ALGORITHM FOR THE DETECTION OF CONGESTIVE HEART FAILURE INDEX

295: Accuracy of Various Methods of B-Line Assessment In the Diagnosis of Congestive Heart Failure Compared by Receiver Operating Characteristic Curves

To evaluate the importance of chronic obstructive pulmonary disease for prognosis and diagnosis of congestive heart failure in patients with acute myocardial infarction. Prospective registration of 6669 consecutive patients admitted with infarction and screened for a randomised controlled trial. A history of COPD was present in 765 (11.5%) patients. Thirty-day and 5-year survival in patients with chronic obstructive pulmonary disease was 86.3 and 42.9%. In patients without pulmonary disease the figures were 87.7 and 57.5%, respectively, giving a relative risk of 1.49 (1.35-1.65). In multivariate analysis the relative risk was 1.15 (1.04-1.28). The prevalence of congestive heart failure was 65.9% in patients with chronic obstructive pulmonary disease and 52.0% in patients without. This difference was most distinct in patients with normal or only slightly decreased left ventricular systolic function. In patients without congestive heart failure, chronic obstructive pulmonary disease was of prognostic importance [RR=1.44 (1.17-1.78)], but not in patients with congestive heart failure [RR=1.09 (0.96-1.23)]. Chronic obstructive pulmonary disease is a predictor of long-term mortality in patients with acute myocardial infarction without congestive heart failure, but is also a confounding factor for the diagnosis of congestive heart failure.

The objective of the present study was to evaluate the diagnostic accuracy of chest radiography in the diagnosis of congestive heart failure (CHF) in a contemporary cohort of consecutive patients...

An efficient detection of congestive heart failure using frequency localized filter banks for the diagnosis with ECG signals

Critical pathways: implementation of the Coleman Care Transitions Program in individuals hospitalized with congestive heart failure.

B-type natriuretic peptide is released from the cardiac ventricles in response to increased wall tension. We conducted a prospective study of 1586 patients who came to the emergency department with acute dyspnea and whose B-type natriuretic peptide was measured with a bedside assay. The clinical diagnosis of congestive heart failure was adjudicated by two independent cardiologists, who were blinded to the results of the B-type natriuretic peptide assay. The final diagnosis was dyspnea due to congestive heart failure in 744 patients (47 percent), dyspnea due to noncardiac causes in 72 patients with a history of left ventricular dysfunction (5 percent), and no finding of congestive heart failure in 770 patients (49 percent). B-type natriuretic peptide levels by themselves were more accurate than any historical or physical findings or laboratory values in identifying congestive heart failure as the cause of dyspnea. The diagnostic accuracy of B-type natriuretic peptide at a cutoff of 100 pg per milliliter was 83.4 percent. The negative predictive value of B-type natriuretic peptide at levels of less than 50 pg per milliliter was 96 percent. In multiple logistic-regression analysis, measurements of B-type natriuretic peptide added significant independent predictive power to other clinical variables in models predicting which patients had congestive heart failure. Used in conjunction with other clinical information, rapid measurement of B-type natriuretic peptide is useful in establishing or excluding the diagnosis of congestive heart failure in patients with acute dyspnea.

I enjoyed reading the excellent article by Marantz and associates 1 on whether clinical evaluation is as useful as radionuclide ventriculography in the management of patients with congestive heart failure. I agree completely with their conclusion that the clinical diagnosis of congestive heart failure, based on clinical evaluation and chest roentgenogram, is a valid predictor of mortality and provides information independent of the radionuclide left ventricular ejection fraction in determining prognosis in these patients. In this era of high technology, laboratory studies cannot substitute for a careful clinical assessment. The authors are so correct when they said "Rather, it is the thorough clinician who judiciously orders and interprets tests of cardiac function who can best make an accurate prognosis." 1 I would like to make three comments. First, although the title of the article is "Prognosis in Ischemic Heart Disease," the text concerns exclusively congestive heart failure, one of the

