation and 13 with both decompensated pathologies were included in the analyses. Of the 96 characteristics of HR and Ox initially evaluated, 19 were selected. Age, sex and baseline disease did not provide greater discriminative power to the models. The techniques with S and E values above 80% were the logistic regression (S: 80.83%; E: 86.25%; A: 83.61%) and support vector machine (S: 81.67%; E: 85%; A: 82.78%) techniques. The diagnostic models developed achieved good diagnostic performance for decompensated HF or COPD exacerbation. To our knowledge, this study is the first to report diagnostic models of decompensation potentially applicable to both COPD and HF patients. However, these results are preliminary and warrant further investigation to be confirmed.

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“…Heart failure (HF) is a chronic, progressive syndrome of signs and symptoms in which the heart is not able to meet the metabolic demands of the body or does so at the cost of increasing ventricular filling pressure [ 1 ]. HF is one of the greatest public health problems worldwide due to its complex and progressive nature, loss of quality of life, frequency of hospital admissions and high rate of mortality [ 2 , 3 , 4 ].…”

Section: Introductionmentioning

confidence: 99%

“…Acute decompensated HF can be defined as the sudden or gradual onset of the signs or symptoms of HF requiring unplanned use of health services, including hospitalization [ 6 ]. This results in increased healthcare expenditure (1.8–3.1% of the total health public budget) [ 3 , 5 ], especially in older adults [ 1 ], with an average length of hospital stay of 9 +/− 5 days [ 5 ]. During hospital admission, the pharmacological treatment of HF patients with and without insomnia is often modified, which could cause complications if not carefully monitored.…”

Section: Introductionmentioning

confidence: 99%

Management of Hypnotics in Patients with Insomnia and Heart Failure during Hospitalization: A Systematic Review

et al. 2021

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Background: Heart failure is a chronic, progressive syndrome of signs and symptoms, which has been associated to a range of comorbidities including insomnia. Acute decompensation of heart failure frequently leads to hospital admission. During hospital admission, long-term pharmacological treatments such as hypnotics can be modified or stopped. Aim: To synthesize the scientific evidence available about the effect of withdrawing hypnotic drugs during hospital admission in patients with decompensated heart failure and insomnia. Method: A systematic review of the literature following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines was carried out in the following scientific databases: PubMed, Scopus, Dialnet and Cochrane. Inclusion criteria: studies including a population of adults with heart failure and sleep disorders in treatment with hypnotics and admitted to hospital, studies written in English or Spanish and published until June 2020. Exclusion criteria: studies involving children, patients admitted to intensive care and patients diagnosed with sleep apnea. Results: We identified a total of 265 documents; only nine papers met the selection criteria. The most frequently used drugs for the treatment of insomnia in patients with heart failure were benzodiazepines and benzodiazepine agonists; their secondary effects can alter perceived quality of life and increase the risk of adverse effects. Withdrawal of these drugs during hospital admission could increase the risk of delirium. Future research in this area should evaluate the management of hypnotics during hospital admission in patients with decompensated heart failure. In addition, safe and efficient non-pharmacological alternatives for the treatment of insomnia in this population should be tested and implemented.

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Insuficiencia cardiaca en España. Epidemiología e importancia del grado de adecuación a las guías de práctica clínica

Cited by 30 publications

References 13 publications

Sleep Quality in Patients with Heart Failure in the Spanish Population: A Cross-Sectional Study

Sleep Quality in Patients with Heart Failure in the Spanish Population: A Cross-Sectional Study

Machine learning for the development of diagnostic models of decompensated heart failure or exacerbation of chronic obstructive pulmonary disease

Management of Hypnotics in Patients with Insomnia and Heart Failure during Hospitalization: A Systematic Review

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