Atrial fibrillation (AF) and congestive heart failure (CHF) are the most prevalent types of cardiovascular disorders as the leading cause of death due to delayed diagnosis. Early diagnosis of these cardiac conditions is possible by manually analyzing electrocardiogram (ECG) signals. However, manual diagnosis is complex, owing to the various characteristics of ECG signals. An accurate classification system for AF and CHF has the potential to save patient lives. Therefore, this study proposed an ECG signal classification system for AF and CHF using a one-dimensional convolutional neural network (1-D CNN) to provide a robust classification system performance. This study used ECG signal recording of AF, CHF, and NSR, which can be accessed on the Physionet website. A total of 5600 ECG signal segments were obtained from 56 subjects, divided into train sets from 42 subjects (N = 4200 ECG segments), and test sets from 14 subjects (N = 1400). We applied for leave-one-out cross-validation in training to select the best model. The proposed 1-D CNN algorithm successfully classified raw data of ECG signals into normal sinus rhythm (NSR), AF, and CHF by providing the highest classification accuracy of 99.643%, f1-score, recall, and precision of 0.996, respectively, with an AUC score of 0.999. The results showed that the proposed method extracted the ECG signal information directly without needing several preprocessing steps and feature extraction methods that potentially reduce the information contained in the ECG signals. Furthermore, the proposed method outperformed previous studies in classifying AF, CHF, and NSR. Therefore, this approach can be considered as an adjunct for medical personnel to diagnose AF, CHF, and NSR.

Physical examination findings in patients who present to the emergency department with congestive heart failure

LARGE-SCALE REGISTRIES PROVIDE AN IMPORTANT WINdow into how medicine is actually practiced. In this issue of JAMA, Al-Khatib et al examined the National Cardiovascular Data Registry’s (NCDR’s) Implantable Cardioverter-Defibrillator (ICD) Registry to determine how often ICD implantations were performed in patients who did not meet criteria suggested in current guidelines for ICD use; specifically, ICD implantation within 40 days of an acute myocardial infarction (MI) or within 3 months of coronary artery bypass graft (CABG) surgery, recent diagnosis of congestive heart failure (CHF), and presence of New York Heart Association (NYHA) class IV symptoms. AlKhatib et al found that almost one-quarter of ICD implantations were performed in patients with these characteristics, mortality and complication rates were higher among these patients than for patients who received an ICD based on evidence-based guidelines, and nonelectrophysiologists performed non–guideline-based ICD implantations with a higher frequency than electrophysiologists. These findings should be used to inform public health policies toward the appropriate use of this life-saving but expensive technology. The first question that needs to be addressed involves the reliability of the data. The ICD Registry is a well-audited tool that is robust and provides important information. Its strengths lie in the large number of patients included in the registry and in the quality of the data monitoring process. Nonetheless, some variables in the registry may not be accurate. For example, more physicians self-reported being board-certified electrophysiologists in the ICD Registry than have actually been board certified. In addition, the largest group of patients who received non–evidence-based ICDs in the report by Al-Khatib et al were those with a recent diagnosis of CHF. In most cases, ICD Registry data are retrospectively abstracted from the medical record by nurses or other health care professionals. The precise onset of CHF may not be well documented in the medical record because unlike the date of MI, evaluating the date of diagnosis of CHF may require a history that is targeted to this variable. The data abstractor may find evidence of CHF based on a recent hospitalization, but a thorough history could identify a much earlier onset. Even though these issues may affect some of the quantitative findings, the qualitative findings from this report are not likely to be affected significantly, particularly given the large size of the registry. Is it appropriate to implant ICDs for patients who do not meet specific criteria recommended in the guidelines? The authors note that there are circumstances in which deviations from guidelines are appropriate based on the physician’s judgment. Accordingly, while there will be some background rate of ICD implantation outside of guideline recommendations, it is unclear what this background rate should be. As shown in Figure 1 of the article by Al-Khatib et al, only a very small number of sites had a non–guidelinebased ICD implantation rate of less than 6%, suggesting this might be a reasonable lower bound. The upper bound is more difficult to determine, but should be less than the 21% rate of non–guideline-based ICD implantation noted among cardiac electrophysiologists. Moreover, for 3 of the 4 indications Al-Khatib et al classified as non–evidence-based ICD implantation, the issue is timing of the ICD implantation. For instance, a valid medical concern would be that a patient who recently experienced an MI, underwent CABG surgery, or was diagnosed with CHF is at high-risk for sudden death during the waiting period that is indicated in the guidelines. However, no data are available in the NCDR’s ICD Registry regarding this assessment or whether alternative approaches such as the use of the wearable cardioverter-defibrillator were considered. In addition, while there are convincing data that early implantation of an ICD after an MI does not improve outcomes, the data may be less convincing for other conditions. One post hoc analysis, although not definitive, has shown that some patients with nonischemic cardiomyopathy may benefit from early ICD implantation. However, the use of non–cardiac resynchronization therapy ICDs in patients with NYHA class IV symptoms is unwarranted. The other critical findings of this study were the higher rates of non–guideline-based ICD implantation performed by nonelectrophysiologists (cardiologists, thoracic sur-

Background. Congenital heart defects (CHD) are the most common type of developmental anomalies in children. At present the early diagnosis of congestive heart failure (CHF) and CHF-associated pathologic conditions is becoming increasingly important for optimization of protocols for following up pediatric patients in the primary health care settings.Objective. The study aimed at determining the prognostic role of brain natriuretic peptide (BNP) as a diagnostic marker of CHF progression and development of CHF-associated pathological conditions in babies with CHD during the first year of life.Methods. A prospective cohort study was carried out in a total of 114 children of the first year of life. The main study group was comprised of 61 children with confirmed diagnosis of CHD, and the control group of 53 health status group I–IIA children without CHD.Results. Diagnostic role of BNP elevation > 30 pg/mL was determined. At this BNP level the risk for developing stage 2A CHF increased 7-fold (OR 7.5 [1.8–31.5]), for developing functional class (FC) 2 CHF — nearly 5-fold (OR 4.6 [1.3–16.0]), and for FC 3 CHF such risk increased 9-fold (OR 9.2 [2.3–36.1]). Our results demonstrated that the BNP level measurements can be used in clinical practice to determine the likelihood of persistence of symptoms of perinatal CNS injuries during the first year of life (OR 7.6 [1.7–34.5]) and protein and energy deficit (PED) (OR 9.5 [2.5–35.5]) in children with CHD.

Congestive heart failure is a major health problem in terms of morbidity, mortality, increasing prevalence in the population, and economic burden to the health care system. The scope of the problem is evident by looking at the numbers (): hospital discharges for heart failure increased 155.2% in the 20-yr period from 1979 to 1999, and currently there are about 4.8 million Americans living with congestive heart failure. There are over a half million new cases of congestive heart failure each year, and the incidence approaches 10% of the population after age 65. Heart failure follows a heart attack in 22% of men and 46% of women, and 75% of heart failure cases were preceded by hypertension, indicating a link between development of heart failure and previous myocardial damage or stress. The need for cost-effective therapeutic approaches is further reinforced by the economics of heart failure (Table 1). Ultimately, heart failure can only be treated by cardiac transplantation, which has dramatically increased in recent years (Fig. 1), and Current pharmacologic interventions at best can only slow progression of deteriorating heart function and provide symptomatic relief. Our inability to mitigate the progression of congestive heart failure is evident from mortality associated with the syndrome, ending in death within 8 yr for 80% of men and 70% of women. Although survival after diagnosis of congestive heart failure is worse in men than women, fewer than 15% of women survive more than 8–12 yr. Clearly, heart failure is a syndrome affecting both sexes, especially in the aging population, that would benefit tremendously from novel therapeutic approaches to management, particularly (Table 1) efforts to inhibit the progression of decompensation and restore contractile function. Table 1 Economic Cost of Cardiovascular Disease: Estimated Direct and Indirect Costs (in Billions of Dollars) of Cardiovascular Diseases and Stroke United States, 2002 Heart Disease b Coronary heart disease Stroke Hypertensive disease Congestive heart failure Total cardiovascular diseases a Direct costs Hospital/nursing home 81.0 41.8 24.5 8.6 15.4 126.1 Physicians/other professionals 15.3 8.6 2.4 8.6 1.6 29.9 Drugs/other medical durables 13.5 6.2 0.8 15.5 2.0 31.8 Home health care 5.2 1.6 3.1 1.7 2.4 11.7 Total expenditures a 115.0 58.2 30.8 34.4 c 21.4 199.5 Indirect costs Lost productivity/morbidity 19.0 8.4 5.6 6.7 NA 30.9 Lost productivity/mortality d 80.0 45.2 13.0 6.1 1.8 98.8 Grand totals 214.0 111.8 49.4 47.2 23.2 329.2 a Totals do not add up because of rounding and overlap. b This category includes coronary heart disease, congestive heart failure, part of hypertensive disease, cardiac heart disease, cardiomyopathy, pulmonary heart disease, and other ill-defined “heart” diseases. c Tom Hodgson and Liming estimated that health care expenditures attributed to hypertension that could not be allocated to cardiovascular complications and other diagnoses totaled $108.8 billion in 1998. d Lost future earnings of persons who will die in 2002, discounted at 4%. NA indicates not available. Open image in new window Fig. 1. Heart transplantation frequency by year. Reproduced with permission from the American Heart Association. World Wide Web Site: http://www.americanheart.org, © 2001, Copyright American Heart Association

The matched case-control, single-centred, prospective study by Ozturk et al. was designed to compare the NT-proBNP levels between hospitalized congestive heart failure (CHF) patients and outpatients.1 The main purpose of their study was to define a certain cut-off NT-proBNP value for hospitalization of CHF patients. We will address five points to challenge their study design and presentation (As summarized in Figure 1): Figure 1 Summary of the study design by Ozturk et al. 1- The small sample size and wide range of NT-proBNP (with wide standard error) in the patient group (range: 245-35,000) may present low analysis power. 2- In order to define a cut point level of NT-proBNP, the area under curve (AUC) should be used. 3- According to Table 3 in their article, confounding variables should be defined and analyzed separately. 4- Since mean of NT-proBNP may vary by age, dividing the patients based on age ( 75 years) would have been more appropriate. 1- In Table 1, that showed baseline characteristics of patients in their paper, data about outpatients (n = 32) should have been separated according to normal and stabilized heart failure (HF) groups. We also should mention additional comments about using BNP or NT-proBNP in diagnosis of CHF: Adding brain natriuretic peptide (BNP) or NT-proBNP tests to standard clinical assessment has been shown to be valuable for an accurate and efficient diagnosis and prognostication of HF. Thus, the use of BNP or NT-proBNP may be associated with im-proved clinical outcomes.2 NT-proBNP may be elevated in a number of other diseases such as heart muscle disease, valvular heart disease, arrhythmia, pulmonary heart disease, stroke and sepsis. Meanwhile, patient-related factors like sex, age, renal and liver failure, hypertension, glucocorticoids use, obesity (negative effect), and also cardioactive drugs may influence the results.2,3 One of the most useful aspects of this test is its negative predictive value. This can be very helpful in patients who need to be reassured about not actively being in CHF.4 Since the gold standard for HF diagnosis in obese patients is hard to precisely define in any situation, using BNP in those patients may not be appropriate. Technical problems about BNP or NT-proBNP measurement should also be considered: NT-proBNP measurement in the central laboratory offers tight quality control and may be the preferred way to go if very pre-cise measurements are desired.3 It was a consensus that the 1-hour time limit should direct which type of test to use.4 Potential overall accuracy of NT-proBNP in the diagnosis of HF in primary care measured by the AUC has been uniformly high across studies.5 However, false negative results may be obtained in some situations including: HF patients with low BNPs are mainly patients with borderline left ventricular systolic dimension (LVSD) or are on cardioactive drugs known to lower NT-proBNP concentrations. NT-proBNP concentrations should be mentioned according to age. The rule-out value of NT-proBNP in this setting is well documented.5 Patients with NT-proBNP concentrations 450 pg/ml ( 900 pg/ml (50–75 years), and > 1800 pg/ml (> 75 years) have a very high probability of having HF as the cause of their acute dyspnea (although the clinical judgment must also consider other diagnoses, namely acute coronary syndrome and pulmonary embolism). According to age, patients with NT-proBNP concentrations between 300 pg/ml and 450, 900, or 1800 pg/ml have several other diagnostic possibilities that should be considered. Finally, cut-points are not yet clearly defined and more work is required to optimize them. In consultation with the local biochemical laboratory, local centers should be audited before deciding on cut-points in their own populations. Characteristics analysis must also be considered.3

The Complex Relationship Between Ischemic Heart Disease and COPD Exacerbations

Background. Congenital heart defects (CHD) are the most common type of developmental anomalies in children. At present the early diagnosis of congestive heart failure (CHF) and CHF-associated pathologic conditions is becoming increasingly important for optimization of protocols for following up pediatric patients in the primary health care settings.Objective. The study aimed at determining the prognostic role of brain natriuretic peptide (BNP) as a diagnostic marker of CHF progression and development of CHF-associated pathological conditions in babies with CHD during the first year of life.Methods. A prospective cohort study was carried out in a total of 114 children of the first year of life. The main study group was comprised of 61 children with confirmed diagnosis of CHD, and the control group of 53 health status group I–IIA children without CHD.Results. Diagnostic role of BNP elevation > 30 pg/mL was determined. At this BNP level the risk for developing stage 2A CHF increased 7-fold (OR 7.5 [1.8–31.5]), for developing functional class (FC) 2 CHF — nearly 5-fold (OR 4.6 [1.3–16.0]), and for FC 3 CHF such risk increased 9-fold (OR 9.2 [2.3–36.1]). Our results demonstrated that the BNP level measurements can be used in clinical practice to determine the likelihood of persistence of symptoms of perinatal CNS injuries during the first year of life (OR 7.6 [1.7–34.5]) and protein and energy deficit (PED) (OR 9.5 [2.5–35.5]) in children with CHD.